From ea3128d5d8b0b3dd448b08f7107f8f517ebb6625 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Mon, 9 Sep 2024 13:42:07 -0400 Subject: [PATCH 01/37] Track 1: No Likelihood Generative Function of Dynamic Object (#146) --- notebooks/bayes3d_paper/online_hb.ipynb | 875 ++---------------- .../chisight/dynamic_object_model/__init__.py | 0 .../dynamic_object_model/drift_kernels.py | 190 ---- .../dynamic_object_inference.py | 561 ----------- .../dynamic_object_model.py | 204 ---- .../likelihoods/__init__.py | 0 .../likelihoods/aggreate_mean_image_kernel.py | 141 --- .../likelihoods/kfold_image_kernel.py | 429 --------- .../project_no_occlusions_kernel.py | 78 -- src/b3d/chisight/gen3d/model.py | 163 ++++ src/b3d/chisight/gen3d/transition_kernels.py | 379 ++++++++ src/b3d/utils.py | 17 +- .../test_dynamic_object_model.py | 99 -- tests/gen3d/test_model.py | 159 ++++ tests/gen3d/test_transition_kernels.py | 22 + 15 files changed, 834 insertions(+), 2483 deletions(-) delete mode 100644 src/b3d/chisight/dynamic_object_model/__init__.py delete mode 100644 src/b3d/chisight/dynamic_object_model/drift_kernels.py delete mode 100644 src/b3d/chisight/dynamic_object_model/dynamic_object_inference.py delete mode 100644 src/b3d/chisight/dynamic_object_model/dynamic_object_model.py delete mode 100644 src/b3d/chisight/dynamic_object_model/likelihoods/__init__.py delete mode 100644 src/b3d/chisight/dynamic_object_model/likelihoods/aggreate_mean_image_kernel.py delete mode 100644 src/b3d/chisight/dynamic_object_model/likelihoods/kfold_image_kernel.py delete mode 100644 src/b3d/chisight/dynamic_object_model/likelihoods/project_no_occlusions_kernel.py delete mode 100644 tests/dynamic_object_model/test_dynamic_object_model.py create mode 100644 tests/gen3d/test_model.py create mode 100644 tests/gen3d/test_transition_kernels.py diff --git a/notebooks/bayes3d_paper/online_hb.ipynb b/notebooks/bayes3d_paper/online_hb.ipynb index 4c03e8ba..7d2c9fb0 100644 --- a/notebooks/bayes3d_paper/online_hb.ipynb +++ b/notebooks/bayes3d_paper/online_hb.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -43,32 +43,32 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Scene 49\n" + "Scene 48\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 13.80it/s]\n" + "100%|██████████| 45/45 [00:04<00:00, 10.90it/s]\n" ] }, { "data": { - "image/jpeg": 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", - "image/png": 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", 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", 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", "text/plain": [ "" ] }, - "execution_count": 3, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -76,7 +76,7 @@ "source": [ "### Loading data ###\n", "b3d.reload(b3d.io.data_loader)\n", - "scene_id = 49\n", + "scene_id = 48\n", "FRAME_RATE = 50\n", "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", "print(f\"Scene {scene_id}\")\n", @@ -105,7 +105,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -116,29 +116,29 @@ "b3d.reload(b3d.chisight.dynamic_object_model.dynamic_object_inference)\n", "from b3d.chisight.dynamic_object_model.dynamic_object_model import (\n", " dynamic_object_generative_model, viz_trace, info_from_trace,\n", - " make_colors_choicemap, make_color_outlier_probabilities_choicemap, make_depth_outlier_probabilities_choicemap\n", - ")\n", - "from b3d.chisight.dynamic_object_model.dynamic_object_inference import (\n", - " inference_step_without_advance,\n", - " inference_step,\n", - " propose_depth_outlier_probability,\n", - " propose_color_and_color_outlier_probability,\n", - " # inference_step_old\n", + " make_colors_choicemap, make_visibiliy_choicemap,make_depth_nonreturn_choicemap,\n", + " image_likelihood\n", ")\n", + "b3d.reload(b3d.chisight.dynamic_object_model.dynamic_object_model)\n", + "import b3d.chisight.dynamic_object_model.drift_kernels as drift_kernels\n", + "b3d.reload(b3d.chisight.dynamic_object_model.drift_kernels)\n", "\n", - "from b3d.chisight.dynamic_object_model import drift_kernels" + "from b3d.chisight.dynamic_object_model.dynamic_object_inference import (\n", + " propose_update,\n", + " inference_step\n", + ")\n" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "182920.1\n" + "21894.166\n" ] } ], @@ -146,7 +146,7 @@ "\n", "T = 0\n", "b3d.rr_set_time(T)\n", - "OBJECT_INDEX = 2\n", + "OBJECT_INDEX = 4\n", "\n", "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", @@ -158,47 +158,70 @@ "model_vertices = template_pose.inv().apply(xyz_rendered[mask])\n", "model_colors = vertex_attributes=all_data[T][\"rgbd\"][..., :3][mask]\n", "\n", + "subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[:len(model_vertices) // 2]\n", + "model_vertices = model_vertices[subset]\n", + "model_colors = model_colors[subset]\n", + "\n", + "model_vertices = meshes[OBJECT_INDEX].vertices\n", + "model_colors = meshes[OBJECT_INDEX].vertex_attributes\n", + "\n", + "\n", "hyperparams = {\n", + " \"pose_transition_kernel\": drift_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", + " \"color_transition_kernel\": drift_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.2),\n", + " \"visibility_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.4\n", + " ),\n", + " \"depth_nonreturn_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.4\n", + " ),\n", + " \"depth_scale_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.4\n", + " ),\n", + " \"color_scale_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.4\n", + " ),\n", + " \"visibility_values\": jnp.array([0.01, 0.99]),\n", + " \"depth_nonreturn_values\": jnp.array([0.01, 0.99]),\n", + " \"color_scale_values\": jnp.array([0.1, 0.15]),\n", + " \"depth_scale_values\": jnp.array([0.0025, 0.005, 0.01]),\n", " \"vertices\": model_vertices,\n", - " \"max_color_shift\": 0.1,\n", - " \"max_pose_position_shift\": 0.1,\n", + "\n", " \"fx\": fx,\n", " \"fy\": fy,\n", " \"cx\": cx,\n", " \"cy\": cy,\n", " \"image_height\": Pytree.const(image_height),\n", " \"image_width\": Pytree.const(image_width),\n", - " \"color_transition_kernel\": drift_kernels.GaussianColorDriftKernel(scale=0.1),\n", - " # Example of writing a mixture kernel:\n", - " # \"color_transition_kernel\": drift_kernels.MixtureDriftKernel(\n", - " # (drift_kernels.UniformColorDriftKernel(max_shift=0.1), drift_kernels.LaplaceColorDriftKernel(scale=0.1)),\n", - " # jnp.array([0.02, 0.98])\n", - " # ),\n", - " \"color_outlier_probability_transition_kernel\": drift_kernels.GaussianDriftKernel(scale=0.1, min_val=0.0, max_val=1.0),\n", - " \"depth_outlier_probability_transition_kernel\": drift_kernels.GaussianDriftKernel(scale=0.1, min_val=0.0, max_val=1.0),\n", + "\n", + " \"image_likelihood\": image_likelihood,\n", "}\n", "\n", + "\n", + "num_vertices = model_vertices.shape[0]\n", "previous_state = {\n", " \"pose\": template_pose,\n", " \"colors\": model_colors,\n", - " \"color_outlier_probabilities\": jnp.ones(len(model_vertices)) * 0.01,\n", - " \"depth_outlier_probabilities\": jnp.ones(len(model_vertices)) * 0.01,\n", + " \"visibility\": jnp.ones(num_vertices) * hyperparams[\"visibility_values\"][1],\n", + " \"depth_nonreturn\": jnp.ones(num_vertices) * hyperparams[\"depth_nonreturn_values\"][0],\n", + " \"depth_scale\": hyperparams[\"depth_scale_values\"][0],\n", + " \"color_scale\": hyperparams[\"color_scale_values\"][0],\n", "}\n", "\n", "choicemap = (\n", " genjax.ChoiceMap.d(\n", " {\n", " \"pose\": previous_state[\"pose\"],\n", - " \"color_variance\": 0.1,\n", - " \"depth_variance\": 0.005,\n", + " \"color_scale\": previous_state[\"color_scale\"],\n", + " \"depth_scale\": previous_state[\"depth_scale\"],\n", " \"rgbd\": all_data[T][\"rgbd\"],\n", " }\n", " ) ^ \n", - " make_depth_outlier_probabilities_choicemap(previous_state[\"depth_outlier_probabilities\"]) ^\n", - " make_color_outlier_probabilities_choicemap(previous_state[\"color_outlier_probabilities\"]) ^\n", - " make_colors_choicemap(previous_state[\"colors\"])\n", + " make_visibiliy_choicemap(previous_state[\"visibility\"]) ^\n", + " make_colors_choicemap(previous_state[\"colors\"]) ^\n", + " make_depth_nonreturn_choicemap(previous_state[\"depth_nonreturn\"])\n", ")\n", - "key = jax.random.PRNGKey(0)\n", + "key = jax.random.PRNGKey(10)\n", "trace, _ = b3d.chisight.dynamic_object_model.dynamic_object_model.dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", "print(trace.get_score())\n", "viz_trace(trace, 0)\n", @@ -207,61 +230,45 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Pose(position=Array([-0.06365717, -0.06389732, 0.9016483 ], dtype=float32), quaternion=Array([ 0.25908902, -0.87780774, 0.36045524, 0.17999579], dtype=float32))\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pose(position=Array([-0.06617196, -0.06403518, 0.9024389 ], dtype=float32), quaternion=Array([ 0.26273286, -0.86704 , 0.38232538, 0.18177064], dtype=float32))\n" + "21894.166\n" ] } ], "source": [ "T = 0\n", - "key = jax.random.split(key)[1]\n", - "print(trace.get_choices()[\"pose\"])\n", - "new_trace = inference_step_without_advance(trace, key)\n", - "print(new_trace.get_choices()[\"pose\"])\n", - "viz_trace(new_trace, T+1, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" + "key = b3d.split_key(key)\n", + "print(trace.get_score())\n", + "trace, log_q = propose_update(trace, key, trace.get_choices()[\"pose\"])\n", + "viz_trace(trace, 0, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/49 [00:00" - ] - }, - "execution_count": 258, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "T = 0\n", - "color_outlier_probability_sweep = jnp.array([0.01, 0.25, 0.5, 0.75, 1.0])\n", - "scores_per_sweep_point_and_vertex = propose_color_and_color_outlier_probability(trace, key, color_outlier_probability_sweep)[-1]\n", - "print(scores_per_sweep_point_and_vertex[...,0])\n", - "plt.matshow(b3d.normalize_log_scores(scores_per_sweep_point_and_vertex[...,0]))\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 105, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 105, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.plot(b3d.normalize_log_scores(scores_per_sweep_point_and_vertex[0,:, 0]))" - ] + "source": [] }, { "cell_type": "code", @@ -422,620 +287,74 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 17, + "execution_count": 76, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Pose(position=Array([-0.06365717, -0.06389732, 0.9016483 ], dtype=float32), quaternion=Array([ 0.25908902, -0.87780774, 0.36045524, 0.17999579], dtype=float32))\n", - "Pose(position=Array([-0.06365717, -0.06389732, 0.9016483 ], dtype=float32), quaternion=Array([ 0.25908902, -0.87780774, 0.36045524, 0.17999579], dtype=float32))\n" + "71235.26\n", + "71235.26\n", + "23732.854\n" ] } ], "source": [ "T = 0\n", - "print(trace.get_choices()[\"pose\"])\n", - "trace = inference_step_without_advance(trace, key)\n", - "print(trace.get_choices()[\"pose\"])\n", - "viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/49 [00:00" - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.matshow(all_scores[:,:30])\n", - "plt.colorbar()" + "print(trace.get_score())\n", + "new_trace, log_q = propose_update(trace, key, trace.get_choices()[\"pose\"])\n", + "print(new_trace.get_score())\n", + "print(log_q)\n", + "viz_trace(new_trace, T+1, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 77, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/49 [00:00()\",\n", - ")\n", - "f(0.1, 0.1, 0.1)" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'outlier_probability_transition_kernel' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[54], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43moutlier_probability_transition_kernel\u001b[49m\u001b[38;5;241m.\u001b[39mlogpdf\n", - "\u001b[0;31mNameError\u001b[0m: name 'outlier_probability_transition_kernel' is not defined" - ] - } - ], - "source": [ - "\n", - "outlier_probability_transition_kernel.logpdf" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/49 [00:00 ArrayLike: - raise NotImplementedError - - @abstractmethod - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - raise NotImplementedError - - -@Pytree.dataclass -class UniformDriftKernel(DriftKernel): - """A drift kernel that samples a new value from a uniform distribution centered - around the previous value. The range of the uniform distribution may shrink - to ensure that the new value is within the bounds of [min_val, max_val]. - - Support: [max(min_val, prev_value - max_shift), min(max_val, prev_value + max_shift)] - """ - - max_shift: float = Pytree.static() - min_val: float = Pytree.static() - max_val: float = Pytree.static() - - def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: - return self._base_dist(prev_value).sample(seed=key) - - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - return self._base_dist(prev_value).log_prob(new_value) - - def _base_dist(self, prev_value: ArrayLike): - """Returns a uniform distribution centered around prev_value, bounded by - min_val and max_val.""" - low = jnp.maximum(prev_value - self.max_shift, self.min_val) - high = jnp.minimum(prev_value + self.max_shift, self.max_val) - return tfp.distributions.Uniform(low, high) - - -@Pytree.dataclass -class UniformColorDriftKernel(UniformDriftKernel): - """A specialized uniform drift kernel with fixed min_val and max_val, with - additional logics to handle the color channels jointly. - - Support: [max(0.0, prev_value - max_shift), min(1.0, prev_value + max_shift)] - """ - - max_shift: float = Pytree.static() - min_val: float = Pytree.static(default=0.0, init=False) - max_val: float = Pytree.static(default=1.0, init=False) - - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - # the summation at the end is to ensure that we get a single value for - # the 3 channels (instead of 3 separate values) - return super().logpdf(new_value, prev_value).sum() - - -@Pytree.dataclass -class LaplaceDriftKernel(DriftKernel): - """A drift kernel that samples from a truncated Laplace distribution centered - at the previous value. Values outside of the bounds will be resampled from a - small uniform window at the boundary. This is a thin wrapper around the - truncated_laplace distribution to provide a consistent interface with other - drift kernels. - - Support: [min_val, max_val] - """ - - scale: float = Pytree.static() - min_val: float = Pytree.static() - max_val: float = Pytree.static() - uniform_window_size: float = Pytree.static() - - def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: - return truncated_laplace.sample( - key, prev_value, self.scale, self.uniform_window_size - ) - - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - return truncated_laplace.logpdf( - new_value, prev_value, self.scale, self.uniform_window_size - ) - - -@Pytree.dataclass -class LaplaceColorDriftKernel(DriftKernel): - """A drift kernel that samples the 3 channels of the color from a specialized - truncated Laplace distribution, centered at the previous color. Values outside - of the bounds will be resampled from a small uniform window at the boundary. - This is a thin wrapper around the truncated_color_laplace distribution to - provide a consistent interface with other drift kernels. - - Support: [0.0, 1.0] - """ - - scale: float = Pytree.static() - uniform_window_size: float = Pytree.static(default=_FIXED_COLOR_UNIFORM_WINDOW) - - def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: - return truncated_color_laplace.sample( - key, prev_value, self.scale, self.uniform_window_size - ) - - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - return truncated_color_laplace.logpdf( - new_value, prev_value, self.scale, self.uniform_window_size - ) - - -@Pytree.dataclass -class GaussianDriftKernel(DriftKernel): - """A drift kernel that samples from a truncated Gaussian distribution centered - at the previous value. Values outside of the bounds will be renormalized. - - Support: [min_val, max_val] - """ - - scale: float = Pytree.static() - min_val: float = Pytree.static() - max_val: float = Pytree.static() - - def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: - return self._base_dist(prev_value).sample(seed=key) - - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - return self._base_dist(prev_value).log_prob(new_value) - - def _base_dist(self, prev_value: ArrayLike): - return tfp.distributions.TruncatedNormal( - loc=prev_value, scale=self.scale, low=self.min_val, high=self.max_val - ) - - -@Pytree.dataclass -class GaussianColorDriftKernel(GaussianDriftKernel): - """A specialized Gaussian drift kernel that samples from a truncated Gaussian - distribution centered at the previous value. Values outside of the bounds - will be renormalized. - - Support: [0.0, 1.0] - """ - - scale: float = Pytree.static() - min_val: float = Pytree.static(default=0.0, init=False) - max_val: float = Pytree.static(default=1.0, init=False) - - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - # the summation at the end is to ensure that we get a single value for - # the 3 channels (instead of 3 separate values) - return super().logpdf(new_value, prev_value).sum() - - -@Pytree.dataclass -class MixtureDriftKernel(DriftKernel): - """A drift kernel that samples from a mixture of distributions according to - the probabilities specified in the `mix_ratio`. - """ - - dists: Sequence[DriftKernel] = Pytree.static() - mix_ratio: ArrayLike = Pytree.static() - - def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: - return PythonMixturePixelModel(self.dists).sample( - key, self.mix_ratio, [(prev_value,)] * len(self.dists) - ) - - def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - return PythonMixturePixelModel(self.dists).logpdf( - new_value, - self.mix_ratio, - [(prev_value,)] * len(self.dists), - ) diff --git a/src/b3d/chisight/dynamic_object_model/dynamic_object_inference.py b/src/b3d/chisight/dynamic_object_model/dynamic_object_inference.py deleted file mode 100644 index 06a048ef..00000000 --- a/src/b3d/chisight/dynamic_object_model/dynamic_object_inference.py +++ /dev/null @@ -1,561 +0,0 @@ -import jax -import jax.numpy as jnp -import jax.random -from genjax import ChoiceMapBuilder as C -from genjax import Diff -from genjax import UpdateProblemBuilder as U - -from b3d import Pose - -from .dynamic_object_model import ( - info_from_trace, - make_color_outlier_probabilities_choicemap, - make_colors_choicemap, - make_depth_outlier_probabilities_choicemap, -) - - -@jax.jit -def advance_time(key, trace, observed_rgbd): - """ - Advance to the next timestep, setting the new latent state to the - same thing as the previous latent state, and setting the new - observed RGBD value. - - Returns a trace where previous_state (stored in the arguments) - and new_state (sampled in the choices and returned) are identical. - """ - hyperparams, _ = trace.get_args() - previous_state = trace.get_retval()["new_state"] - trace, _, _, _ = trace.update( - key, - U.g( - (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), - C.kw(rgbd=observed_rgbd), - ), - ) - return trace - - -#### New Inference Programs - - -# Propose new depth outlier probabilities -@jax.jit -def propose_depth_outlier_probability(trace, key): - depth_outlier_probability_sweep = jnp.array([0.01, 0.5, 1.0]) # (k, ) - - current_depth_outlier_probabilities = trace.get_args()[1][ - "depth_outlier_probabilities" - ] # (num_vertices, ) - - depth_outlier_probability_sweep_full = ( - depth_outlier_probability_sweep[..., None] - * jnp.ones_like(current_depth_outlier_probabilities) - ) # (k, num_vertices) where the values in row i are all depth_outlier_probability_sweep[i] - - # Function takes in depth outlier probability array of shape (num_vertices,) and gives scores for each vertex (num_vertices,) - - def get_per_vertex_likelihoods_with_new_depth_outlier_probabilities( - depth_outlier_probabilities, - ): - return info_from_trace( - trace.update( - key, - make_depth_outlier_probabilities_choicemap(depth_outlier_probabilities), - )[0] - )["scores"] - - # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep - likelihood_scores_per_sweep_point_and_vertex = jax.vmap( - get_per_vertex_likelihoods_with_new_depth_outlier_probabilities - )(depth_outlier_probability_sweep_full) # (k, num_vertices) - # P(pixel / nothing | depth outlier prob, latent point) - - depth_outlier_probability_transition_kernel = trace.get_args()[0][ - "depth_outlier_probability_transition_kernel" - ] - vectorized_outlier_probability_transition_kernel_logpdf = jnp.vectorize( - depth_outlier_probability_transition_kernel.logpdf, signature="(),()->()" - ) - - transition_scores_per_sweep_point_and_vertex = ( - vectorized_outlier_probability_transition_kernel_logpdf( - depth_outlier_probability_sweep_full, # (k, num_vertices) - current_depth_outlier_probabilities, # (num_vertices, ) - ) - ) # (k, num_vertices) - - scores_per_sweep_point_and_vertex = ( - likelihood_scores_per_sweep_point_and_vertex - + transition_scores_per_sweep_point_and_vertex - ) - normalized_log_probabilities = jax.nn.log_softmax( - scores_per_sweep_point_and_vertex, axis=0 - ) - - sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) - # sampled_indices = jnp.argmax(scores_per_sweep_point_and_vertex, axis=0) - - sampled_depth_outlier_probabilities = depth_outlier_probability_sweep[ - sampled_indices - ] - - # normalized_log_probabilities is (k, num_vertices) - log_q_depth_outlier_probability = normalized_log_probabilities[ - sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) - ].sum() - - return ( - sampled_depth_outlier_probabilities, - log_q_depth_outlier_probability, - scores_per_sweep_point_and_vertex, - ) - - -# @jax.jit -# def propose_pose(trace, key, pose_sample_variance, pose_sample_concentration): -# pose = Pose.sample_gaussian_vmf_pose( -# key, -# trace.get_choices()["pose"], -# pose_sample_variance, -# pose_sample_concentration, -# ) -# log_q_pose = Pose.logpdf_gaussian_vmf_pose( -# pose, -# trace.get_choices()["pose"], -# pose_sample_variance, -# pose_sample_concentration, -# ) -# return pose, log_q_pose - - -@jax.jit -def propose_color_and_color_outlier_probability(trace, key, outlier_probability_sweep): - # color_outlier_probability_sweep is (k,) shape array - - current_color_outlier_probabilities = trace.get_args()[1][ - "color_outlier_probabilities" - ] - current_colors = trace.get_args()[1]["colors"] - - # num_vertices = current_colors.shape[0] - # num_outlier_grid_points = outlier_probability_sweep.shape[0] - color_outlier_probabilities_sweep = ( - outlier_probability_sweep[..., None] # (num_outlier_grid_points, 1) - * jnp.ones_like(current_color_outlier_probabilities) # (num_vertices,) - ) # (num_outlier_grid_points, num_vertices) - - # We will grid over color values, using a grid that mixes the old and observed - # colors in a set of exact proportions. - # We regard these as coming from uniform proposals where we sample the RGB - # values uniformly between the mixed R, G, and B values with mixtures between - # [0., .125], [.125, .5], [.5, .875], [.875, 1.]. - # So the q scores will be .125^3, .375^3, .375^3, .125^3. - # TODO: we really ought to add a small amount of proposal probability mass - # onto the points at the end, to capture the fact that the posterior could allow - # colors outside the considered interpolation window. - color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) - # num_color_grid_points = len(color_interpolations_per_proposal) - - observed_colors = info_from_trace(trace)["observed_rgbd_masked"][ - ..., :3 - ] # (num_vertices, 3) - color_sweep = observed_colors[None, ...] * color_interpolations_per_proposal[ - :, None, None - ] + current_colors[None, ...] * ( - 1 - color_interpolations_per_proposal[:, None, None] - ) # (num_color_grid_points, num_vertices, 3) - - # Function takes in color and color outlier probabilities array of shapes (num_vertices,3) and (num_vertices,) respectively - # and gives scores for each vertex (num_vertices,) - def get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities( - colors, color_outlier_probabilities - ): - return info_from_trace( - trace.update( - key, - make_color_outlier_probabilities_choicemap(color_outlier_probabilities) - ^ make_colors_choicemap(colors), - )[0] - )["scores"] - - vmap_version = jax.vmap( - jax.vmap( - get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities, - in_axes=(None, 0), - ), - in_axes=(0, None), - ) - - # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep - likelihood_scores_per_sweep_point_and_vertex = vmap_version( - color_sweep, color_outlier_probabilities_sweep - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - # Color outlier transition scores - color_outlier_probability_transition_kernel = trace.get_args()[0][ - "color_outlier_probability_transition_kernel" - ] - vectorized_outlier_probability_transition_kernel_logpdf = jnp.vectorize( - color_outlier_probability_transition_kernel.logpdf, signature="(),()->()" - ) - color_outlier_transition_scores_per_sweep_point_and_vertex = vectorized_outlier_probability_transition_kernel_logpdf( - color_outlier_probabilities_sweep, # (num_outlier_grid_points, num_vertices) - current_color_outlier_probabilities, - ) # (num_outlier_grid_points, num_vertices) - - color_transition_kernel = trace.get_args()[0]["color_transition_kernel"] - vectorized_color_transition_kernel_logpdf = jnp.vectorize( - color_transition_kernel.logpdf, signature="(3),(3)->()" - ) - color_transition_scores_per_sweep_point_and_vertex = ( - vectorized_color_transition_kernel_logpdf(color_sweep, current_colors) - ) # (num_color_grid_points, num_vertices) - - scores_per_sweep_point_and_vertex = ( - likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points, num_vertices) - + color_outlier_transition_scores_per_sweep_point_and_vertex[None, ...] - + color_transition_scores_per_sweep_point_and_vertex[:, None, ...] - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - unraveled_scores = scores_per_sweep_point_and_vertex.reshape( - -1, scores_per_sweep_point_and_vertex.shape[-1] - ) - normalized_log_probabilities = jax.nn.log_softmax(unraveled_scores, axis=0) - sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) - - color_sweep_indices, color_outlier_sweep_indices = jnp.unravel_index( - sampled_indices, scores_per_sweep_point_and_vertex.shape[:2] - ) - - # color_sweep is (num_outlier_grid_points, num_vertices, 3) - # outlier_probability_sweep is (num_outlier_grid_points,) - # color_outlier_probabilities_sweep is (num_outlier_grid_points, num_vertices) - sampled_colors = color_sweep[color_sweep_indices, jnp.arange(color_sweep.shape[1])] - sampled_color_outlier_probabilities = outlier_probability_sweep[ - color_outlier_sweep_indices - ] - - log_q_color_and_color_outlier_probability = normalized_log_probabilities[ - sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) - ].sum() - - # log_q = estimate of q(all these colors, all these outliers ; inputs) - # Only source of real randomness = sampling indices. Captured in log_q_color_and_color_outlier_probability. - # But we also want to be careful with the continuous values... - # (1) outlier probs. --> change the model to have discrete grid. [Do later.] - # (2) colors. --> 1/q() - # uniform(old r, 2/3 oldr + 1/3 newr) 0 | uniform(0, 0.1) - # uniform(1/3, 2/3) # .5 | uniform(.1, .9) - # uniform(2/3, 1) # 1 | uniform(.9, 1) - # - # q(c1) * q(c2) * q(c3) - # but we just output c2 - # q(the c values we output, marginalizing over the other choices) - # -> just output q(c2) - - # We will treat this like the case where each sweep is uniform, so the q scores - # are each (oldr - obsr)/3 * (oldg - obsg)/3 * (oldb - obsb)/3. - q_prob_per_vertex = ( - 1.0 / ((jnp.abs(current_colors - observed_colors) / 3) + 0.001) - ).prod(-1) - log_q_for_the_color_proposal = jnp.log(q_prob_per_vertex).sum() - - return ( - sampled_colors, - sampled_color_outlier_probabilities, - log_q_color_and_color_outlier_probability + log_q_for_the_color_proposal, - scores_per_sweep_point_and_vertex, - ) - - -@jax.jit -def propose_depth_variance(trace, key, depth_variance_sweep): - scores = jax.vmap( - lambda variance: trace.update(key, C["depth_variance"].set(variance))[ - 0 - ].get_score() - )(depth_variance_sweep) - scores = jax.nn.log_softmax(scores) - sampled_index = jax.random.categorical(key, scores) - sampled_depth_variance = depth_variance_sweep[sampled_index] - log_q_depth_variance = scores[sampled_index] - return sampled_depth_variance, log_q_depth_variance - - -@jax.jit -def propose_color_variance(trace, key, color_variance_sweep): - scores = jax.vmap( - lambda variance: trace.update(key, C["color_variance"].set(variance))[ - 0 - ].get_score() - )(color_variance_sweep) - scores = jax.nn.log_softmax(scores) - sampled_index = jax.random.categorical(key, scores) - sampled_color_variance = color_variance_sweep[sampled_index] - log_q_color_variance = scores[sampled_index] - return sampled_color_variance, log_q_color_variance - - -@jax.jit -def propose_update(trace, key, pose): - total_log_q = 0.0 - - # Update pose - # pose, log_q_pose = propose_pose( - # trace, key, pose_sample_variance, pose_sample_concentration - # ) - trace = trace.update(key, C["pose"].set(pose))[0] - # total_log_q += log_q_pose - - # Update depth outlier probability - sampled_depth_outlier_probability, log_q_depth_outlier_probability, _ = ( - propose_depth_outlier_probability(trace, key) - ) - trace = trace.update( - key, - make_depth_outlier_probabilities_choicemap(sampled_depth_outlier_probability), - )[0] - total_log_q += log_q_depth_outlier_probability - - # Update color and color outlier probability - color_outlier_probability_sweep = jnp.array([0.01, 0.5, 1.0]) - colors, color_outlier_probability, log_q_color_color_outlier_probability, _ = ( - propose_color_and_color_outlier_probability( - trace, key, color_outlier_probability_sweep - ) - ) - trace = trace.update( - key, - make_colors_choicemap(colors) - ^ make_color_outlier_probabilities_choicemap(color_outlier_probability), - )[0] - total_log_q += log_q_color_color_outlier_probability - - # # Update depth variance - # depth_variance_sweep = jnp.array([0.0005, 0.001, 0.0025, 0.005, 0.01]) - # depth_variance, log_q_depth_variance = propose_depth_variance( - # trace, key, depth_variance_sweep - # ) - # trace = trace.update(key, C["depth_variance"].set(depth_variance))[0] - # total_log_q += log_q_depth_variance - - # # Update color variance - # color_variance_sweep = jnp.array([0.005, 0.01, 0.05, 0.1, 0.2]) - # color_variance, log_q_color_variance = propose_color_variance( - # trace, key, color_variance_sweep - # ) - # trace.update(key, C["color_variance"].set(color_variance))[0] - # total_log_q += log_q_color_variance - return trace, total_log_q - - -@jax.jit -def propose_update_get_score(trace, key, pose): - new_trace, log_q = propose_update(trace, key, pose) - # score is an estimate of P(data, pose | previous state) - return new_trace.get_score() - log_q - - -propose_update_get_score_vmap = jax.jit( - jax.vmap(propose_update_get_score, in_axes=(None, None, 0)) -) - - -def inference_step_without_advance(trace, key): - number = 20000 - - var, conc = 0.02, 2000.0 - - for _ in range(10): - key = jax.random.split(key, 2)[-1] - keys = jax.random.split(key, number) - poses = Pose.concatenate_poses( - [ - Pose.sample_gaussian_vmf_pose_vmap( - keys, trace.get_choices()["pose"], var, conc - ), - trace.get_choices()["pose"][None, ...], - ] - ) - pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( - poses, trace.get_choices()["pose"], var, conc - ) - scores = propose_update_get_score_vmap(trace, key, poses) - scores = ( - scores - pose_scores - ) # After this, scores are fair estimates of P(data | previous state) - # and can be used to resample the choice sets. - index = jax.random.categorical(key, scores) - trace = propose_update(trace, key, poses[index])[0] - - return trace - - -def inference_step(trace, key, observed_rgbd): - trace = advance_time(key, trace, observed_rgbd) - trace = inference_step_without_advance(trace, key) - return trace - - -# ## Old Inference moves ### -# @jax.jit -# def update_colors(trace): -# key = jax.random.PRNGKey(0) -# info = info_from_trace(trace) - -# color_delta = ( -# info["observed_rgbd_masked"][..., :3] - trace.get_choices()["colors", ...] -# ) -# max_color_shift = trace.get_args()[0]["max_color_shift"] -# color_delta_clipped = jnp.clip(color_delta, -max_color_shift, max_color_shift) - -# trace = trace.update( -# key, -# make_colors_choicemap(trace.get_choices()["colors", ...] + color_delta_clipped), -# )[0] -# return trace - - -# @jax.jit -# def score_with_give_pose_and_then_color_update(trace, pose, outlier_probability_sweep): -# key = jax.random.PRNGKey(0) -# trace = trace.update(key, C["pose"].set(pose))[0] - -# trace = update_colors(trace) - -# trace = grid_move_on_color_outlier_probability(trace, outlier_probability_sweep) -# trace = grid_move_on_depth_outlier_probability(trace, outlier_probability_sweep) - -# return trace.get_score() - - -# @jax.jit -# def grid_move_on_depth_outlier_probability(trace, sweep): -# current_setting = trace.get_choices()["depth_outlier_probabilities", ...] -# potential_values = sweep[..., None] * jnp.ones_like(current_setting) -# key = jax.random.PRNGKey(0) -# get_vertex_scores_vmap = jax.vmap( -# lambda x: info_from_trace( -# trace.update(key, make_depth_outlier_probabilities_choicemap(x))[0] -# )["scores"] -# ) -# scores = get_vertex_scores_vmap(potential_values) -# best_setting = sweep[jnp.argmax(scores, axis=0)] -# return trace.update(key, make_depth_outlier_probabilities_choicemap(best_setting))[ -# 0 -# ] - - -# @jax.jit -# def grid_move_on_color_outlier_probability(trace, sweep): -# current_setting = trace.get_choices()["color_outlier_probabilities", ...] - -# potential_values = sweep[..., None] * jnp.ones_like(current_setting) -# key = jax.random.PRNGKey(0) -# get_vertex_scores_vmap = jax.vmap( -# lambda x: info_from_trace( -# trace.update(key, make_color_outlier_probabilities_choicemap(x))[0] -# )["scores"] -# ) -# scores = get_vertex_scores_vmap(potential_values) -# best_setting = sweep[jnp.argmax(scores, axis=0)] -# return trace.update(key, make_color_outlier_probabilities_choicemap(best_setting))[ -# 0 -# ] - - -# @jax.jit -# def update_address_with_sweep(trace, address, sweep): -# scores = b3d.enumerate_choices_get_scores(trace, address, sweep) -# best_setting = sweep[jnp.argmax(scores)] -# return b3d.update_choices(trace, address, best_setting) - - -# @partial(jax.jit, static_argnames=("number",)) -# def gaussian_vmf_enumerative_move_with_other_updates( -# trace, key, address, varianc, conc, number, outlier_probability_sweep -# ): -# keys = jax.random.split(key, number) -# poses = Pose.concatenate_poses( -# [ -# Pose.sample_gaussian_vmf_pose_vmap( -# keys, trace.get_choices()["pose"], 0.02, 2000.0 -# ), -# trace.get_choices()["pose"][None, ...], -# ] -# ) - -# scores = jax.vmap( -# score_with_give_pose_and_then_color_update, in_axes=(None, 0, None) -# )(trace, poses, outlier_probability_sweep) - -# key = b3d.split_key(keys[-1]) -# sampled_pose = poses[scores.argmax()] -# trace = trace.update(key, C["pose"].set(sampled_pose))[0] -# return trace, key - - -# def inference_step_old(trace, key, observed_rgbd): -# trace = advance_time(key, trace, observed_rgbd) - -# outlier_probability_sweep = jnp.array([0.01, 0.5, 1.0]) -# num_grid_points = 20000 -# for _ in range(2): -# trace, key = gaussian_vmf_enumerative_move_with_other_updates( -# trace, -# key, -# Pytree.const(("pose",)), -# 0.04, -# 200.0, -# num_grid_points, -# outlier_probability_sweep, -# ) -# trace, key = gaussian_vmf_enumerative_move_with_other_updates( -# trace, -# key, -# Pytree.const(("pose",)), -# 0.01, -# 500.0, -# num_grid_points, -# outlier_probability_sweep, -# ) -# trace, key = gaussian_vmf_enumerative_move_with_other_updates( -# trace, -# key, -# Pytree.const(("pose",)), -# 0.005, -# 1000.0, -# num_grid_points, -# outlier_probability_sweep, -# ) -# trace, key = gaussian_vmf_enumerative_move_with_other_updates( -# trace, -# key, -# Pytree.const(("pose",)), -# 0.001, -# 2000.0, -# num_grid_points, -# outlier_probability_sweep, -# ) - -# trace = grid_move_on_color_outlier_probability(trace, outlier_probability_sweep) -# trace = grid_move_on_depth_outlier_probability(trace, outlier_probability_sweep) - -# trace = update_address_with_sweep( -# trace, -# Pytree.const(("color_variance",)), -# jnp.array([0.005, 0.01, 0.05, 0.1, 0.2]), -# ) -# trace = update_address_with_sweep( -# trace, -# Pytree.const(("depth_variance",)), -# jnp.array([0.0005, 0.001, 0.0025, 0.005, 0.01]), -# ) - -# trace = update_colors(trace) - -# trace = grid_move_on_color_outlier_probability(trace, outlier_probability_sweep) -# trace = grid_move_on_depth_outlier_probability(trace, outlier_probability_sweep) -# return trace diff --git a/src/b3d/chisight/dynamic_object_model/dynamic_object_model.py b/src/b3d/chisight/dynamic_object_model/dynamic_object_model.py deleted file mode 100644 index 2542d16d..00000000 --- a/src/b3d/chisight/dynamic_object_model/dynamic_object_model.py +++ /dev/null @@ -1,204 +0,0 @@ -import genjax -import jax -import jax.numpy as jnp -import rerun as rr -from genjax import ChoiceMapBuilder as C -from genjax import Pytree - -import b3d -from b3d import Pose - -# LIKELIHOOD = "aggregate_mean" -LIKELIHOOD = "project_no_occlusions" - -if LIKELIHOOD == "project_no_occlusions": - from b3d.chisight.dynamic_object_model.likelihoods.project_no_occlusions_kernel import ( - likelihood_func, - sample_func, - ) -elif LIKELIHOOD == "aggregate_mean": - from b3d.chisight.dynamic_object_model.likelihoods.aggreate_mean_image_kernel import ( - likelihood_func, - sample_func, - ) -else: - raise NotImplementedError(f"Unknown likelihood: {LIKELIHOOD}") - - -@Pytree.dataclass -class ImageLikelihood(genjax.ExactDensity): - def sample(self, key, likelihood_args): - return sample_func(key, likelihood_args) - - def logpdf(self, observed_rgbd, likelihood_args): - return likelihood_func(observed_rgbd, likelihood_args)["score"] - - -image_likelihood = ImageLikelihood() - - -@jax.jit -def info_from_trace(trace): - return likelihood_func( - trace.get_choices()["rgbd"], - trace.get_retval()["likelihood_args"], - ) - - -@genjax.gen -def dynamic_object_generative_model(hyperparams, previous_state): - vertices = hyperparams["vertices"] - - pose = ( - Pose.uniform_pose_centered( - previous_state["pose"], - -hyperparams["max_pose_position_shift"] * jnp.ones(3), - hyperparams["max_pose_position_shift"] * jnp.ones(3), - ) - @ "pose" - ) - - color_transition_kernel = hyperparams["color_transition_kernel"] - colors = color_transition_kernel.vmap()(previous_state["colors"]) @ "colors" - - color_outlier_probability_transition_kernel = hyperparams[ - "color_outlier_probability_transition_kernel" - ] - color_outlier_probabilities = ( - color_outlier_probability_transition_kernel.vmap()( - previous_state["color_outlier_probabilities"] - ) - @ "color_outlier_probabilities" - ) - - depth_outlier_probability_transition_kernel = hyperparams[ - "depth_outlier_probability_transition_kernel" - ] - depth_outlier_probabilities = ( - depth_outlier_probability_transition_kernel.vmap()( - previous_state["depth_outlier_probabilities"] - ) - @ "depth_outlier_probabilities" - ) - - depth_variance = genjax.uniform(0.0001, 100000.0) @ "depth_variance" - color_variance = genjax.uniform(0.0001, 100000.0) @ "color_variance" - - likelihood_args = { - "fx": hyperparams["fx"], - "fy": hyperparams["fy"], - "cx": hyperparams["cx"], - "cy": hyperparams["cy"], - "image_height": hyperparams["image_height"], - "image_width": hyperparams["image_width"], - "vertices": vertices, - "pose": pose, - "colors": colors, - "color_outlier_probabilities": color_outlier_probabilities, - "depth_outlier_probabilities": depth_outlier_probabilities, - "depth_variance": depth_variance, - "color_variance": color_variance, - } - rgbd = image_likelihood(likelihood_args) @ "rgbd" - - new_state = { - "pose": pose, - "colors": colors, - "color_outlier_probabilities": color_outlier_probabilities, - "depth_outlier_probabilities": depth_outlier_probabilities, - } - return { - "new_state": new_state, - "rgbd": rgbd, - "likelihood_args": likelihood_args, - } - - -def make_colors_choicemap(colors): - return jax.vmap(lambda idx: C["colors", idx].set(colors[idx]))( - jnp.arange(len(colors)) - ) - - -def make_color_outlier_probabilities_choicemap(color_outlier_probabilities): - return jax.vmap( - lambda idx: C["color_outlier_probabilities", idx].set( - color_outlier_probabilities[idx] - ) - )(jnp.arange(len(color_outlier_probabilities))) - - -def make_depth_outlier_probabilities_choicemap(depth_outlier_probabilities): - return jax.vmap( - lambda idx: C["depth_outlier_probabilities", idx].set( - depth_outlier_probabilities[idx] - ) - )(jnp.arange(len(depth_outlier_probabilities))) - - -### Viz ### -def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): - info = info_from_trace(trace) - b3d.utils.rr_set_time(t) - likelihood_args = trace.get_retval()["likelihood_args"] - fx, fy, cx, cy = ( - likelihood_args["fx"], - likelihood_args["fy"], - likelihood_args["cx"], - likelihood_args["cy"], - ) - vertices = trace.get_args()[0]["vertices"] - - info = info_from_trace(trace) - rr.log("image", rr.Image(trace.get_choices()["rgbd"][..., :3])) - b3d.rr_log_rgb(trace.get_choices()["rgbd"][..., :3], "image/rgb/observed") - b3d.rr_log_rgb(info["latent_rgbd"][..., :3], "image/rgb/latent") - b3d.rr_log_depth(trace.get_choices()["rgbd"][..., 3], "image/depth/observed") - b3d.rr_log_depth(info["latent_rgbd"][..., 3], "image/depth/latent") - - b3d.rr_log_cloud( - info["transformed_points"], - "scene/latent", - trace.get_choices()["colors", ...], - ) - b3d.rr_log_cloud( - b3d.xyz_from_depth( - trace.get_retval()["rgbd"][..., 3], - fx, - fy, - cx, - cy, - ), - "scene/observed", - trace.get_retval()["rgbd"][..., :3].reshape(-1, 3), - ) - - b3d.rr_log_cloud( - vertices, - "object/model", - trace.get_choices()["colors", ...], - ) - b3d.rr_log_cloud( - vertices, - "object/color_outlier_probabilities", - jnp.array([[1.0, 0.0, 0.0]]) - * trace.get_choices()["color_outlier_probabilities", ...][:, None], - ) - b3d.rr_log_cloud( - vertices, - "object/depth_outlier_probabilities", - jnp.array([[0.0, 1.0, 0.0]]) - * trace.get_choices()["depth_outlier_probabilities", ...][:, None], - ) - - if ground_truth_vertices is not None: - b3d.rr_log_cloud( - trace.get_choices()["pose"].apply(ground_truth_vertices), - "scene/full_object_model", - ) - - if ground_truth_pose: - b3d.rr_log_cloud( - ground_truth_pose.apply(ground_truth_vertices), - "scene/ground_truth_object_mesh", - ) diff --git a/src/b3d/chisight/dynamic_object_model/likelihoods/__init__.py b/src/b3d/chisight/dynamic_object_model/likelihoods/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/src/b3d/chisight/dynamic_object_model/likelihoods/aggreate_mean_image_kernel.py b/src/b3d/chisight/dynamic_object_model/likelihoods/aggreate_mean_image_kernel.py deleted file mode 100644 index bc236479..00000000 --- a/src/b3d/chisight/dynamic_object_model/likelihoods/aggreate_mean_image_kernel.py +++ /dev/null @@ -1,141 +0,0 @@ -import genjax -import jax -import jax.numpy as jnp - -import b3d - -# # Version 2 [approximate this with a mean]: -# # `pts` is the set of all points projecting to one pixel (i, j) -# # `nonregistration_prob[pt]` = probability a point is not registered, if it is the only one observed (nonregistration_prob = "outlier prob") -# # `color[pt]` = RGB or D value for the point -# # 1. Compute overall_p_nonregistered = prod_{pt} nonregistration_prob[pt]. [Set to 1.0 if pts is empty.] -# # 2. Compute the mean of all the colors for each point, where the color for `pt` is weighted proportionally to (1 - nonregistration_prob[pt]) -# # 3. Sample from a mixture of [1] a uniform, with probability `nonregistration_prob[pt]`, and [2] a laplace around the mean color - - -@jax.jit -def sample_func(key, args): - transformed_points = args["pose"].apply(args["vertices"]) - pixels = jnp.rint( - b3d.xyz_to_pixel_coordinates( - transformed_points, args["fx"], args["fy"], args["cx"], args["cy"] - ) - - 0.5 - ).astype(jnp.int32) - - latent_image_sum = jnp.zeros( - (args["image_height"].const, args["image_width"].const, 4) - ) - latent_image_sum = latent_image_sum.at[pixels[..., 0], pixels[..., 1], :3].add( - args["colors"] * (1 - args["color_outlier_probability"])[:, None] - ) - latent_image_sum = latent_image_sum.at[pixels[..., 0], pixels[..., 1], 3].add( - transformed_points[..., 2] * (1 - args["depth_outlier_probability"]) - ) - - projected_points_count = jnp.zeros( - (args["image_height"].const, args["image_width"].const) - ) - projected_points_count = projected_points_count.at[ - pixels[..., 0], pixels[..., 1] - ].add(1) - - non_registration_probability = jnp.ones( - (args["image_height"].const, args["image_width"].const) - ) - non_registration_probability = non_registration_probability.at[ - pixels[..., 0], pixels[..., 1] - ].multiply(args["color_outlier_probability"]) - - latent_image_mean = latent_image_sum / (projected_points_count[..., None] + 1e-10) - - is_outlier_pixel = ( - jax.random.uniform(key, non_registration_probability.shape) - < non_registration_probability - ) - variances = jnp.array( - [ - args["color_variance"], - args["color_variance"], - args["color_variance"], - args["depth_variance"], - ] - ) - latent_image_noised = genjax.laplace.sample(key, latent_image_mean, variances) - latent_image_uniform = jax.random.uniform(key, latent_image_mean.shape) * jnp.array( - [1.0, 1.0, 1.0, 5.0] - ) - return ( - latent_image_noised * ~is_outlier_pixel[..., None] - + latent_image_uniform * is_outlier_pixel[..., None] - ) - - -@jax.jit -def likelihood_func(observed_rgbd, args): - transformed_points = args["pose"].apply(args["vertices"]) - pixels = jnp.rint( - b3d.xyz_to_pixel_coordinates( - transformed_points, args["fx"], args["fy"], args["cx"], args["cy"] - ) - ).astype(jnp.int32) - - latent_image_sum = jnp.zeros( - (args["image_height"].const, args["image_width"].const, 4) - ) - latent_image_sum = latent_image_sum.at[pixels[..., 0], pixels[..., 1], :3].add( - args["colors"] * (1 - args["color_outlier_probability"])[:, None] - ) - latent_image_sum = latent_image_sum.at[pixels[..., 0], pixels[..., 1], 3].add( - transformed_points[..., 2] * (1 - args["depth_outlier_probability"]) - ) - - projected_points_count = jnp.zeros( - (args["image_height"].const, args["image_width"].const) - ) - projected_points_count = projected_points_count.at[ - pixels[..., 0], pixels[..., 1] - ].add(1) - - non_registration_probability = jnp.ones( - (args["image_height"].const, args["image_width"].const) - ) - non_registration_probability = non_registration_probability.at[ - pixels[..., 0], pixels[..., 1] - ].multiply(args["color_outlier_probability"]) - - latent_image_mean = latent_image_sum / (projected_points_count[..., None] + 1e-10) - - variances = jnp.array( - [ - args["color_variance"], - args["color_variance"], - args["color_variance"], - args["depth_variance"], - ] - ) - - # pixel_probability = jax.scipy.stats.laplace.logpdf( - # observed_rgbd, latent_image_mean, variances - # ) + jnp.log(1 - non_registration_probability)[...,None] - - pixel_probability = jnp.logaddexp( - jax.scipy.stats.laplace.logpdf(observed_rgbd, latent_image_mean, variances) - + jnp.log(1 - non_registration_probability)[..., None], - (jnp.log(non_registration_probability) + jnp.log(1 / 1.0**3))[..., None] - * jnp.ones_like(observed_rgbd), - ) - - return { - "score": pixel_probability.sum(), - "scores": pixel_probability, - "latent_rgbd": latent_image_mean, - "transformed_points": transformed_points, - "observed_rgbd_masked": observed_rgbd[pixels[..., 0], pixels[..., 1]], - } - - -aggregate_mean_image_kerenel_likelihood_func_and_sample_func = ( - likelihood_func, - sample_func, -) diff --git a/src/b3d/chisight/dynamic_object_model/likelihoods/kfold_image_kernel.py b/src/b3d/chisight/dynamic_object_model/likelihoods/kfold_image_kernel.py deleted file mode 100644 index f874e70b..00000000 --- a/src/b3d/chisight/dynamic_object_model/likelihoods/kfold_image_kernel.py +++ /dev/null @@ -1,429 +0,0 @@ -import genjax -import jax -import jax.numpy as jnp -from genjax import Pytree -from tensorflow_probability.substrates import jax as tfp - -import b3d -from b3d.chisight.dense.likelihoods.other_likelihoods import ( - ImageDistFromPixelDist, -) - - -def raycast_to_image_nondeterministic(key, intrinsics, vertices_in_camera_frame, K): - """ - Returns an array of shape (H, W, K) containing K point indices, or -1 to indicate no point was registered. - """ - N_pts = vertices_in_camera_frame.shape[0] - key1, key2 = jax.random.split(key, 2) - - projected_pixel_coordinates = jnp.rint( - b3d.xyz_to_pixel_coordinates( - vertices_in_camera_frame, - intrinsics["fx"], - intrinsics["fy"], - intrinsics["cx"], - intrinsics["cy"], - ) - - 0.5 - ).astype(jnp.int32) - permutation = jax.random.permutation(key1, N_pts) - shuffled_pixel_coordinates = projected_pixel_coordinates[permutation] - # shuffled_pixel_coordinates = projected_pixel_coordinates # = jax.random.permutation(key, projected_pixel_coordinates) - - random_indices = jax.random.randint( - key2, (N_pts,), 0, K - ) # (N_pts,) array of random indices from 0 to K-1 - registered_pixel_indices = -jnp.ones( - (intrinsics["height"], intrinsics["width"], K), dtype=int - ) - registered_pixel_indices = registered_pixel_indices.at[ - shuffled_pixel_coordinates[:, 0], - shuffled_pixel_coordinates[:, 1], - random_indices, - ].set(permutation) # jnp.arange(N_pts)) - - return registered_pixel_indices - - -@Pytree.dataclass -class TruncatedLaplace(genjax.ExactDensity): - """ - This is a distribution on the interval (low, high). - The generative process is: - 1. Sample x ~ laplace(loc, scale). - 2. If x < low, sample y ~ uniform(low, low + uniform_window_size) and return y. - 3. If x > high, sample y ~ uniform(high - uniform_window_size, high) and return y. - 4. Otherwise, return x. - - Args: - - loc: float - - scale: float - - low: float - - high: float - - uniform_window_size: float - - Support: - - x in (low, high) [a float] - """ - - def sample(self, key, loc, scale, low, high, uniform_window_size): - assert low < high - assert low + uniform_window_size < high - uniform_window_size - k1, k2 = jax.random.split(key, 2) - x = tfp.distributions.Laplace(loc, scale).sample(seed=k1) - u = jax.random.uniform(k2, ()) * uniform_window_size - return jnp.where( - x > high, high - uniform_window_size + u, jnp.where(x < low, low + u, x) - ) - - def logpdf(self, obs, loc, scale, low, high, uniform_window_size): - assert low < high - assert low + uniform_window_size < high - uniform_window_size - laplace_logpdf = tfp.distributions.Laplace(loc, scale).log_prob(obs) - laplace_logp_below_low = tfp.distributions.Laplace(loc, scale).log_cdf(low) - laplace_logp_above_high = tfp.distributions.Laplace( - loc, scale - ).log_survival_function(high) - log_window_size = jnp.log(uniform_window_size) - - return jnp.where( - jnp.logical_and( - low + uniform_window_size < obs, obs < high - uniform_window_size - ), - laplace_logpdf, - jnp.where( - obs < low + uniform_window_size, - jnp.logaddexp(laplace_logp_below_low - log_window_size, laplace_logpdf), - jnp.logaddexp( - laplace_logp_above_high - log_window_size, laplace_logpdf - ), - ), - ) - - -truncated_laplace = TruncatedLaplace() - - -_FIXED_COLOR_UNIFORM_WINDOW = 1 / 255 -_FIXED_DEPTH_UNIFORM_WINDOW = 0.01 - - -@Pytree.dataclass -class TruncatedColorLaplace(genjax.ExactDensity): - """ - Args: - - loc: (3,) array (loc for R, G, B channels) - - shared_scale: float (scale, shared across R, G, B channels) - - uniform_window_size: float [optional; defaults to 1/255] - - Support: - - rgb in [0, 1]^3 [a 3D array] - """ - - def sample( - self, key, loc, shared_scale, uniform_window_size=_FIXED_COLOR_UNIFORM_WINDOW - ): - return jax.vmap( - lambda k, lc: truncated_laplace.sample( - k, lc, shared_scale, 0.0, 1.0, uniform_window_size - ), - in_axes=(0, 0), - )(jax.random.split(key, loc.shape[0]), loc) - - def logpdf( - self, obs, loc, shared_scale, uniform_window_size=_FIXED_COLOR_UNIFORM_WINDOW - ): - return jax.vmap( - lambda o, lc: truncated_laplace.logpdf( - o, lc, shared_scale, 0.0, 1.0, uniform_window_size - ), - in_axes=(0, 0), - )(obs, loc).sum() - - -truncated_color_laplace = TruncatedColorLaplace() - - -def _access(arr, idx): - return jax.lax.dynamic_index_in_dim(arr, idx, axis=0, keepdims=False) - - -@Pytree.dataclass -class PixelDistribution(genjax.ExactDensity): - """ - Distribution over the color observed at a pixel of an RGBD image, - given a set of points that may be registered at the pixel. - Each of the N points has an associated color_outlier_prob, - depth_outlier_prob, and RGBD value. - There is a global color_scale and depth_scale. - An array `registered_point_indices` of shape (K,) - is provided giving the indices of all the points registered at this pixel; - the value -1 indicates that no point is registered at this slot of the - `registered_point_indices` array. - - Args: - registered_point_indices: (K,) - all_rgbds: (N, 4) - color_outlier_probs: (N,) - depth_outlier_probs: (N,) - color_scale: float - depth_scale: float - near: float - far: float - - Support: - - `rgbd` in [0, 1]^3 x [near, far] [a 4D array] - - K is the max number of points registered at a pixel, and - N is the number of points in the scene. - Indices in registered_point_indices are in the range [-1, N-1]; - -1 indicates that no point is registered in this slot. - - The generative process is: - 1. If there are no registered points, sample uniformly from the color and depth ranges. - 2. Otherwise, sample an index idx from registered_point_indices s.t. idx > -1. - 3. Get the rgbd, color_outlier_prob, and depth_outlier_prob for this index. - 4. Sample is_depth_outlier ~ Bernoulli(depth_outlier_prob). - 5. Sample is_color_outlier ~ Bernoulli(color_outlier_prob). - 6. If is_depth_outlier, sample depth uniformly from [near, far]. - 7. Otherwise, sample depth from a truncated Laplace distribution centered at all_rgbds[idx, 3]. - 8. If is_color_outlier, sample color uniformly from [0, 1]^3. - 9. Otherwise, sample color from a truncated Laplace distribution centered at all_rgbds[idx, :3]. - - The generative process for the truncated Laplace distribuitons - sample from a Laplace, and if the sample is outside the range [low, high] - (which is either [near, far] for depth or [0, 1] for color), the sample is replaced with a uniform sample - from the range [low, low + uniform_window_size] or [high - uniform_window_size, high]. - The value `uniform_window_size` is currently fixed at 0.01 for depth and 1/255 for color. - """ - - def sample( - self, - key, - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ): - k1, k2, k3, k4, k5, k6, k7 = jax.random.split(key, 7) - n_registered_points = jnp.sum(registered_point_indices != -1) - idxprobs = jnp.where( - registered_point_indices >= 0, 1.0 / n_registered_points, 0.0 - ) - idx = genjax.categorical.sample(k1, jnp.log(idxprobs)) - depth_outlier_prob = jnp.where( - n_registered_points == 0, - 1.0, - _access(depth_outlier_probs, _access(registered_point_indices, idx)), - ) - color_outlier_prob = jnp.where( - n_registered_points == 0, - 1.0, - _access(color_outlier_probs, _access(registered_point_indices, idx)), - ) - uniform_depth_sample = jax.random.uniform(k2, (), minval=near, maxval=far) - laplace_depth_sample = truncated_laplace.sample( - k3, - _access(all_rgbds, _access(registered_point_indices, idx))[3], - depth_scale, - near, - far, - _FIXED_DEPTH_UNIFORM_WINDOW, - ) - uniform_rgb_sample = jax.random.uniform(k4, (3,), minval=0.0, maxval=1.0) - laplace_rgb_sample = truncated_color_laplace.sample( - k5, - _access(all_rgbds, _access(registered_point_indices, idx))[:3], - color_scale, - ) - depth_is_outlier = jax.random.bernoulli(k6, depth_outlier_prob) - color_is_outlier = jax.random.bernoulli(k7, color_outlier_prob) - depth_sample = jnp.where( - depth_is_outlier, uniform_depth_sample, laplace_depth_sample - ) - rgb_sample = jnp.where(color_is_outlier, uniform_rgb_sample, laplace_rgb_sample) - return jnp.concatenate([rgb_sample, jnp.array([depth_sample])]) - - def logpdf( - self, - obs, - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ): - uniform_depth_logpdf = -jnp.log(far - near) - uniform_rgb_logpdf = -jnp.log(1.0**3) - - def get_logpdf_given_idx(idx): - depth_outlier_prob = _access( - depth_outlier_probs, _access(registered_point_indices, idx) - ) - color_outlier_prob = _access( - color_outlier_probs, _access(registered_point_indices, idx) - ) - laplace_depth_logpdf = truncated_laplace.logpdf( - obs[3], - _access(all_rgbds, _access(registered_point_indices, idx))[3], - depth_scale, - near, - far, - _FIXED_DEPTH_UNIFORM_WINDOW, - ) - laplace_rgb_logpdf = truncated_color_laplace.logpdf( - obs[:3], - _access(all_rgbds, _access(registered_point_indices, idx))[:3], - color_scale, - ) - log_p_depth = jnp.logaddexp( - jnp.log(depth_outlier_prob) + uniform_depth_logpdf, - jnp.log(1 - depth_outlier_prob) + laplace_depth_logpdf, - ) - log_p_rgb = jnp.logaddexp( - jnp.log(color_outlier_prob) + uniform_rgb_logpdf, - jnp.log(1 - color_outlier_prob) + laplace_rgb_logpdf, - ) - return log_p_depth + log_p_rgb - - n_registered_points = jnp.sum(registered_point_indices != -1) - logpdfs_given_each_idx = jax.vmap(get_logpdf_given_idx)( - jnp.arange(registered_point_indices.shape[0]) - ) - logpdf_of_choosing_each_idx = jnp.where( - registered_point_indices < 0, -jnp.inf, -jnp.log(n_registered_points) - ) - assert len((logpdf_of_choosing_each_idx + logpdfs_given_each_idx).shape) == 1 - return jnp.where( - n_registered_points > 0, - jax.scipy.special.logsumexp( - logpdf_of_choosing_each_idx + logpdfs_given_each_idx - ), - uniform_depth_logpdf + uniform_rgb_logpdf, - ) - - -pixel_distribution = PixelDistribution() - -mapped_pixel_distribution = ImageDistFromPixelDist( - # The only mapped arg is the first one; the others are shared across pixels. - pixel_distribution, - (True, False, False, False, False, False, False, False), -) -# ^ This distribution accepts (height, width, registered_pixel_indices, *args), -# where `registered_pixel_indices` has shape (height, width, K), -# and `args` is the list of all args to PixelDistribution after `registered_pixel_indices`. - - -@Pytree.dataclass -class KfoldMixturePointsToImageKernel(genjax.Distribution): - """ - KfoldMixturePointsToImageKernel(K) is a kernel from a set of points to an image. - Each pixel in the image will register a random subset of up to K points from the - subset of the provided points which project directly to that pixel. - - Given those up to K registered points per pixel, each pixel is independently - sampled from `PixelDistribution` (see docstring for `PixelDistribution` for details). - - Constructor args: - - K: int - - Distribution args: - - intrinsics: dict with keys "height", "width", "fx", "fy", "cx", "cy", "near", "far" - - vertices_in_camera_frame: (N, 3) array of points in camera frame - - point_rgbds: (N, 4) array of RGBD values for each point - - point_color_outlier_probs: (N,) array of color outlier probabilities for each point - - point_depth_outlier_probs: (N,) array of depth outlier probabilities for each point - - color_scale: float (shared) - - depth_scale: float (shared) - - Distribution support: - - image: (height, width, 4) array of RGBD values (RGB values in [0, 1]^3; D values in [near, far]) - """ - - K: int - - def __init__(self, K): - self.K = K - - def random_weighted( - self, - key, - intrinsics, - vertices_in_camera_frame, - point_rgbds, - point_color_outlier_probs, - point_depth_outlier_probs, - color_scale, - depth_scale, - ): - h, w = intrinsics["height"], intrinsics["width"] - raycasted_image = raycast_to_image_nondeterministic( - key, intrinsics, vertices_in_camera_frame, self.K - ) - value = mapped_pixel_distribution.sample( - key, - h, - w, - raycasted_image, - point_rgbds, - point_color_outlier_probs, - point_depth_outlier_probs, - color_scale, - depth_scale, - intrinsics["near"], - intrinsics["far"], - ) - logpdf_estimate = mapped_pixel_distribution.logpdf( - value, - h, - w, - raycasted_image, - point_rgbds, - point_color_outlier_probs, - point_depth_outlier_probs, - color_scale, - depth_scale, - intrinsics["near"], - intrinsics["far"], - ) - return value, logpdf_estimate - - def estimate_logpdf( - self, - key, - obs, - intrinsics, - vertices_in_camera_frame, - point_rgbds, - point_color_outlier_probs, - point_depth_outlier_probs, - color_scale, - depth_scale, - ): - h, w = intrinsics["height"], intrinsics["width"] - raycasted_image = raycast_to_image_nondeterministic( - key, intrinsics, vertices_in_camera_frame, self.K - ) - logpdf_estimate = mapped_pixel_distribution.logpdf( - obs, - h, - w, - raycasted_image, - point_rgbds, - point_color_outlier_probs, - point_depth_outlier_probs, - color_scale, - depth_scale, - intrinsics["near"], - intrinsics["far"], - ) - return logpdf_estimate diff --git a/src/b3d/chisight/dynamic_object_model/likelihoods/project_no_occlusions_kernel.py b/src/b3d/chisight/dynamic_object_model/likelihoods/project_no_occlusions_kernel.py deleted file mode 100644 index 24bb8003..00000000 --- a/src/b3d/chisight/dynamic_object_model/likelihoods/project_no_occlusions_kernel.py +++ /dev/null @@ -1,78 +0,0 @@ -import jax -import jax.numpy as jnp - -import b3d - - -@jax.jit -def likelihood_func(observed_rgbd, args): - transformed_points = args["pose"].apply(args["vertices"]) - - projected_pixel_coordinates = jnp.rint( - b3d.xyz_to_pixel_coordinates( - transformed_points, args["fx"], args["fy"], args["cx"], args["cy"] - ) - ).astype(jnp.int32) - - observed_rgbd_masked = observed_rgbd[ - projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1] - ] - - color_outlier_probabilities = args["color_outlier_probabilities"] - depth_outlier_probabilities = args["depth_outlier_probabilities"] - - color_probability = jnp.logaddexp( - jax.scipy.stats.laplace.logpdf( - observed_rgbd_masked[..., :3], args["colors"], args["color_variance"] - ).sum(axis=-1) - + jnp.log(1 - color_outlier_probabilities), - jnp.log(color_outlier_probabilities) - + jnp.log(1 / 1.0**3), # <- log(1) == 0 tho - ) - depth_probability = jnp.logaddexp( - jax.scipy.stats.laplace.logpdf( - observed_rgbd_masked[..., 3], - transformed_points[..., 2], - args["depth_variance"], - ) - + jnp.log(1 - depth_outlier_probabilities), - jnp.log(depth_outlier_probabilities) + jnp.log(1 / 1.0), - ) - - scores = color_probability + depth_probability - - # Visualization - latent_rgbd = jnp.zeros_like(observed_rgbd) - latent_rgbd = latent_rgbd.at[ - projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1], :3 - ].set(args["colors"]) - latent_rgbd = latent_rgbd.at[ - projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1], 3 - ].set(transformed_points[..., 2]) - - return { - "score": scores.sum(), - "scores": scores, - "transformed_points": transformed_points, - "observed_rgbd_masked": observed_rgbd_masked, - "color_probability": color_probability, - "depth_probability": depth_probability, - "latent_rgbd": latent_rgbd, - } - - -@jax.jit -def sample_func(key, likelihood_args): - return jnp.zeros( - ( - likelihood_args["image_height"].const, - likelihood_args["image_width"].const, - 4, - ) - ) - - -project_no_occlusions_kernel_likelihood_func_and_sample_func = ( - likelihood_func, - sample_func, -) diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index e69de29b..3415ed29 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -0,0 +1,163 @@ +import genjax +import jax +import jax.numpy as jnp +import rerun as rr +from genjax import ChoiceMapBuilder as C + +import b3d + +# TODOs +# 1. Tests of drift kernels +# 2. Test of choicemap creation, and model updating + + +@genjax.gen +def dynamic_object_generative_model(hyperparams, previous_state): + hyperparams["vertices"] + + pose_kernel = hyperparams["pose_kernel"] + color_kernel = hyperparams["color_kernel"] + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] + depth_scale_kernel = hyperparams["depth_scale_kernel"] + color_scale_kernel = hyperparams["color_scale_kernel"] + + pose = pose_kernel(previous_state["pose"]) @ "pose" + colors = color_kernel.vmap()(previous_state["colors"]) @ "colors" + visibility_prob = ( + visibility_prob_kernel.vmap()(previous_state["visibility_prob"]) + @ "visibility_prob" + ) + depth_nonreturn_prob = ( + depth_nonreturn_prob_kernel.vmap()(previous_state["depth_nonreturn_prob"]) + @ "depth_nonreturn_prob" + ) + depth_scale = depth_scale_kernel(previous_state["depth_scale"]) @ "depth_scale" + color_scale = color_scale_kernel(previous_state["color_scale"]) @ "color_scale" + + new_state = { + "pose": pose, + "colors": colors, + "visibility_prob": visibility_prob, + "depth_nonreturn_prob": depth_nonreturn_prob, + "depth_scale": depth_scale, + "color_scale": color_scale, + } + + if "image_likelihood" not in hyperparams: + rgbd = None + else: + rgbd = hyperparams["image_likelihood"](new_state, hyperparams) @ "rgbd" + + return { + "new_state": new_state, + "rgbd": rgbd, + } + + +### Helpers ### +def make_colors_choicemap(colors): + return jax.vmap(lambda idx: C["colors", idx].set(colors[idx]))( + jnp.arange(len(colors)) + ) + + +def make_visibility_prob_choicemap(visibility_prob): + return jax.vmap(lambda idx: C["visibility_prob", idx].set(visibility_prob[idx]))( + jnp.arange(len(visibility_prob)) + ) + + +def make_depth_nonreturn_prob_choicemap(depth_nonreturn_prob): + return jax.vmap( + lambda idx: C["depth_nonreturn_prob", idx].set(depth_nonreturn_prob[idx]) + )(jnp.arange(len(depth_nonreturn_prob))) + + +### Visualization Code ### +def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): + b3d.rr_set_time(t) + hyperparams, _ = trace.get_args() + new_state = trace.get_retval()["new_state"] + + pose = new_state["pose"] + colors = new_state["colors"] + visibility_prob = new_state["visibility_prob"] + depth_nonreturn_prob = new_state["depth_nonreturn_prob"] + + vertices = hyperparams["vertices"] + b3d.rr_log_cloud( + vertices, + "object/model", + colors, + ) + b3d.rr_log_cloud( + vertices, + "object/visibility_prob", + jnp.array([[1.0, 0.0, 0.0]]) * visibility_prob[..., None], + ) + b3d.rr_log_cloud( + vertices, + "object/depth_nonreturn_prob", + jnp.array([[0.0, 1.0, 0.0]]) * depth_nonreturn_prob[..., None], + ) + + rr.log( + "info", + rr.TextDocument( + f""" + depth_scale: {new_state["depth_scale"]} + color_scale: {new_state["color_scale"]} + """.strip(), + media_type=rr.MediaType.MARKDOWN, + ), + ) + + vertices_transformed = pose.apply(vertices) + b3d.rr_log_cloud( + vertices_transformed, + "scene/model", + colors, + ) + + # output = trace.get_retval() + # if output["rgbd"] is not None: + # info = info_from_trace(trace) + # b3d.rr_log_rgb(output["rgbd"][..., :3], "image") + # b3d.rr_log_rgb(output["rgbd"][..., :3], "image/rgb/observed") + # b3d.rr_log_depth(output["rgbd"][..., 3], "image/depth/observed") + + # latent_rgbd = info["latent_rgbd"] + # b3d.rr_log_rgb(latent_rgbd[..., :3], "image/rgb/latent") + # b3d.rr_log_depth(latent_rgbd[..., 3], "image/depth/latent") + + # likelihood_args = trace.get_retval()["likelihood_args"] + # fx, fy, cx, cy = ( + # likelihood_args["fx"], + # likelihood_args["fy"], + # likelihood_args["cx"], + # likelihood_args["cy"], + # ) + # b3d.rr_log_cloud( + # b3d.xyz_from_depth( + # output["rgbd"][..., 3], + # fx, + # fy, + # cx, + # cy, + # ), + # "scene/observed", + # output["rgbd"][..., :3].reshape(-1, 3), + # ) + + # if ground_truth_vertices is not None: + # b3d.rr_log_cloud( + # trace.get_choices()["pose"].apply(ground_truth_vertices), + # "scene/full_object_model", + # ) + + # if ground_truth_pose: + # b3d.rr_log_cloud( + # ground_truth_pose.apply(ground_truth_vertices), + # "scene/ground_truth_object_mesh", + # ) diff --git a/src/b3d/chisight/gen3d/transition_kernels.py b/src/b3d/chisight/gen3d/transition_kernels.py index e69de29b..25dd8162 100644 --- a/src/b3d/chisight/gen3d/transition_kernels.py +++ b/src/b3d/chisight/gen3d/transition_kernels.py @@ -0,0 +1,379 @@ +from abc import abstractmethod +from typing import Sequence + +import genjax +import jax +import jax.numpy as jnp +from genjax import Pytree +from genjax.typing import ArrayLike, PRNGKey +from tensorflow_probability.substrates import jax as tfp + +from b3d import Pose +from b3d.chisight.dense.likelihoods.other_likelihoods import PythonMixturePixelModel + + +@Pytree.dataclass +class TruncatedLaplace(genjax.ExactDensity): + """ + This is a distribution on the interval (low, high). + The generative process is: + 1. Sample x ~ laplace(loc, scale). + 2. If x < low, sample y ~ uniform(low, low + uniform_window_size) and return y. + 3. If x > high, sample y ~ uniform(high - uniform_window_size, high) and return y. + 4. Otherwise, return x. + + Args: + - loc: float + - scale: float + - low: float + - high: float + - uniform_window_size: float + + Support: + - x in (low, high) [a float] + """ + + def sample(self, key, loc, scale, low, high, uniform_window_size): + assert low < high + assert low + uniform_window_size < high - uniform_window_size + k1, k2 = jax.random.split(key, 2) + x = tfp.distributions.Laplace(loc, scale).sample(seed=k1) + u = jax.random.uniform(k2, ()) * uniform_window_size + return jnp.where( + x > high, high - uniform_window_size + u, jnp.where(x < low, low + u, x) + ) + + def logpdf(self, obs, loc, scale, low, high, uniform_window_size): + assert low < high + assert low + uniform_window_size < high - uniform_window_size + laplace_logpdf = tfp.distributions.Laplace(loc, scale).log_prob(obs) + laplace_logp_below_low = tfp.distributions.Laplace(loc, scale).log_cdf(low) + laplace_logp_above_high = tfp.distributions.Laplace( + loc, scale + ).log_survival_function(high) + log_window_size = jnp.log(uniform_window_size) + + return jnp.where( + jnp.logical_and( + low + uniform_window_size < obs, obs < high - uniform_window_size + ), + laplace_logpdf, + jnp.where( + obs < low + uniform_window_size, + jnp.logaddexp(laplace_logp_below_low - log_window_size, laplace_logpdf), + jnp.logaddexp( + laplace_logp_above_high - log_window_size, laplace_logpdf + ), + ), + ) + + +truncated_laplace = TruncatedLaplace() + + +_FIXED_COLOR_UNIFORM_WINDOW = 1 / 255 +_FIXED_DEPTH_UNIFORM_WINDOW = 0.01 + + +@Pytree.dataclass +class TruncatedColorLaplace(genjax.ExactDensity): + """ + Args: + - loc: (3,) array (loc for R, G, B channels) + - shared_scale: float (scale, shared across R, G, B channels) + - uniform_window_size: float [optional; defaults to 1/255] + + Support: + - rgb in [0, 1]^3 [a 3D array] + """ + + def sample( + self, key, loc, shared_scale, uniform_window_size=_FIXED_COLOR_UNIFORM_WINDOW + ): + return jax.vmap( + lambda k, lc: truncated_laplace.sample( + k, lc, shared_scale, 0.0, 1.0, uniform_window_size + ), + in_axes=(0, 0), + )(jax.random.split(key, loc.shape[0]), loc) + + def logpdf( + self, obs, loc, shared_scale, uniform_window_size=_FIXED_COLOR_UNIFORM_WINDOW + ): + return jax.vmap( + lambda o, lc: truncated_laplace.logpdf( + o, lc, shared_scale, 0.0, 1.0, uniform_window_size + ), + in_axes=(0, 0), + )(obs, loc).sum() + + +truncated_color_laplace = TruncatedColorLaplace() + + +@Pytree.dataclass +class DriftKernel(genjax.ExactDensity): + """An abstract class that defines the common interface for drift kernels.""" + + @abstractmethod + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + raise NotImplementedError + + @abstractmethod + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + raise NotImplementedError + + +@Pytree.dataclass +class UniformDriftKernel(DriftKernel): + """A drift kernel that samples a new value from a uniform distribution centered + around the previous value. The range of the uniform distribution may shrink + to ensure that the new value is within the bounds of [min_val, max_val]. + + Support: [max(min_val, prev_value - max_shift), min(max_val, prev_value + max_shift)] + """ + + max_shift: float = Pytree.static() + min_val: float = Pytree.static() + max_val: float = Pytree.static() + + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + return self._base_dist(prev_value).sample(seed=key) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + return self._base_dist(prev_value).log_prob(new_value) + + def _base_dist(self, prev_value: ArrayLike): + """Returns a uniform distribution centered around prev_value, bounded by + min_val and max_val.""" + low = jnp.maximum(prev_value - self.max_shift, self.min_val) + high = jnp.minimum(prev_value + self.max_shift, self.max_val) + return tfp.distributions.Uniform(low, high) + + +@Pytree.dataclass +class UniformColorDriftKernel(UniformDriftKernel): + """A specialized uniform drift kernel with fixed min_val and max_val, with + additional logics to handle the color channels jointly. + + Support: [max(0.0, prev_value - max_shift), min(1.0, prev_value + max_shift)] + """ + + max_shift: float = Pytree.static() + min_val: float = Pytree.static(default=0.0, init=False) + max_val: float = Pytree.static(default=1.0, init=False) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + # the summation at the end is to ensure that we get a single value for + # the 3 channels (instead of 3 separate values) + return super().logpdf(new_value, prev_value).sum() + + +@Pytree.dataclass +class LaplaceDriftKernel(DriftKernel): + """A drift kernel that samples from a truncated Laplace distribution centered + at the previous value. Values outside of the bounds will be resampled from a + small uniform window at the boundary. This is a thin wrapper around the + truncated_laplace distribution to provide a consistent interface with other + drift kernels. + + Support: [min_val, max_val] + """ + + scale: float = Pytree.static() + min_val: float = Pytree.static() + max_val: float = Pytree.static() + uniform_window_size: float = Pytree.static() + + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + return truncated_laplace.sample( + key, prev_value, self.scale, self.uniform_window_size + ) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + return truncated_laplace.logpdf( + new_value, prev_value, self.scale, self.uniform_window_size + ) + + +@Pytree.dataclass +class LaplaceColorDriftKernel(DriftKernel): + """A drift kernel that samples the 3 channels of the color from a specialized + truncated Laplace distribution, centered at the previous color. Values outside + of the bounds will be resampled from a small uniform window at the boundary. + This is a thin wrapper around the truncated_color_laplace distribution to + provide a consistent interface with other drift kernels. + + Support: [0.0, 1.0] + """ + + scale: float = Pytree.static() + uniform_window_size: float = Pytree.static(default=_FIXED_COLOR_UNIFORM_WINDOW) + + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + return truncated_color_laplace.sample( + key, prev_value, self.scale, self.uniform_window_size + ) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + return truncated_color_laplace.logpdf( + new_value, prev_value, self.scale, self.uniform_window_size + ) + + +@Pytree.dataclass +class LaplaceNotTruncatedColorDriftKernel(DriftKernel): + """A drift kernel that samples the 3 channels of the color from a specialized + truncated Laplace distribution, centered at the previous color. Values outside + of the bounds will be resampled from a small uniform window at the boundary. + This is a thin wrapper around the truncated_color_laplace distribution to + provide a consistent interface with other drift kernels. + + Support: [0.0, 1.0] + """ + + scale: float = Pytree.static() + uniform_window_size: float = Pytree.static(default=_FIXED_COLOR_UNIFORM_WINDOW) + + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + return genjax.laplace.sample(key, prev_value, self.scale) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + return jax.scipy.stats.laplace.logpdf(new_value, prev_value, self.scale).sum() + + +@Pytree.dataclass +class GaussianDriftKernel(DriftKernel): + """A drift kernel that samples from a truncated Gaussian distribution centered + at the previous value. Values outside of the bounds will be renormalized. + + Support: [min_val, max_val] + """ + + scale: float = Pytree.static() + min_val: float = Pytree.static() + max_val: float = Pytree.static() + + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + return self._base_dist(prev_value).sample(seed=key) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + return self._base_dist(prev_value).log_prob(new_value) + + def _base_dist(self, prev_value: ArrayLike): + return tfp.distributions.TruncatedNormal( + loc=prev_value, scale=self.scale, low=self.min_val, high=self.max_val + ) + + +@Pytree.dataclass +class GaussianColorDriftKernel(GaussianDriftKernel): + """A specialized Gaussian drift kernel that samples from a truncated Gaussian + distribution centered at the previous value. Values outside of the bounds + will be renormalized. + + Support: [0.0, 1.0] + """ + + scale: float = Pytree.static() + min_val: float = Pytree.static(default=0.0, init=False) + max_val: float = Pytree.static(default=1.0, init=False) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + # the summation at the end is to ensure that we get a single value for + # the 3 channels (instead of 3 separate values) + return super().logpdf(new_value, prev_value).sum() + + +@Pytree.dataclass +class MixtureDriftKernel(DriftKernel): + """A drift kernel that samples from a mixture of distributions according to + the probabilities specified in the `mix_ratio`. + """ + + dists: Sequence[DriftKernel] = Pytree.static() + mix_ratio: ArrayLike = Pytree.static() + + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + return PythonMixturePixelModel(self.dists).sample( + key, self.mix_ratio, [(prev_value,)] * len(self.dists) + ) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + return PythonMixturePixelModel(self.dists).logpdf( + new_value, + self.mix_ratio, + [(prev_value,)] * len(self.dists), + ) + + +# Pose Drift Kernels + + +@Pytree.dataclass +class UniformPoseDriftKernel(DriftKernel): + """A specialized uniform drift kernel with fixed min_val and max_val, with + additional logics to handle the color channels jointly. + + Support: [max(0.0, prev_value - max_shift), min(1.0, prev_value + max_shift)] + """ + + max_shift: float = Pytree.static() + + def sample(self, key: PRNGKey, prev_pose): + keys = jax.random.split(key, 2) + pos = ( + jax.random.uniform(keys[0], (3,)) * (2 * self.max_shift) + - self.max_shift + + prev_pose.position + ) + quat = jax.random.normal(keys[1], (4,)) + quat = quat / jnp.linalg.norm(quat) + return Pose(pos, quat) + + def logpdf(self, new_pose, prev_pose) -> ArrayLike: + position_delta = new_pose.pos - prev_pose.pos + valid = jnp.all(jnp.abs(position_delta) < self.max_shift) + position_score = jnp.log( + (valid * 1.0) * (jnp.ones_like(position_delta) / (2 * self.max_shift)) + ).sum() + return position_score + jnp.pi**2 + + +# Discrete Kernels + + +@Pytree.dataclass +class DiscreteKernel(genjax.ExactDensity): + """An abstract class that defines the common interface for drift kernels.""" + + @abstractmethod + def sample(self, key: PRNGKey, prev_value, possible_values): + raise NotImplementedError + + @abstractmethod + def logpdf(self, new_value, prev_value, possible_values): + raise NotImplementedError + + +@Pytree.dataclass +class DiscreteFlipKernel(DiscreteKernel): + resample_probability: float = Pytree.static() + possible_values: ArrayLike = Pytree.static() + + def sample(self, key: PRNGKey, prev_value): + should_resample = jax.random.bernoulli(key, self.resample_probability) + return ( + should_resample + * self.possible_values[jax.random.choice(key, len(self.possible_values))] + + (1 - should_resample) * prev_value + ) + + def logpdf(self, new_value, prev_value): + match = new_value == prev_value + return jnp.logaddexp( + jnp.log(1.0 - self.resample_probability) + jnp.log(1.0 * match), + jnp.log(self.resample_probability) + - jnp.log(len(self.possible_values) - 1) + + jnp.log(1.0 * (1 - match)), + ) diff --git a/src/b3d/utils.py b/src/b3d/utils.py index 137aa567..798064a5 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -1,3 +1,4 @@ +import functools import inspect import os import subprocess @@ -150,10 +151,20 @@ def xyz_from_depth(z: rr.DepthImage, fx, fy, cx, cy): ) +@functools.partial( + jnp.vectorize, + signature="(3)->(2)", + excluded=( + 1, + 2, + 3, + 4, + ), +) def xyz_to_pixel_coordinates(xyz, fx, fy, cx, cy): - x = fx * xyz[..., 0] / (xyz[..., 2]) + cx - y = fy * xyz[..., 1] / (xyz[..., 2]) + cy - return jnp.stack([y, x], axis=-1) + x = fx * xyz[0] / (xyz[2]) + cx + y = fy * xyz[1] / (xyz[2]) + cy + return jnp.array([y, x]) def segment_point_cloud(point_cloud, threshold=0.01, min_points_in_cluster=0): diff --git a/tests/dynamic_object_model/test_dynamic_object_model.py b/tests/dynamic_object_model/test_dynamic_object_model.py deleted file mode 100644 index 92053858..00000000 --- a/tests/dynamic_object_model/test_dynamic_object_model.py +++ /dev/null @@ -1,99 +0,0 @@ -### IMPORTS ### - - -import b3d -import jax -import jax.numpy as jnp -from b3d import Pose -from genjax import ChoiceMapBuilder as C -from genjax import Pytree - -b3d.reload(b3d.chisight.dynamic_object_model) - - -def make_trace_and_condition_values(): - key = jax.random.PRNGKey(0) - model_vertices = jax.random.uniform(key, (1000, 3), minval=-0.5, maxval=0.5) - - fx, fy, cx, cy = 100.0, 100.0, 50.0, 50.0 - image_height, image_width = 100, 100 - - hyperparams = { - "vertices": model_vertices, - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - "image_height": Pytree.const(image_height), - "image_width": Pytree.const(image_width), - "max_pose_position_shift": 0.1, - "color_shift_scale": 0.1, - "color_outlier_probability_shift_scale": 0.1, - "depth_outlier_probability_shift_scale": 0.1, - } - - template_pose = Pose.identity() - model_colors = jnp.zeros((len(model_vertices), 3)) - color_outlier_probabilities = jnp.ones(len(model_vertices)) * 0.01 - depth_outlier_probabilities = jnp.ones(len(model_vertices)) * 0.01 - - previous_state = { - "pose": template_pose, - "colors": model_colors, - "color_outlier_probabilities": color_outlier_probabilities, - "depth_outlier_probabilities": depth_outlier_probabilities, - } - - choicemap = C.n() - - key = jax.random.PRNGKey(0) - trace, _ = ( - b3d.chisight.dynamic_object_model.dynamic_object_model.dynamic_object_generative_model.importance( - key, choicemap, (hyperparams, previous_state) - ) - ) - - # Overwrite colors - colors = trace.get_choices()("colors").c.v - new_colors = jnp.ones_like(colors) - assert not jnp.allclose(trace.get_choices()("colors").c.v, new_colors) - chm = jax.vmap(lambda idx: C["colors", idx].set(new_colors[idx]))( - jnp.arange(len(new_colors)) - ) - trace = trace.update(key, chm)[0] - assert jnp.allclose(trace.get_choices()("colors").c.v, new_colors) - - # Overwite pose - # pose = trace.get_choices()("pose").v - new_pose = Pose.from_translation(jnp.array([0.1, 0.1, 0.1])) - chm = C["pose"].set(new_pose) - trace = trace.update(key, chm)[0] - assert jnp.allclose(trace.get_choices()("pose").v.pos, new_pose.pos) - assert jnp.allclose(trace.get_choices()("pose").v.quat, new_pose.quat) - - # TODO test choicemap creators - - # Test proposals - b3d.reload(b3d.chisight.dynamic_object_model.dynamic_object_inference) - from b3d.chisight.dynamic_object_model.dynamic_object_inference import ( - propose_color_and_color_outlier_probability, - propose_depth_outlier_probability, - propose_pose, - ) - - sampled_values, _ = propose_depth_outlier_probability( - trace, key, jnp.linspace(0.0, 1.0, 128) - ) - print(sampled_values.max(), sampled_values.mean()) - propose_pose(trace, key, 0.2, 200.0) - ( - _, - sampled_color_outlier_probabilities, - _, - ) = propose_color_and_color_outlier_probability( - trace, key, jnp.array([0.0, 0.5, 1.0]) - ) - print( - sampled_color_outlier_probabilities.max(), - sampled_color_outlier_probabilities.mean(), - ) diff --git a/tests/gen3d/test_model.py b/tests/gen3d/test_model.py new file mode 100644 index 00000000..9a5ae75b --- /dev/null +++ b/tests/gen3d/test_model.py @@ -0,0 +1,159 @@ +### IMPORTS ### +import os + +import b3d +import b3d.chisight.gen3d.model +import b3d.chisight.gen3d.transition_kernels as transition_kernels +import b3d.io.data_loader +import jax +import jax.numpy as jnp +from b3d import Mesh, Pose +from b3d.chisight.gen3d.model import ( + make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, + make_visibility_prob_choicemap, +) +from genjax import ChoiceMapBuilder as C + +b3d.rr_init("test_gen3d_model") + + +def test_model_no_likelihood(): + importance = jax.jit( + b3d.chisight.gen3d.model.dynamic_object_generative_model.importance + ) + + # num_vertices = 100 + # vertices = jax.random.uniform( + # jax.random.PRNGKey(0), (num_vertices, 3), minval=-1, maxval=1 + # ) + # colors = jax.random.uniform( + # jax.random.PRNGKey(1), (num_vertices, 3), minval=0, maxval=1 + # ) + ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") + id = 0 + mesh = Mesh.from_obj_file( + os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') + ).scale(0.001) + vertices = mesh.vertices + colors = mesh.vertex_attributes + num_vertices = vertices.shape[0] + + key = jax.random.PRNGKey(0) + hyperparams = { + "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.1), + "color_kernel": transition_kernels.LaplaceColorDriftKernel(scale=0.05), + "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, possible_values=jnp.array([0.01, 0.99]) + ), + "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, possible_values=jnp.array([0.01, 0.99]) + ), + "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, possible_values=jnp.array([0.005, 0.01, 0.02]) + ), + "color_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, possible_values=jnp.array([0.05, 0.1, 0.15]) + ), + "vertices": vertices, + } + + previous_state = { + "pose": Pose.identity(), + "colors": colors, + "visibility_prob": jnp.ones(num_vertices) + * hyperparams["visibility_prob_kernel"].possible_values[-1], + "depth_nonreturn_prob": jnp.ones(num_vertices) + * hyperparams["depth_nonreturn_prob_kernel"].possible_values[0], + "depth_scale": hyperparams["depth_scale_kernel"].possible_values[0], + "color_scale": hyperparams["color_scale_kernel"].possible_values[0], + } + + key = jax.random.PRNGKey(0) + trace = importance(key, C.n(), (hyperparams, previous_state))[0] + + key = jax.random.PRNGKey(0) + hyperparams, previous_state = trace.get_args() + + traces = [trace] + for t in range(100): + key = b3d.split_key(key) + previous_state = trace.get_retval()["new_state"] + trace, _ = importance(key, C.n(), (hyperparams, previous_state)) + b3d.chisight.gen3d.model.viz_trace(trace, t) + traces.append(trace) + + colors_over_time = jnp.array( + [trace.get_choices()["colors", ...] for trace in traces] + ) + + import matplotlib.pyplot as plt + + fig, ax = plt.subplots(4, 1, sharex=True, figsize=(10, 20)) + point_index = 0 + + fig.suptitle( + f""" +pose_kernel max_shift: {hyperparams['pose_kernel'].max_shift}, +color_kernel scale: {hyperparams['color_kernel'].scale}, +visibility_prob_kernel resample_probability: {hyperparams['visibility_prob_kernel'].resample_probability}, +depth_nonreturn_prob_kernel resample_probability: {hyperparams['depth_nonreturn_prob_kernel'].resample_probability}, +depth_scale_kernel resample_probability: {hyperparams['depth_scale_kernel'].resample_probability}, +color_scale_kernel resample_probability: {hyperparams['color_scale_kernel'].resample_probability}""" + ) + ax[0].set_title(f"Color of vertex {point_index}") + ax[0].plot(colors_over_time[..., point_index, 0], color="r") + ax[0].plot(colors_over_time[..., point_index, 1], color="g") + ax[0].plot(colors_over_time[..., point_index, 2], color="b") + ax[0].set_ylim(-0.01, 1.01) + + first_n = 10 + ax[1].set_title("Visibility") + ax[1].plot( + [trace.get_choices()["visibility_prob", ...][:first_n] for trace in traces], + alpha=0.5, + ) + + ax[2].set_title("Depth Non Return") + ax[2].plot( + [ + trace.get_choices()["depth_nonreturn_prob", ...][:first_n] + for trace in traces + ], + alpha=0.5, + ) + + ax[3].set_title("Inlier Scale") + ax[3].plot([trace.get_choices()["depth_scale"] for trace in traces], label="depth") + ax[3].plot([trace.get_choices()["color_scale"] for trace in traces], label="color") + ax[3].legend() + fig.supxlabel("Time") + fig.savefig("test_gen3d_model.png") + + colors = trace.get_choices()["colors", ...] + new_colors = colors + 0.01 + new_colors_choicemap = make_colors_choicemap(new_colors) + new_trace = trace.update(key, new_colors_choicemap)[0] + assert jnp.allclose(new_trace.get_choices()["colors", ...], new_colors) + + visibility_prob = trace.get_choices()["visibility_prob", ...] + new_visibility_prob = visibility_prob + 0.01 + new_visibility_prob_choicemap = make_visibility_prob_choicemap(new_visibility_prob) + new_trace = trace.update(key, new_visibility_prob_choicemap)[0] + assert jnp.allclose( + new_trace.get_choices()["visibility_prob", ...], new_visibility_prob + ) + + depth_nonreturn_prob = trace.get_choices()["depth_nonreturn_prob", ...] + new_depth_nonreturn_prob = depth_nonreturn_prob + 0.01 + new_depth_nonreturn_prob_choicemap = make_depth_nonreturn_prob_choicemap( + new_depth_nonreturn_prob + ) + new_trace = trace.update(key, new_depth_nonreturn_prob_choicemap)[0] + assert jnp.allclose( + new_trace.get_choices()["depth_nonreturn_prob", ...], new_depth_nonreturn_prob + ) + + +if __name__ == "__main__": + test_model_no_likelihood() diff --git a/tests/gen3d/test_transition_kernels.py b/tests/gen3d/test_transition_kernels.py new file mode 100644 index 00000000..96f8dba3 --- /dev/null +++ b/tests/gen3d/test_transition_kernels.py @@ -0,0 +1,22 @@ +### IMPORTS ### + +import b3d.chisight.gen3d.transition_kernels as transition_kernels +import jax.numpy as jnp + + +def test_discrete_flip_kernel(): + num_values = 10 + possible_values = jnp.linspace(0, 1, num_values) + flip_probability = 0.1 + kernel = transition_kernels.DiscreteFlipKernel( + resample_probability=flip_probability, possible_values=possible_values + ) + + assert jnp.isclose( + kernel.logpdf(possible_values[0], possible_values[0]), + jnp.log(1 - flip_probability), + ) + assert jnp.isclose( + kernel.logpdf(possible_values[0], possible_values[-1]), + jnp.log(flip_probability / (num_values - 1)), + ) From 02b1119173b0fb1af7a37957b706f54fcac4a465 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Mon, 9 Sep 2024 20:09:33 -0400 Subject: [PATCH 02/37] Image Kernel (#151) --- notebooks/bayes3d_paper/online_hb.ipynb | 204 +++++++++------- src/b3d/chisight/gen3d/image_kernel.py | 108 +++++++++ src/b3d/chisight/gen3d/inference.py | 242 +++++++++++++++++++ src/b3d/chisight/gen3d/model.py | 81 +++---- src/b3d/chisight/gen3d/transition_kernels.py | 24 +- tests/gen3d/test_model.py | 6 +- 6 files changed, 530 insertions(+), 135 deletions(-) diff --git a/notebooks/bayes3d_paper/online_hb.ipynb b/notebooks/bayes3d_paper/online_hb.ipynb index 7d2c9fb0..66612a77 100644 --- a/notebooks/bayes3d_paper/online_hb.ipynb +++ b/notebooks/bayes3d_paper/online_hb.ipynb @@ -2,17 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 1, + "execution_count": 134, "metadata": {}, "outputs": [], "source": [ @@ -38,37 +28,37 @@ "from genjax import SelectionBuilder as S\n", "from genjax import ChoiceMapBuilder as C\n", "\n", - "b3d.rr_init(\"dynamics\")" + "b3d.rr_init(\"dynamics2\")" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 135, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Scene 48\n" + "Scene 49\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 45/45 [00:04<00:00, 10.90it/s]\n" + "100%|██████████| 49/49 [00:03<00:00, 14.06it/s]\n" ] }, { "data": { - "image/jpeg": 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", 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", 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", 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", "text/plain": [ "" ] }, - "execution_count": 2, + "execution_count": 135, "metadata": {}, "output_type": "execute_result" } @@ -76,7 +66,7 @@ "source": [ "### Loading data ###\n", "b3d.reload(b3d.io.data_loader)\n", - "scene_id = 48\n", + "scene_id = 49\n", "FRAME_RATE = 50\n", "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", "print(f\"Scene {scene_id}\")\n", @@ -105,40 +95,41 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 154, "metadata": {}, "outputs": [], "source": [ - "### Set up model ###\n", - "import b3d.chisight.dynamic_object_model.dynamic_object_model\n", - "import b3d.chisight.dynamic_object_model.dynamic_object_inference\n", - "b3d.reload(b3d.chisight.dynamic_object_model.dynamic_object_model)\n", - "b3d.reload(b3d.chisight.dynamic_object_model.dynamic_object_inference)\n", - "from b3d.chisight.dynamic_object_model.dynamic_object_model import (\n", - " dynamic_object_generative_model, viz_trace, info_from_trace,\n", - " make_colors_choicemap, make_visibiliy_choicemap,make_depth_nonreturn_choicemap,\n", - " image_likelihood\n", + "import b3d\n", + "import b3d.chisight.gen3d.model\n", + "b3d.reload(b3d.chisight.gen3d.model)\n", + "import b3d.chisight.gen3d.transition_kernels as transition_kernels\n", + "b3d.reload(b3d.chisight.gen3d.transition_kernels)\n", + "import b3d.chisight.gen3d.image_kernel as image_kernel\n", + "b3d.reload(b3d.chisight.gen3d.image_kernel)\n", + "import b3d.io.data_loader\n", + "import jax\n", + "import jax.numpy as jnp\n", + "from b3d import Mesh, Pose\n", + "from b3d.chisight.gen3d.model import (\n", + " make_colors_choicemap,\n", + " make_depth_nonreturn_prob_choicemap,\n", + " make_visibility_prob_choicemap,\n", ")\n", - "b3d.reload(b3d.chisight.dynamic_object_model.dynamic_object_model)\n", - "import b3d.chisight.dynamic_object_model.drift_kernels as drift_kernels\n", - "b3d.reload(b3d.chisight.dynamic_object_model.drift_kernels)\n", - "\n", - "from b3d.chisight.dynamic_object_model.dynamic_object_inference import (\n", - " propose_update,\n", - " inference_step\n", - ")\n" + "from b3d.chisight.gen3d.model import dynamic_object_generative_model\n", + "from genjax import ChoiceMapBuilder as C\n", + "from genjax import Pytree" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 152, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "21894.166\n" + "22682.564\n" ] } ], @@ -146,7 +137,7 @@ "\n", "T = 0\n", "b3d.rr_set_time(T)\n", - "OBJECT_INDEX = 4\n", + "OBJECT_INDEX = 1\n", "\n", "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", @@ -158,34 +149,27 @@ "model_vertices = template_pose.inv().apply(xyz_rendered[mask])\n", "model_colors = vertex_attributes=all_data[T][\"rgbd\"][..., :3][mask]\n", "\n", - "subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[:len(model_vertices) // 2]\n", - "model_vertices = model_vertices[subset]\n", - "model_colors = model_colors[subset]\n", - "\n", - "model_vertices = meshes[OBJECT_INDEX].vertices\n", - "model_colors = meshes[OBJECT_INDEX].vertex_attributes\n", - "\n", + "# subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[:len(model_vertices) // 2]\n", + "# model_vertices = model_vertices[subset]\n", + "# model_colors = model_colors[subset]\n", "\n", "hyperparams = {\n", - " \"pose_transition_kernel\": drift_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", - " \"color_transition_kernel\": drift_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.2),\n", - " \"visibility_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.4\n", + " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", + " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.15),\n", + " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, possible_values=jnp.array([0.01, 0.99])\n", " ),\n", - " \"depth_nonreturn_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.4\n", + " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, possible_values=jnp.array([0.01, 0.99])\n", " ),\n", - " \"depth_scale_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.4\n", + " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, possible_values=jnp.array([0.0025, 0.01, 0.02])\n", " ),\n", - " \"color_scale_transition_kernel\": drift_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.4\n", + " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, possible_values=jnp.array([0.05, 0.1, 0.15])\n", " ),\n", - " \"visibility_values\": jnp.array([0.01, 0.99]),\n", - " \"depth_nonreturn_values\": jnp.array([0.01, 0.99]),\n", - " \"color_scale_values\": jnp.array([0.1, 0.15]),\n", - " \"depth_scale_values\": jnp.array([0.0025, 0.005, 0.01]),\n", - " \"vertices\": model_vertices,\n", + "\n", + " \"image_likelihood\": image_kernel.SimpleNoRenderImageLikelihood(),\n", "\n", " \"fx\": fx,\n", " \"fy\": fy,\n", @@ -193,19 +177,20 @@ " \"cy\": cy,\n", " \"image_height\": Pytree.const(image_height),\n", " \"image_width\": Pytree.const(image_width),\n", - "\n", - " \"image_likelihood\": image_likelihood,\n", + " \n", + " \"vertices\":model_vertices\n", "}\n", "\n", - "\n", "num_vertices = model_vertices.shape[0]\n", "previous_state = {\n", " \"pose\": template_pose,\n", " \"colors\": model_colors,\n", - " \"visibility\": jnp.ones(num_vertices) * hyperparams[\"visibility_values\"][1],\n", - " \"depth_nonreturn\": jnp.ones(num_vertices) * hyperparams[\"depth_nonreturn_values\"][0],\n", - " \"depth_scale\": hyperparams[\"depth_scale_values\"][0],\n", - " \"color_scale\": hyperparams[\"color_scale_values\"][0],\n", + " \"visibility_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"visibility_prob_kernel\"].possible_values[-1],\n", + " \"depth_nonreturn_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"depth_nonreturn_prob_kernel\"].possible_values[0],\n", + " \"depth_scale\": hyperparams[\"depth_scale_kernel\"].possible_values[0],\n", + " \"color_scale\": hyperparams[\"color_scale_kernel\"].possible_values[0],\n", "}\n", "\n", "choicemap = (\n", @@ -217,27 +202,60 @@ " \"rgbd\": all_data[T][\"rgbd\"],\n", " }\n", " ) ^ \n", - " make_visibiliy_choicemap(previous_state[\"visibility\"]) ^\n", + " make_visibility_prob_choicemap(previous_state[\"visibility_prob\"]) ^\n", " make_colors_choicemap(previous_state[\"colors\"]) ^\n", - " make_depth_nonreturn_choicemap(previous_state[\"depth_nonreturn\"])\n", + " make_depth_nonreturn_prob_choicemap(previous_state[\"depth_nonreturn_prob\"])\n", ")\n", - "key = jax.random.PRNGKey(10)\n", - "trace, _ = b3d.chisight.dynamic_object_model.dynamic_object_model.dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", + "key = jax.random.PRNGKey(0)\n", + "\n", + "trace= dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))[0]\n", "print(trace.get_score())\n", - "viz_trace(trace, 0)\n", + "b3d.chisight.gen3d.model.viz_trace(trace, 0)\n", "results = {}" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 153, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 0%| | 0/49 [00:00()", + )(visibility_sweep, previous_visibility) + + info_from_trace = hyperparams["image_likelihood"].info_from_trace + + # We will grid over color values, using a grid that mixes the old and observed + # colors in a set of exact proportions. + # We regard these as coming from uniform proposals where we sample the RGB + # values uniformly between the mixed R, G, and B values with mixtures between + # [0., .125], [.125, .5], [.5, .875], [.875, 1.]. + # So the q scores will be .125^3, .375^3, .375^3, .125^3. + # TODO: we really ought to add a small amount of proposal probability mass + # onto the points at the end, to capture the fact that the posterior could allow + # colors outside the considered interpolation window. + color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) + # num_color_grid_points = len(color_interpolations_per_proposal) + + observed_colors = info_from_trace(trace)["observed_rgbd_masked"][ + ..., :3 + ] # (num_vertices, 3) + color_sweep = observed_colors[None, ...] * color_interpolations_per_proposal[ + :, None, None + ] + previous_colors[None, ...] * ( + 1 - color_interpolations_per_proposal[:, None, None] + ) # (num_color_grid_points, num_vertices, 3) + + color_kernel = hyperparams["color_kernel"] + color_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( + color_kernel.logpdf, + signature="(3),(3)->()", + )(color_sweep, previous_colors) + + # Function takes in color and color outlier probabilities array of shapes (num_vertices,3) and (num_vertices,) respectively + # and gives scores for each vertex (num_vertices,) + def get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities( + colors, visibility + ): + return info_from_trace( + trace.update( + key, + make_colors_choicemap(colors) + ^ make_visibility_prob_choicemap(visibility), + )[0] + )["scores"] + + vmap_version = jax.vmap( + jax.vmap( + get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities, + in_axes=(None, 0), + ), + in_axes=(0, None), + ) + + # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep + likelihood_scores_per_sweep_point_and_vertex = vmap_version( + color_sweep, visibility_sweep + ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + scores_per_sweep_point_and_vertex = ( + likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + visibility_transition_scores_per_sweep_point_and_vertex[None, ...] + + color_transition_scores_per_sweep_point_and_vertex[:, None, ...] + ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + unraveled_scores = scores_per_sweep_point_and_vertex.reshape( + -1, scores_per_sweep_point_and_vertex.shape[-1] + ) + normalized_log_probabilities = jax.nn.log_softmax(unraveled_scores, axis=0) + sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) + + color_sweep_indices, visibility_sweep_indices = jnp.unravel_index( + sampled_indices, scores_per_sweep_point_and_vertex.shape[:2] + ) + + # color_sweep is (num_outlier_grid_points, num_vertices, 3) + # outlier_probability_sweep is (num_outlier_grid_points,) + # color_outlier_probabilities_sweep is (num_outlier_grid_points, num_vertices) + sampled_colors = color_sweep[color_sweep_indices, jnp.arange(color_sweep.shape[1])] + sampled_color_outlier_probabilities = visibility_values[visibility_sweep_indices] + + log_q_color_and_color_outlier_probability = normalized_log_probabilities[ + sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) + ].sum() + + # log_q = estimate of q(all these colors, all these outliers ; inputs) + # Only source of real randomness = sampling indices. Captured in log_q_color_and_color_outlier_probability. + # But we also want to be careful with the continuous values... + # (1) outlier probs. --> change the model to have discrete grid. [Do later.] + # (2) colors. --> 1/q() + # uniform(old r, 2/3 oldr + 1/3 newr) 0 | uniform(0, 0.1) + # uniform(1/3, 2/3) # .5 | uniform(.1, .9) + # uniform(2/3, 1) # 1 | uniform(.9, 1) + # + # q(c1) * q(c2) * q(c3) + # but we just output c2 + # q(the c values we output, marginalizing over the other choices) + # -> just output q(c2) + + # We will treat this like the case where each sweep is uniform, so the q scores + # are each (oldr - obsr)/3 * (oldg - obsg)/3 * (oldb - obsb)/3. + + hyperparams = trace.get_args()[0] + color_shift_scale = hyperparams["color_kernel"].scale + color_scale = trace.get_choices()["color_scale"] + + d = 1 / (1 / color_shift_scale + 1 / color_scale) + + q_prob_per_vertex = ( + 1.0 / ((jnp.abs(previous_colors - observed_colors) / 3) + 4 * d) + ).prod(-1) + log_q_for_the_color_proposal = jnp.log(q_prob_per_vertex).sum() + + return ( + sampled_colors, + sampled_color_outlier_probabilities, + log_q_color_and_color_outlier_probability + log_q_for_the_color_proposal, + scores_per_sweep_point_and_vertex, + ) + + +@jax.jit +def propose_update(trace, key, pose): + total_log_q = 0.0 + + # Update pose + # pose, log_q_pose = propose_pose( + # trace, key, pose_sample_variance, pose_sample_concentration + # ) + trace = trace.update(key, C["pose"].set(pose))[0] + + # Update color and color outlier probability + sampled_colors, sampled_visibility, log_q, _ = propose_color_and_visibility( + trace, key + ) + trace = trace.update( + key, + make_colors_choicemap(sampled_colors) + ^ make_visibility_prob_choicemap(sampled_visibility), + )[0] + total_log_q += log_q + + return trace, total_log_q + + +@jax.jit +def propose_update_get_score(trace, key, pose): + new_trace, log_q = propose_update(trace, key, pose) + # score is an estimate of P(data, pose | previous state) + return new_trace.get_score() - log_q + + +propose_update_get_score_vmap = jax.jit( + jax.vmap(propose_update_get_score, in_axes=(None, None, 0)) +) + + +def inference_step_without_advance(trace, key): + number = 15000 + current_pose = trace.get_choices()["pose"] + var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] + for var, conc in var_conc: + key = jax.random.split(key, 2)[-1] + keys = jax.random.split(key, number) + poses = Pose.concatenate_poses( + [ + Pose.sample_gaussian_vmf_pose_vmap(keys, current_pose, var, conc), + current_pose[None, ...], + ] + ) + pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( + poses, trace.get_choices()["pose"], var, conc + ) + scores = propose_update_get_score_vmap(trace, key, poses) + scores_pose_q_correction = ( + scores - pose_scores + ) # After this, scores are fair estimates of P(data | previous state) + # and can be used to resample the choice sets. + index = jax.random.categorical(key, scores) + current_pose = poses[index] + trace = propose_update(trace, key, current_pose)[0] + return trace, scores, scores_pose_q_correction + + +def inference_step(trace, key, observed_rgbd): + trace = advance_time(key, trace, observed_rgbd) + trace = inference_step_without_advance(trace, key)[0] + return trace diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index 3415ed29..69759a89 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -120,44 +120,43 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): colors, ) - # output = trace.get_retval() - # if output["rgbd"] is not None: - # info = info_from_trace(trace) - # b3d.rr_log_rgb(output["rgbd"][..., :3], "image") - # b3d.rr_log_rgb(output["rgbd"][..., :3], "image/rgb/observed") - # b3d.rr_log_depth(output["rgbd"][..., 3], "image/depth/observed") - - # latent_rgbd = info["latent_rgbd"] - # b3d.rr_log_rgb(latent_rgbd[..., :3], "image/rgb/latent") - # b3d.rr_log_depth(latent_rgbd[..., 3], "image/depth/latent") - - # likelihood_args = trace.get_retval()["likelihood_args"] - # fx, fy, cx, cy = ( - # likelihood_args["fx"], - # likelihood_args["fy"], - # likelihood_args["cx"], - # likelihood_args["cy"], - # ) - # b3d.rr_log_cloud( - # b3d.xyz_from_depth( - # output["rgbd"][..., 3], - # fx, - # fy, - # cx, - # cy, - # ), - # "scene/observed", - # output["rgbd"][..., :3].reshape(-1, 3), - # ) - - # if ground_truth_vertices is not None: - # b3d.rr_log_cloud( - # trace.get_choices()["pose"].apply(ground_truth_vertices), - # "scene/full_object_model", - # ) - - # if ground_truth_pose: - # b3d.rr_log_cloud( - # ground_truth_pose.apply(ground_truth_vertices), - # "scene/ground_truth_object_mesh", - # ) + output = trace.get_retval() + if output["rgbd"] is not None: + info = hyperparams["image_likelihood"].info_from_trace(trace) + b3d.rr_log_rgb(output["rgbd"][..., :3], "image") + b3d.rr_log_rgb(output["rgbd"][..., :3], "image/rgb/observed") + b3d.rr_log_depth(output["rgbd"][..., 3], "image/depth/observed") + + latent_rgbd = info["latent_rgbd"] + b3d.rr_log_rgb(latent_rgbd[..., :3], "image/rgb/latent") + b3d.rr_log_depth(latent_rgbd[..., 3], "image/depth/latent") + + fx, fy, cx, cy = ( + hyperparams["fx"], + hyperparams["fy"], + hyperparams["cx"], + hyperparams["cy"], + ) + b3d.rr_log_cloud( + b3d.xyz_from_depth( + output["rgbd"][..., 3], + fx, + fy, + cx, + cy, + ), + "scene/observed", + output["rgbd"][..., :3].reshape(-1, 3), + ) + + if ground_truth_vertices is not None: + b3d.rr_log_cloud( + trace.get_choices()["pose"].apply(ground_truth_vertices), + "scene/full_object_model", + ) + + if ground_truth_pose: + b3d.rr_log_cloud( + ground_truth_pose.apply(ground_truth_vertices), + "scene/ground_truth_object_mesh", + ) diff --git a/src/b3d/chisight/gen3d/transition_kernels.py b/src/b3d/chisight/gen3d/transition_kernels.py index 25dd8162..bc8a9514 100644 --- a/src/b3d/chisight/gen3d/transition_kernels.py +++ b/src/b3d/chisight/gen3d/transition_kernels.py @@ -196,6 +196,26 @@ def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: ) +@Pytree.dataclass +class LaplaceNotTruncatedDriftKernel(DriftKernel): + """A drift kernel that samples the 3 channels of the color from a specialized + truncated Laplace distribution, centered at the previous color. Values outside + of the bounds will be resampled from a small uniform window at the boundary. + This is a thin wrapper around the truncated_color_laplace distribution to + provide a consistent interface with other drift kernels. + + Support: [0.0, 1.0] + """ + + scale: float = Pytree.static() + + def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: + return genjax.laplace.sample(key, prev_value, self.scale) + + def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: + return jax.scipy.stats.laplace.logpdf(new_value, prev_value, self.scale).sum() + + @Pytree.dataclass class LaplaceColorDriftKernel(DriftKernel): """A drift kernel that samples the 3 channels of the color from a specialized @@ -365,7 +385,9 @@ def sample(self, key: PRNGKey, prev_value): should_resample = jax.random.bernoulli(key, self.resample_probability) return ( should_resample - * self.possible_values[jax.random.choice(key, len(self.possible_values))] + * self.possible_values.at[ + jax.random.choice(key, len(self.possible_values)) + ].get() + (1 - should_resample) * prev_value ) diff --git a/tests/gen3d/test_model.py b/tests/gen3d/test_model.py index 9a5ae75b..d78d00cd 100644 --- a/tests/gen3d/test_model.py +++ b/tests/gen3d/test_model.py @@ -19,9 +19,7 @@ def test_model_no_likelihood(): - importance = jax.jit( - b3d.chisight.gen3d.model.dynamic_object_generative_model.importance - ) + importance = b3d.chisight.gen3d.model.dynamic_object_generative_model.importance # num_vertices = 100 # vertices = jax.random.uniform( @@ -30,6 +28,7 @@ def test_model_no_likelihood(): # colors = jax.random.uniform( # jax.random.PRNGKey(1), (num_vertices, 3), minval=0, maxval=1 # ) + ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") id = 0 mesh = Mesh.from_obj_file( @@ -71,6 +70,7 @@ def test_model_no_likelihood(): key = jax.random.PRNGKey(0) trace = importance(key, C.n(), (hyperparams, previous_state))[0] + trace = importance(key, C.n(), (hyperparams, previous_state))[0] key = jax.random.PRNGKey(0) hyperparams, previous_state = trace.get_args() From cc85318261cee2b92c1320a3803f6f73bca5982d Mon Sep 17 00:00:00 2001 From: georgematheos Date: Tue, 10 Sep 2024 14:41:19 -0400 Subject: [PATCH 03/37] Inference algorithm rewrite outline (#153) This adds in a template for the full inference algorithm, and implementations of some of the subsidiary methods. I added `notebooks/bayes3d_paper/tester.ipynb` which runs this partial inference algorithm. I have made several changes to the existing code: - I have changed the interfaces to the pixel kernels slightly, and added docstrings more fully specifying the interfaces the rest of the codebase expects these kernels to satisfy. - I have added utility methods to `PixelsPointsAssociation`. - I have added methods for getting the active pixel kernels to the Image Kernel. - I have renamed the `possible_values` of the discrete kernels to `support` (I thought this was a more standard name - but we can revert this if desired). --- notebooks/bayes3d_paper/online_hb.ipynb | 85 ++-- notebooks/bayes3d_paper/tester.ipynb | 381 ++++++++++++++++++ src/b3d/chisight/gen3d/block_moves.py | 0 .../gen3d/deprecated/__OLD_inference.py | 241 +++++++++++ src/b3d/chisight/gen3d/image_kernel.py | 164 ++++---- src/b3d/chisight/gen3d/inference.py | 250 +++--------- src/b3d/chisight/gen3d/inference_moves.py | 227 +++++++++++ src/b3d/chisight/gen3d/model.py | 38 +- .../chisight/gen3d/pixel_kernels/__init__.py | 23 ++ .../pixel_kernels/pixel_color_kernels.py | 82 ++-- .../pixel_kernels/pixel_depth_kernels.py | 78 ++-- .../gen3d/pixel_kernels/pixel_rgbd_kernels.py | 41 +- src/b3d/chisight/gen3d/projection.py | 158 ++++++++ src/b3d/chisight/gen3d/transition_kernels.py | 25 +- .../kfold_image_kernel_real_data.py | 127 ------ .../kfold_image_kernel_unit_test.py | 162 -------- .../test_pixel_distribution.py | 380 ----------------- .../test_raycast_nondeterministic.py | 71 ---- .../test_truncated_laplace.py | 114 ------ tests/gen3d/test_model.py | 16 +- tests/gen3d/test_pixel_color_kernels.py | 33 +- tests/gen3d/test_pixel_depth_kernels.py | 27 +- tests/gen3d/test_pixel_rgbd_kernels.py | 20 +- tests/gen3d/test_transition_kernels.py | 2 +- 24 files changed, 1452 insertions(+), 1293 deletions(-) create mode 100644 notebooks/bayes3d_paper/tester.ipynb delete mode 100644 src/b3d/chisight/gen3d/block_moves.py create mode 100644 src/b3d/chisight/gen3d/deprecated/__OLD_inference.py create mode 100644 src/b3d/chisight/gen3d/inference_moves.py create mode 100644 src/b3d/chisight/gen3d/projection.py delete mode 100644 tests/dynamic_object_model/kfold_image_kernel_real_data.py delete mode 100644 tests/dynamic_object_model/kfold_image_kernel_unit_test.py delete mode 100644 tests/dynamic_object_model/test_pixel_distribution.py delete mode 100644 tests/dynamic_object_model/test_raycast_nondeterministic.py delete mode 100644 tests/dynamic_object_model/test_truncated_laplace.py diff --git a/notebooks/bayes3d_paper/online_hb.ipynb b/notebooks/bayes3d_paper/online_hb.ipynb index 66612a77..855ad3d1 100644 --- a/notebooks/bayes3d_paper/online_hb.ipynb +++ b/notebooks/bayes3d_paper/online_hb.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 134, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 135, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -47,7 +47,17 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 14.06it/s]\n" + " 0%| | 0/49 [00:00" ] }, - "execution_count": 135, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -95,7 +105,7 @@ }, { "cell_type": "code", - "execution_count": 154, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -122,19 +132,19 @@ }, { "cell_type": "code", - "execution_count": 152, + "execution_count": 4, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "22682.564\n" - ] - } - ], + "outputs": [], + "source": [ + "near, far = 0.001, 100." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], "source": [ - "\n", "T = 0\n", "b3d.rr_set_time(T)\n", "OBJECT_INDEX = 1\n", @@ -169,7 +179,9 @@ " resample_probability=0.05, possible_values=jnp.array([0.05, 0.1, 0.15])\n", " ),\n", "\n", - " \"image_likelihood\": image_kernel.SimpleNoRenderImageLikelihood(),\n", + " \"image_likelihood\": image_kernel.NoOcclusionPerVertexImageKernel(\n", + " near, far, image_height, image_width\n", + " ),\n", "\n", " \"fx\": fx,\n", " \"fy\": fy,\n", @@ -178,9 +190,36 @@ " \"image_height\": Pytree.const(image_height),\n", " \"image_width\": Pytree.const(image_width),\n", " \n", - " \"vertices\":model_vertices\n", - "}\n", - "\n", + " \"vertices\": model_vertices\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "82541.78\n" + ] + }, + { + "ename": "AttributeError", + "evalue": "'NoOcclusionPerVertexImageKernel' object has no attribute 'info_from_trace'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[6], line 30\u001b[0m\n\u001b[1;32m 28\u001b[0m trace\u001b[38;5;241m=\u001b[39m dynamic_object_generative_model\u001b[38;5;241m.\u001b[39mimportance(key, choicemap, (hyperparams, previous_state))[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 29\u001b[0m \u001b[38;5;28mprint\u001b[39m(trace\u001b[38;5;241m.\u001b[39mget_score())\n\u001b[0;32m---> 30\u001b[0m \u001b[43mb3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchisight\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mviz_trace\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 31\u001b[0m results \u001b[38;5;241m=\u001b[39m {}\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/model.py:125\u001b[0m, in \u001b[0;36mviz_trace\u001b[0;34m(trace, t, ground_truth_vertices, ground_truth_pose)\u001b[0m\n\u001b[1;32m 123\u001b[0m output \u001b[38;5;241m=\u001b[39m trace\u001b[38;5;241m.\u001b[39mget_retval()\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m output[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 125\u001b[0m info \u001b[38;5;241m=\u001b[39m \u001b[43mhyperparams\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mimage_likelihood\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minfo_from_trace\u001b[49m(trace)\n\u001b[1;32m 126\u001b[0m b3d\u001b[38;5;241m.\u001b[39mrr_log_rgb(output[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m][\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 127\u001b[0m b3d\u001b[38;5;241m.\u001b[39mrr_log_rgb(output[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m][\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage/rgb/observed\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mAttributeError\u001b[0m: 'NoOcclusionPerVertexImageKernel' object has no attribute 'info_from_trace'" + ] + } + ], + "source": [ "num_vertices = model_vertices.shape[0]\n", "previous_state = {\n", " \"pose\": template_pose,\n", @@ -236,7 +275,7 @@ ], "source": [ "b3d.reload(b3d.chisight.gen3d.inference)\n", - "from b3d.chisight.gen3d.inference import propose_update, inference_step\n", + "from b3d.chisight.gen3d.deprecated.__OLD_inference import propose_update, inference_step\n", "### Run inference ###\n", "for T in tqdm(range(len(all_data))):\n", " key = b3d.split_key(key)\n", @@ -391,7 +430,7 @@ ], "metadata": { "kernelspec": { - "display_name": "b3d", + "display_name": "gpu", "language": "python", "name": "python3" }, @@ -405,7 +444,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb new file mode 100644 index 00000000..51db36e7 --- /dev/null +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -0,0 +1,381 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d\n", + "import jax.numpy as jnp\n", + "import os\n", + "from tqdm import tqdm\n", + "from b3d import Mesh, Pose\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init(\"inference_test\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Scene 49\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 49/49 [00:03<00:00, 12.57it/s]\n", + "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", + "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/jpeg": 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", 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", + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scene_id = 49\n", + "FRAME_RATE = 50\n", + "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", + "print(f\"Scene {scene_id}\")\n", + "b3d.reload(b3d.io.data_loader)\n", + "num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id)\n", + "\n", + "# image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE)\n", + "image_ids = range(1, num_scenes + 1, FRAME_RATE)\n", + "all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, image_ids)\n", + "\n", + "meshes = [\n", + " Mesh.from_obj_file(\n", + " os.path.join(ycb_dir, f'models/obj_{f\"{id + 1}\".rjust(6, \"0\")}.ply')\n", + " ).scale(0.001)\n", + " for id in all_data[0][\"object_types\"]\n", + "]\n", + "\n", + "image_height, image_width = all_data[0][\"rgbd\"].shape[:2]\n", + "fx,fy,cx,cy = all_data[0][\"camera_intrinsics\"]\n", + "scaling_factor = 1.0\n", + "renderer = b3d.renderer.renderer_original.RendererOriginal(\n", + " image_width * scaling_factor, image_height * scaling_factor, fx * scaling_factor, fy * scaling_factor, cx * scaling_factor, cy * scaling_factor, 0.01, 2.0\n", + ")\n", + "b3d.viz_rgb(all_data[0][\"rgbd\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d\n", + "import b3d.chisight.gen3d.model\n", + "b3d.reload(b3d.chisight.gen3d.model)\n", + "import b3d.chisight.gen3d.transition_kernels as transition_kernels\n", + "b3d.reload(b3d.chisight.gen3d.transition_kernels)\n", + "import b3d.chisight.gen3d.image_kernel as image_kernel\n", + "b3d.reload(b3d.chisight.gen3d.image_kernel)\n", + "import b3d.io.data_loader\n", + "import jax\n", + "import jax.numpy as jnp\n", + "from b3d import Mesh, Pose\n", + "from b3d.chisight.gen3d.model import (\n", + " make_colors_choicemap,\n", + " make_depth_nonreturn_prob_choicemap,\n", + " make_visibility_prob_choicemap,\n", + ")\n", + "from b3d.chisight.gen3d.model import dynamic_object_generative_model\n", + "from genjax import ChoiceMapBuilder as C\n", + "from genjax import Pytree\n", + "import genjax" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "near, far = 0.001, 100." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "T = 0\n", + "b3d.rr_set_time(T)\n", + "\n", + "OBJECT_INDEX = 1\n", + "\n", + "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", + "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", + "xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy)\n", + "\n", + "fx, fy, cx, cy = all_data[T][\"camera_intrinsics\"]\n", + "xyz_observed = b3d.xyz_from_depth(all_data[T][\"rgbd\"][..., 3], fx, fy, cx, cy)\n", + "mask = all_data[T][\"masks\"][OBJECT_INDEX] * (xyz_observed[..., 2] > 0) * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01)\n", + "model_vertices = template_pose.inv().apply(xyz_rendered[mask])\n", + "model_colors = vertex_attributes=all_data[T][\"rgbd\"][..., :3][mask]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "img_model = image_kernel.NoOcclusionPerVertexImageKernel(\n", + " near, far, image_height, image_width\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "hyperparams = {\n", + " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", + " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.15),\n", + " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", + " ),\n", + " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", + " ),\n", + " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02])\n", + " ),\n", + " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.05, 0.1, 0.15])\n", + " ),\n", + "\n", + " \"image_kernel\": img_model,\n", + "\n", + " \"intrinsics\": {\n", + " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy\n", + " },\n", + " \"image_height\": Pytree.const(image_height),\n", + " \"image_width\": Pytree.const(image_width),\n", + " \n", + " \"vertices\": model_vertices\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from b3d.chisight.gen3d.inference import InferenceHyperparams\n", + "inference_hyperparams = InferenceHyperparams(\n", + " n_poses=100,\n", + " pose_proposal_std=0.04,\n", + " pose_proposal_conc=1000.,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "num_vertices = model_vertices.shape[0]\n", + "previous_state = {\n", + " \"pose\": template_pose,\n", + " \"colors\": model_colors,\n", + " \"visibility_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"visibility_prob_kernel\"].support[-1],\n", + " \"depth_nonreturn_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"depth_nonreturn_prob_kernel\"].support[0],\n", + " \"depth_scale\": hyperparams[\"depth_scale_kernel\"].support[0],\n", + " \"color_scale\": hyperparams[\"color_scale_kernel\"].support[0],\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "choicemap = (\n", + " genjax.ChoiceMap.d(\n", + " {\n", + " \"pose\": previous_state[\"pose\"],\n", + " \"color_scale\": previous_state[\"color_scale\"],\n", + " \"depth_scale\": previous_state[\"depth_scale\"],\n", + " \"rgbd\": all_data[T][\"rgbd\"],\n", + " }\n", + " ) ^ \n", + " make_visibility_prob_choicemap(previous_state[\"visibility_prob\"]) ^\n", + " make_colors_choicemap(previous_state[\"colors\"]) ^\n", + " make_depth_nonreturn_prob_choicemap(previous_state[\"depth_nonreturn_prob\"])\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array(82541.78, dtype=float32)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "key = jax.random.PRNGKey(0)\n", + "trace, weight = dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", + "weight" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array(82541.78, dtype=float32)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "trace.get_score()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d.chisight.gen3d.inference as i\n", + "b3d.reload(b3d.chisight.gen3d.projection)\n", + "b3d.reload(b3d.chisight.gen3d.inference_moves)\n", + "b3d.reload(i)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array(36987.824, dtype=float32)" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inference_hyperparams = InferenceHyperparams(\n", + " n_poses=10000,\n", + " pose_proposal_std=0.04,\n", + " pose_proposal_conc=1000.,\n", + ")\n", + "\n", + "stepped_trace, step_weight = i.inference_step(\n", + " jax.random.PRNGKey(20),\n", + " trace,\n", + " all_data[1][\"rgbd\"],\n", + " inference_hyperparams\n", + ")\n", + "step_weight" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.reload(b3d.chisight.gen3d.model)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "T = 1\n", + "b3d.chisight.gen3d.model.viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "gpu", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/src/b3d/chisight/gen3d/block_moves.py b/src/b3d/chisight/gen3d/block_moves.py deleted file mode 100644 index e69de29b..00000000 diff --git a/src/b3d/chisight/gen3d/deprecated/__OLD_inference.py b/src/b3d/chisight/gen3d/deprecated/__OLD_inference.py new file mode 100644 index 00000000..02c439c9 --- /dev/null +++ b/src/b3d/chisight/gen3d/deprecated/__OLD_inference.py @@ -0,0 +1,241 @@ +import jax +import jax.numpy as jnp +import jax.random +from b3d import Pose +from genjax import ChoiceMapBuilder as C +from genjax import Diff +from genjax import UpdateProblemBuilder as U + +from ..model import ( + make_colors_choicemap, + make_visibility_prob_choicemap, +) + + +@jax.jit +def advance_time(key, trace, observed_rgbd): + """ + Advance to the next timestep, setting the new latent state to the + same thing as the previous latent state, and setting the new + observed RGBD value. + + Returns a trace where previous_state (stored in the arguments) + and new_state (sampled in the choices and returned) are identical. + """ + hyperparams, _ = trace.get_args() + previous_state = trace.get_retval()["new_state"] + trace, _, _, _ = trace.update( + key, + U.g( + (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), + C.kw(rgbd=observed_rgbd), + ), + ) + return trace + + +@jax.jit +def propose_color_and_visibility(trace, key): + # color_outlier_probability_sweep is (k,) shape array + hyperparams, previous_state = trace.get_args() + previous_visibility = previous_state["visibility_prob"] + previous_colors = previous_state["colors"] + + visibility_values = hyperparams["visibility_prob_kernel"].possible_values + + visibility_sweep = ( + visibility_values[..., None] # (num_outlier_grid_points, 1) + * jnp.ones_like(previous_visibility) # (num_vertices,) + ) # (num_outlier_grid_points, num_vertices) + + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + + visibility_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( + visibility_prob_kernel.logpdf, + signature="(),()->()", + )(visibility_sweep, previous_visibility) + + info_from_trace = hyperparams["image_likelihood"].info_from_trace + + # We will grid over color values, using a grid that mixes the old and observed + # colors in a set of exact proportions. + # We regard these as coming from uniform proposals where we sample the RGB + # values uniformly between the mixed R, G, and B values with mixtures between + # [0., .125], [.125, .5], [.5, .875], [.875, 1.]. + # So the q scores will be .125^3, .375^3, .375^3, .125^3. + # TODO: we really ought to add a small amount of proposal probability mass + # onto the points at the end, to capture the fact that the posterior could allow + # colors outside the considered interpolation window. + color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) + # num_color_grid_points = len(color_interpolations_per_proposal) + + observed_colors = info_from_trace(trace)["observed_rgbd_masked"][ + ..., :3 + ] # (num_vertices, 3) + color_sweep = observed_colors[None, ...] * color_interpolations_per_proposal[ + :, None, None + ] + previous_colors[None, ...] * ( + 1 - color_interpolations_per_proposal[:, None, None] + ) # (num_color_grid_points, num_vertices, 3) + + color_kernel = hyperparams["color_kernel"] + color_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( + color_kernel.logpdf, + signature="(3),(3)->()", + )(color_sweep, previous_colors) + + # Function takes in color and color outlier probabilities array of shapes (num_vertices,3) and (num_vertices,) respectively + # and gives scores for each vertex (num_vertices,) + def get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities( + colors, visibility + ): + return info_from_trace( + trace.update( + key, + make_colors_choicemap(colors) + ^ make_visibility_prob_choicemap(visibility), + )[0] + )["scores"] + + vmap_version = jax.vmap( + jax.vmap( + get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities, + in_axes=(None, 0), + ), + in_axes=(0, None), + ) + + # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep + likelihood_scores_per_sweep_point_and_vertex = vmap_version( + color_sweep, visibility_sweep + ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + scores_per_sweep_point_and_vertex = ( + likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + visibility_transition_scores_per_sweep_point_and_vertex[None, ...] + + color_transition_scores_per_sweep_point_and_vertex[:, None, ...] + ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + unraveled_scores = scores_per_sweep_point_and_vertex.reshape( + -1, scores_per_sweep_point_and_vertex.shape[-1] + ) + normalized_log_probabilities = jax.nn.log_softmax(unraveled_scores, axis=0) + sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) + + color_sweep_indices, visibility_sweep_indices = jnp.unravel_index( + sampled_indices, scores_per_sweep_point_and_vertex.shape[:2] + ) + + # color_sweep is (num_outlier_grid_points, num_vertices, 3) + # outlier_probability_sweep is (num_outlier_grid_points,) + # color_outlier_probabilities_sweep is (num_outlier_grid_points, num_vertices) + sampled_colors = color_sweep[color_sweep_indices, jnp.arange(color_sweep.shape[1])] + sampled_color_outlier_probabilities = visibility_values[visibility_sweep_indices] + + log_q_color_and_color_outlier_probability = normalized_log_probabilities[ + sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) + ].sum() + + # log_q = estimate of q(all these colors, all these outliers ; inputs) + # Only source of real randomness = sampling indices. Captured in log_q_color_and_color_outlier_probability. + # But we also want to be careful with the continuous values... + # (1) outlier probs. --> change the model to have discrete grid. [Do later.] + # (2) colors. --> 1/q() + # uniform(old r, 2/3 oldr + 1/3 newr) 0 | uniform(0, 0.1) + # uniform(1/3, 2/3) # .5 | uniform(.1, .9) + # uniform(2/3, 1) # 1 | uniform(.9, 1) + # + # q(c1) * q(c2) * q(c3) + # but we just output c2 + # q(the c values we output, marginalizing over the other choices) + # -> just output q(c2) + + # We will treat this like the case where each sweep is uniform, so the q scores + # are each (oldr - obsr)/3 * (oldg - obsg)/3 * (oldb - obsb)/3. + + hyperparams = trace.get_args()[0] + color_shift_scale = hyperparams["color_kernel"].scale + color_scale = trace.get_choices()["color_scale"] + + d = 1 / (1 / color_shift_scale + 1 / color_scale) + + q_prob_per_vertex = ( + 1.0 / ((jnp.abs(previous_colors - observed_colors) / 3) + 4 * d) + ).prod(-1) + log_q_for_the_color_proposal = jnp.log(q_prob_per_vertex).sum() + + return ( + sampled_colors, + sampled_color_outlier_probabilities, + log_q_color_and_color_outlier_probability + log_q_for_the_color_proposal, + scores_per_sweep_point_and_vertex, + ) + + +@jax.jit +def propose_update(trace, key, pose): + total_log_q = 0.0 + + # Update pose + # pose, log_q_pose = propose_pose( + # trace, key, pose_sample_variance, pose_sample_concentration + # ) + trace = trace.update(key, C["pose"].set(pose))[0] + + # Update color and color outlier probability + sampled_colors, sampled_visibility, log_q, _ = propose_color_and_visibility( + trace, key + ) + trace = trace.update( + key, + make_colors_choicemap(sampled_colors) + ^ make_visibility_prob_choicemap(sampled_visibility), + )[0] + total_log_q += log_q + + return trace, total_log_q + + +@jax.jit +def propose_update_get_score(trace, key, pose): + new_trace, log_q = propose_update(trace, key, pose) + # score is an estimate of P(data, pose | previous state) + return new_trace.get_score() - log_q + + +propose_update_get_score_vmap = jax.jit( + jax.vmap(propose_update_get_score, in_axes=(None, None, 0)) +) + + +def inference_step_without_advance(trace, key): + number = 15000 + current_pose = trace.get_choices()["pose"] + var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] + for var, conc in var_conc: + key = jax.random.split(key, 2)[-1] + keys = jax.random.split(key, number) + poses = Pose.concatenate_poses( + [ + Pose.sample_gaussian_vmf_pose_vmap(keys, current_pose, var, conc), + current_pose[None, ...], + ] + ) + pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( + poses, trace.get_choices()["pose"], var, conc + ) + scores = propose_update_get_score_vmap(trace, key, poses) + scores_pose_q_correction = ( + scores - pose_scores + ) # After this, scores are fair estimates of P(data | previous state) + # and can be used to resample the choice sets. + index = jax.random.categorical(key, scores) + current_pose = poses[index] + trace = propose_update(trace, key, current_pose)[0] + return trace, scores, scores_pose_q_correction + + +def inference_step(trace, key, observed_rgbd): + trace = advance_time(key, trace, observed_rgbd) + trace = inference_step_without_advance(trace, key)[0] + return trace diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index 892af51e..e92cdc93 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -1,108 +1,108 @@ from abc import abstractmethod +from typing import Mapping import genjax import jax import jax.numpy as jnp from genjax import Pytree -from genjax.typing import PRNGKey +from genjax.typing import FloatArray, PRNGKey -import b3d +from b3d.chisight.gen3d.pixel_kernels import ( + FullPixelColorDistribution, + FullPixelDepthDistribution, + PixelDepthDistribution, + PixelRGBDDistribution, +) +from b3d.chisight.gen3d.projection import PixelsPointsAssociation @Pytree.dataclass -class ImageLikelihood(genjax.ExactDensity): - """An abstract class that defines the common interface for drift kernels.""" +class ImageKernel(genjax.ExactDensity): + """An abstract class that defines the common interface for image kernels, + which generates a new RGBD image from the current state, controlled by + the hyperparameters. + + The support of the distribution is [0, 1]^3 x [near, far]. + """ + + near: float = Pytree.static() + far: float = Pytree.static() + image_height: int = Pytree.static() + image_width: int = Pytree.static() + + def get_pixels_points_association( + self, transformed_points, hyperparams: Mapping + ) -> PixelsPointsAssociation: + return PixelsPointsAssociation.from_points_and_intrinsics( + transformed_points, + hyperparams["intrinsics"], + self.image_height, + self.image_width, + ) @abstractmethod - def sample(self, key: PRNGKey, new_state, hyperparams): + def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: raise NotImplementedError - def logpdf(self, observed_rgbd, new_state, hyperparams): - return self.info(observed_rgbd, new_state, hyperparams)["score"] + @abstractmethod + def logpdf( + self, obseved_rgbd: FloatArray, state: Mapping, hyperparams: Mapping + ) -> FloatArray: + raise NotImplementedError - def info_from_trace(self, trace): - hyperparams, _ = trace.get_args() - return self.info( - trace.get_retval()["rgbd"], trace.get_retval()["new_state"], hyperparams - ) + def get_depth_vertex_kernel(self) -> PixelDepthDistribution: + raise NotImplementedError - def info(self, observed_rgbd, new_state, hyperparams): + def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: raise NotImplementedError @Pytree.dataclass -class SimpleNoRenderImageLikelihood(ImageLikelihood): - def sample(self, key: PRNGKey, new_state, hyperparams): - return jnp.zeros( - ( - hyperparams["image_height"].const, - hyperparams["image_width"].const, - 4, - ) +class NoOcclusionPerVertexImageKernel(ImageKernel): + near: float = Pytree.static() + far: float = Pytree.static() + image_height: int = Pytree.static() + image_width: int = Pytree.static() + + def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: + """Generate latent RGBD image by projecting the vertices directly to the image + plane, without checking for occlusions. + """ + # TODO: to be finished... + return jnp.zeros((self.image_height, self.image_width, 4)) + + def logpdf( + self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping + ) -> FloatArray: + transformed_points = state["pose"].apply(hyperparams["vertices"]) + points_to_pixels = self.get_pixels_points_association( + transformed_points, hyperparams ) - - def logpdf(self, observed_rgbd, new_state, hyperparams): - return self.info(observed_rgbd, new_state, hyperparams)["score"] - - def info(self, observed_rgbd, new_state, hyperparams): - transformed_points = new_state["pose"].apply(hyperparams["vertices"]) - projected_pixel_coordinates = jnp.rint( - b3d.xyz_to_pixel_coordinates( - transformed_points, - hyperparams["fx"], - hyperparams["fy"], - hyperparams["cx"], - hyperparams["cy"], - ) - ).astype(jnp.int32) - - observed_rgbd_masked = observed_rgbd[ - projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1] - ] - - color_visible_branch_score = jax.scipy.stats.laplace.logpdf( - observed_rgbd_masked[..., :3], new_state["colors"], new_state["color_scale"] - ).sum(axis=-1) - color_not_visible_score = jnp.log(1 / 1.0**3) - color_score = jnp.logaddexp( - color_visible_branch_score + jnp.log(new_state["visibility_prob"]), - color_not_visible_score + jnp.log(1 - new_state["visibility_prob"]), + vertex_kernel = self.get_rgbd_vertex_kernel() + observed_rgbd_per_point = observed_rgbd.at[ + points_to_pixels.x, points_to_pixels.y + ].get(mode="drop", fill_value=-1.0) + latent_rgbd_per_point = jnp.concatenate( + (state["colors"], transformed_points[..., 2, None]), axis=-1 ) - depth_visible_branch_score = jax.scipy.stats.laplace.logpdf( - observed_rgbd_masked[..., 3], - transformed_points[..., 2], - new_state["depth_scale"], + scores = jax.vmap(vertex_kernel.logpdf, in_axes=(0, 0, None, None, 0, 0))( + observed_rgbd_per_point, + latent_rgbd_per_point, + state["color_scale"], + state["depth_scale"], + state["visibility_prob"], + state["depth_nonreturn_prob"], ) - depth_not_visible_score = jnp.log(1 / 1.0) - _depth_score = jnp.logaddexp( - depth_visible_branch_score + jnp.log(new_state["visibility_prob"]), - depth_not_visible_score + jnp.log(1 - new_state["visibility_prob"]), - ) - is_depth_non_return = observed_rgbd_masked[..., 3] < 0.0001 - - non_return_probability = 0.05 - depth_score = jnp.where( - is_depth_non_return, jnp.log(non_return_probability), _depth_score + return scores.sum() + + def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: + # Note: The distributions were originally defined for per-pixel computation, + # but they should work for per-vertex computation as well + return PixelRGBDDistribution( + FullPixelColorDistribution(), + FullPixelDepthDistribution(self.near, self.far), ) - lmbda = 0.5 - scores = lmbda * color_score + (1.0 - lmbda) * depth_score - - # Visualization - latent_rgbd = jnp.zeros_like(observed_rgbd) - latent_rgbd = latent_rgbd.at[ - projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1], :3 - ].set(new_state["colors"]) - latent_rgbd = latent_rgbd.at[ - projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1], 3 - ].set(transformed_points[..., 2]) - - return { - "score": scores.sum(), - "scores": scores, - "pixel_coordinates": projected_pixel_coordinates, - "transformed_points": transformed_points, - "observed_rgbd_masked": observed_rgbd_masked, - "latent_rgbd": latent_rgbd, - } + def get_depth_vertex_kernel(self) -> PixelDepthDistribution: + return self.get_rgbd_vertex_kernel().depth_kernel diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 5540edb1..83c08de2 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -1,15 +1,26 @@ +from collections import namedtuple +from functools import partial + import jax import jax.numpy as jnp import jax.random from genjax import ChoiceMapBuilder as C from genjax import Diff from genjax import UpdateProblemBuilder as U +from jax.random import split -from b3d import Pose - +from .inference_moves import ( + propose_other_latents_given_pose, + propose_pose, +) from .model import ( - make_colors_choicemap, - make_visibility_prob_choicemap, + get_hypers, + get_prev_state, +) + +# Use namedtuple rather than dict so we can hash this, and use it as a static arg to a jitted function. +InferenceHyperparams = namedtuple( + "InferenceHyperparams", ["n_poses", "pose_proposal_std", "pose_proposal_conc"] ) @@ -23,220 +34,61 @@ def advance_time(key, trace, observed_rgbd): Returns a trace where previous_state (stored in the arguments) and new_state (sampled in the choices and returned) are identical. """ - hyperparams, _ = trace.get_args() - previous_state = trace.get_retval()["new_state"] trace, _, _, _ = trace.update( key, U.g( - (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), + ( + Diff.no_change(get_hypers(trace)), + Diff.unknown_change(get_prev_state(trace)), + ), C.kw(rgbd=observed_rgbd), ), ) return trace -@jax.jit -def propose_color_and_visibility(trace, key): - # color_outlier_probability_sweep is (k,) shape array - hyperparams, previous_state = trace.get_args() - previous_visibility = previous_state["visibility_prob"] - previous_colors = previous_state["colors"] - - visibility_values = hyperparams["visibility_prob_kernel"].possible_values - - visibility_sweep = ( - visibility_values[..., None] # (num_outlier_grid_points, 1) - * jnp.ones_like(previous_visibility) # (num_vertices,) - ) # (num_outlier_grid_points, num_vertices) - - visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - - visibility_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( - visibility_prob_kernel.logpdf, - signature="(),()->()", - )(visibility_sweep, previous_visibility) - - info_from_trace = hyperparams["image_likelihood"].info_from_trace - - # We will grid over color values, using a grid that mixes the old and observed - # colors in a set of exact proportions. - # We regard these as coming from uniform proposals where we sample the RGB - # values uniformly between the mixed R, G, and B values with mixtures between - # [0., .125], [.125, .5], [.5, .875], [.875, 1.]. - # So the q scores will be .125^3, .375^3, .375^3, .125^3. - # TODO: we really ought to add a small amount of proposal probability mass - # onto the points at the end, to capture the fact that the posterior could allow - # colors outside the considered interpolation window. - color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) - # num_color_grid_points = len(color_interpolations_per_proposal) - - observed_colors = info_from_trace(trace)["observed_rgbd_masked"][ - ..., :3 - ] # (num_vertices, 3) - color_sweep = observed_colors[None, ...] * color_interpolations_per_proposal[ - :, None, None - ] + previous_colors[None, ...] * ( - 1 - color_interpolations_per_proposal[:, None, None] - ) # (num_color_grid_points, num_vertices, 3) - - color_kernel = hyperparams["color_kernel"] - color_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( - color_kernel.logpdf, - signature="(3),(3)->()", - )(color_sweep, previous_colors) - - # Function takes in color and color outlier probabilities array of shapes (num_vertices,3) and (num_vertices,) respectively - # and gives scores for each vertex (num_vertices,) - def get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities( - colors, visibility - ): - return info_from_trace( - trace.update( - key, - make_colors_choicemap(colors) - ^ make_visibility_prob_choicemap(visibility), - )[0] - )["scores"] - - vmap_version = jax.vmap( - jax.vmap( - get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities, - in_axes=(None, 0), - ), - in_axes=(0, None), - ) - - # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep - likelihood_scores_per_sweep_point_and_vertex = vmap_version( - color_sweep, visibility_sweep - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - scores_per_sweep_point_and_vertex = ( - likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points, num_vertices) - + visibility_transition_scores_per_sweep_point_and_vertex[None, ...] - + color_transition_scores_per_sweep_point_and_vertex[:, None, ...] - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) +@partial(jax.jit, static_argnums=(3,)) +def inference_step(key, old_trace, observed_rgbd, inference_hyperparams): + """ + Perform over the latent state at time T, given the observed + rgbd at this timestep, and the old trace from time T-1. - unraveled_scores = scores_per_sweep_point_and_vertex.reshape( - -1, scores_per_sweep_point_and_vertex.shape[-1] - ) - normalized_log_probabilities = jax.nn.log_softmax(unraveled_scores, axis=0) - sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) + Also returns an estimate of the marginal likelihood of + the observed rgbd, given the latent state from time T-1. + """ + k1, k2, k3, k4 = split(key, 4) - color_sweep_indices, visibility_sweep_indices = jnp.unravel_index( - sampled_indices, scores_per_sweep_point_and_vertex.shape[:2] - ) + trace = advance_time(k1, old_trace, observed_rgbd) - # color_sweep is (num_outlier_grid_points, num_vertices, 3) - # outlier_probability_sweep is (num_outlier_grid_points,) - # color_outlier_probabilities_sweep is (num_outlier_grid_points, num_vertices) - sampled_colors = color_sweep[color_sweep_indices, jnp.arange(color_sweep.shape[1])] - sampled_color_outlier_probabilities = visibility_values[visibility_sweep_indices] - - log_q_color_and_color_outlier_probability = normalized_log_probabilities[ - sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) - ].sum() - - # log_q = estimate of q(all these colors, all these outliers ; inputs) - # Only source of real randomness = sampling indices. Captured in log_q_color_and_color_outlier_probability. - # But we also want to be careful with the continuous values... - # (1) outlier probs. --> change the model to have discrete grid. [Do later.] - # (2) colors. --> 1/q() - # uniform(old r, 2/3 oldr + 1/3 newr) 0 | uniform(0, 0.1) - # uniform(1/3, 2/3) # .5 | uniform(.1, .9) - # uniform(2/3, 1) # 1 | uniform(.9, 1) - # - # q(c1) * q(c2) * q(c3) - # but we just output c2 - # q(the c values we output, marginalizing over the other choices) - # -> just output q(c2) - - # We will treat this like the case where each sweep is uniform, so the q scores - # are each (oldr - obsr)/3 * (oldg - obsg)/3 * (oldb - obsb)/3. - - hyperparams = trace.get_args()[0] - color_shift_scale = hyperparams["color_kernel"].scale - color_scale = trace.get_choices()["color_scale"] - - d = 1 / (1 / color_shift_scale + 1 / color_scale) - - q_prob_per_vertex = ( - 1.0 / ((jnp.abs(previous_colors - observed_colors) / 3) + 4 * d) - ).prod(-1) - log_q_for_the_color_proposal = jnp.log(q_prob_per_vertex).sum() - - return ( - sampled_colors, - sampled_color_outlier_probabilities, - log_q_color_and_color_outlier_probability + log_q_for_the_color_proposal, - scores_per_sweep_point_and_vertex, + pose_generation_keys = split(k2, inference_hyperparams.n_poses) + proposed_poses, log_q_poses = jax.vmap(propose_pose, in_axes=(0, None, None))( + pose_generation_keys, trace, inference_hyperparams ) + param_generation_keys = split(k3, inference_hyperparams.n_poses) + proposed_traces, log_q_nonpose_latents = jax.vmap( + propose_other_latents_given_pose, in_axes=(0, None, 0, None) + )(param_generation_keys, trace, proposed_poses, inference_hyperparams) + p_scores = jax.vmap(lambda tr: tr.get_score())(proposed_traces) -@jax.jit -def propose_update(trace, key, pose): - total_log_q = 0.0 - - # Update pose - # pose, log_q_pose = propose_pose( - # trace, key, pose_sample_variance, pose_sample_concentration - # ) - trace = trace.update(key, C["pose"].set(pose))[0] - - # Update color and color outlier probability - sampled_colors, sampled_visibility, log_q, _ = propose_color_and_visibility( - trace, key - ) - trace = trace.update( - key, - make_colors_choicemap(sampled_colors) - ^ make_visibility_prob_choicemap(sampled_visibility), - )[0] - total_log_q += log_q + scores = p_scores - log_q_poses - log_q_nonpose_latents + chosen_index = jax.random.categorical(k4, scores) + new_trace = jax.tree.map(lambda x: x[chosen_index], proposed_traces) - return trace, total_log_q + return new_trace, logmeanexp(scores) -@jax.jit -def propose_update_get_score(trace, key, pose): - new_trace, log_q = propose_update(trace, key, pose) - # score is an estimate of P(data, pose | previous state) - return new_trace.get_score() - log_q +def inference_step_noweight(*args): + """ + Same as inference_step, but only returns the new trace + (not the weight). + """ + return inference_step(*args)[0] -propose_update_get_score_vmap = jax.jit( - jax.vmap(propose_update_get_score, in_axes=(None, None, 0)) -) +### Utils ### -def inference_step_without_advance(trace, key): - number = 15000 - current_pose = trace.get_choices()["pose"] - var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] - for var, conc in var_conc: - key = jax.random.split(key, 2)[-1] - keys = jax.random.split(key, number) - poses = Pose.concatenate_poses( - [ - Pose.sample_gaussian_vmf_pose_vmap(keys, current_pose, var, conc), - current_pose[None, ...], - ] - ) - pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( - poses, trace.get_choices()["pose"], var, conc - ) - scores = propose_update_get_score_vmap(trace, key, poses) - scores_pose_q_correction = ( - scores - pose_scores - ) # After this, scores are fair estimates of P(data | previous state) - # and can be used to resample the choice sets. - index = jax.random.categorical(key, scores) - current_pose = poses[index] - trace = propose_update(trace, key, current_pose)[0] - return trace, scores, scores_pose_q_correction - - -def inference_step(trace, key, observed_rgbd): - trace = advance_time(key, trace, observed_rgbd) - trace = inference_step_without_advance(trace, key)[0] - return trace +def logmeanexp(vec): + vec = jnp.where(jnp.isnan(vec), -jnp.inf, vec) + return jax.scipy.special.logsumexp(vec) - jnp.log(len(vec)) diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py new file mode 100644 index 00000000..0518383d --- /dev/null +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -0,0 +1,227 @@ +import jax +import jax.numpy as jnp +import jax.random +from genjax import ChoiceMapBuilder as C +from genjax import Diff +from genjax import UpdateProblemBuilder as U +from jax.random import split + +from b3d import Pose + +from .model import ( + get_hypers, + get_n_vertices, + get_new_state, + get_observed_rgbd, + get_prev_state, +) +from .projection import PixelsPointsAssociation + + +def propose_pose(key, advanced_trace, inference_hyperparams): + """ + Propose a random pose near the previous timestep's pose. + Returns (proposed_pose, log_proposal_density). + """ + previous_pose = get_prev_state(advanced_trace)["pose"] + ih = inference_hyperparams + pose = Pose.sample_gaussian_vmf_pose( + key, previous_pose, ih.pose_proposal_std, ih.pose_proposal_conc + ) + log_q = Pose.logpdf_gaussian_vmf_pose( + pose, previous_pose, ih.pose_proposal_std, ih.pose_proposal_conc + ) + return pose, log_q + + +def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperparams): + """ + Proposes all latents other than the pose, conditional upon the pose and observed RGBD + in `advanced_trace`. + Returns (proposed_trace, log_q) where `propose_trace` is the new trace with the + proposed latents (and the same pose and observed rgbd as in the given trace). + `log_q` is (a fair estimate of) the log proposal density. + """ + k1, k2, k3, k4, k5, k6 = split(key, 6) + + trace_with_pose = update_field(k1, advanced_trace, "pose", pose) + + depth_nonreturn_probs, log_q_dnrps = propose_depth_nonreturn_probs( + k2, trace_with_pose + ) + colors, visibility_probs, log_q_cvp = propose_colors_and_visibility_probs( + k3, trace_with_pose + ) + depth_scale, log_q_ds = propose_depth_scale(k4, trace_with_pose) + color_scale, log_q_cs = propose_color_scale(k5, trace_with_pose) + + proposed_trace = update_fields( + k6, + trace_with_pose, + [ + "depth_nonreturn_prob", + "colors", + "visibility_prob", + "depth_scale", + "color_scale", + ], + [depth_nonreturn_probs, colors, visibility_probs, depth_scale, color_scale], + ) + log_q = log_q_dnrps + log_q_cvp + log_q_ds + log_q_cs + + return proposed_trace, log_q + + +def propose_depth_nonreturn_probs(key, trace): + """ + Propose a new depth nonreturn probability for every vertex, conditioned + upon the other values in `trace`. + Returns (depth_nonreturn_probs, log_q) where `depth_nonreturn_probs` is + a vector of shape (n_vertices,) and `log_q` is (a fair estimate of) + the log proposal density of this list of values. + """ + observed_depths_per_points = PixelsPointsAssociation.from_hyperparams_and_pose( + get_hypers(trace), get_new_state(trace)["pose"] + ).get_point_depths(get_observed_rgbd(trace)) + + depth_nonreturn_probs, per_vertex_log_qs = jax.vmap( + propose_vertex_depth_nonreturn_prob, in_axes=(0, 0, 0, None, None, None) + )( + split(key, get_n_vertices(trace)), + jnp.arange(get_n_vertices(trace)), + observed_depths_per_points, + get_prev_state(trace), + get_new_state(trace), + get_hypers(trace), + ) + + return depth_nonreturn_probs, per_vertex_log_qs.sum() + + +def propose_colors_and_visibility_probs(key, trace): + """ + Propose a new color and visibility probability for every vertex, conditioned + upon the other values in `trace`. + Returns (colors, visibility_probs, log_q) where `colors` has shape + (n_vertices, 3), `visibility_probs` is a vector of shape (n_vertices,) + and `log_q` is (a fair estimate of) the log proposal density of these + values. + """ + observed_rgbds_per_points = PixelsPointsAssociation.from_hyperparams_and_pose( + get_hypers(trace), get_new_state(trace)["pose"] + ).get_point_rgbds(get_observed_rgbd(trace)) + + colors, visibility_probs, per_vertex_log_qs = jax.vmap( + propose_vertex_color_and_visibility_prob, in_axes=(0, 0, 0, None, None, None) + )( + split(key, get_n_vertices(trace)), + jnp.arange(get_n_vertices(trace)), + observed_rgbds_per_points, + get_prev_state(trace), + get_new_state(trace), + get_hypers(trace), + ) + + return colors, visibility_probs, per_vertex_log_qs.sum() + + +def propose_vertex_depth_nonreturn_prob( + key, vertex_index, observed_depth, previous_state, new_state, hyperparams +): + """ + Propose a new depth nonreturn probability for the single vertex + with index `vertex_index`. + Returns (depth_nonreturn_prob, log_q) where `depth_nonreturn_prob` is + the proposed value and `log_q` is (a fair estimate of) the log proposal density. + """ + + # TODO: could factor into a sub-function that just receives the values + # we pull out of the previous and new state here, if that facilitates + # unit testing. + + previous_dnrp = previous_state["depth_nonreturn_prob"][vertex_index] + visibility_prob = new_state["visibility_prob"][vertex_index] + latent_depth = new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2] + depth_scale = new_state["depth_scale"] + obs_depth_kernel = hyperparams["image_kernel"].get_depth_vertex_kernel() + + def score_dnrp_value(dnrp_value): + transition_score = hyperparams["depth_nonreturn_prob_kernel"].logpdf( + dnrp_value, previous_dnrp + ) + likelihood_score = obs_depth_kernel.logpdf( + observed_depth, latent_depth, visibility_prob, dnrp_value, depth_scale + ) + return transition_score + likelihood_score + + support = hyperparams["depth_nonreturn_prob_kernel"].support + log_pscores = jax.vmap(score_dnrp_value)(support) + log_normalized_scores = log_pscores - jax.scipy.special.logsumexp(log_pscores) + index = jax.random.categorical(key, log_normalized_scores) + # ^ since we are enumerating over every value in the domain, it is unnecessary + # to add a 1/q score when resampling. (Equivalently, we could include + # q = 1/len(support), which does not change the resampling distribuiton at all.) + + return support[index], log_normalized_scores[index] + + +def propose_vertex_color_and_visibility_prob( + key, vertex_index, observed_rgbd, previous_state, new_state, hyperparams +): + """ + Propose a new color and visibility probability for the single vertex + with index `vertex_index`. + Returns (color, visibility_prob, log_q) where `color` and `visibility_prob` + are the proposed values and `log_q` is (a fair estimate of) the log proposal density. + """ + # Placeholder + return ( + previous_state["colors"][vertex_index], + previous_state["visibility_prob"][vertex_index], + 0.0, + ) + + +def propose_depth_scale(key, trace): + """ + Propose a new global depth scale, conditioned upon the other values in `trace`. + Returns (depth_scale, log_q) where `depth_scale` is the proposed value and + `log_q` is (a fair estimate of) the log proposal density. + """ + # Placeholder + return get_prev_state(trace)["depth_scale"], 0.0 + + +def propose_color_scale(key, trace): + """ + Propose a new global color scale, conditioned upon the other values in `trace`. + Returns (color_scale, log_q) where `color_scale` is the proposed value and + `log_q` is (a fair estimate of) the log proposal density. + """ + # Placeholder + return get_prev_state(trace)["color_scale"], 0.0 + + +### Utils ### +def update_field(key, trace, fieldname, value): + """ + Update `trace` by changing the value at address `fieldname` to `value`. + Returns a new trace. + """ + return update_fields(key, trace, [fieldname], [value]) + + +def update_fields(key, trace, fieldnames, values): + """ + Update `trace` by changing the values at the addresses in `fieldnames` to the + corresponding values in `values`. Returns a new trace. + """ + hyperparams, previous_state = trace.get_args() + trace, _, _, _ = trace.update( + key, + U.g( + (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), + C.kw(**dict(zip(fieldnames, values))), + ), + ) + return trace diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index 69759a89..55b716f4 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -44,10 +44,10 @@ def dynamic_object_generative_model(hyperparams, previous_state): "color_scale": color_scale, } - if "image_likelihood" not in hyperparams: + if "image_kernel" not in hyperparams: rgbd = None else: - rgbd = hyperparams["image_likelihood"](new_state, hyperparams) @ "rgbd" + rgbd = hyperparams["image_kernel"](new_state, hyperparams) @ "rgbd" return { "new_state": new_state, @@ -74,6 +74,26 @@ def make_depth_nonreturn_prob_choicemap(depth_nonreturn_prob): )(jnp.arange(len(depth_nonreturn_prob))) +def get_hypers(trace): + return trace.get_args()[0] + + +def get_prev_state(trace): + return trace.get_args()[1] + + +def get_new_state(trace): + return trace.get_retval()["new_state"] + + +def get_n_vertices(trace): + return get_hypers(trace)["vertices"].shape[0] + + +def get_observed_rgbd(trace): + return trace.get_retval()["rgbd"] + + ### Visualization Code ### def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): b3d.rr_set_time(t) @@ -122,20 +142,18 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): output = trace.get_retval() if output["rgbd"] is not None: - info = hyperparams["image_likelihood"].info_from_trace(trace) b3d.rr_log_rgb(output["rgbd"][..., :3], "image") b3d.rr_log_rgb(output["rgbd"][..., :3], "image/rgb/observed") b3d.rr_log_depth(output["rgbd"][..., 3], "image/depth/observed") - latent_rgbd = info["latent_rgbd"] - b3d.rr_log_rgb(latent_rgbd[..., :3], "image/rgb/latent") - b3d.rr_log_depth(latent_rgbd[..., 3], "image/depth/latent") + # TODO: should we add in a way to visualize a noise-free projection + # of the points to the camera plane? fx, fy, cx, cy = ( - hyperparams["fx"], - hyperparams["fy"], - hyperparams["cx"], - hyperparams["cy"], + hyperparams["intrinsics"]["fx"], + hyperparams["intrinsics"]["fy"], + hyperparams["intrinsics"]["cx"], + hyperparams["intrinsics"]["cy"], ) b3d.rr_log_cloud( b3d.xyz_from_depth( diff --git a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py b/src/b3d/chisight/gen3d/pixel_kernels/__init__.py index e69de29b..471cf3aa 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/__init__.py @@ -0,0 +1,23 @@ +from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( + FullPixelColorDistribution, + MixturePixelColorDistribution, + PixelColorDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( + FullPixelDepthDistribution, + MixturePixelDepthDistribution, + PixelDepthDistribution, + UnexplainedPixelDepthDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import PixelRGBDDistribution + +__all__ = [ + "FullPixelColorDistribution", + "FullPixelDepthDistribution", + "MixturePixelColorDistribution", + "MixturePixelDepthDistribution", + "PixelColorDistribution", + "PixelDepthDistribution", + "PixelRGBDDistribution", + "UnexplainedPixelDepthDistribution", +] diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py index ead5bdbe..867f84d5 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py @@ -39,7 +39,17 @@ def is_unexplained(latent_value: FloatArray) -> bool: @Pytree.dataclass class PixelColorDistribution(genjax.ExactDensity): - """An abstract class that defines the common interface for pixel color kernels.""" + """ + An abstract class that defines the common interface for pixel color kernels. + + Distribuiton args: + - latent_rgb + - rgb_scale + - visibility_prob + + Support: + - An RGB value in [0, 1]^3. + """ @abstractmethod def sample( @@ -70,19 +80,23 @@ class TruncatedLaplacePixelColorDistribution(PixelColorDistribution): controlled by color_scale. The support of the distribution is ([0, 1]^3). """ - color_scale: float # the uniform window is used to wrapped the truncated laplace distribution # to ensure that the color generated is within the range of [0, 1] uniform_window_size: float = Pytree.static(default=_FIXED_COLOR_UNIFORM_WINDOW) def sample( - self, key: PRNGKey, latent_color: FloatArray, *args, **kwargs + self, + key: PRNGKey, + latent_color: FloatArray, + color_scale: FloatArray, + *args, + **kwargs, ) -> FloatArray: return jax.vmap( lambda k, color: truncated_laplace.sample( k, color, - self.color_scale, + color_scale, COLOR_MIN_VAL, COLOR_MAX_VAL, self.uniform_window_size, @@ -91,13 +105,18 @@ def sample( )(jax.random.split(key, latent_color.shape[0]), latent_color) def logpdf_per_channel( - self, observed_color: FloatArray, latent_color: FloatArray, *args, **kwargs + self, + observed_color: FloatArray, + latent_color: FloatArray, + color_scale: FloatArray, + *args, + **kwargs, ) -> FloatArray: return jax.vmap( lambda obs, latent: truncated_laplace.logpdf( obs, latent, - self.color_scale, + color_scale, COLOR_MIN_VAL, COLOR_MAX_VAL, self.uniform_window_size, @@ -134,49 +153,52 @@ class MixturePixelColorDistribution(PixelColorDistribution): distribution is ([0, 1]^3). """ - color_scale: float - @property def _occluded_dist(self) -> PixelColorDistribution: return UniformPixelColorDistribution() @property def _inlier_dist(self) -> PixelColorDistribution: - return TruncatedLaplacePixelColorDistribution(self.color_scale) + return TruncatedLaplacePixelColorDistribution() @property def _mixture_dists(self) -> tuple[PixelColorDistribution, PixelColorDistribution]: return (self._occluded_dist, self._inlier_dist) - def _get_mix_ratio(self, occluded_prob: float) -> FloatArray: - return jnp.array((occluded_prob, 1 - occluded_prob)) + def _get_mix_ratio(self, visibility_prob: float) -> FloatArray: + return jnp.array((1 - visibility_prob, visibility_prob)) def sample( self, key: PRNGKey, latent_color: FloatArray, - occluded_prob: float, + color_scale: FloatArray, + visibility_prob: float, *args, **kwargs, ) -> FloatArray: return PythonMixtureDistribution(self._mixture_dists).sample( - key, self._get_mix_ratio(occluded_prob), [(), (latent_color,)] + key, self._get_mix_ratio(visibility_prob), [(), (latent_color, color_scale)] ) def logpdf_per_channel( self, observed_color: FloatArray, latent_color: FloatArray, - occluded_prob: float, + color_scale: FloatArray, + visibility_prob: float, *args, **kwargs, ) -> FloatArray: # Since the mixture model class does not keep the per-channel information, # we have to redefine this method to allow for testing logprobs = [] - for dist, prob in zip(self._mixture_dists, self._get_mix_ratio(occluded_prob)): + for dist, prob in zip( + self._mixture_dists, self._get_mix_ratio(visibility_prob) + ): logprobs.append( - dist.logpdf_per_channel(observed_color, latent_color) + jnp.log(prob) + dist.logpdf_per_channel(observed_color, latent_color, color_scale) + + jnp.log(prob) ) return jnp.logaddexp(*logprobs) @@ -196,26 +218,24 @@ class FullPixelColorDistribution(PixelColorDistribution): ) Constructor args: - - color_scale: float. The scale of the truncated Laplace distribution - centered around the latent color used for inlier color observations. Distribution args: - `latent_color`: 3-array. If no latent point hits the pixel, should contain 3 negative values. If a latent point hits the pixel, should contain the point's color as an RGB value in [0, 1]^3. - - `color_occluded_prob`: float. If a latent point hits the pixel, should contain + - color_scale: float. The scale of the truncated Laplace distribution + centered around the latent color used for inlier color observations. + - `color_visibility_prob`: float. If a latent point hits the pixel, should contain the probability associated with that point that the generated color is - an occluded. If no latent point hits the pixel, this value is ignored. + visible (non-occluded). If no latent point hits the pixel, this value is ignored. Distribution support: - An RGB value in [0, 1]^3. """ - color_scale: float - @property def _color_from_latent(self) -> PixelColorDistribution: - return MixturePixelColorDistribution(self.color_scale) + return MixturePixelColorDistribution() @property def _unexplained_color(self) -> PixelColorDistribution: @@ -225,9 +245,8 @@ def sample( self, key: PRNGKey, latent_color: FloatArray, - occluded_prob: FloatArray, - *args, - **kwargs, + color_scale: FloatArray, + visibility_prob: FloatArray, ) -> FloatArray: return jax.lax.cond( is_unexplained(latent_color), @@ -236,16 +255,16 @@ def sample( # sample args key, latent_color, - occluded_prob, + color_scale, + visibility_prob, ) def logpdf_per_channel( self, observed_color: FloatArray, latent_color: FloatArray, - occluded_prob: float, - *args, - **kwargs, + color_scale: FloatArray, + visibility_prob: float, ) -> FloatArray: return jax.lax.cond( is_unexplained(latent_color), @@ -254,5 +273,6 @@ def logpdf_per_channel( # logpdf args observed_color, latent_color, - occluded_prob, + color_scale, + visibility_prob, ) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py index ccf77dbe..186e9931 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py @@ -24,7 +24,17 @@ @Pytree.dataclass class PixelDepthDistribution(genjax.ExactDensity): - """An abstract class that defines the common interface for pixel depth kernels.""" + """ + An abstract class that defines the common interface for pixel depth kernels. + + Distribution args: + - latent_depth + - depth_scale + - visibility_prob + - depth_nonreturn_prob + + Support: depth value in [near, far], or DEPTH_NONRETURN_VAL. + """ @abstractmethod def sample(self, key: PRNGKey, latent_depth: float, *args, **kwargs) -> float: @@ -46,28 +56,34 @@ class TruncatedLaplacePixelDepthDistribution(PixelDepthDistribution): near: float = Pytree.static() far: float = Pytree.static() - depth_scale: float # the uniform window is used to wrapped the truncated laplace distribution # to ensure that the depth generated is within the range of [near, far] uniform_window_size: float = Pytree.static(default=_FIXED_DEPTH_UNIFORM_WINDOW) - def sample(self, key: PRNGKey, latent_depth: float, *args, **kwargs) -> float: + def sample( + self, key: PRNGKey, latent_depth: float, depth_scale: float, *args, **kwargs + ) -> float: return truncated_laplace.sample( key, latent_depth, - self.depth_scale, + depth_scale, self.near, self.far, self.uniform_window_size, ) def logpdf( - self, observed_depth: float, latent_depth: float, *args, **kwargs + self, + observed_depth: float, + latent_depth: float, + depth_scale: float, + *args, + **kwargs, ) -> float: return truncated_laplace.logpdf( observed_depth, latent_depth, - self.depth_scale, + depth_scale, self.near, self.far, self.uniform_window_size, @@ -113,7 +129,7 @@ def logpdf(self, sampled_val: Any, *args, **kwargs) -> float: class MixturePixelDepthDistribution(PixelDepthDistribution): """A distribution that generates the depth of a pixel from mixture( - [delta(-1), uniform(near, far), laplace(latent_depth; depth_scale)], + [delta(DEPTH_NONRETURN_VAL), uniform(near, far), laplace(latent_depth; depth_scale)], [depth_nonreturn_prob, (1 - depth_nonreturn_prob) * occluded_prob, remaining_prob] ) @@ -122,7 +138,6 @@ class MixturePixelDepthDistribution(PixelDepthDistribution): near: float = Pytree.static() far: float = Pytree.static() - depth_scale: float @property def _nonreturn_dist(self) -> PixelDepthDistribution: @@ -134,9 +149,7 @@ def _occluded_dist(self) -> PixelDepthDistribution: @property def _inlier_dist(self) -> PixelDepthDistribution: - return TruncatedLaplacePixelDepthDistribution( - self.near, self.far, self.depth_scale - ) + return TruncatedLaplacePixelDepthDistribution(self.near, self.far) @property def _mixture_dist(self) -> PythonMixtureDistribution: @@ -145,13 +158,13 @@ def _mixture_dist(self) -> PythonMixtureDistribution: ) def _get_mix_ratio( - self, occluded_prob: float, depth_nonreturn_prob: float + self, visibility_prob: float, depth_nonreturn_prob: float ) -> FloatArray: return jnp.array( ( depth_nonreturn_prob, - (1 - depth_nonreturn_prob) * occluded_prob, - (1 - depth_nonreturn_prob) * (1 - occluded_prob), + (1 - depth_nonreturn_prob) * (1 - visibility_prob), + (1 - depth_nonreturn_prob) * visibility_prob, ) ) @@ -159,30 +172,32 @@ def sample( self, key: PRNGKey, latent_depth: float, - occluded_prob: float, + depth_scale: float, + visibility_prob: float, depth_nonreturn_prob: float, *args, **kwargs, ) -> float: return self._mixture_dist.sample( key, - self._get_mix_ratio(occluded_prob, depth_nonreturn_prob), - [(), (), (latent_depth,)], + self._get_mix_ratio(visibility_prob, depth_nonreturn_prob), + [(), (), (latent_depth, depth_scale)], ) def logpdf( self, observed_depth: float, latent_depth: float, - occluded_prob: float, + depth_scale: float, + visibility_prob: float, depth_nonreturn_prob: float, *args, **kwargs, ) -> float: return self._mixture_dist.logpdf( observed_depth, - self._get_mix_ratio(occluded_prob, depth_nonreturn_prob), - [(), (), (latent_depth,)], + self._get_mix_ratio(visibility_prob, depth_nonreturn_prob), + [(), (), (latent_depth, depth_scale)], ) @@ -190,7 +205,7 @@ def logpdf( class UnexplainedPixelDepthDistribution(PixelDepthDistribution): """A distribution that generates the depth of a pixel from mixture( - [delta(-1), uniform(near, far)], + [delta(DEPTH_NONRETURN_VAL), uniform(near, far)], [unexplained_depth_nonreturn_prob, 1 - unexplained_depth_nonreturn_prob] ), for pixels that are not explained by the latent points. @@ -249,23 +264,22 @@ class FullPixelDepthDistribution(PixelDepthDistribution): if no latent point hits the pixel: depth ~ mixture( - [delta(-1), uniform(near, far)], + [delta(DEPTH_NONRETURN_VAL), uniform(near, far)], [unexplained_depth_nonreturn_prob, 1 - unexplained_depth_nonreturn_prob] ) else: mixture( - [delta(-1), uniform(near, far), laplace(latent_depth; depth_scale)], - [depth_nonreturn_prob, (1 - depth_nonreturn_prob) * occluded_prob, remaining_prob] + [delta(DEPTH_NONRETURN_VAL), uniform(near, far), laplace(latent_depth; depth_scale)], + [depth_nonreturn_prob, (1 - depth_nonreturn_prob) * (1 - visibility_prob), remaining_prob] ) """ near: float = Pytree.static() far: float = Pytree.static() - depth_scale: float @property def _depth_from_latent(self) -> PixelDepthDistribution: - return MixturePixelDepthDistribution(self.near, self.far, self.depth_scale) + return MixturePixelDepthDistribution(self.near, self.far) @property def _unexplained_depth(self) -> PixelDepthDistribution: @@ -275,7 +289,8 @@ def sample( self, key: PRNGKey, latent_depth: FloatArray, - occluded_prob: FloatArray, + depth_scale: FloatArray, + visibility_prob: FloatArray, depth_nonreturn_prob: float, *args, **kwargs, @@ -287,7 +302,8 @@ def sample( # sample args key, latent_depth, - occluded_prob, + depth_scale, + visibility_prob, depth_nonreturn_prob, ) @@ -295,7 +311,8 @@ def logpdf( self, observed_depth: FloatArray, latent_depth: FloatArray, - occluded_prob: float, + depth_scale: FloatArray, + visibility_prob: float, depth_nonreturn_prob: float, *args, **kwargs, @@ -307,6 +324,7 @@ def logpdf( # logpdf args observed_depth, latent_depth, - occluded_prob, + depth_scale, + visibility_prob, depth_nonreturn_prob, ) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py index f887994e..026e613e 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py @@ -10,28 +10,57 @@ @Pytree.dataclass class PixelRGBDDistribution(genjax.ExactDensity): + """ + Distribution args: + - latent_rgbd: 4-array: RGBD value. (Should be [-1, -1, -1, -1] to indicate no point hits here.) + - rgb_scale: float + - depth_scale: float + - visibility_prob: float + - depth_nonreturn_prob: float + + The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). + + If the logpdf of [-1, -1, -1, -1] is requested, this will return 0.0. + """ + color_kernel: PixelColorDistribution depth_kernel: PixelDepthDistribution def sample( - self, key: PRNGKey, latent_rgbd: FloatArray, *args, **kwargs + self, + key: PRNGKey, + latent_rgbd: FloatArray, + rgb_scale, + depth_scale, + visibility_prob, + depth_nonreturn_prob, ) -> FloatArray: keys = jax.random.split(key, 2) observed_color = self.color_kernel.sample( - keys[0], latent_rgbd[:3], *args, **kwargs + keys[0], latent_rgbd[:3], rgb_scale, visibility_prob ) observed_depth = self.depth_kernel.sample( - keys[1], latent_rgbd[3], *args, **kwargs + keys[1], latent_rgbd[3], depth_scale, visibility_prob, depth_nonreturn_prob ) return jnp.append(observed_color, observed_depth) def logpdf( - self, observed_rgbd: FloatArray, latent_rgbd: FloatArray, *args, **kwargs + self, + observed_rgbd: FloatArray, + latent_rgbd: FloatArray, + rgb_scale, + depth_scale, + visibility_prob, + depth_nonreturn_prob, ) -> float: color_logpdf = self.color_kernel.logpdf( - observed_rgbd[:3], latent_rgbd[:3], *args, **kwargs + observed_rgbd[:3], latent_rgbd[:3], rgb_scale, visibility_prob ) depth_logpdf = self.depth_kernel.logpdf( - observed_rgbd[3], latent_rgbd[3], *args, **kwargs + observed_rgbd[3], + latent_rgbd[3], + depth_scale, + visibility_prob, + depth_nonreturn_prob, ) return color_logpdf + depth_logpdf diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py new file mode 100644 index 00000000..09e00947 --- /dev/null +++ b/src/b3d/chisight/gen3d/projection.py @@ -0,0 +1,158 @@ +from functools import cached_property + +import jax.numpy as jnp +from genjax import Pytree +from genjax.typing import FloatArray, IntArray + +import b3d.utils + +# using this in combination with mode="drop" in the .at[] +# methods can help filter out vertices that are not visible in the image +INVALID_IDX = jnp.iinfo(jnp.int32).min # -2147483648 + + +@Pytree.dataclass +class PixelsPointsAssociation(Pytree): + """A utility class to associate 3D points with their projected 2D pixel.""" + + projected_pixel_coordinates: IntArray # (num_vertices, 2) + image_height: int + image_width: int + + @classmethod + def from_hyperparams_and_pose(cls, hyperparams, pose_CO): + """`pose_CO` is the same thing as `pose` in the model.""" + vertices_O = hyperparams["vertices"] + vertices_C = pose_CO.apply(vertices_O) + return cls.from_points_and_intrinsics( + vertices_C, + hyperparams["intrinsics"], + hyperparams["image_height"].const, + hyperparams["image_width"].const, + ) + + @classmethod + def from_points_and_intrinsics( + cls, + points: FloatArray, + intrinsics: dict, + image_height: int, + image_width: int, + ) -> "PixelsPointsAssociation": + """Create a PixelsPointsAssociation object from a set of 3D points and + the camera intrinsics. + + Args: + points (FloatArray): The points/vertices in 3D space (num_vertices, 3). + intrinsics (dict): Camera intrinsics. + image_height (int): Height of the image. + image_width (int): Width of the image. + """ + projected_coords = jnp.rint( + b3d.utils.xyz_to_pixel_coordinates( + points, + intrinsics["fx"], + intrinsics["fy"], + intrinsics["cx"], + intrinsics["cy"], + ) + ) + # handle NaN before converting to int (otherwise NaN will be converted + # to 0) + projected_coords = jnp.nan_to_num(projected_coords, nan=INVALID_IDX) + + # handle the case where the projected coordinates are outside the image + projected_coords = jnp.where( + projected_coords > 0, projected_coords, INVALID_IDX + ) + projected_coords = jnp.where( + projected_coords < jnp.array([image_height, image_width]), + projected_coords, + INVALID_IDX, + ) + + return cls(projected_coords.astype(jnp.int32), image_height, image_width) + + def __len__(self) -> int: + return self.projected_pixel_coordinates.shape[0] + + def shape(self) -> tuple[int, int]: + return self.projected_pixel_coordinates.shape + + @property + def x(self) -> IntArray: + return self.projected_pixel_coordinates[:, 0] + + @property + def y(self) -> IntArray: + return self.projected_pixel_coordinates[:, 1] + + def get_point_rgbds(self, rgbd_image: FloatArray) -> FloatArray: + """ + Get a (num_vertices, 4) array of RGBD values for each vertex + by indexing into the given image. + Vertices that don't hit a pixel will have a value of (-1, -1, -1, -1). + """ + unfiltered = rgbd_image[self.x, self.y] + invalid_indices = jnp.logical_or(self.x == INVALID_IDX, self.y == INVALID_IDX) + return jnp.where( + invalid_indices[:, None], -jnp.ones_like(unfiltered), unfiltered + ) + + def get_point_depths(self, rgbd_image: FloatArray) -> FloatArray: + """ + Get a (num_vertices,) array of depth values for each vertex + by indexing into the given image, or -1 if the vertex doesn't hit a pixel. + """ + return self.get_point_rgbds(rgbd_image)[..., 3] + + def get_point_rgbs(self, rgbd: FloatArray) -> FloatArray: + """ + Get a (num_vertices, 3) array of RGB values for each vertex + by indexing into the given image, or [-1, -1, -1] if the vertex doesn't hit a pixel. + """ + return self.get_point_rgbds(rgbd)[..., :3] + + @cached_property + def num_point_per_pixel(self) -> IntArray: + """Return a 2D array of shape (image_height, image_width) where each + element is the number of points that project to that pixel. + """ + counts = jnp.zeros((self.image_height, self.image_width), dtype=jnp.int32) + counts = counts.at[self.x, self.y].add(1, mode="drop") + return counts + + @cached_property + def pixel_to_point_idx(self) -> IntArray: + """Return a 2D array of shape (image_height, image_width) where each + element is the index of the point that projects to that pixel (if any). + If none of the points project to that pixel, the value is set to INVALID_IDX. + + Warning: this implementaion does not handle race condition. That is, if + multiple points project to the same pixel, this method will randomly + return one of them (the non-determinism is subject to GPU parallelism). + """ + registered_pixel_idx = jnp.full( + (self.image_height, self.image_width), INVALID_IDX, dtype=jnp.int32 + ) + registered_pixel_idx = registered_pixel_idx.at[self.x, self.y].set( + jnp.arange(len(self)) + ) + return registered_pixel_idx + + def get_pixel_idx(self, point_idx: int) -> IntArray: + return self.projected_pixel_coordinates[point_idx] + + def pixels_with_multiple_points(self) -> tuple[IntArray, IntArray]: + """Return a tuple of (x_coords, y_coords) of pixels that have more than + one vertices associated with them. Note that this method is not JIT-compatible + because the return values are not of fixed shape. + """ + return jnp.nonzero(self.num_point_per_pixel > 1) + + def get_one_latent_point_idx(self, pixel_x: int, pixel_y: int) -> int: + """Return the index of one of the points that project to the given pixel. + If there are multiple points, this method will return one of them randomly + (the non-determinism is subject to GPU parallelism). + """ + return self.pixel_to_point_idx[pixel_x, pixel_y] diff --git a/src/b3d/chisight/gen3d/transition_kernels.py b/src/b3d/chisight/gen3d/transition_kernels.py index bc8a9514..40c9eb36 100644 --- a/src/b3d/chisight/gen3d/transition_kernels.py +++ b/src/b3d/chisight/gen3d/transition_kernels.py @@ -362,32 +362,21 @@ def logpdf(self, new_pose, prev_pose) -> ArrayLike: # Discrete Kernels - -@Pytree.dataclass -class DiscreteKernel(genjax.ExactDensity): - """An abstract class that defines the common interface for drift kernels.""" - - @abstractmethod - def sample(self, key: PRNGKey, prev_value, possible_values): - raise NotImplementedError - - @abstractmethod - def logpdf(self, new_value, prev_value, possible_values): - raise NotImplementedError +# TODO: add back in the base class for discretekernel. +# I removed it since its listed interface had become +# out of sync with `DiscreteFlipKernel`. @Pytree.dataclass -class DiscreteFlipKernel(DiscreteKernel): +class DiscreteFlipKernel(genjax.ExactDensity): resample_probability: float = Pytree.static() - possible_values: ArrayLike = Pytree.static() + support: ArrayLike = Pytree.static() def sample(self, key: PRNGKey, prev_value): should_resample = jax.random.bernoulli(key, self.resample_probability) return ( should_resample - * self.possible_values.at[ - jax.random.choice(key, len(self.possible_values)) - ].get() + * self.support.at[jax.random.choice(key, len(self.support))].get() + (1 - should_resample) * prev_value ) @@ -396,6 +385,6 @@ def logpdf(self, new_value, prev_value): return jnp.logaddexp( jnp.log(1.0 - self.resample_probability) + jnp.log(1.0 * match), jnp.log(self.resample_probability) - - jnp.log(len(self.possible_values) - 1) + - jnp.log(len(self.support) - 1) + jnp.log(1.0 * (1 - match)), ) diff --git a/tests/dynamic_object_model/kfold_image_kernel_real_data.py b/tests/dynamic_object_model/kfold_image_kernel_real_data.py deleted file mode 100644 index d4154169..00000000 --- a/tests/dynamic_object_model/kfold_image_kernel_real_data.py +++ /dev/null @@ -1,127 +0,0 @@ -### IMPORTS ### - -import os - -import b3d -import b3d.chisight.dynamic_object_model.kfold_image_kernel as kik -import jax -import jax.numpy as jnp -from b3d import Mesh - -b3d.rr_init("kfold_image_kernel2") - - -def test_sampling_on_real_data(): - ### Loading data ### - - scene_id = 55 - FRAME_RATE = 50 - ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") - print(f"Scene {scene_id}") - b3d.reload(b3d.io.data_loader) - num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id) - - # image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE) - image_ids = range(1, num_scenes + 1, FRAME_RATE) - all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, image_ids) - - meshes = [ - Mesh.from_obj_file( - os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') - ).scale(0.001) - for id in all_data[0]["object_types"] - ] - - image_height, image_width = all_data[0]["rgbd"].shape[:2] - fx, fy, cx, cy = all_data[0]["camera_intrinsics"] - scaling_factor = 1.0 - renderer = b3d.renderer.renderer_original.RendererOriginal( - image_width * scaling_factor, - image_height * scaling_factor, - fx * scaling_factor, - fy * scaling_factor, - cx * scaling_factor, - cy * scaling_factor, - 0.01, - 2.0, - ) - b3d.viz_rgb(all_data[0]["rgbd"]) - - ###### - - T = 0 - OBJECT_INDEX = 2 - - template_pose = ( - all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] - ) - rendered_rgbd = renderer.render_rgbd_from_mesh( - meshes[OBJECT_INDEX].transform(template_pose) - ) - xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy) - - fx, fy, cx, cy = all_data[T]["camera_intrinsics"] - xyz_observed = b3d.xyz_from_depth(all_data[T]["rgbd"][..., 3], fx, fy, cx, cy) - mask = ( - all_data[T]["masks"][OBJECT_INDEX] - * (xyz_observed[..., 2] > 0) - * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) - ) - - vertices = xyz_rendered[mask] - vertices.shape - - model_rgbd = all_data[T]["rgbd"][mask] - model_rgbd.shape - - intrinsics = { - "fx": fx // 4, - "fy": fy // 4, - "cx": cx // 4, - "cy": cy // 4, - "height": image_height // 4, - "width": image_width // 4, - "near": 0.001, - "far": 100.0, - } - - image_kernel = kik.KfoldMixturePointsToImageKernel(5) - - def get_sample(key): - sample, _ = image_kernel.random_weighted( - key, - intrinsics, - vertices, - model_rgbd, - # color outlier probs - 0.003 * jnp.ones(vertices.shape[0]), - # depth outlier probs - 0.001 * jnp.ones(vertices.shape[0]), - # color scale - 0.01, - # depth scale - 0.04, - ) - return sample - - samples_20 = jax.vmap(get_sample)(jax.random.split(jax.random.PRNGKey(0), 20)) - assert samples_20.shape == (20, image_height // 4, image_width // 4, 4) - - assert ( - image_kernel.estimate_logpdf( - jax.random.PRNGKey(10), - samples_20[0], - intrinsics, - vertices, - model_rgbd, - # color outlier probs - 0.003 * jnp.ones(vertices.shape[0]), - # depth outlier probs - 0.001 * jnp.ones(vertices.shape[0]), - # color scale - 0.01, - # depth scale - 0.04, - ).shape - == () - ) diff --git a/tests/dynamic_object_model/kfold_image_kernel_unit_test.py b/tests/dynamic_object_model/kfold_image_kernel_unit_test.py deleted file mode 100644 index f2465bec..00000000 --- a/tests/dynamic_object_model/kfold_image_kernel_unit_test.py +++ /dev/null @@ -1,162 +0,0 @@ -import importlib - -import b3d -import b3d.chisight.dynamic_object_model.likelihoods.kfold_image_kernel as kik -import jax.numpy as jnp -from jax.random import PRNGKey - -importlib.reload(kik) - - -def expected_logpdf_given_idx(args, value, point_idx): - ( - _, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) = args - i = point_idx - - color_pdf_should_be = jnp.logaddexp( - jnp.log(1 - color_outlier_probs[i]) - + kik.truncated_color_laplace.logpdf(value[:3], all_rgbds[i][:3], color_scale), - jnp.log(color_outlier_probs[i]) + jnp.log(1.0**3), - ) - depth_pdf_should_be = jnp.logaddexp( - jnp.log(1 - depth_outlier_probs[i]) - + kik.truncated_laplace.logpdf( - value[3], - all_rgbds[i][3], - depth_scale, - near, - far, - kik._FIXED_DEPTH_UNIFORM_WINDOW, - ), - jnp.log(depth_outlier_probs[i]) + jnp.log(1 / (far - near)), - ) - return color_pdf_should_be + depth_pdf_should_be - - -def test_logpdfs_in_image_with_one_point_per_pixel(): - intrinsics = ( - 3, - 3, - 200.0, - 200.0, - 50.0, - 50.0, - 0.01, - 10.0, - ) - image_width, image_height, fx, fy, cx, cy, _, _ = intrinsics - - intrinsics_dict = { - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - "width": image_width, - "height": image_height, - "near": 0.01, - "far": 100.0, - } - depth_image = jnp.ones((image_height, image_width), dtype=jnp.float32) - vertices = b3d.camera.camera_from_depth(depth_image, intrinsics).reshape(-1, 3) - - # result = kik.raycast_to_image_nondeterministic( - # PRNGKey(0), - # { - # "height": image_height, - # "width": image_width, - # "fx": fx, - # "fy": fy, - # "cx": cx, - # "cy": cy, - # }, - # vertices, - # 2, - # ) - # result - - rgbds = jnp.tile(jnp.array([1.0, 0.0, 0.0, 5.0]), (9, 1)) - color_outlier_probs = 0.003 * jnp.arange(9) - depth_outlier_probs = (10 - jnp.arange(9)) / 100 - color_scale = 0.01 - depth_scale = 0.04 - - image_kernel = kik.KfoldMixturePointsToImageKernel(1) - sample, lp1 = image_kernel.random_weighted( - PRNGKey(0), - intrinsics_dict, - vertices, - rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - ) - lp2 = image_kernel.estimate_logpdf( - PRNGKey(10), - sample, - intrinsics_dict, - vertices, - rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - ) - assert lp1 == lp2 - expected_lp = sum( - [ - expected_logpdf_given_idx( - ( - None, - rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - intrinsics_dict["near"], - intrinsics_dict["far"], - ), - sample[*jnp.unravel_index(i, (3, 3))], - i, - ) - for i in range(9) - ] - ) - assert lp1 == expected_lp - - test_image = jnp.tile(jnp.array([1.0, 0.0, 0.0, 5.0]), (3, 3, 1)) - test_image_2 = jnp.tile(jnp.array([1.0, 0.0, 1.0, 5.0]), (3, 3, 1)) - lp3 = image_kernel.estimate_logpdf( - PRNGKey(10), - test_image, - intrinsics_dict, - vertices, - rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - ) - lp4 = image_kernel.estimate_logpdf( - PRNGKey(10), - test_image_2, - intrinsics_dict, - vertices, - rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - ) - assert lp3 > lp4 - - -# TODO: we could do more thorough testing. diff --git a/tests/dynamic_object_model/test_pixel_distribution.py b/tests/dynamic_object_model/test_pixel_distribution.py deleted file mode 100644 index a29828d9..00000000 --- a/tests/dynamic_object_model/test_pixel_distribution.py +++ /dev/null @@ -1,380 +0,0 @@ -import importlib - -import b3d.chisight.dynamic_object_model.likelihoods.kfold_image_kernel as kik -import jax -import jax.numpy as jnp - -importlib.reload(kik) - - -def test_pixel_distribution_sampling_with_two_of_three_slots(): - registered_point_indices = jnp.array([0, -1, 1]) - all_rgbds = jnp.array( - [[1.0, 0.0, 0.0, 2.0], [0.0, 1.0, 0.0, 3.0], [0.0, 0.0, 1.0, 4.0]] - ) - near, far = 0.001, 100.0 - color_outlier_probs = jnp.array([0.01, 0.5, 0.95]) - depth_outlier_probs = jnp.array([0.5, 0.01, 0.1]) - color_scale = 0.04 - depth_scale = 0.01 - - args = ( - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) - - key = jax.random.PRNGKey(0) - samples_100 = jax.vmap(lambda k: kik.pixel_distribution.sample(k, *args))( - jax.random.split(key, 100) - ) - samples_100 - - # shouldn't be able to pick index 2, so should have very few - # that are close to [0.0, 0.0, 1.0, 4.0] - def is_close_to_0014(rgbd): - return jnp.logical_and( - jnp.allclose(rgbd[:3], jnp.array([0.0, 0.0, 1.0]), atol=0.1), - jnp.abs(rgbd[3] - 4.0) < 0.1, - ) - - n_close = jnp.sum(jax.vmap(is_close_to_0014)(samples_100)) - assert n_close < 4 - - # Should have close to half the samples pick index 0. - # Most of these should have color values close to [1.0, 0.0, 0.0]. - def color_near_100(rgbd): - return jnp.allclose(rgbd[:3], jnp.array([1.0, 0.0, 0.0]), atol=0.15) - - n_color_near_100 = jnp.sum(jax.vmap(color_near_100)(samples_100)) - assert n_color_near_100 > 40 - assert n_color_near_100 < 60 - - # Of these, about half should have a depth outlier, and half should have - # a depth value close to 2.0. - def color_near_100_and_depth_near_2(rgbd): - return jnp.logical_and(color_near_100(rgbd), jnp.abs(rgbd[3] - 2.0) < 0.15) - - n_color_near_100_and_depth_near_2 = jnp.sum( - jax.vmap(color_near_100_and_depth_near_2)(samples_100) - ) - assert n_color_near_100_and_depth_near_2 > n_color_near_100 / 2 - 5 - assert n_color_near_100_and_depth_near_2 < n_color_near_100 / 2 + 5 - - # Test that of the outliers, some are far from 2.0 - def color_near_100_and_far_depth_outlier(rgbd): - return jnp.logical_and(color_near_100(rgbd), jnp.abs(rgbd[3] - 2.0) > 5.0) - - n_color_near_100_and_far_depth_outlier = jnp.sum( - jax.vmap(color_near_100_and_far_depth_outlier)(samples_100) - ) - assert n_color_near_100_and_far_depth_outlier > 1 - - # Should have close to half the samples pick index 1. - # Most of these should have depth values close to 3.0. - def depth_near_3(rgbd): - return jnp.abs(rgbd[3] - 3.0) < 0.15 - - n_depth_near_3 = jnp.sum(jax.vmap(depth_near_3)(samples_100)) - assert n_depth_near_3 > 40 - assert n_depth_near_3 < 60 - - # Of these, about half should have a color outlier, and half should have - # a color value close to [0.0, 1.0, 0.0]. - def depth_near_3_and_color_near_010(rgbd): - return jnp.logical_and( - depth_near_3(rgbd), - jnp.allclose(rgbd[:3], jnp.array([0.0, 1.0, 0.0]), atol=0.15), - ) - - n_depth_near_3_and_color_near_010 = jnp.sum( - jax.vmap(depth_near_3_and_color_near_010)(samples_100) - ) - assert n_depth_near_3_and_color_near_010 > n_depth_near_3 / 2 - 5 - assert n_depth_near_3_and_color_near_010 < n_depth_near_3 / 2 + 5 - - # Test that of the outliers, some are far from [0.0, 1.0, 0.0] - def depth_near_3_and_far_color_outlier(rgbd): - return jnp.logical_and( - depth_near_3(rgbd), - ~jnp.allclose(rgbd[:3], jnp.array([0.0, 1.0, 0.0]), atol=0.3), - ) - - n_depth_near_3_and_far_color_outlier = jnp.sum( - jax.vmap(depth_near_3_and_far_color_outlier)(samples_100) - ) - assert n_depth_near_3_and_far_color_outlier > 1 - - -def test_pixel_distribution_sampling_with_no_slots(): - registered_point_indices = jnp.array([-1, -1, -1]) - all_rgbds = jnp.array( - [[1.0, 0.0, 0.0, 2.0], [0.0, 1.0, 0.0, 3.0], [0.0, 0.0, 1.0, 4.0]] - ) - near, far = 0.001, 100.0 - color_outlier_probs = jnp.array([0.01, 0.5, 0.95]) - depth_outlier_probs = jnp.array([0.5, 0.01, 0.1]) - color_scale = 0.04 - depth_scale = 0.01 - - args = ( - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) - - key = jax.random.PRNGKey(0) - samples_100 = jax.vmap(lambda k: kik.pixel_distribution.sample(k, *args))( - jax.random.split(key, 100) - ) - samples_100 - - # Check that almost all of these seem to be outliers in both color - # and depth. - def is_color_and_depth_outlier(rgbd, base_rgbd): - return jnp.logical_and( - ~jnp.allclose(rgbd[:3], base_rgbd[:3], atol=0.15), - jnp.abs(rgbd[3] - base_rgbd[3]) > 2.0, - ) - - def is_color_and_depth_outlier_for_all(rgbd): - return jnp.all( - jax.vmap(lambda base_rgbd: is_color_and_depth_outlier(rgbd, base_rgbd))( - all_rgbds - ) - ) - - n_color_and_depth_outliers = jnp.sum( - jax.vmap(is_color_and_depth_outlier_for_all)(samples_100) - ) - assert n_color_and_depth_outliers > 90 - - -def test_singleslot_pixel_distribution_sampling(): - registered_point_indices = jnp.array([0, 0, 0]) - all_rgbds = jnp.array( - [[1.0, 0.0, 0.0, 2.0], [0.0, 1.0, 0.0, 3.0], [0.0, 0.0, 1.0, 4.0]] - ) - near, far = 0.001, 100.0 - color_outlier_probs = jnp.array([0.01, 0.5, 0.95]) - depth_outlier_probs = jnp.array([0.5, 0.01, 0.1]) - color_scale = 0.04 - depth_scale = 0.01 - - args = ( - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) - key = jax.random.PRNGKey(0) - samples_100 = jax.vmap(lambda k: kik.pixel_distribution.sample(k, *args))( - jax.random.split(key, 100) - ) - - # Should have close to all the samples pick index 0. - # Most of these should have color values close to [1.0, 0.0, 0.0]. - def color_near_100(rgbd): - return jnp.allclose(rgbd[:3], jnp.array([1.0, 0.0, 0.0]), atol=0.15) - - n_color_near_100 = jnp.sum(jax.vmap(color_near_100)(samples_100)) - assert n_color_near_100 > 90 - - # Of these, about half should have a depth outlier, and half should have - # a depth value close to 2.0. - def color_near_100_and_depth_near_2(rgbd): - return jnp.logical_and(color_near_100(rgbd), jnp.abs(rgbd[3] - 2.0) < 0.15) - - n_color_near_100_and_depth_near_2 = jnp.sum( - jax.vmap(color_near_100_and_depth_near_2)(samples_100) - ) - assert n_color_near_100_and_depth_near_2 > 40 - assert n_color_near_100_and_depth_near_2 < 60 - - -def test_pixel_distribution_logpdf_with_one_of_three_slots(): - def test_logpdf_for_value(value, args): - logpdf = kik.pixel_distribution.logpdf(value, *args) - ( - _, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) = args - color_pdf_should_be = jnp.logaddexp( - jnp.log(1 - color_outlier_probs[0]) - + kik.truncated_color_laplace.logpdf( - value[:3], all_rgbds[0][:3], color_scale - ), - jnp.log(color_outlier_probs[0]) + jnp.log(1.0**3), - ) - depth_pdf_should_be = jnp.logaddexp( - jnp.log(1 - depth_outlier_probs[0]) - + kik.truncated_laplace.logpdf( - value[3], - all_rgbds[0][3], - depth_scale, - near, - far, - kik._FIXED_DEPTH_UNIFORM_WINDOW, - ), - jnp.log(depth_outlier_probs[0]) + jnp.log(1 / (far - near)), - ) - assert jnp.isclose(logpdf, color_pdf_should_be + depth_pdf_should_be, atol=1e-3) - - registered_point_indices = jnp.array([0, -1, -1]) - all_rgbds = jnp.array( - [[1.0, 0.0, 0.0, 2.0], [0.0, 1.0, 0.0, 3.0], [0.0, 0.0, 1.0, 4.0]] - ) - near, far = 0.001, 100.0 - color_outlier_probs = jnp.array([0.01, 0.5, 0.95]) - depth_outlier_probs = jnp.array([0.5, 0.01, 0.1]) - color_scale = 0.04 - depth_scale = 0.01 - - args = ( - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) - - samples_10 = jax.vmap(lambda k: kik.pixel_distribution.sample(k, *args))( - jax.random.split(jax.random.PRNGKey(0), 10) - ) - for sample in samples_10: - test_logpdf_for_value(sample, args) - - ### 3 copies of the same idx shoudln't change this... - registered_point_indices = jnp.array([0, 0, 0]) - args = ( - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) - samples_10 = jax.vmap(lambda k: kik.pixel_distribution.sample(k, *args))( - jax.random.split(jax.random.PRNGKey(0), 10) - ) - for sample in samples_10: - test_logpdf_for_value(sample, args) - - -def test_logpdf_with_no_slot(): - registered_point_indices = jnp.array([-1, -1, -1]) - all_rgbds = jnp.array( - [[1.0, 0.0, 0.0, 2.0], [0.0, 1.0, 0.0, 3.0], [0.0, 0.0, 1.0, 4.0]] - ) - near, far = 0.001, 100.0 - color_outlier_probs = jnp.array([0.01, 0.5, 0.95]) - depth_outlier_probs = jnp.array([0.5, 0.01, 0.1]) - color_scale = 0.04 - depth_scale = 0.01 - - args = ( - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) - - samples_10 = jax.vmap(lambda k: kik.pixel_distribution.sample(k, *args))( - jax.random.split(jax.random.PRNGKey(0), 10) - ) - - def assert_is_correct_logpdf(value): - logpdf = kik.pixel_distribution.logpdf(value, *args) - assert jnp.isclose( - logpdf, jnp.log(1.0**3) + jnp.log(1 / (far - near)), atol=1e-3 - ) - - for sample in samples_10: - assert_is_correct_logpdf(sample) - - -def test_pixel_distribution_logpdf_with_two_of_three_slots(): - registered_point_indices = jnp.array([0, -1, 1]) - all_rgbds = jnp.array( - [[1.0, 0.0, 0.0, 2.0], [0.0, 1.0, 0.0, 3.0], [0.0, 0.0, 1.0, 4.0]] - ) - near, far = 0.001, 100.0 - color_outlier_probs = jnp.array([0.01, 0.5, 0.95]) - depth_outlier_probs = jnp.array([0.5, 0.01, 0.1]) - color_scale = 0.04 - depth_scale = 0.01 - - args = ( - registered_point_indices, - all_rgbds, - color_outlier_probs, - depth_outlier_probs, - color_scale, - depth_scale, - near, - far, - ) - - def expected_logpdf_given_idx(value, i): - color_pdf_should_be = jnp.logaddexp( - jnp.log(1 - color_outlier_probs[i]) - + kik.truncated_color_laplace.logpdf( - value[:3], all_rgbds[i][:3], color_scale - ), - jnp.log(color_outlier_probs[i]) + jnp.log(1.0**3), - ) - depth_pdf_should_be = jnp.logaddexp( - jnp.log(1 - depth_outlier_probs[i]) - + kik.truncated_laplace.logpdf( - value[3], - all_rgbds[i][3], - depth_scale, - near, - far, - kik._FIXED_DEPTH_UNIFORM_WINDOW, - ), - jnp.log(depth_outlier_probs[i]) + jnp.log(1 / (far - near)), - ) - return color_pdf_should_be + depth_pdf_should_be - - def expected_logpdf(value): - return jnp.logaddexp( - jnp.log(1 / 2) + expected_logpdf_given_idx(value, 0), - jnp.log(1 / 2) + expected_logpdf_given_idx(value, 1), - ) - - samples_10 = jax.vmap(lambda k: kik.pixel_distribution.sample(k, *args))( - jax.random.split(jax.random.PRNGKey(0), 10) - ) - for sample in samples_10: - logpdf = kik.pixel_distribution.logpdf(sample, *args) - assert jnp.isclose(logpdf, expected_logpdf(sample), atol=1e-3) diff --git a/tests/dynamic_object_model/test_raycast_nondeterministic.py b/tests/dynamic_object_model/test_raycast_nondeterministic.py deleted file mode 100644 index 52bccb4b..00000000 --- a/tests/dynamic_object_model/test_raycast_nondeterministic.py +++ /dev/null @@ -1,71 +0,0 @@ -import importlib - -import b3d -import b3d.chisight.dynamic_object_model.likelihoods.kfold_image_kernel as kfk -import jax.numpy as jnp -from jax.random import PRNGKey, split - -importlib.reload(kfk) - - -def run_test(): - intrinsics = ( - 5, - 5, - 200.0, - 200.0, - 50.0, - 50.0, - 0.01, - 10.0, - ) - image_width, image_height, fx, fy, cx, cy, _, _ = intrinsics - - depth_image = jnp.ones((image_height, image_width), dtype=jnp.float32) - points = b3d.camera.camera_from_depth(depth_image, intrinsics).reshape(-1, 3) - - result = kfk.raycast_to_image_nondeterministic( - PRNGKey(0), - { - "height": image_height, - "width": image_width, - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - }, - points, - 2, - ) - assert jnp.all( - jnp.max(result, axis=2) - == jnp.arange(points.shape[0]).reshape(image_height, image_width) - ) - - # With 3x points per pixel, most of the time we'll register two of them. - # The probability of not registering 1 is 0.25. - # (This is the probability of the second and third point writing to the same - # slot as the first, which is 1/4.) - # Test that this seems to work out. - points_replicated_3x = jnp.tile(points, (3, 1)) - n_tests = 10 - keys = split(PRNGKey(0), n_tests) - total_num_misses = 0 - for key in keys: - result_x3 = kfk.raycast_to_image_nondeterministic( - key, - { - "height": image_height, - "width": image_width, - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - }, - points_replicated_3x, - 2, - ) - total_num_misses += jnp.sum(result_x3 == -1) - mean_num_misses = total_num_misses / n_tests - estimated_p_miss = mean_num_misses / (image_width * image_height) - assert jnp.allclose(estimated_p_miss, 0.25, atol=0.05) diff --git a/tests/dynamic_object_model/test_truncated_laplace.py b/tests/dynamic_object_model/test_truncated_laplace.py deleted file mode 100644 index 3c152680..00000000 --- a/tests/dynamic_object_model/test_truncated_laplace.py +++ /dev/null @@ -1,114 +0,0 @@ -import b3d.chisight.dynamic_object_model.likelihoods.kfold_image_kernel as kik -import jax -import jax.numpy as jnp - -# importlib.reload(kik) -# loc, scale, low, high, uniform_window_size = 0.0, 0.01, 0.0, 1.0, 0.1 -# n_grid_steps = 1000 -# x = jnp.linspace(low, high, n_grid_steps) -# stepsize = (high - low) / n_grid_steps -# logpdfs = jax.vmap( -# lambda x: kik.truncated_laplace.logpdf(x, loc, scale, low, high, uniform_window_size) -# )(x) -# pdfs = jnp.exp(logpdfs) -# jnp.sum(pdfs * stepsize) - - -def confirm_logpdf_looks_valid( - loc, scale, low, high, uniform_window_size, n_grid_steps=100000 -): - """ - Test that the pdf value seems to integrate to 1. - """ - x = jnp.linspace(low, high, n_grid_steps) - stepsize = (high - low) / n_grid_steps - logpdfs = jax.vmap( - lambda x: kik.truncated_laplace.logpdf( - x, loc, scale, low, high, uniform_window_size - ) - )(x) - pdfs = jnp.exp(logpdfs) - total_pmass = jnp.sum(pdfs * stepsize) - assert jnp.isclose(total_pmass, 1.0, atol=1e-3) - - -def ensure_laplace_samples_have_sufficient_spread( - key, loc, scale, low, high, uniform_window_size, scale_mult=0.1 -): - samples = jax.vmap( - lambda k: kik.truncated_laplace.sample( - k, loc, scale, low, high, uniform_window_size - ) - )(jax.random.split(key, 3)) - assert ( - jnp.abs(samples[0] - samples[1]) > scale * scale_mult - or jnp.abs(samples[0] - samples[2]) > scale * scale_mult - or jnp.abs(samples[1] - samples[2]) > scale * scale_mult - ) - - -def test_truncated_laplace(): - confirm_logpdf_looks_valid(0.5, 1.0, 0.0, 1.0, 0.1) - confirm_logpdf_looks_valid(1.0, 1.0, 0.0, 1.0, 0.1) - confirm_logpdf_looks_valid(0.0, 1.0, 0.0, 1.0, 0.1) - confirm_logpdf_looks_valid(0.5, 0.01, 0.0, 1.0, 0.1) - confirm_logpdf_looks_valid(0.0, 0.01, 0.0, 1.0, 0.1) - confirm_logpdf_looks_valid(1.0, 0.01, 0.0, 1.0, 0.1) - confirm_logpdf_looks_valid(0.99, 0.1, 0.0, 1.0, 0.2) - confirm_logpdf_looks_valid(0.01, 0.1, 0.0, 1.0, 0.2) - confirm_logpdf_looks_valid(1.99, 0.1, -1.0, 2.0, 0.2) - confirm_logpdf_looks_valid(-0.99, 0.1, -1.0, 2.0, 0.2) - confirm_logpdf_looks_valid(0.0, 5.0, -1.0, 2.0, 0.2) - - ensure_laplace_samples_have_sufficient_spread( - jax.random.PRNGKey(0), 0.5, 0.1, 0.0, 1.0, 0.1 - ) - - # TODO: the code below ehre could be cleaner. - # I think the functionality is right, though. - - key = jax.random.PRNGKey(1) - for j in range(5): - key, _ = jax.random.split(key) - x = kik.truncated_laplace.sample(key, 0.01, 0.01, 0.0, 1.0, 0.001) - assert 0.0 < x < 0.05 - - # test that the logpdf function puts almost all mass to the left - x = jnp.linspace(0.0, 1.0, int(1e6)) - stepsize = 1e-6 - logpdfs = jax.vmap( - lambda x: kik.truncated_laplace.logpdf(x, 0.01, 0.01, 0.0, 1.0, 0.001) - )(x) - pdfs = jnp.exp(logpdfs) - assert jnp.sum(pdfs[: int(1e6 * 0.05)] * stepsize) > 0.98 - - for j in range(5): - key, _ = jax.random.split(key) - x = kik.truncated_laplace.sample(key, -0.04, 0.01, 0.0, 1.0, 0.001) - assert 0.0 < x < 0.001 - - # test that the logpdf function also puts almost all mass to the left of 0.001 - x = jnp.linspace(0.0, 1.0, int(1e6)) - stepsize = 1e-6 - logpdfs = jax.vmap( - lambda x: kik.truncated_laplace.logpdf(x, -0.04, 0.01, 0.0, 1.0, 0.001) - )(x) - pdfs = jnp.exp(logpdfs) - assert jnp.sum(pdfs[: int(1e6 * 0.001)] * stepsize) > 0.98 - - -def test_color_truncated_logpdf(): - s1 = kik.truncated_color_laplace.sample( - jax.random.PRNGKey(0), jnp.array([1.0, 0.0, 0.5]), 0.2 - ) - keys = jax.random.split(jax.random.PRNGKey(0), 3) - r = kik.truncated_laplace.sample(keys[0], 1.0, 0.2, 0.0, 1.0, 1 / 255) - g = kik.truncated_laplace.sample(keys[1], 0.0, 0.2, 0.0, 1.0, 1 / 255) - b = kik.truncated_laplace.sample(keys[2], 0.5, 0.2, 0.0, 1.0, 1 / 255) - assert jnp.allclose(s1, jnp.array([r, g, b])) - - logpdf = kik.truncated_color_laplace.logpdf(s1, jnp.array([1.0, 0.0, 0.5]), 0.2) - logpdf_r = kik.truncated_laplace.logpdf(r, 1.0, 0.2, 0.0, 1.0, 1 / 255) - logpdf_g = kik.truncated_laplace.logpdf(g, 0.0, 0.2, 0.0, 1.0, 1 / 255) - logpdf_b = kik.truncated_laplace.logpdf(b, 0.5, 0.2, 0.0, 1.0, 1 / 255) - assert jnp.allclose(logpdf, logpdf_r + logpdf_g + logpdf_b) diff --git a/tests/gen3d/test_model.py b/tests/gen3d/test_model.py index d78d00cd..6932de89 100644 --- a/tests/gen3d/test_model.py +++ b/tests/gen3d/test_model.py @@ -43,16 +43,16 @@ def test_model_no_likelihood(): "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.1), "color_kernel": transition_kernels.LaplaceColorDriftKernel(scale=0.05), "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, possible_values=jnp.array([0.01, 0.99]) + resample_probability=0.1, support=jnp.array([0.01, 0.99]) ), "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, possible_values=jnp.array([0.01, 0.99]) + resample_probability=0.1, support=jnp.array([0.01, 0.99]) ), "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, possible_values=jnp.array([0.005, 0.01, 0.02]) + resample_probability=0.1, support=jnp.array([0.005, 0.01, 0.02]) ), "color_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, possible_values=jnp.array([0.05, 0.1, 0.15]) + resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15]) ), "vertices": vertices, } @@ -61,11 +61,11 @@ def test_model_no_likelihood(): "pose": Pose.identity(), "colors": colors, "visibility_prob": jnp.ones(num_vertices) - * hyperparams["visibility_prob_kernel"].possible_values[-1], + * hyperparams["visibility_prob_kernel"].support[-1], "depth_nonreturn_prob": jnp.ones(num_vertices) - * hyperparams["depth_nonreturn_prob_kernel"].possible_values[0], - "depth_scale": hyperparams["depth_scale_kernel"].possible_values[0], - "color_scale": hyperparams["color_scale_kernel"].possible_values[0], + * hyperparams["depth_nonreturn_prob_kernel"].support[0], + "depth_scale": hyperparams["depth_scale_kernel"].support[0], + "color_scale": hyperparams["color_scale_kernel"].support[0], } key = jax.random.PRNGKey(0) diff --git a/tests/gen3d/test_pixel_color_kernels.py b/tests/gen3d/test_pixel_color_kernels.py index 3a968ec9..e861b4b8 100644 --- a/tests/gen3d/test_pixel_color_kernels.py +++ b/tests/gen3d/test_pixel_color_kernels.py @@ -35,9 +35,21 @@ def generate_color_grid(n_grid_steps: int): sample_kernels_to_test = [ (UniformPixelColorDistribution(), ()), - (TruncatedLaplacePixelColorDistribution(0.1), ()), - (MixturePixelColorDistribution(0.3), (0.5,)), # occluded_prob - (FullPixelColorDistribution(0.5), (0.3,)), # occluded_prob + (TruncatedLaplacePixelColorDistribution(), (0.1,)), + ( + MixturePixelColorDistribution(), + ( + 0.3, + 0.5, + ), + ), + ( + FullPixelColorDistribution(), + ( + 0.5, + 1 - 0.3, + ), + ), ] @@ -73,28 +85,29 @@ def test_sample_in_valid_color_range(kernel_spec, latent_color): def test_relative_logpdf(): - kernel = FullPixelColorDistribution(0.01) + kernel = FullPixelColorDistribution() + scale = 0.01 obs_color = jnp.array([0.0, 0.0, 1.0]) # a blue pixel # case 1: no color hit the pixel latent_color = -jnp.ones(3) # use -1 to denote invalid pixel - logpdf_1 = kernel.logpdf(obs_color, latent_color, 0.2) - logpdf_2 = kernel.logpdf(obs_color, latent_color, 0.8) + logpdf_1 = kernel.logpdf(obs_color, latent_color, scale, 0.8) + logpdf_2 = kernel.logpdf(obs_color, latent_color, scale, 0.2) # the logpdf should be the same because the occluded probability is not used # in the case when no color hit the pixel assert jnp.allclose(logpdf_1, logpdf_2) # case 2: a color hit the pixel, but the color is not close to the observed color latent_color = jnp.array([1.0, 0.5, 0.0]) - logpdf_3 = kernel.logpdf(obs_color, latent_color, 0.2) - logpdf_4 = kernel.logpdf(obs_color, latent_color, 0.8) + logpdf_3 = kernel.logpdf(obs_color, latent_color, scale, 0.8) + logpdf_4 = kernel.logpdf(obs_color, latent_color, scale, 0.2) # the pixel should be more likely to be an occluded assert logpdf_3 < logpdf_4 # case 3: a color hit the pixel, and the color is close to the observed color latent_color = jnp.array([0.0, 0.0, 0.9]) - logpdf_5 = kernel.logpdf(obs_color, latent_color, 0.2) - logpdf_6 = kernel.logpdf(obs_color, latent_color, 0.8) + logpdf_5 = kernel.logpdf(obs_color, latent_color, 0.01, 0.8) + logpdf_6 = kernel.logpdf(obs_color, latent_color, scale, 0.2) # the pixel should be more likely to be an inlier assert logpdf_5 > logpdf_6 # the score of the pixel should be higher when the color is closer diff --git a/tests/gen3d/test_pixel_depth_kernels.py b/tests/gen3d/test_pixel_depth_kernels.py index 45e06f9e..03aff1c9 100644 --- a/tests/gen3d/test_pixel_depth_kernels.py +++ b/tests/gen3d/test_pixel_depth_kernels.py @@ -17,19 +17,21 @@ # each kernel specs is a tuple of (kernel, additional_args) sample_kernels_to_test = [ (UniformPixelDepthDistribution(near, far), ()), - (TruncatedLaplacePixelDepthDistribution(near, far, 0.25), ()), + (TruncatedLaplacePixelDepthDistribution(near, far), (0.25,)), (UnexplainedPixelDepthDistribution(near, far), ()), ( - MixturePixelDepthDistribution(near, far, 0.15), + MixturePixelDepthDistribution(near, far), ( - 0.5, # occluded_prob + 0.15, # scale + 0.5, # visibility_prob 0.23, # depth_nonreturn_prob ), ), ( - FullPixelDepthDistribution(near, far, 0.5), + FullPixelDepthDistribution(near, far), ( - 0.3, # occluded_prob + 0.5, # scale + 1 - 0.3, # visibility_prob 0.1, # depth_nonreturn_prob ), ), @@ -75,32 +77,33 @@ def test_sample_in_valid_depth_range(kernel_spec, latent_depth): def test_relative_logpdf(): - kernel = FullPixelDepthDistribution(near, far, 0.1) + kernel = FullPixelDepthDistribution(near, far) + scale = 0.1 # case 1: depth is missing in observation (nonreturn) obs_depth = DEPTH_NONRETURN_VAL latent_depth = DEPTH_NONRETURN_VAL depth_nonreturn_prob = 0.2 - logpdf_1 = kernel.logpdf(obs_depth, latent_depth, 0.8, depth_nonreturn_prob) + logpdf_1 = kernel.logpdf(obs_depth, latent_depth, scale, 0.8, depth_nonreturn_prob) assert logpdf_1 == jnp.log(depth_nonreturn_prob) latent_depth = -1.0 # no depth information from latent - logpdf_2 = kernel.logpdf(obs_depth, latent_depth, 0.8, depth_nonreturn_prob) + logpdf_2 = kernel.logpdf(obs_depth, latent_depth, scale, 0.8, depth_nonreturn_prob) # nonreturn obs cannot be generates from latent that is not nonreturn assert logpdf_2 == jnp.log(UNEXPLAINED_DEPTH_NONRETURN_PROB) # case 2: valid depth is observed, but latent depth is far from the observed depth obs_depth = 10.0 latent_depth = 0.01 - logpdf_3 = kernel.logpdf(obs_depth, latent_depth, 0.9, depth_nonreturn_prob) - logpdf_4 = kernel.logpdf(obs_depth, latent_depth, 0.1, depth_nonreturn_prob) + logpdf_3 = kernel.logpdf(obs_depth, latent_depth, scale, 0.1, depth_nonreturn_prob) + logpdf_4 = kernel.logpdf(obs_depth, latent_depth, scale, 0.9, depth_nonreturn_prob) # the pixel should be more likely to be an occluded assert logpdf_3 > logpdf_4 # case 3: valid depth is observed, but latent depth is close from the observed depth obs_depth = 6.0 latent_depth = 6.01 - logpdf_5 = kernel.logpdf(obs_depth, latent_depth, 0.9, depth_nonreturn_prob) - logpdf_6 = kernel.logpdf(obs_depth, latent_depth, 0.1, depth_nonreturn_prob) + logpdf_5 = kernel.logpdf(obs_depth, latent_depth, scale, 0.1, depth_nonreturn_prob) + logpdf_6 = kernel.logpdf(obs_depth, latent_depth, scale, 0.9, depth_nonreturn_prob) # the pixel should be more likely to be an inliner assert logpdf_5 < logpdf_6 diff --git a/tests/gen3d/test_pixel_rgbd_kernels.py b/tests/gen3d/test_pixel_rgbd_kernels.py index f42da130..33a1e44f 100644 --- a/tests/gen3d/test_pixel_rgbd_kernels.py +++ b/tests/gen3d/test_pixel_rgbd_kernels.py @@ -16,11 +16,13 @@ sample_kernels_to_test = [ ( PixelRGBDDistribution( - FullPixelColorDistribution(0.01), - FullPixelDepthDistribution(near, far, 0.01), + FullPixelColorDistribution(), + FullPixelDepthDistribution(near, far), ), ( - 0.3, # occluded_prob + 0.01, # rgb_scale + 0.01, # depth_scale + 1 - 0.3, # visibility_prob 0.1, # depth_nonreturn_prob ), ) @@ -58,10 +60,10 @@ def test_relative_logpdf(kernel_spec): # case 1: no vertex hit the pixel latent_rgbd = -jnp.ones(4) # use -1 to denote invalid pixel logpdf_1 = kernel.logpdf( - obs_rgbd, latent_rgbd, occluded_prob=0.2, depth_nonreturn_prob=0.1 + obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.8, depth_nonreturn_prob=0.1 ) logpdf_2 = kernel.logpdf( - obs_rgbd, latent_rgbd, occluded_prob=0.8, depth_nonreturn_prob=0.1 + obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.2, depth_nonreturn_prob=0.1 ) # the logpdf should be the same because the occluded probability is not used # in the case when no vertex hit the pixel @@ -70,10 +72,10 @@ def test_relative_logpdf(kernel_spec): # case 2: a vertex hit the pixel, but the rgbd is not close to the observed rgbd latent_rgbd = jnp.array([1.0, 0.5, 0.0, 12.0]) logpdf_3 = kernel.logpdf( - obs_rgbd, latent_rgbd, occluded_prob=0.2, depth_nonreturn_prob=0.1 + obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.8, depth_nonreturn_prob=0.1 ) logpdf_4 = kernel.logpdf( - obs_rgbd, latent_rgbd, occluded_prob=0.8, depth_nonreturn_prob=0.1 + obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.2, depth_nonreturn_prob=0.1 ) # the pixel should be more likely to be an occluded assert logpdf_3 < logpdf_4 @@ -81,10 +83,10 @@ def test_relative_logpdf(kernel_spec): # case 3: a vertex hit the pixel, and the rgbd is close to the observed rgbd latent_rgbd = jnp.array([0.0, 0.0, 0.95, 0.022]) logpdf_5 = kernel.logpdf( - obs_rgbd, latent_rgbd, occluded_prob=0.2, depth_nonreturn_prob=0.1 + obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.8, depth_nonreturn_prob=0.1 ) logpdf_6 = kernel.logpdf( - obs_rgbd, latent_rgbd, occluded_prob=0.8, depth_nonreturn_prob=0.1 + obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.2, depth_nonreturn_prob=0.1 ) # the pixel should be more likely to be an inlier assert logpdf_5 > logpdf_6 diff --git a/tests/gen3d/test_transition_kernels.py b/tests/gen3d/test_transition_kernels.py index 96f8dba3..578ae03b 100644 --- a/tests/gen3d/test_transition_kernels.py +++ b/tests/gen3d/test_transition_kernels.py @@ -9,7 +9,7 @@ def test_discrete_flip_kernel(): possible_values = jnp.linspace(0, 1, num_values) flip_probability = 0.1 kernel = transition_kernels.DiscreteFlipKernel( - resample_probability=flip_probability, possible_values=possible_values + resample_probability=flip_probability, support=possible_values ) assert jnp.isclose( From f23a55ba3adc0d8c1c735e36b49044e735451d70 Mon Sep 17 00:00:00 2001 From: georgematheos Date: Tue, 10 Sep 2024 14:55:10 -0400 Subject: [PATCH 04/37] Gm/gen3d/inference2 (#154) --- notebooks/bayes3d_paper/tester.ipynb | 77 ++++++---- src/b3d/chisight/gen3d/inference.py | 2 +- src/b3d/chisight/gen3d/inference_moves.py | 177 +++++++++++++++++++++- 3 files changed, 217 insertions(+), 39 deletions(-) diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 51db36e7..6c582ebe 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -39,10 +39,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 12.57it/s]\n", - "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", - "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", - " warnings.warn(\n" + " 0%| | 0/49 [00:00" ] }, - "execution_count": 3, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -88,7 +92,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -116,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ @@ -125,7 +129,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -147,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -158,7 +162,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -192,7 +196,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ @@ -206,7 +210,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 39, "metadata": {}, "outputs": [], "source": [ @@ -225,7 +229,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 40, "metadata": {}, "outputs": [], "source": [ @@ -246,7 +250,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 41, "metadata": {}, "outputs": [ { @@ -255,7 +259,7 @@ "Array(82541.78, dtype=float32)" ] }, - "execution_count": 12, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -268,7 +272,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -277,7 +281,7 @@ "Array(82541.78, dtype=float32)" ] }, - "execution_count": 13, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -288,7 +292,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 86, "metadata": {}, "outputs": [], "source": [ @@ -300,16 +304,16 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 87, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(36987.824, dtype=float32)" + "Array(35023.812, dtype=float32)" ] }, - "execution_count": 27, + "execution_count": 87, "metadata": {}, "output_type": "execute_result" } @@ -321,8 +325,8 @@ " pose_proposal_conc=1000.,\n", ")\n", "\n", - "stepped_trace, step_weight = i.inference_step(\n", - " jax.random.PRNGKey(20),\n", + "stepped_trace, step_weight, metadata = i.inference_step(\n", + " jax.random.PRNGKey(21),\n", " trace,\n", " all_data[1][\"rgbd\"],\n", " inference_hyperparams\n", @@ -332,21 +336,30 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 89, "metadata": {}, "outputs": [], "source": [ - "b3d.reload(b3d.chisight.gen3d.model)" + "T = 1\n", + "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 62, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2024-09-10T18:07:03Z WARN re_log_types::path::parse_path] When parsing the entity path \"proposed positions\": Unescaped whitespace. The path will be interpreted as /proposed\\ positions\n" + ] + } + ], "source": [ - "T = 1\n", - "b3d.chisight.gen3d.model.viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" + "import rerun as rr\n", + "rr.log(\"proposed positions\", rr.Points3D(metadata[\"proposed_poses\"].position))" ] }, { diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 83c08de2..7db9ddbe 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -75,7 +75,7 @@ def inference_step(key, old_trace, observed_rgbd, inference_hyperparams): chosen_index = jax.random.categorical(k4, scores) new_trace = jax.tree.map(lambda x: x[chosen_index], proposed_traces) - return new_trace, logmeanexp(scores) + return new_trace, logmeanexp(scores), {"proposed_poses": proposed_poses} def inference_step_noweight(*args): diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index 0518383d..539f3dd4 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -7,6 +7,7 @@ from jax.random import split from b3d import Pose +from b3d.modeling_utils import uniform from .model import ( get_hypers, @@ -52,6 +53,7 @@ def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperp colors, visibility_probs, log_q_cvp = propose_colors_and_visibility_probs( k3, trace_with_pose ) + log_q_cvp = 0.0 depth_scale, log_q_ds = propose_depth_scale(k4, trace_with_pose) color_scale, log_q_cs = propose_color_scale(k5, trace_with_pose) @@ -166,7 +168,12 @@ def score_dnrp_value(dnrp_value): def propose_vertex_color_and_visibility_prob( - key, vertex_index, observed_rgbd, previous_state, new_state, hyperparams + key, + vertex_index, + observed_rgbd_for_this_vertex, + previous_state, + new_state, + hyperparams, ): """ Propose a new color and visibility probability for the single vertex @@ -174,12 +181,170 @@ def propose_vertex_color_and_visibility_prob( Returns (color, visibility_prob, log_q) where `color` and `visibility_prob` are the proposed values and `log_q` is (a fair estimate of) the log proposal density. """ - # Placeholder - return ( - previous_state["colors"][vertex_index], - previous_state["visibility_prob"][vertex_index], - 0.0, + k1, k2 = split(key, 2) + previous_rgb = previous_state["colors"][vertex_index] + previous_visibility_prob = previous_state["visibility_prob"][vertex_index] + latent_depth = new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2] + all_vis_probs = hyperparams["visibility_prob_kernel"].support + + def score_visprob_rgb(visprob, rgb): + """ + Compute P(visprob, rgb, observed_rgbd_for_this_vertex | previous_visprob, previous_rgb). + """ + rgb_transition_score = hyperparams["color_kernel"].logpdf(rgb, previous_rgb) + visprob_transition_score = hyperparams["visibility_prob_kernel"].logpdf( + visprob, previous_visibility_prob + ) + likelihood_score = ( + hyperparams["image_kernel"] + .get_rgbd_vertex_kernel() + .logpdf( + observed_rgbd_for_this_vertex, + jnp.append(rgb, latent_depth), + new_state["color_scale"], + new_state["depth_scale"], + visprob, + new_state["depth_nonreturn_prob"][vertex_index], + ) + ) + return rgb_transition_score + visprob_transition_score + likelihood_score + + # Propose a rgb value for each visprob. + # `rgbs` has shape (len(all_vis_probs), 3). + # `log_qs_rgb` has shape (len(all_vis_probs),). + rgbs, log_qs_rgb = jax.vmap( + lambda k, visprob: propose_vertex_color_given_visibility( + k, + visprob, + observed_rgbd_for_this_vertex[:3], + score_visprob_rgb, + previous_rgb, + new_state, + hyperparams, + ) + )(split(k1, len(all_vis_probs)), all_vis_probs) + + # shape: (len(all_vis_probs),) + log_pscores = jax.vmap(score_visprob_rgb, in_axes=(0, 0))(all_vis_probs, rgbs) + + # We don't need to subtract a q score for the visibility probability, since + # we are enumerating over every value in the domain. (Equivalently, + # we could subtract a log q score of log(1/len(support)) for each value.) + log_weights = log_pscores - log_qs_rgb + log_normalized_scores = log_weights - jax.scipy.special.logsumexp(log_weights) + index = jax.random.categorical(k2, log_normalized_scores) + + rgb = rgbs[index] + visibility_prob = all_vis_probs[index] + log_q_score = log_normalized_scores[index] + log_qs_rgb[index] + + return rgb, visibility_prob, log_q_score + + +def propose_vertex_color_given_visibility( + key, + visprob, + observed_rgb, + score_visprob_and_rgb, + previous_rgb, + new_state, + hyperparams, +): + """ + This samples an rgb value from a proposal which first proposes 3 different rgb values, + then resamples one. The log q score is estimated using + simple logic for "filling in the auxiliary randomness" with a backward ("L") proposal, + as in SMCP3 or RAVI. + Returns (sampled_rgb, log_q_score). + + Specifically, this proposes 3 RGB values: + - One from a tight uniform around previous_rgb + - One from a tight uniform around observed_rgb + - One from a potentially broader uniform around the midpoint of the two. + + One of these 3 RGB values is then resampled. + + This creates a "forward" ("K") proposal, which has sampled (1) the chosen RGB value, + (2) the index amoung [0, 1, 2] for which of the 3 proposals generated it, and (3) + two additional RGB values. + + We then imagine having an "L" proposal which, given (1), proposes (2) and (3). + To estimate the probability of having proposed (1) alone, we return log_K - log_L. + + One remaining TODO: this proposal has no probability of generating a value that is far outside + the range of the previous and observed values. This means we technically do not have absolute continuity. + In practice this means if the posterior ever assigns mass to RGB values outside this range, we can't + propose traces that match that part of the posterior. + """ + color_shift_scale = hyperparams["color_kernel"].scale + color_scale = new_state["color_scale"] + d = 1 / (1 / color_shift_scale + 1 / color_scale) + + r_diff = jnp.abs(previous_rgb[0] - observed_rgb[0]) + g_diff = jnp.abs(previous_rgb[1] - observed_rgb[1]) + b_diff = jnp.abs(previous_rgb[2] - observed_rgb[2]) + diffs = jnp.array([r_diff, g_diff, b_diff]) + + (k1, k2, k3) = split(key, 3) + + ## Proposal 1: near the previous value. + min_rgbs1 = previous_rgb - diffs / 10 - 2 * d + max_rgbs1 = previous_rgb + diffs / 10 + 2 * d + proposed_rgb_1 = uniform.sample(k1, min_rgbs1, max_rgbs1) + log_q_rgb_1 = uniform.logpdf(proposed_rgb_1, min_rgbs1, max_rgbs1) + + ## Proposal 2: near the observed value. + min_rgbs2 = observed_rgb - diffs / 10 - 2 * d + max_rgbs2 = observed_rgb + diffs / 10 + 2 * d + proposed_rgb_2 = uniform.sample(k2, min_rgbs2, max_rgbs2) + log_q_rgb_2 = uniform.logpdf(proposed_rgb_2, min_rgbs2, max_rgbs2) + + ## Proposal 3: somewhere in the middle + mean_rgb = (previous_rgb + observed_rgb) / 2 + min_rgbs3 = mean_rgb - 8 / 10 * diffs - 2 * d + max_rgbs3 = mean_rgb + 8 / 10 * diffs + 2 * d + proposed_rgb_3 = uniform.sample(k3, min_rgbs3, max_rgbs3) + log_q_rgb_3 = uniform.logpdf(proposed_rgb_3, min_rgbs3, max_rgbs3) + + ## Resample one of the values. + + proposed_rgbs = jnp.array([proposed_rgb_1, proposed_rgb_2, proposed_rgb_3]) + log_qs = jnp.array([log_q_rgb_1, log_q_rgb_2, log_q_rgb_3]) + + scores = ( + jax.vmap(lambda rgb: score_visprob_and_rgb(visprob, rgb))(proposed_rgbs) + - log_qs + ) + normalized_scores = scores - jax.scipy.special.logsumexp(scores) + sampled_index = jax.random.categorical(key, normalized_scores) + sampled_rgb = proposed_rgbs[sampled_index] + log_K_score = log_qs.sum() + normalized_scores[sampled_index] + + ## "L proposal": given the sampled rgb, estimate the probability that + # it came from the one of the 3 proposals that actually was used. + log_qs_for_this_rgb = jnp.array( + [ + uniform.logpdf(sampled_rgb, min_rgbs1, max_rgbs1), + uniform.logpdf(sampled_rgb, min_rgbs2, max_rgbs2), + uniform.logpdf(sampled_rgb, min_rgbs3, max_rgbs3), + ] ) + normalized_L_logprobs = log_qs_for_this_rgb - jax.scipy.special.logsumexp( + log_qs_for_this_rgb + ) + + # L score for proposing the index + log_L_score = normalized_L_logprobs[sampled_index] + + # Also add in the L score for proposing the other two RGB values. + # The L proposal over these values will just generate them from their prior. + log_L_score += jnp.sum(log_qs) - log_qs[sampled_index] + + ## Compute the overall score. + overall_score = log_K_score - log_L_score + + ## Return + return sampled_rgb, overall_score def propose_depth_scale(key, trace): From f1ed0822867a702105cdd2bc91ebed569f008e75 Mon Sep 17 00:00:00 2001 From: georgematheos Date: Tue, 10 Sep 2024 17:39:59 -0400 Subject: [PATCH 05/37] Gm/gen3d/inference3 (#156) --- notebooks/bayes3d_paper/tester.ipynb | 1442 ++++++++++++++++- src/b3d/chisight/gen3d/inference.py | 18 +- src/b3d/chisight/gen3d/inference_moves.py | 222 ++- src/b3d/chisight/gen3d/projection.py | 1 + .../test_depth_nonreturn_prob_inference.py | 32 + 5 files changed, 1619 insertions(+), 96 deletions(-) create mode 100644 tests/gen3d/inference/test_depth_nonreturn_prob_inference.py diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 6c582ebe..0c9560c0 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 30, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -16,7 +16,17 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import genjax\n", + "genjax.pretty()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -25,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -46,7 +56,10 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 14.41it/s]\n" + "100%|██████████| 49/49 [00:03<00:00, 12.99it/s]\n", + "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", + "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", + " warnings.warn(\n" ] }, { @@ -57,7 +70,7 @@ "" ] }, - "execution_count": 32, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -92,7 +105,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -120,7 +133,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -129,7 +142,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -151,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -162,7 +175,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -196,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -210,7 +223,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -229,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -250,16 +263,43 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
" + ], "text/plain": [ - "Array(82541.78, dtype=float32)" + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" ] }, - "execution_count": 41, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -272,16 +312,43 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], "text/plain": [ - "Array(82541.78, dtype=float32)" + "" ] }, - "execution_count": 42, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -292,7 +359,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -304,31 +371,59 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 31, "metadata": {}, "outputs": [ { "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], "text/plain": [ - "Array(35023.812, dtype=float32)" + "" ] }, - "execution_count": 87, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "inference_hyperparams = InferenceHyperparams(\n", - " n_poses=10000,\n", + "inference_hyperparams = i.InferenceHyperparams(\n", + " n_poses=6000,\n", " pose_proposal_std=0.04,\n", " pose_proposal_conc=1000.,\n", + " color_proposal_params=None\n", ")\n", "\n", "stepped_trace, step_weight, metadata = i.inference_step(\n", " jax.random.PRNGKey(21),\n", " trace,\n", - " all_data[1][\"rgbd\"],\n", + " all_data[0][\"rgbd\"],\n", " inference_hyperparams\n", ")\n", "step_weight" @@ -336,30 +431,1315 @@ }, { "cell_type": "code", - "execution_count": 89, + "execution_count": 32, "metadata": {}, "outputs": [], "source": [ - "T = 1\n", + "T = 0\n", "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" ] }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 37, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "[2024-09-10T18:07:03Z WARN re_log_types::path::parse_path] When parsing the entity path \"proposed positions\": Unescaped whitespace. The path will be interpreted as /proposed\\ positions\n" + "100%|██████████| 49/49 [00:59<00:00, 1.21s/it]\n" ] } ], "source": [ "import rerun as rr\n", - "rr.log(\"proposed positions\", rr.Points3D(metadata[\"proposed_poses\"].position))" + "\n", + "### Run inference ###\n", + "for T in tqdm(range(len(all_data))):\n", + " key = b3d.split_key(key)\n", + " trace, wt, _ = i.inference_step(\n", + " key,\n", + " trace,\n", + " all_data[T][\"rgbd\"],\n", + " inference_hyperparams\n", + " )\n", + " b3d.chisight.gen3d.model.viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])\n", + " rr.log(\"importance_weight\", rr.Scalar(wt))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "dict_keys(['chosen_pose_index', 'log_q_nonpose_latents', 'log_q_poses', 'other_latents_metadata', 'p_scores', 'proposed_poses'])" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metadata.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jax.nn.softmax(jnp.array([-jnp.inf, -jnp.inf]))" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metadata[\"other_latents_metadata\"][\"depth_nonreturn_proposal\"][\"log_normalized_scores\"]\n", + "metadata[\"other_latents_metadata\"][\"depth_nonreturn_proposal\"][\"likelihood_score\"][4]" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "i = jnp.argmax(metadata[\"p_scores\"])\n", + "metadata[\"p_scores\"][i-3:i+3]" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# get the 10 largest values in p_scores\n", + "jnp.sort(metadata[\"p_scores\"])[-10:]" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jnp.max(metadata[\"log_q_poses\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jnp.min(jnp.nan_to_num(metadata[\"log_q_nonpose_latents\"], -jnp.inf))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "dict_keys(['chosen_pose_index', 'other_latents_metadata', 'proposed_poses'])" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metadata.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "{'depth_nonreturn_proposal': {'index': ,\n", + " 'latent_depth': ,\n", + " 'likelihood_score': \n", + " >,\n", + " 'log_normalized_scores': \n", + " >,\n", + " 'observed_depth': ,\n", + " 'prev_dnrp': ,\n", + " 'support': \n", + " >,\n", + " 'transition_score': \n", + " >},\n", + " 'dnrps': }" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "md = jax.tree.map(lambda x: x[metadata['chosen_pose_index']], metadata['other_latents_metadata'])\n", + "jax.tree.map(lambda x: x[0], md)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def sample(key):\n", + " return jax.random.categorical(key, jnp.array([-1.01509 , -0.44999695]))\n", + "\n", + "key = jax.random.PRNGKey(0)\n", + "jax.vmap(sample)(jax.random.split(key, 100))" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jnp.exp(jnp.array([-1.01509 , -0.44999695]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b3d.reload(b3d.chisight.gen3d.projection)\n", + "from b3d.chisight.gen3d.projection import PixelsPointsAssociation\n", + "import b3d.chisight.gen3d.model as m\n", + "\n", + "obs_point_depths = PixelsPointsAssociation.from_hyperparams_and_pose(\n", + " m.get_hypers(trace), m.get_new_state(trace)[\"pose\"]\n", + ").get_point_depths(m.get_observed_rgbd(trace))\n", + "\n", + "true_point_depths = template_pose.apply(hyperparams[\"vertices\"])[:, 2]\n", + "\n", + "jnp.all(jnp.abs(obs_point_depths - true_point_depths) < 1e-3)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jnp.any(jnp.abs(obs_point_depths - true_point_depths[0]) < 1e-6)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "true_point_colors = m.get_prev_state(trace)[\"colors\"]\n", + "obs_point_colors = PixelsPointsAssociation.from_hyperparams_and_pose(\n", + " m.get_hypers(trace), m.get_new_state(trace)[\"pose\"]\n", + ").get_point_rgbds(m.get_observed_rgbd(trace))[..., :3]\n", + "\n", + "true_point_colors - obs_point_colors" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "dict_keys(['chosen_pose_index', 'other_latents_metadata', 'proposed_poses'])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metadata.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jnp.all(stepped_trace.get_retval()[\"new_state\"][\"depth_nonreturn_prob\"] == metadata[\"other_latents_metadata\"][\"dnrps\"][metadata[\"chosen_pose_index\"]])" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "# jax.Array float32(100,) ≈0.68 ±0.46 [≥0.01, ≤0.99] nonzero:100\n", + " Array([0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01,\n", + " 0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.99, 0.99, 0.01, 0.99, 0.99,\n", + " 0.01, 0.01, 0.99, 0.01, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01,\n", + " 0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.01, 0.01, 0.99, 0.99,\n", + " 0.99, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99,\n", + " 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01,\n", + " 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01, 0.99, 0.99, 0.01, 0.99,\n", + " 0.99, 0.01, 0.99, 0.01, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.99,\n", + " 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.01, 0.99, 0.01, 0.99, 0.99,\n", + " 0.01], dtype=float32)\n" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "stepped_trace.get_retval()[\"new_state\"][\"depth_nonreturn_prob\"][:100]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "T = 0\n", + "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "{'depth_nonreturn_proposal': {'index': \n", + " >,\n", + " 'log_normalized_scores': \n", + " >,\n", + " 'support': \n", + " >}}" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jax.tree.map(\n", + " lambda x: x[closest_pose_idx], metadata[\"other_latents_metadata\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "gt_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metadata[\"proposed_poses\"].position" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "closest_pose_idx" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "closest_pose_idx = jnp.argmin(\n", + " jnp.linalg.norm(\n", + " metadata[\"proposed_poses\"].position - gt_pose.position, axis=-1\n", + " )\n", + ")\n", + "metadata[\"proposed_poses\"].quaternion[closest_pose_idx]" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "\n", + ">" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gt_pose.quaternion" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [], + "source": [ + "T = 1\n", + "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[2024-09-10T18:07:03Z WARN re_log_types::path::parse_path] When parsing the entity path \"proposed positions\": Unescaped whitespace. The path will be interpreted as /proposed\\ positions\n" + ] + } + ], + "source": [ + "import rerun as rr\n", + "rr.log(\"proposed positions\", rr.Points3D(metadata[\"proposed_poses\"].position))" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jax.scipy.special.logsumexp(jnp.array([-jnp.inf, -.2, -1.]))" ] }, { diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 7db9ddbe..611911fe 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -20,7 +20,8 @@ # Use namedtuple rather than dict so we can hash this, and use it as a static arg to a jitted function. InferenceHyperparams = namedtuple( - "InferenceHyperparams", ["n_poses", "pose_proposal_std", "pose_proposal_conc"] + "InferenceHyperparams", + ["n_poses", "pose_proposal_std", "pose_proposal_conc", "color_proposal_params"], ) @@ -66,7 +67,7 @@ def inference_step(key, old_trace, observed_rgbd, inference_hyperparams): ) param_generation_keys = split(k3, inference_hyperparams.n_poses) - proposed_traces, log_q_nonpose_latents = jax.vmap( + proposed_traces, log_q_nonpose_latents, other_latents_metadata = jax.vmap( propose_other_latents_given_pose, in_axes=(0, None, 0, None) )(param_generation_keys, trace, proposed_poses, inference_hyperparams) p_scores = jax.vmap(lambda tr: tr.get_score())(proposed_traces) @@ -75,7 +76,18 @@ def inference_step(key, old_trace, observed_rgbd, inference_hyperparams): chosen_index = jax.random.categorical(k4, scores) new_trace = jax.tree.map(lambda x: x[chosen_index], proposed_traces) - return new_trace, logmeanexp(scores), {"proposed_poses": proposed_poses} + return ( + new_trace, + logmeanexp(scores), + { + "proposed_poses": proposed_poses, + "chosen_pose_index": chosen_index, + "p_scores": p_scores, + "log_q_poses": log_q_poses, + "log_q_nonpose_latents": log_q_nonpose_latents, + "other_latents_metadata": other_latents_metadata, + }, + ) def inference_step_noweight(*args): diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index 539f3dd4..f8842ed3 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -19,6 +19,18 @@ from .projection import PixelsPointsAssociation +def normalize_log_scores(scores): + """ + Util for constructing log resampling distributions, avoiding NaN issues. + + (Conversely, since there will be no NaNs, this could make it harder to debug.) + """ + val = scores - jax.scipy.special.logsumexp(scores) + return jnp.where( + jnp.any(jnp.isnan(val)), -jnp.log(len(val)) * jnp.ones_like(val), val + ) + + def propose_pose(key, advanced_trace, inference_hyperparams): """ Propose a random pose near the previous timestep's pose. @@ -43,35 +55,41 @@ def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperp proposed latents (and the same pose and observed rgbd as in the given trace). `log_q` is (a fair estimate of) the log proposal density. """ - k1, k2, k3, k4, k5, k6 = split(key, 6) + k1, k2, k3, k4, k5 = split(key, 5) - trace_with_pose = update_field(k1, advanced_trace, "pose", pose) + trace = update_field(k1, advanced_trace, "pose", pose) - depth_nonreturn_probs, log_q_dnrps = propose_depth_nonreturn_probs( - k2, trace_with_pose + k2a, k2b = split(k2) + depth_nonreturn_probs, log_q_dnrps, dnrp_metadata = propose_depth_nonreturn_probs( + k2a, trace + ) + trace = update_vmapped_field( + k2b, trace, "depth_nonreturn_prob", depth_nonreturn_probs ) + + k3a, k3b = split(k3) colors, visibility_probs, log_q_cvp = propose_colors_and_visibility_probs( - k3, trace_with_pose + k3a, trace, inference_hyperparams + ) + trace = update_vmapped_fields( + k3b, trace, ["colors", "visibility_prob"], [colors, visibility_probs] ) log_q_cvp = 0.0 - depth_scale, log_q_ds = propose_depth_scale(k4, trace_with_pose) - color_scale, log_q_cs = propose_color_scale(k5, trace_with_pose) - proposed_trace = update_fields( - k6, - trace_with_pose, - [ - "depth_nonreturn_prob", - "colors", - "visibility_prob", - "depth_scale", - "color_scale", - ], - [depth_nonreturn_probs, colors, visibility_probs, depth_scale, color_scale], - ) - log_q = log_q_dnrps + log_q_cvp + log_q_ds + log_q_cs + k4a, k4b = split(k4) + depth_scale, log_q_ds = propose_depth_scale(k4a, trace) + trace = update_field(k4b, trace, "depth_scale", depth_scale) + + k5a, k5b = split(k5) + color_scale, log_q_cs = propose_color_scale(k5a, trace) + trace = update_field(k5b, trace, "color_scale", color_scale) - return proposed_trace, log_q + log_q = log_q_dnrps + log_q_cvp + log_q_ds + log_q_cs + return ( + trace, + log_q, + {"depth_nonreturn_proposal": dnrp_metadata, "dnrps": depth_nonreturn_probs}, + ) def propose_depth_nonreturn_probs(key, trace): @@ -86,7 +104,7 @@ def propose_depth_nonreturn_probs(key, trace): get_hypers(trace), get_new_state(trace)["pose"] ).get_point_depths(get_observed_rgbd(trace)) - depth_nonreturn_probs, per_vertex_log_qs = jax.vmap( + depth_nonreturn_probs, per_vertex_log_qs, metadata = jax.vmap( propose_vertex_depth_nonreturn_prob, in_axes=(0, 0, 0, None, None, None) )( split(key, get_n_vertices(trace)), @@ -97,10 +115,10 @@ def propose_depth_nonreturn_probs(key, trace): get_hypers(trace), ) - return depth_nonreturn_probs, per_vertex_log_qs.sum() + return depth_nonreturn_probs, per_vertex_log_qs.sum(), metadata -def propose_colors_and_visibility_probs(key, trace): +def propose_colors_and_visibility_probs(key, trace, inference_hyperparams): """ Propose a new color and visibility probability for every vertex, conditioned upon the other values in `trace`. @@ -114,7 +132,8 @@ def propose_colors_and_visibility_probs(key, trace): ).get_point_rgbds(get_observed_rgbd(trace)) colors, visibility_probs, per_vertex_log_qs = jax.vmap( - propose_vertex_color_and_visibility_prob, in_axes=(0, 0, 0, None, None, None) + propose_vertex_color_and_visibility_prob, + in_axes=(0, 0, 0, None, None, None, None), )( split(key, get_n_vertices(trace)), jnp.arange(get_n_vertices(trace)), @@ -122,6 +141,7 @@ def propose_colors_and_visibility_probs(key, trace): get_prev_state(trace), get_new_state(trace), get_hypers(trace), + inference_hyperparams, ) return colors, visibility_probs, per_vertex_log_qs.sum() @@ -136,35 +156,78 @@ def propose_vertex_depth_nonreturn_prob( Returns (depth_nonreturn_prob, log_q) where `depth_nonreturn_prob` is the proposed value and `log_q` is (a fair estimate of) the log proposal density. """ - - # TODO: could factor into a sub-function that just receives the values - # we pull out of the previous and new state here, if that facilitates - # unit testing. - previous_dnrp = previous_state["depth_nonreturn_prob"][vertex_index] visibility_prob = new_state["visibility_prob"][vertex_index] latent_depth = new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2] - depth_scale = new_state["depth_scale"] - obs_depth_kernel = hyperparams["image_kernel"].get_depth_vertex_kernel() + return _propose_vertex_depth_nonreturn_prob( + key, + observed_depth, + latent_depth, + visibility_prob, + new_state["depth_scale"], + previous_dnrp, + hyperparams["depth_nonreturn_prob_kernel"], + hyperparams["image_kernel"].get_depth_vertex_kernel(), + ) + +def _propose_vertex_depth_nonreturn_prob( + key, + observed_depth, + latent_depth, + visibility_prob, + depth_scale, + previous_dnrp, + dnrp_transition_kernel, + obs_depth_kernel, + return_metadata=True, +): def score_dnrp_value(dnrp_value): - transition_score = hyperparams["depth_nonreturn_prob_kernel"].logpdf( - dnrp_value, previous_dnrp - ) + transition_score = dnrp_transition_kernel.logpdf(dnrp_value, previous_dnrp) likelihood_score = obs_depth_kernel.logpdf( - observed_depth, latent_depth, visibility_prob, dnrp_value, depth_scale + observed_depth=observed_depth, + latent_depth=latent_depth, + depth_scale=depth_scale, + visibility_prob=visibility_prob, + depth_nonreturn_prob=dnrp_value, ) return transition_score + likelihood_score - support = hyperparams["depth_nonreturn_prob_kernel"].support + support = dnrp_transition_kernel.support log_pscores = jax.vmap(score_dnrp_value)(support) - log_normalized_scores = log_pscores - jax.scipy.special.logsumexp(log_pscores) + log_normalized_scores = normalize_log_scores(log_pscores) index = jax.random.categorical(key, log_normalized_scores) # ^ since we are enumerating over every value in the domain, it is unnecessary # to add a 1/q score when resampling. (Equivalently, we could include # q = 1/len(support), which does not change the resampling distribuiton at all.) - return support[index], log_normalized_scores[index] + if return_metadata: + metadata = { + "support": support, + "log_normalized_scores": log_normalized_scores, + "index": index, + "observed_depth": observed_depth, + "latent_depth": latent_depth, + "prev_dnrp": previous_dnrp, + "transition_score": jax.vmap( + lambda dnrp_value: dnrp_transition_kernel.logpdf( + dnrp_value, previous_dnrp + ) + )(support), + "likelihood_score": jax.vmap( + lambda dnrp_value: obs_depth_kernel.logpdf( + observed_depth, + latent_depth, + visibility_prob, + dnrp_value, + depth_scale, + ) + )(support), + } + else: + metadata = {} + + return support[index], log_normalized_scores[index], metadata def propose_vertex_color_and_visibility_prob( @@ -174,6 +237,7 @@ def propose_vertex_color_and_visibility_prob( previous_state, new_state, hyperparams, + inference_hyperparams, ): """ Propose a new color and visibility probability for the single vertex @@ -199,12 +263,12 @@ def score_visprob_rgb(visprob, rgb): hyperparams["image_kernel"] .get_rgbd_vertex_kernel() .logpdf( - observed_rgbd_for_this_vertex, - jnp.append(rgb, latent_depth), - new_state["color_scale"], - new_state["depth_scale"], - visprob, - new_state["depth_nonreturn_prob"][vertex_index], + observed_rgbd=observed_rgbd_for_this_vertex, + latent_rgbd=jnp.append(rgb, latent_depth), + rgb_scale=new_state["color_scale"], + depth_scale=new_state["depth_scale"], + visibility_prob=visprob, + depth_nonreturn_prob=new_state["depth_nonreturn_prob"][vertex_index], ) ) return rgb_transition_score + visprob_transition_score + likelihood_score @@ -231,7 +295,7 @@ def score_visprob_rgb(visprob, rgb): # we are enumerating over every value in the domain. (Equivalently, # we could subtract a log q score of log(1/len(support)) for each value.) log_weights = log_pscores - log_qs_rgb - log_normalized_scores = log_weights - jax.scipy.special.logsumexp(log_weights) + log_normalized_scores = normalize_log_scores(log_weights) index = jax.random.categorical(k2, log_normalized_scores) rgb = rgbs[index] @@ -288,21 +352,21 @@ def propose_vertex_color_given_visibility( (k1, k2, k3) = split(key, 3) ## Proposal 1: near the previous value. - min_rgbs1 = previous_rgb - diffs / 10 - 2 * d - max_rgbs1 = previous_rgb + diffs / 10 + 2 * d + min_rgbs1 = jnp.maximum(0.0, previous_rgb - diffs / 10 - 2 * d) + max_rgbs1 = jnp.minimum(1.0, previous_rgb + diffs / 10 + 2 * d) proposed_rgb_1 = uniform.sample(k1, min_rgbs1, max_rgbs1) log_q_rgb_1 = uniform.logpdf(proposed_rgb_1, min_rgbs1, max_rgbs1) ## Proposal 2: near the observed value. - min_rgbs2 = observed_rgb - diffs / 10 - 2 * d - max_rgbs2 = observed_rgb + diffs / 10 + 2 * d + min_rgbs2 = jnp.maximum(0.0, observed_rgb - diffs / 10 - 2 * d) + max_rgbs2 = jnp.minimum(1.0, observed_rgb + diffs / 10 + 2 * d) proposed_rgb_2 = uniform.sample(k2, min_rgbs2, max_rgbs2) log_q_rgb_2 = uniform.logpdf(proposed_rgb_2, min_rgbs2, max_rgbs2) ## Proposal 3: somewhere in the middle mean_rgb = (previous_rgb + observed_rgb) / 2 - min_rgbs3 = mean_rgb - 8 / 10 * diffs - 2 * d - max_rgbs3 = mean_rgb + 8 / 10 * diffs + 2 * d + min_rgbs3 = jnp.maximum(0.0, mean_rgb - 8 / 10 * diffs - 2 * d) + max_rgbs3 = jnp.minimum(1.0, mean_rgb + 8 / 10 * diffs + 2 * d) proposed_rgb_3 = uniform.sample(k3, min_rgbs3, max_rgbs3) log_q_rgb_3 = uniform.logpdf(proposed_rgb_3, min_rgbs3, max_rgbs3) @@ -315,13 +379,16 @@ def propose_vertex_color_given_visibility( jax.vmap(lambda rgb: score_visprob_and_rgb(visprob, rgb))(proposed_rgbs) - log_qs ) - normalized_scores = scores - jax.scipy.special.logsumexp(scores) + normalized_scores = normalize_log_scores(scores) sampled_index = jax.random.categorical(key, normalized_scores) sampled_rgb = proposed_rgbs[sampled_index] log_K_score = log_qs.sum() + normalized_scores[sampled_index] - ## "L proposal": given the sampled rgb, estimate the probability that - # it came from the one of the 3 proposals that actually was used. + ## "L proposal": given the sampled rgb, the L proposal proposes + # an index for which of the 3 proposals may have produced this sample RGB, + # and also proposes the other two RGB values. + # Here, we need to compute the logpdf of this L proposal having produced + # the values we sampled out of the K proposal. log_qs_for_this_rgb = jnp.array( [ uniform.logpdf(sampled_rgb, min_rgbs1, max_rgbs1), @@ -329,18 +396,19 @@ def propose_vertex_color_given_visibility( uniform.logpdf(sampled_rgb, min_rgbs3, max_rgbs3), ] ) - normalized_L_logprobs = log_qs_for_this_rgb - jax.scipy.special.logsumexp( - log_qs_for_this_rgb - ) + normalized_L_logprobs = normalize_log_scores(log_qs_for_this_rgb) # L score for proposing the index - log_L_score = normalized_L_logprobs[sampled_index] + log_L_score_for_index = normalized_L_logprobs[sampled_index] # Also add in the L score for proposing the other two RGB values. # The L proposal over these values will just generate them from their prior. - log_L_score += jnp.sum(log_qs) - log_qs[sampled_index] + log_L_score_for_unused_values = jnp.sum(log_qs) - log_qs[sampled_index] + + # full L score + log_L_score = log_L_score_for_index + log_L_score_for_unused_values - ## Compute the overall score. + ## Compute the overall estimate of the marginal density of proposing `sampled_rgb`. overall_score = log_K_score - log_L_score ## Return @@ -385,8 +453,38 @@ def update_fields(key, trace, fieldnames, values): trace, _, _, _ = trace.update( key, U.g( - (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), + (Diff.no_change(hyperparams), Diff.no_change(previous_state)), C.kw(**dict(zip(fieldnames, values))), ), ) return trace + + +def update_vmapped_fields(key, trace, fieldnames, values): + """ + For each `fieldname` in fieldnames, and each array `arr` in the + corresponding slot in `values`, updates `trace` at addresses + (0, fieldname) through (len(arr) - 1, fieldname) to the corresponding + values in `arr`. + (That is, this assumes for each fieldname, there is a vmap combinator + sampled at that address in the trace.) + """ + c = C.n() + for addr, val in zip(fieldnames, values): + c = c ^ jax.vmap(lambda idx: C[addr, idx].set(val[idx]))( + jnp.arange(val.shape[0]) + ) + + hyperparams, previous_state = trace.get_args() + trace, _, _, _ = trace.update( + key, + U.g((Diff.no_change(hyperparams), Diff.no_change(previous_state)), c), + ) + return trace + + +def update_vmapped_field(key, trace, fieldname, value): + """ + For information, see `update_vmapped_fields`. + """ + return update_vmapped_fields(key, trace, [fieldname], [value]) diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index 09e00947..e2b011c9 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -56,6 +56,7 @@ def from_points_and_intrinsics( intrinsics["cx"], intrinsics["cy"], ) + - 0.5 ) # handle NaN before converting to int (otherwise NaN will be converted # to 0) diff --git a/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py b/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py new file mode 100644 index 00000000..4af3e1db --- /dev/null +++ b/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py @@ -0,0 +1,32 @@ +import b3d.chisight.gen3d.inference_moves as im +import b3d.chisight.gen3d.transition_kernels as transition_kernels +import jax +import jax.numpy as jnp +import jax.random as r +from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( + FullPixelDepthDistribution, +) + +near, far = 0.001, 1.0 + +dnrp_transition_kernel = transition_kernels.DiscreteFlipKernel( + resample_probability=0.05, support=jnp.array([0.01, 0.99]) +) + + +def propose_val(k): + return im._propose_vertex_depth_nonreturn_prob( + k, + observed_depth=0.8, + latent_depth=1.0, + visibility_prob=1.0, + depth_scale=0.00001, + previous_dnrp=0.01, + dnrp_transition_kernel=dnrp_transition_kernel, + obs_depth_kernel=FullPixelDepthDistribution(near, far), + ) + + +values, log_qs, _ = jax.vmap(propose_val)(r.split(r.PRNGKey(0), 1000)) +n_01 = jnp.sum((values == 0.01).astype(jnp.int32)) +assert n_01 >= 950 From 99bef1a1474c564730f532a0693d51f3798afe3c Mon Sep 17 00:00:00 2001 From: georgematheos Date: Tue, 10 Sep 2024 18:40:49 -0400 Subject: [PATCH 06/37] Add depth and color scale proposals (#157) --- notebooks/bayes3d_paper/tester.ipynb | 89 ++++++++++++-------- src/b3d/chisight/gen3d/inference.py | 20 ++++- src/b3d/chisight/gen3d/inference_moves.py | 40 +++++++-- src/b3d/chisight/gen3d/model.py | 3 + src/b3d/chisight/gen3d/transition_kernels.py | 2 +- 5 files changed, 110 insertions(+), 44 deletions(-) diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 0c9560c0..eb787fa9 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -56,7 +56,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 12.99it/s]\n", + "100%|██████████| 49/49 [00:03<00:00, 13.18it/s]\n", "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", " warnings.warn(\n" @@ -179,9 +179,24 @@ "metadata": {}, "outputs": [], "source": [ + "color_transiton_scale = 0.001\n", + "p_resample_color = 0.005\n", + "\n", + "# This parameter is needed for the inference hyperparameters.\n", + "# See the `InferenceHyperparams` docstring in `inference.py` for details.\n", + "effective_color_transition_scale = color_transiton_scale + p_resample_color * 1/2\n", + "\n", "hyperparams = {\n", " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", - " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.15),\n", + " \"color_kernel\": transition_kernels.MixtureDriftKernel(\n", + " [\n", + " transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=color_transiton_scale),\n", + " transition_kernels.UniformDriftKernel(\n", + " max_shift=0.15, min_val=jnp.zeros(3), max_val=jnp.ones(3)\n", + " )\n", + " ],\n", + " jnp.array([1-p_resample_color, p_resample_color])\n", + " ),\n", " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", " ),\n", @@ -189,10 +204,10 @@ " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", " ),\n", " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02])\n", + " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02, .1, .4, 1.])\n", " ),\n", " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.05, 0.1, 0.15])\n", + " resample_probability=0.05, support=jnp.array([0.05, 0.1, 0.15, .3, .8])\n", " ),\n", "\n", " \"image_kernel\": img_model,\n", @@ -213,12 +228,7 @@ "metadata": {}, "outputs": [], "source": [ - "from b3d.chisight.gen3d.inference import InferenceHyperparams\n", - "inference_hyperparams = InferenceHyperparams(\n", - " n_poses=100,\n", - " pose_proposal_std=0.04,\n", - " pose_proposal_conc=1000.,\n", - ")" + "from b3d.chisight.gen3d.inference import InferenceHyperparams" ] }, { @@ -263,13 +273,13 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
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" ], "text/plain": [ "" @@ -342,10 +352,10 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ - "" + "" ] }, "execution_count": 14, @@ -359,7 +369,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -371,13 +381,13 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
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" ], "text/plain": [ "" @@ -401,13 +411,13 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ - "" + "" ] }, - "execution_count": 31, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -417,10 +427,10 @@ " n_poses=6000,\n", " pose_proposal_std=0.04,\n", " pose_proposal_conc=1000.,\n", - " color_proposal_params=None\n", + " effective_color_transition_scale=effective_color_transition_scale\n", ")\n", "\n", - "stepped_trace, step_weight, metadata = i.inference_step(\n", + "trace, step_weight, metadata = i.inference_step(\n", " jax.random.PRNGKey(21),\n", " trace,\n", " all_data[0][\"rgbd\"],\n", @@ -431,24 +441,31 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "T = 0\n", - "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" + "b3d.chisight.gen3d.model.viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:59<00:00, 1.21s/it]\n" + " 0%| | 0/49 [00:00 ArrayLike: return self._base_dist(prev_value).sample(seed=key) def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: - return self._base_dist(prev_value).log_prob(new_value) + return self._base_dist(prev_value).log_prob(new_value).sum() def _base_dist(self, prev_value: ArrayLike): """Returns a uniform distribution centered around prev_value, bounded by From 900f227f917d096915889a848ff36a8531216cbb Mon Sep 17 00:00:00 2001 From: George Matheos Date: Tue, 10 Sep 2024 22:46:07 +0000 Subject: [PATCH 07/37] improve docstring --- src/b3d/chisight/gen3d/inference_moves.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index 7c5be2cf..3e284bac 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -321,19 +321,22 @@ def propose_vertex_color_given_visibility( as in SMCP3 or RAVI. Returns (sampled_rgb, log_q_score). - Specifically, this proposes 3 RGB values: + Specifically, this proposal works by proposing 3 RGB values: - One from a tight uniform around previous_rgb - One from a tight uniform around observed_rgb - One from a potentially broader uniform around the midpoint of the two. - One of these 3 RGB values is then resampled. + Then, one of these 3 RGB values is resampled and return. - This creates a "forward" ("K") proposal, which has sampled (1) the chosen RGB value, + This process is a "forward" ("K") proposal, which has sampled (1) the chosen RGB value, (2) the index amoung [0, 1, 2] for which of the 3 proposals generated it, and (3) two additional RGB values. We then imagine having an "L" proposal which, given (1), proposes (2) and (3). - To estimate the probability of having proposed (1) alone, we return log_K - log_L. + To estimate the _marginal_ probability of K having proposed (1), marginalizing + over the choice of (2) and (3), we can return the value log_K - log_L + (where these terms are the log densities of the K and L proposals, respectively, + evaluated at the values we sampled out of the K proposal). One remaining TODO: this proposal has no probability of generating a value that is far outside the range of the previous and observed values. This means we technically do not have absolute continuity. From 6639183b87d1b3e3c91c25b65ac965e8ceaba937 Mon Sep 17 00:00:00 2001 From: Xiaoyan Wang Date: Wed, 11 Sep 2024 04:23:35 -0400 Subject: [PATCH 08/37] PixelRGBDDistribution: Additional tests on invalid RGBD values (#159) This PR includes some additional tests to make sure the behavior of the `logpdf` method is what we expect when it receives invalid RGBD values (`[-1., -1., -1., -1.]`). Since the distribution is defined on the pixel level, it doesn't really expect the observed RGBD to be invalid, so when we use it to vmap over vertices, we need to handle the case where a vertex does not hit the image plane manually. I'm also updating the image kernel slightly to make sure that we can handle those corner cases. (note that this is different from the case where a pixel does not have an associated vertex, which can be handle natively in the pixel distribution) # Test Plan ```bash pytest tests/gen3d/test_pixel_rgbd_kernels.py ``` --- src/b3d/chisight/gen3d/image_kernel.py | 14 +++-- src/b3d/chisight/gen3d/inference.py | 51 +++++++++---------- src/b3d/chisight/gen3d/inference_moves.py | 2 +- .../chisight/gen3d/pixel_kernels/__init__.py | 4 ++ .../gen3d/pixel_kernels/pixel_rgbd_kernels.py | 27 +++++----- src/b3d/chisight/gen3d/projection.py | 6 +-- src/b3d/chisight/gen3d/transition_kernels.py | 11 ++-- tests/gen3d/test_pixel_rgbd_kernels.py | 44 +++++++++++++--- 8 files changed, 97 insertions(+), 62 deletions(-) diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index e92cdc93..6cea373a 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -12,6 +12,7 @@ FullPixelDepthDistribution, PixelDepthDistribution, PixelRGBDDistribution, + is_unexplained, ) from b3d.chisight.gen3d.projection import PixelsPointsAssociation @@ -79,9 +80,7 @@ def logpdf( transformed_points, hyperparams ) vertex_kernel = self.get_rgbd_vertex_kernel() - observed_rgbd_per_point = observed_rgbd.at[ - points_to_pixels.x, points_to_pixels.y - ].get(mode="drop", fill_value=-1.0) + observed_rgbd_per_point = points_to_pixels.get_point_rgbds(observed_rgbd) latent_rgbd_per_point = jnp.concatenate( (state["colors"], transformed_points[..., 2, None]), axis=-1 ) @@ -94,11 +93,18 @@ def logpdf( state["visibility_prob"], state["depth_nonreturn_prob"], ) + # the pixel kernel does not expect invalid observed_rgbd and will return + # -inf if it is invalid. We need to filter those out here. + # (invalid rgbd could happen when the vertex is projected out of the image) + scores = jnp.where(is_unexplained(observed_rgbd_per_point), 0.0, scores) + return scores.sum() def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: # Note: The distributions were originally defined for per-pixel computation, - # but they should work for per-vertex computation as well + # but they should work for per-vertex computation as well, except that + # they don't expect observed_rgbd to be invalid, so we need to handle + # that manually. return PixelRGBDDistribution( FullPixelColorDistribution(), FullPixelDepthDistribution(self.near, self.far), diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 1c256ea7..6c5c59d5 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -1,5 +1,5 @@ -from collections import namedtuple -from functools import partial +from functools import partial, wraps +from typing import NamedTuple import jax import jax.numpy as jnp @@ -9,38 +9,36 @@ from genjax import UpdateProblemBuilder as U from jax.random import split -from .inference_moves import ( +from b3d.chisight.gen3d.inference_moves import ( propose_other_latents_given_pose, propose_pose, ) -from .model import ( +from b3d.chisight.gen3d.model import ( get_hypers, get_prev_state, ) + # Use namedtuple rather than dict so we can hash this, and use it as a static arg to a jitted function. -InferenceHyperparams = namedtuple( - "InferenceHyperparams", - [ - "n_poses", - "pose_proposal_std", - "pose_proposal_conc", - "effective_color_transition_scale", - ], -) -""" -Parameters for the inference algorithm. -- n_poses: Number of poses to propose at each timestep. -- pose_proposal_std: Standard deviation of the position distribution for the pose. -- pose_proposal_conc: Concentration parameter for the orientation distribution for the pose. -- effective_color_transition_scale: This parameter is used in the color proposal. - When the color transition kernel is a laplace, this should be its scale. - When the color transition kernel is a different distribution, set this to something - that would make a laplace transition kernel propose with a somewhat similar spread - to the kernel you are using. (This parameter is used to decide - the size of the proposal in the color proposal, using a simple analysis - we conducted in the laplace case.) -""" +class InferenceHyperparams(NamedTuple): + """ + Parameters for the inference algorithm. + - n_poses: Number of poses to propose at each timestep. + - pose_proposal_std: Standard deviation of the position distribution for the pose. + - pose_proposal_conc: Concentration parameter for the orientation distribution for the pose. + - effective_color_transition_scale: This parameter is used in the color proposal. + When the color transition kernel is a laplace, this should be its scale. + When the color transition kernel is a different distribution, set this to something + that would make a laplace transition kernel propose with a somewhat similar spread + to the kernel you are using. (This parameter is used to decide + the size of the proposal in the color proposal, using a simple analysis + we conducted in the laplace case.) + """ + + n_poses: int + pose_proposal_std: float + pose_proposal_conc: float + effective_color_transition_scale: float @jax.jit @@ -108,6 +106,7 @@ def inference_step(key, old_trace, observed_rgbd, inference_hyperparams): ) +@wraps(inference_step) def inference_step_noweight(*args): """ Same as inference_step, but only returns the new trace diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index 3e284bac..e77e6772 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -265,7 +265,7 @@ def score_visprob_rgb(visprob, rgb): .logpdf( observed_rgbd=observed_rgbd_for_this_vertex, latent_rgbd=jnp.append(rgb, latent_depth), - rgb_scale=new_state["color_scale"], + color_scale=new_state["color_scale"], depth_scale=new_state["depth_scale"], visibility_prob=visprob, depth_nonreturn_prob=new_state["depth_nonreturn_prob"][vertex_index], diff --git a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py b/src/b3d/chisight/gen3d/pixel_kernels/__init__.py index 471cf3aa..401b95b7 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/__init__.py @@ -2,8 +2,10 @@ FullPixelColorDistribution, MixturePixelColorDistribution, PixelColorDistribution, + is_unexplained, ) from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( + DEPTH_NONRETURN_VAL, FullPixelDepthDistribution, MixturePixelDepthDistribution, PixelDepthDistribution, @@ -12,6 +14,8 @@ from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import PixelRGBDDistribution __all__ = [ + "is_unexplained", + "DEPTH_NONRETURN_VAL", "FullPixelColorDistribution", "FullPixelDepthDistribution", "MixturePixelColorDistribution", diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py index 026e613e..af0f0506 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py @@ -12,15 +12,16 @@ class PixelRGBDDistribution(genjax.ExactDensity): """ Distribution args: - - latent_rgbd: 4-array: RGBD value. (Should be [-1, -1, -1, -1] to indicate no point hits here.) - - rgb_scale: float + - latent_rgbd: 4-array: RGBD value. (a value of [-1, -1, -1, -1] indicates no point hits here.) + - color_scale: float - depth_scale: float - visibility_prob: float - depth_nonreturn_prob: float The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). - If the logpdf of [-1, -1, -1, -1] is requested, this will return 0.0. + Note that this distribution expects the observed_rgbd to be valid. If an invalid + pixel is observed, the logpdf will return -inf. """ color_kernel: PixelColorDistribution @@ -30,14 +31,14 @@ def sample( self, key: PRNGKey, latent_rgbd: FloatArray, - rgb_scale, - depth_scale, - visibility_prob, - depth_nonreturn_prob, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, ) -> FloatArray: keys = jax.random.split(key, 2) observed_color = self.color_kernel.sample( - keys[0], latent_rgbd[:3], rgb_scale, visibility_prob + keys[0], latent_rgbd[:3], color_scale, visibility_prob ) observed_depth = self.depth_kernel.sample( keys[1], latent_rgbd[3], depth_scale, visibility_prob, depth_nonreturn_prob @@ -48,13 +49,13 @@ def logpdf( self, observed_rgbd: FloatArray, latent_rgbd: FloatArray, - rgb_scale, - depth_scale, - visibility_prob, - depth_nonreturn_prob, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, ) -> float: color_logpdf = self.color_kernel.logpdf( - observed_rgbd[:3], latent_rgbd[:3], rgb_scale, visibility_prob + observed_rgbd[:3], latent_rgbd[:3], color_scale, visibility_prob ) depth_logpdf = self.depth_kernel.logpdf( observed_rgbd[3], diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index e2b011c9..c8fbf696 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -94,11 +94,7 @@ def get_point_rgbds(self, rgbd_image: FloatArray) -> FloatArray: by indexing into the given image. Vertices that don't hit a pixel will have a value of (-1, -1, -1, -1). """ - unfiltered = rgbd_image[self.x, self.y] - invalid_indices = jnp.logical_or(self.x == INVALID_IDX, self.y == INVALID_IDX) - return jnp.where( - invalid_indices[:, None], -jnp.ones_like(unfiltered), unfiltered - ) + return rgbd_image.at[self.x, self.y].get(mode="drop", fill_value=-1.0) def get_point_depths(self, rgbd_image: FloatArray) -> FloatArray: """ diff --git a/src/b3d/chisight/gen3d/transition_kernels.py b/src/b3d/chisight/gen3d/transition_kernels.py index 69d96953..08dbf88f 100644 --- a/src/b3d/chisight/gen3d/transition_kernels.py +++ b/src/b3d/chisight/gen3d/transition_kernels.py @@ -224,7 +224,7 @@ class LaplaceColorDriftKernel(DriftKernel): This is a thin wrapper around the truncated_color_laplace distribution to provide a consistent interface with other drift kernels. - Support: [0.0, 1.0] + Support: [0.0, 1.0]^3 """ scale: float = Pytree.static() @@ -244,16 +244,13 @@ def logpdf(self, new_value: ArrayLike, prev_value: ArrayLike) -> ArrayLike: @Pytree.dataclass class LaplaceNotTruncatedColorDriftKernel(DriftKernel): """A drift kernel that samples the 3 channels of the color from a specialized - truncated Laplace distribution, centered at the previous color. Values outside - of the bounds will be resampled from a small uniform window at the boundary. - This is a thin wrapper around the truncated_color_laplace distribution to - provide a consistent interface with other drift kernels. + truncated Laplace distribution, centered at the previous color. Values may + go outside of the valid color range ([0.0, 1.0]^3). - Support: [0.0, 1.0] + Support: [-inf, inf]^3 """ scale: float = Pytree.static() - uniform_window_size: float = Pytree.static(default=_FIXED_COLOR_UNIFORM_WINDOW) def sample(self, key: PRNGKey, prev_value: ArrayLike) -> ArrayLike: return genjax.laplace.sample(key, prev_value, self.scale) diff --git a/tests/gen3d/test_pixel_rgbd_kernels.py b/tests/gen3d/test_pixel_rgbd_kernels.py index 33a1e44f..704e623a 100644 --- a/tests/gen3d/test_pixel_rgbd_kernels.py +++ b/tests/gen3d/test_pixel_rgbd_kernels.py @@ -1,14 +1,12 @@ import jax import jax.numpy as jnp import pytest -from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( - FullPixelColorDistribution, -) -from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( +from b3d.chisight.gen3d.pixel_kernels import ( DEPTH_NONRETURN_VAL, + FullPixelColorDistribution, FullPixelDepthDistribution, + PixelRGBDDistribution, ) -from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import PixelRGBDDistribution near = 0.01 far = 20.0 @@ -20,7 +18,7 @@ FullPixelDepthDistribution(near, far), ), ( - 0.01, # rgb_scale + 0.01, # color_scale 0.01, # depth_scale 1 - 0.3, # visibility_prob 0.1, # depth_nonreturn_prob @@ -92,3 +90,37 @@ def test_relative_logpdf(kernel_spec): assert logpdf_5 > logpdf_6 # the score of the pixel should be higher when the rgbd is closer assert logpdf_5 > logpdf_3 + + +@pytest.mark.parametrize("kernel_spec", sample_kernels_to_test) +def test_invalid_pixel(kernel_spec): + kernel, additional_args = kernel_spec + + # Latent value of [-1, -1, -1, -1] indicates no point hits here. + latent_rgbd = -jnp.ones(4) + logpdf_1 = kernel.logpdf( + jnp.array([1.0, 0.5, 0.2, 4.0]), latent_rgbd, *additional_args + ) + logpdf_2 = kernel.logpdf( + jnp.array([0.0, 0.0, 0.0, 0.02]), latent_rgbd, *additional_args + ) + # the observation does not affect the logpdf + assert logpdf_1 == logpdf_2 + + logpdf_3 = kernel.logpdf( + jnp.array([1.0, 0.5, 0.2, 4.0]), latent_rgbd, 0.1, 0.4, 0.2, 0.1 + ) + logpdf_4 = kernel.logpdf( + jnp.array([0.0, 0.0, 0.0, 0.02]), latent_rgbd, 0.3, 0.5, 0.4, 0.2 + ) + # and the values of the parameters doesn't matter either + assert logpdf_2 == logpdf_3 + assert logpdf_3 == logpdf_4 + + # IMPORTANT: note that, by designed, every pixel should have a valid color, + # and an observation of [-1, -1, -1, -1] is actually not within the support + # of the pixel distribution. + logpdf_5 = kernel.logpdf( + jnp.array([-1.0, -1.0, -1.0, -1.0]), latent_rgbd, *additional_args + ) + assert logpdf_5 == -jnp.inf From 36d5fabdb490c9257f5c67181f242e4c1136c96c Mon Sep 17 00:00:00 2001 From: Xiaoyan Wang Date: Wed, 11 Sep 2024 04:54:57 -0400 Subject: [PATCH 09/37] Implement `.sample()` on `NoOcclusionPerVertexImageKernel` (#160) Disclaimer: I've tested this out in the scratch section of the `tester.ipynb` notebook, but I haven't got the time to write the unit tests for the image kernel or the projection stuff yet. The `sample()` method let us sample RGBD image like this now, which might be useful for debugging purpose: ![image](https://github.com/user-attachments/assets/2379f191-7f4f-485e-aa1c-f610d9b2147e) (note that the sampled depth looks really dark on the actual object itself because our far is set to be very large, so uniform(near, far) can results in depth values much larger than the depth of the object) --- notebooks/bayes3d_paper/tester.ipynb | 279 +++++++++++++------------ src/b3d/chisight/gen3d/image_kernel.py | 37 +++- src/b3d/chisight/gen3d/projection.py | 11 +- 3 files changed, 192 insertions(+), 135 deletions(-) diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index eb787fa9..73396def 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -2,31 +2,33 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "import b3d\n", - "import jax.numpy as jnp\n", - "import os\n", - "from tqdm import tqdm\n", - "from b3d import Mesh, Pose\n", - "import matplotlib.pyplot as plt" + "%load_ext autoreload\n", + "%autoreload 2" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ + "import b3d\n", + "import jax.numpy as jnp\n", + "import os\n", + "from tqdm import tqdm\n", + "from b3d import Mesh, Pose\n", + "import matplotlib.pyplot as plt\n", "import genjax\n", - "genjax.pretty()" + "# genjax.pretty()" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -35,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -49,17 +51,7 @@ "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/49 [00:00" ] }, - "execution_count": 4, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -105,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -133,7 +125,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -142,7 +134,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -164,7 +156,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 85, "metadata": {}, "outputs": [], "source": [ @@ -175,7 +167,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -224,7 +216,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -233,7 +225,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -252,7 +244,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -273,43 +265,16 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 23, "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 16, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "inference_hyperparams = i.InferenceHyperparams(\n", + "inference_hyperparams = InferenceHyperparams(\n", " n_poses=6000,\n", " pose_proposal_std=0.04,\n", " pose_proposal_conc=1000.,\n", @@ -441,7 +352,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -451,7 +362,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -465,7 +376,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [01:11<00:00, 1.47s/it]\n" + "100%|██████████| 49/49 [01:16<00:00, 1.56s/it]\n" ] } ], @@ -503,17 +414,121 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 68, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "transformed_points = transformed_points = previous_state[\"pose\"].apply(hyperparams[\"vertices\"])\n", + "points_to_pixels = img_model.get_pixels_points_association(transformed_points, hyperparams)" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 69, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "pixel_to_point_idx = points_to_pixels.pixel_to_point_idx" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# setting invalid pixel to a value that's closer to valid pixel so the color\n", + "# map doesn't get stretched too much\n", + "plt.imshow(jnp.where(pixel_to_point_idx < 0, -1, pixel_to_point_idx))" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1\n", + "(Array([], shape=(0,), dtype=int32), Array([], shape=(0,), dtype=int32))\n" + ] + } + ], + "source": [ + "num_point_per_pixel = points_to_pixels.num_point_per_pixel\n", + "\n", + "# plt.imshow(num_point_per_pixel)\n", + "print(jnp.max(num_point_per_pixel))\n", + "# at the current frame there's no projection conflicts\n", + "print(points_to_pixels.get_pixels_with_multiple_points())" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(480, 640, 4)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sampled_rgbd = img_model.sample(key, previous_state, hyperparams)\n", + "\n", + "print(sampled_rgbd.shape)\n", + "plt.figure(figsize=(13, 5))\n", + "plt.subplot(1, 3, 1)\n", + "plt.axis(\"off\")\n", + "plt.title(\"Sampled RGB\")\n", + "plt.imshow(sampled_rgbd[..., :3])\n", + "plt.subplot(1, 3, 2)\n", + "plt.axis(\"off\")\n", + "plt.title(\"Sampled Depth\")\n", + "plt.imshow(sampled_rgbd[..., 3])\n", + "plt.subplot(1, 3, 3)\n", + "plt.axis(\"off\")\n", + "plt.title(\"Observed RGB\")\n", + "plt.imshow(choicemap[\"rgbd\"][..., :3]);" + ] }, { "cell_type": "code", @@ -524,7 +539,7 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 92, "metadata": {}, "outputs": [ { @@ -1785,7 +1800,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.5" + "version": "3.11.9" } }, "nbformat": 4, diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index 6cea373a..58ff5c29 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -69,8 +69,41 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr """Generate latent RGBD image by projecting the vertices directly to the image plane, without checking for occlusions. """ - # TODO: to be finished... - return jnp.zeros((self.image_height, self.image_width, 4)) + transformed_points = state["pose"].apply(hyperparams["vertices"]) + points_to_pixels = self.get_pixels_points_association( + transformed_points, hyperparams + ) + vertex_kernel = self.get_rgbd_vertex_kernel() + + # assuming that at most one vertex hit the pixel, we can convert the + # per-vertex attributes into per-pixel attributes, then vmap the + # RGBD pixel kernel over the pixels to generate the image. + pixel_visibility_prob = points_to_pixels.get_pixel_attributes( + state["visibility_prob"] + ) + pixel_depth_nonreturn_prob = points_to_pixels.get_pixel_attributes( + state["depth_nonreturn_prob"] + ) + pixel_latent_rgbd = points_to_pixels.get_pixel_attributes(state["colors"]) + pixel_latent_depth = points_to_pixels.get_pixel_attributes( + transformed_points[..., 2] + ) + pixel_latent_rgbd = jnp.concatenate( + [pixel_latent_rgbd, pixel_latent_depth[..., None]], axis=-1 + ) + + keys = jax.random.split(key, (self.image_height, self.image_width)) + return jax.vmap( + jax.vmap(vertex_kernel.sample, in_axes=(0, 0, None, None, 0, 0)), + in_axes=(0, 0, None, None, 0, 0), + )( + keys, + pixel_latent_rgbd, + state["color_scale"], + state["depth_scale"], + pixel_visibility_prob, + pixel_depth_nonreturn_prob, + ) def logpdf( self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index c8fbf696..7899316f 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -88,6 +88,15 @@ def x(self) -> IntArray: def y(self) -> IntArray: return self.projected_pixel_coordinates[:, 1] + def get_pixel_attributes(self, point_attributes: FloatArray) -> FloatArray: + """Given a (num_vertices, attribute_length) array of point attributes, + return a (image_height, image_width, attribute_length) array of attributes. + Pixels that don't hit a vertex will have a value filled with -1. + """ + return point_attributes.at[self.pixel_to_point_idx].get( + mode="drop", fill_value=-1 + ) + def get_point_rgbds(self, rgbd_image: FloatArray) -> FloatArray: """ Get a (num_vertices, 4) array of RGBD values for each vertex @@ -140,7 +149,7 @@ def pixel_to_point_idx(self) -> IntArray: def get_pixel_idx(self, point_idx: int) -> IntArray: return self.projected_pixel_coordinates[point_idx] - def pixels_with_multiple_points(self) -> tuple[IntArray, IntArray]: + def get_pixels_with_multiple_points(self) -> tuple[IntArray, IntArray]: """Return a tuple of (x_coords, y_coords) of pixels that have more than one vertices associated with them. Note that this method is not JIT-compatible because the return values are not of fixed shape. From ac49e9384e4ef2c2e040d5e38dd20234665fecad Mon Sep 17 00:00:00 2001 From: georgematheos Date: Wed, 11 Sep 2024 17:15:12 -0400 Subject: [PATCH 10/37] Add renormalized laplace and gaussian distribution and kernels (#162) --- .../pixel_kernels/pixel_color_kernels.py | 56 +++++++++++++++++ .../pixel_kernels/pixel_depth_kernels.py | 61 +++++++++++++++++++ src/b3d/modeling_utils.py | 35 +++++++++++ tests/gen3d/test_pixel_color_kernels.py | 8 ++- tests/gen3d/test_pixel_depth_kernels.py | 8 ++- 5 files changed, 164 insertions(+), 4 deletions(-) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py index 867f84d5..7c7f7a9b 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py @@ -6,11 +6,13 @@ import jax.numpy as jnp from genjax import Pytree from genjax.typing import FloatArray, PRNGKey +from jax.random import split from tensorflow_probability.substrates import jax as tfp from b3d.modeling_utils import ( _FIXED_COLOR_UNIFORM_WINDOW, PythonMixtureDistribution, + renormalized_laplace, truncated_laplace, ) @@ -73,6 +75,60 @@ def logpdf_per_channel( raise NotImplementedError +@Pytree.dataclass +class RenormalizedGaussianPixelColorDistribution(PixelColorDistribution): + """ + Sample a color from a renormalized Gaussian distribution centered around the given + latent_color (rgb value), given the color_scale (stddev of the Gaussian). + + The support of the distribution is ([0, 1]^3). + """ + + def sample(self, key, latent_color, color_scale, *args, **kwargs): + return jax.vmap( + genjax.truncated_normal.sample, in_axes=(0, 0, None, None, None) + )( + split(key, latent_color.shape[0]), + latent_color, + color_scale, + COLOR_MIN_VAL, + COLOR_MAX_VAL, + ) + + def logpdf_per_channel( + self, observed_color, latent_color, color_scale, *args, **kwargs + ): + return jax.vmap( + genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None) + )(observed_color, latent_color, color_scale, COLOR_MIN_VAL, COLOR_MAX_VAL) + + +@Pytree.dataclass +class RenormalizedLaplacePixelColorDistribution(PixelColorDistribution): + """ + Sample a color from a renormalized Laplace distribution centered around the given + latent_color (rgb value), given the color_scale (scale of the laplace). + + The support of the distribution is ([0, 1]^3). + """ + + def sample(self, key, latent_color, color_scale, *args, **kwargs): + return jax.vmap(renormalized_laplace.sample, in_axes=(0, 0, None, None, None))( + split(key, latent_color.shape[0]), + latent_color, + color_scale, + COLOR_MIN_VAL, + COLOR_MAX_VAL, + ) + + def logpdf_per_channel( + self, observed_color, latent_color, color_scale, *args, **kwargs + ): + return jax.vmap(renormalized_laplace.logpdf, in_axes=(0, 0, None, None, None))( + observed_color, latent_color, color_scale, COLOR_MIN_VAL, COLOR_MAX_VAL + ) + + @Pytree.dataclass class TruncatedLaplacePixelColorDistribution(PixelColorDistribution): """A distribution that generates the color of a pixel from a truncated diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py index 186e9931..9d4e4adf 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py @@ -12,6 +12,7 @@ from b3d.modeling_utils import ( _FIXED_DEPTH_UNIFORM_WINDOW, PythonMixtureDistribution, + renormalized_laplace, truncated_laplace, ) @@ -47,6 +48,66 @@ def logpdf( raise NotImplementedError +@Pytree.dataclass +class RenormalizedGaussianPixelDepthDistribution(PixelDepthDistribution): + """A distribution that generates the depth of a pixel from a Gaussian + distribution centered around the latent depth, with the spread controlled + by depth_scale. The support of the distribution is [near, far]. + """ + + near: float = Pytree.static() + far: float = Pytree.static() + + def sample( + self, key: PRNGKey, latent_depth: float, depth_scale: float, *args, **kwargs + ) -> float: + return genjax.truncated_normal.sample( + key, latent_depth, depth_scale, self.near, self.far + ) + + def logpdf( + self, + observed_depth: float, + latent_depth: float, + depth_scale: float, + *args, + **kwargs, + ) -> float: + return genjax.truncated_normal.logpdf( + observed_depth, latent_depth, depth_scale, self.near, self.far + ) + + +@Pytree.dataclass +class RenormalizedLaplacePixelDepthDistribution(PixelDepthDistribution): + """A distribution that generates the depth of a pixel from a Laplace + distribution centered around the latent depth, with the spread controlled + by depth_scale. The support of the distribution is [near, far]. + """ + + near: float = Pytree.static() + far: float = Pytree.static() + + def sample( + self, key: PRNGKey, latent_depth: float, depth_scale: float, *args, **kwargs + ) -> float: + return renormalized_laplace.sample( + key, latent_depth, depth_scale, self.near, self.far + ) + + def logpdf( + self, + observed_depth: float, + latent_depth: float, + depth_scale: float, + *args, + **kwargs, + ) -> float: + return renormalized_laplace.logpdf( + observed_depth, latent_depth, depth_scale, self.near, self.far + ) + + @Pytree.dataclass class TruncatedLaplacePixelDepthDistribution(PixelDepthDistribution): """A distribution that generates the depth of a pixel from a truncated diff --git a/src/b3d/modeling_utils.py b/src/b3d/modeling_utils.py index e10431f4..e2d9c0e5 100644 --- a/src/b3d/modeling_utils.py +++ b/src/b3d/modeling_utils.py @@ -1,3 +1,5 @@ +import warnings + import genjax import jax import jax.numpy as jnp @@ -74,6 +76,39 @@ def logpdf(v, *args, **kwargs): bernoulli = tfp_distribution(lambda logits: tfp.distributions.Bernoulli(logits=logits)) normal = tfp_distribution(tfp.distributions.Normal) + +### + + +@Pytree.dataclass +class RenormalizedLaplace(genjax.ExactDensity): + def sample(self, key, loc, scale, low, high): + warnings.warn( + "RenormalizedLaplace sampling is currently not implemented correctly." + ) + x = tfp.distributions.Laplace(loc, scale).sample(seed=key) + return jnp.clip(x, low, high) + + def logpdf(self, obs, loc, scale, low, high): + laplace_logpdf = tfp.distributions.Laplace(loc, scale).log_prob(obs) + p_below_low = tfp.distributions.Laplace(loc, scale).cdf(low) + p_below_high = tfp.distributions.Laplace(loc, scale).cdf(high) + log_integral_of_laplace_pdf_within_this_range = jnp.log( + p_below_high - p_below_low + ) + logpdf_if_in_range = ( + laplace_logpdf - log_integral_of_laplace_pdf_within_this_range + ) + + return jnp.where( + jnp.logical_and(obs >= low, obs <= high), + logpdf_if_in_range, + -jnp.inf, + ) + + +renormalized_laplace = RenormalizedLaplace() + ### Mixture distribution combinator ### diff --git a/tests/gen3d/test_pixel_color_kernels.py b/tests/gen3d/test_pixel_color_kernels.py index e861b4b8..10505756 100644 --- a/tests/gen3d/test_pixel_color_kernels.py +++ b/tests/gen3d/test_pixel_color_kernels.py @@ -8,6 +8,8 @@ COLOR_MIN_VAL, FullPixelColorDistribution, MixturePixelColorDistribution, + RenormalizedGaussianPixelColorDistribution, + RenormalizedLaplacePixelColorDistribution, TruncatedLaplacePixelColorDistribution, UniformPixelColorDistribution, ) @@ -36,6 +38,8 @@ def generate_color_grid(n_grid_steps: int): sample_kernels_to_test = [ (UniformPixelColorDistribution(), ()), (TruncatedLaplacePixelColorDistribution(), (0.1,)), + (RenormalizedLaplacePixelColorDistribution(), (0.1,)), + (RenormalizedGaussianPixelColorDistribution(), (0.1,)), ( MixturePixelColorDistribution(), ( @@ -80,8 +84,8 @@ def test_sample_in_valid_color_range(kernel_spec, latent_color): keys ) assert colors.shape == (num_samples, 3) - assert jnp.all(colors > 0) - assert jnp.all(colors < 1) + assert jnp.all(colors >= 0) + assert jnp.all(colors <= 1) def test_relative_logpdf(): diff --git a/tests/gen3d/test_pixel_depth_kernels.py b/tests/gen3d/test_pixel_depth_kernels.py index 03aff1c9..4c4aceac 100644 --- a/tests/gen3d/test_pixel_depth_kernels.py +++ b/tests/gen3d/test_pixel_depth_kernels.py @@ -6,6 +6,8 @@ UNEXPLAINED_DEPTH_NONRETURN_PROB, FullPixelDepthDistribution, MixturePixelDepthDistribution, + RenormalizedGaussianPixelDepthDistribution, + RenormalizedLaplacePixelDepthDistribution, TruncatedLaplacePixelDepthDistribution, UnexplainedPixelDepthDistribution, UniformPixelDepthDistribution, @@ -19,6 +21,8 @@ (UniformPixelDepthDistribution(near, far), ()), (TruncatedLaplacePixelDepthDistribution(near, far), (0.25,)), (UnexplainedPixelDepthDistribution(near, far), ()), + (RenormalizedLaplacePixelDepthDistribution(near, far), (0.25,)), + (RenormalizedGaussianPixelDepthDistribution(near, far), (0.25,)), ( MixturePixelDepthDistribution(near, far), ( @@ -72,8 +76,8 @@ def test_sample_in_valid_depth_range(kernel_spec, latent_depth): keys ) assert depths.shape == (num_samples,) - assert jnp.all((depths > near) | (depths == DEPTH_NONRETURN_VAL)) - assert jnp.all((depths < far) | (depths == DEPTH_NONRETURN_VAL)) + assert jnp.all((depths >= near) | (depths == DEPTH_NONRETURN_VAL)) + assert jnp.all((depths <= far) | (depths == DEPTH_NONRETURN_VAL)) def test_relative_logpdf(): From 9fd1eddcf9c834fd6814e67023ced3bee663f57c Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Wed, 11 Sep 2024 18:09:00 -0400 Subject: [PATCH 11/37] Refactor RGBD Pixel Kernel (#161) Co-authored-by: George Matheos --- notebooks/bayes3d_paper/tester.ipynb | 124 +++++-- src/b3d/chisight/gen3d/image_kernel.py | 36 +- src/b3d/chisight/gen3d/inference_moves.py | 323 +++++++----------- .../chisight/gen3d/pixel_kernels/__init__.py | 12 +- .../pixel_kernels/pixel_color_kernels.py | 90 ----- .../pixel_kernels/pixel_depth_kernels.py | 75 ---- .../gen3d/pixel_kernels/pixel_rgbd_kernels.py | 127 +++++-- .../test_depth_nonreturn_prob_inference.py | 52 +-- tests/gen3d/test_pixel_color_kernels.py | 64 ++-- tests/gen3d/test_pixel_depth_kernels.py | 64 ++-- tests/gen3d/test_pixel_rgbd_kernels.py | 20 +- 11 files changed, 457 insertions(+), 530 deletions(-) diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 73396def..5e05220e 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -37,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -51,7 +51,10 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:06<00:00, 7.29it/s]\n" + "100%|██████████| 49/49 [00:03<00:00, 13.52it/s]\n", + "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", + "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", + " warnings.warn(\n" ] }, { @@ -62,7 +65,7 @@ "" ] }, - "execution_count": 14, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -97,7 +100,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -125,7 +128,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -134,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -156,7 +159,7 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -167,7 +170,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -216,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -225,7 +228,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -244,7 +247,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -265,16 +268,16 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(158743.16, dtype=float32)" + "Array(158884.22, dtype=float32)" ] }, - "execution_count": 23, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -287,16 +290,16 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(158743.16, dtype=float32)" + "Array(158884.22, dtype=float32)" ] }, - "execution_count": 24, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -307,7 +310,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 39, "metadata": {}, "outputs": [], "source": [ @@ -319,16 +322,16 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(43753.14, dtype=float32)" + "Array(43455.8, dtype=float32)" ] }, - "execution_count": 26, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -352,7 +355,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -721,6 +724,75 @@ "metadata[\"p_scores\"][i-3:i+3]" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array([[0, 5],\n", + " [0, 6],\n", + " [0, 7],\n", + " [1, 5],\n", + " [1, 6],\n", + " [1, 7],\n", + " [2, 5],\n", + " [2, 6],\n", + " [2, 7],\n", + " [3, 5],\n", + " [3, 6],\n", + " [3, 7]], dtype=int32)" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def all_pairs_2(X, Y):\n", + " return jnp.swapaxes(jnp.stack(jnp.meshgrid(X, Y), axis=-1), 0, 1).reshape(-1, 2)\n", + "\n", + "all_pairs_2(jnp.arange(0, 4), jnp.arange(5, 8))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": 84, @@ -1800,7 +1872,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index 58ff5c29..b3362a27 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -7,12 +7,18 @@ from genjax import Pytree from genjax.typing import FloatArray, PRNGKey -from b3d.chisight.gen3d.pixel_kernels import ( - FullPixelColorDistribution, - FullPixelDepthDistribution, - PixelDepthDistribution, +from b3d.chisight.gen3d.pixel_kernels import is_unexplained +from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( + TruncatedLaplacePixelColorDistribution, + UniformPixelColorDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( + TruncatedLaplacePixelDepthDistribution, + UniformPixelDepthDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import ( + FullPixelRGBDDistribution, PixelRGBDDistribution, - is_unexplained, ) from b3d.chisight.gen3d.projection import PixelsPointsAssociation @@ -51,9 +57,6 @@ def logpdf( ) -> FloatArray: raise NotImplementedError - def get_depth_vertex_kernel(self) -> PixelDepthDistribution: - raise NotImplementedError - def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: raise NotImplementedError @@ -126,11 +129,11 @@ def logpdf( state["visibility_prob"], state["depth_nonreturn_prob"], ) - # the pixel kernel does not expect invalid observed_rgbd and will return - # -inf if it is invalid. We need to filter those out here. - # (invalid rgbd could happen when the vertex is projected out of the image) + # Points that don't hit the camera plane should not contribute to the score. scores = jnp.where(is_unexplained(observed_rgbd_per_point), 0.0, scores) + # TODO: add scoring for pixels that are not explained by the latent points + return scores.sum() def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: @@ -138,10 +141,9 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: # but they should work for per-vertex computation as well, except that # they don't expect observed_rgbd to be invalid, so we need to handle # that manually. - return PixelRGBDDistribution( - FullPixelColorDistribution(), - FullPixelDepthDistribution(self.near, self.far), + return FullPixelRGBDDistribution( + TruncatedLaplacePixelColorDistribution(), + UniformPixelColorDistribution(), + TruncatedLaplacePixelDepthDistribution(self.near, self.far), + UniformPixelDepthDistribution(self.near, self.far), ) - - def get_depth_vertex_kernel(self) -> PixelDepthDistribution: - return self.get_rgbd_vertex_kernel().depth_kernel diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index e77e6772..ce90429e 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -55,263 +55,194 @@ def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperp proposed latents (and the same pose and observed rgbd as in the given trace). `log_q` is (a fair estimate of) the log proposal density. """ - k1, k2, k3, k4, k5 = split(key, 5) + k1, k2, k3, k4 = split(key, 4) trace = update_field(k1, advanced_trace, "pose", pose) k2a, k2b = split(k2) - depth_nonreturn_probs, log_q_dnrps, dnrp_metadata = propose_depth_nonreturn_probs( - k2a, trace - ) - trace = update_vmapped_field( - k2b, trace, "depth_nonreturn_prob", depth_nonreturn_probs + ( + colors, + visibility_probs, + depth_nonreturn_probs, + log_q_point_attributes, + point_proposal_metadata, + ) = propose_all_pointlevel_attributes(k2a, trace, inference_hyperparams) + trace = update_vmapped_fields( + k2b, + trace, + ["colors", "visibility_prob", "depth_nonreturn_prob"], + [colors, visibility_probs, depth_nonreturn_probs], ) + # TODO: debug these scores -- right now they are causing bad behavior + log_q_point_attributes = 0.0 k3a, k3b = split(k3) - colors, visibility_probs, log_q_cvp = propose_colors_and_visibility_probs( - k3a, trace, inference_hyperparams - ) - trace = update_vmapped_fields( - k3b, trace, ["colors", "visibility_prob"], [colors, visibility_probs] - ) - log_q_cvp = 0.0 + depth_scale, log_q_ds = propose_depth_scale(k3a, trace) + trace = update_field(k3b, trace, "depth_scale", depth_scale) k4a, k4b = split(k4) - depth_scale, log_q_ds = propose_depth_scale(k4a, trace) - trace = update_field(k4b, trace, "depth_scale", depth_scale) - - k5a, k5b = split(k5) - color_scale, log_q_cs = propose_color_scale(k5a, trace) - trace = update_field(k5b, trace, "color_scale", color_scale) + color_scale, log_q_cs = propose_color_scale(k4a, trace) + trace = update_field(k4b, trace, "color_scale", color_scale) - log_q = log_q_dnrps + log_q_cvp + log_q_ds + log_q_cs + log_q = log_q_point_attributes + log_q_ds + log_q_cs return ( trace, log_q, - {"depth_nonreturn_proposal": dnrp_metadata, "dnrps": depth_nonreturn_probs}, + {"point_attribute_proposal_metadata": point_proposal_metadata}, ) -def propose_depth_nonreturn_probs(key, trace): +def propose_all_pointlevel_attributes(key, trace, inference_hyperparams): """ - Propose a new depth nonreturn probability for every vertex, conditioned - upon the other values in `trace`. - Returns (depth_nonreturn_probs, log_q) where `depth_nonreturn_probs` is - a vector of shape (n_vertices,) and `log_q` is (a fair estimate of) - the log proposal density of this list of values. - """ - observed_depths_per_points = PixelsPointsAssociation.from_hyperparams_and_pose( - get_hypers(trace), get_new_state(trace)["pose"] - ).get_point_depths(get_observed_rgbd(trace)) - - depth_nonreturn_probs, per_vertex_log_qs, metadata = jax.vmap( - propose_vertex_depth_nonreturn_prob, in_axes=(0, 0, 0, None, None, None) - )( - split(key, get_n_vertices(trace)), - jnp.arange(get_n_vertices(trace)), - observed_depths_per_points, - get_prev_state(trace), - get_new_state(trace), - get_hypers(trace), - ) + Propose a new color, visibility probability, and depth non-return probability + for every vertex, conditioned upon the other values in `trace`. - return depth_nonreturn_probs, per_vertex_log_qs.sum(), metadata - - -def propose_colors_and_visibility_probs(key, trace, inference_hyperparams): - """ - Propose a new color and visibility probability for every vertex, conditioned - upon the other values in `trace`. - Returns (colors, visibility_probs, log_q) where `colors` has shape - (n_vertices, 3), `visibility_probs` is a vector of shape (n_vertices,) - and `log_q` is (a fair estimate of) the log proposal density of these - values. + Returns (colors, visibility_probs, depth_nonreturn_probs, log_q, metadata), + where colors has shape (n_vertices, 3), visibility_probs and depth_nonreturn_probs + have shape (n_vertices,), log_q (a float) is (an estimate of) + the overall log proposal density, and metadata is a dict. """ - observed_rgbds_per_points = PixelsPointsAssociation.from_hyperparams_and_pose( + observed_rgbds_per_point = PixelsPointsAssociation.from_hyperparams_and_pose( get_hypers(trace), get_new_state(trace)["pose"] ).get_point_rgbds(get_observed_rgbd(trace)) - colors, visibility_probs, per_vertex_log_qs = jax.vmap( - propose_vertex_color_and_visibility_prob, - in_axes=(0, 0, 0, None, None, None, None), + colors, visibility_probs, depth_nonreturn_probs, log_qs, metadata = jax.vmap( + propose_a_points_attributes, in_axes=(0, 0, 0, None, None, None, None) )( split(key, get_n_vertices(trace)), jnp.arange(get_n_vertices(trace)), - observed_rgbds_per_points, + observed_rgbds_per_point, get_prev_state(trace), get_new_state(trace), get_hypers(trace), inference_hyperparams, ) - return colors, visibility_probs, per_vertex_log_qs.sum() + return colors, visibility_probs, depth_nonreturn_probs, log_qs.sum(), metadata -def propose_vertex_depth_nonreturn_prob( - key, vertex_index, observed_depth, previous_state, new_state, hyperparams +def propose_a_points_attributes( + key, + vertex_index, + observed_rgbd_for_point, + prev_state, + new_state, + hyperparams, + inference_hyperparams, ): """ - Propose a new depth nonreturn probability for the single vertex - with index `vertex_index`. - Returns (depth_nonreturn_prob, log_q) where `depth_nonreturn_prob` is - the proposed value and `log_q` is (a fair estimate of) the log proposal density. + Propose a new color, visibility probability, and depth non-return probability + for the vertex with index `vertex_index`. + + Returns (color, visibility_prob, depth_nonreturn_prob, log_q, metadata), + where color is a 3-array, visibility_prob and depth_nonreturn_prob are floats, + log_q (a float) is (a fair estimate of) the log proposal density, + and metadata is a dict. """ - previous_dnrp = previous_state["depth_nonreturn_prob"][vertex_index] - visibility_prob = new_state["visibility_prob"][vertex_index] - latent_depth = new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2] - return _propose_vertex_depth_nonreturn_prob( + return _propose_a_points_attributes( key, - observed_depth, - latent_depth, - visibility_prob, - new_state["depth_scale"], - previous_dnrp, - hyperparams["depth_nonreturn_prob_kernel"], - hyperparams["image_kernel"].get_depth_vertex_kernel(), + observed_rgbd=observed_rgbd_for_point, + latent_depth=new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2], + previous_color=prev_state["colors"][vertex_index], + previous_visibility_prob=prev_state["visibility_prob"][vertex_index], + previous_dnrp=prev_state["depth_nonreturn_prob"][vertex_index], + dnrp_transition_kernel=hyperparams["depth_nonreturn_prob_kernel"], + visibility_transition_kernel=hyperparams["visibility_prob_kernel"], + color_kernel=hyperparams["color_kernel"], + obs_rgbd_kernel=hyperparams["image_kernel"].get_rgbd_vertex_kernel(), + color_scale=new_state["color_scale"], + depth_scale=new_state["depth_scale"], + inference_hyperparams=inference_hyperparams, ) -def _propose_vertex_depth_nonreturn_prob( +def _propose_a_points_attributes( key, - observed_depth, + observed_rgbd, latent_depth, - visibility_prob, - depth_scale, + previous_color, + previous_visibility_prob, previous_dnrp, dnrp_transition_kernel, - obs_depth_kernel, - return_metadata=True, -): - def score_dnrp_value(dnrp_value): - transition_score = dnrp_transition_kernel.logpdf(dnrp_value, previous_dnrp) - likelihood_score = obs_depth_kernel.logpdf( - observed_depth=observed_depth, - latent_depth=latent_depth, - depth_scale=depth_scale, - visibility_prob=visibility_prob, - depth_nonreturn_prob=dnrp_value, - ) - return transition_score + likelihood_score - - support = dnrp_transition_kernel.support - log_pscores = jax.vmap(score_dnrp_value)(support) - log_normalized_scores = normalize_log_scores(log_pscores) - index = jax.random.categorical(key, log_normalized_scores) - # ^ since we are enumerating over every value in the domain, it is unnecessary - # to add a 1/q score when resampling. (Equivalently, we could include - # q = 1/len(support), which does not change the resampling distribuiton at all.) - - if return_metadata: - metadata = { - "support": support, - "log_normalized_scores": log_normalized_scores, - "index": index, - "observed_depth": observed_depth, - "latent_depth": latent_depth, - "prev_dnrp": previous_dnrp, - "transition_score": jax.vmap( - lambda dnrp_value: dnrp_transition_kernel.logpdf( - dnrp_value, previous_dnrp - ) - )(support), - "likelihood_score": jax.vmap( - lambda dnrp_value: obs_depth_kernel.logpdf( - observed_depth, - latent_depth, - visibility_prob, - dnrp_value, - depth_scale, - ) - )(support), - } - else: - metadata = {} - - return support[index], log_normalized_scores[index], metadata - - -def propose_vertex_color_and_visibility_prob( - key, - vertex_index, - observed_rgbd_for_this_vertex, - previous_state, - new_state, - hyperparams, + visibility_transition_kernel, + color_kernel, + obs_rgbd_kernel, + color_scale, + depth_scale, inference_hyperparams, + return_metadata=True, ): - """ - Propose a new color and visibility probability for the single vertex - with index `vertex_index`. - Returns (color, visibility_prob, log_q) where `color` and `visibility_prob` - are the proposed values and `log_q` is (a fair estimate of) the log proposal density. - """ k1, k2 = split(key, 2) - previous_rgb = previous_state["colors"][vertex_index] - previous_visibility_prob = previous_state["visibility_prob"][vertex_index] - latent_depth = new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2] - all_vis_probs = hyperparams["visibility_prob_kernel"].support - - def score_visprob_rgb(visprob, rgb): - """ - Compute P(visprob, rgb, observed_rgbd_for_this_vertex | previous_visprob, previous_rgb). - """ - rgb_transition_score = hyperparams["color_kernel"].logpdf(rgb, previous_rgb) - visprob_transition_score = hyperparams["visibility_prob_kernel"].logpdf( + + def score_attribute_assignment(color, visprob, dnrprob): + visprob_transition_score = visibility_transition_kernel.logpdf( visprob, previous_visibility_prob ) - likelihood_score = ( - hyperparams["image_kernel"] - .get_rgbd_vertex_kernel() - .logpdf( - observed_rgbd=observed_rgbd_for_this_vertex, - latent_rgbd=jnp.append(rgb, latent_depth), - color_scale=new_state["color_scale"], - depth_scale=new_state["depth_scale"], - visibility_prob=visprob, - depth_nonreturn_prob=new_state["depth_nonreturn_prob"][vertex_index], - ) + dnrprob_transition_score = dnrp_transition_kernel.logpdf(dnrprob, previous_dnrp) + color_transition_score = color_kernel.logpdf(color, previous_color) + likelihood_score = obs_rgbd_kernel.logpdf( + observed_rgbd=observed_rgbd, + latent_rgbd=jnp.append(color, latent_depth), + color_scale=color_scale, + depth_scale=depth_scale, + visibility_prob=visprob, + depth_nonreturn_prob=dnrprob, + ) + return ( + visprob_transition_score + + dnrprob_transition_score + + color_transition_score + + likelihood_score ) - return rgb_transition_score + visprob_transition_score + likelihood_score - # Propose a rgb value for each visprob. - # `rgbs` has shape (len(all_vis_probs), 3). - # `log_qs_rgb` has shape (len(all_vis_probs),). + # Say there are V values in visibility_transition_kernel.support + # and D values in dnrp_transition_kernel.support. + + # (D*V, 2) array of all pairs of values in the support of the two kernels. + all_visprob_dnrprob_pairs = all_pairs( + visibility_transition_kernel.support, dnrp_transition_kernel.support + ) + + # Propose a color for each visprob-dnrprob pair. rgbs, log_qs_rgb = jax.vmap( - lambda k, visprob: propose_vertex_color_given_visibility( - k, - visprob, - observed_rgbd_for_this_vertex[:3], - score_visprob_rgb, - previous_rgb, - new_state, - inference_hyperparams, + lambda k, visprob_dnrprob_pair: propose_vertex_color_given_other_attributes( + key=k, + visprob=visprob_dnrprob_pair[0], + dnrprob=visprob_dnrprob_pair[1], + observed_rgb=observed_rgbd[:3], + score_attribute_assignment=score_attribute_assignment, + previous_rgb=previous_color, + color_scale=color_scale, + inference_hyperparams=inference_hyperparams, ) - )(split(k1, len(all_vis_probs)), all_vis_probs) + )(split(k1, len(all_visprob_dnrprob_pairs)), all_visprob_dnrprob_pairs) - # shape: (len(all_vis_probs),) - log_pscores = jax.vmap(score_visprob_rgb, in_axes=(0, 0))(all_vis_probs, rgbs) + log_pscores = jax.vmap( + lambda visprob_dnrprob_pair, rgb: score_attribute_assignment( + rgb, visprob_dnrprob_pair[0], visprob_dnrprob_pair[1] + ), + in_axes=(0, 0), + )(all_visprob_dnrprob_pairs, rgbs) - # We don't need to subtract a q score for the visibility probability, since - # we are enumerating over every value in the domain. (Equivalently, - # we could subtract a log q score of log(1/len(support)) for each value.) log_weights = log_pscores - log_qs_rgb log_normalized_scores = normalize_log_scores(log_weights) index = jax.random.categorical(k2, log_normalized_scores) rgb = rgbs[index] - visibility_prob = all_vis_probs[index] + visibility_prob, dnr_prob = all_visprob_dnrprob_pairs[index] log_q_score = log_normalized_scores[index] + log_qs_rgb[index] - return rgb, visibility_prob, log_q_score + return rgb, visibility_prob, dnr_prob, log_q_score, {} -def propose_vertex_color_given_visibility( +def propose_vertex_color_given_other_attributes( key, visprob, + dnrprob, observed_rgb, - score_visprob_and_rgb, + score_attribute_assignment, previous_rgb, - new_state, + color_scale, inference_hyperparams, ): """ @@ -344,7 +275,6 @@ def propose_vertex_color_given_visibility( propose traces that match that part of the posterior. """ color_shift_scale = inference_hyperparams.effective_color_transition_scale - color_scale = new_state["color_scale"] d = 1 / (1 / color_shift_scale + 1 / color_scale) r_diff = jnp.abs(previous_rgb[0] - observed_rgb[0]) @@ -379,7 +309,9 @@ def propose_vertex_color_given_visibility( log_qs = jnp.array([log_q_rgb_1, log_q_rgb_2, log_q_rgb_3]) scores = ( - jax.vmap(lambda rgb: score_visprob_and_rgb(visprob, rgb))(proposed_rgbs) + jax.vmap(lambda rgb: score_attribute_assignment(rgb, visprob, dnrprob))( + proposed_rgbs + ) - log_qs ) normalized_scores = normalize_log_scores(scores) @@ -517,3 +449,12 @@ def update_vmapped_field(key, trace, fieldname, value): For information, see `update_vmapped_fields`. """ return update_vmapped_fields(key, trace, [fieldname], [value]) + + +def all_pairs(X, Y): + """ + Return an array `ret` of shape (|X| * |Y|, 2) where each row + is a pair of values from X and Y. + That is, `ret[i, :]` is a pair [x, y] for some x in X and y in Y. + """ + return jnp.swapaxes(jnp.stack(jnp.meshgrid(X, Y), axis=-1), 0, 1).reshape(-1, 2) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py b/src/b3d/chisight/gen3d/pixel_kernels/__init__.py index 401b95b7..307026aa 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/__init__.py @@ -1,27 +1,27 @@ from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( - FullPixelColorDistribution, MixturePixelColorDistribution, PixelColorDistribution, - is_unexplained, ) from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( DEPTH_NONRETURN_VAL, - FullPixelDepthDistribution, MixturePixelDepthDistribution, PixelDepthDistribution, UnexplainedPixelDepthDistribution, ) -from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import PixelRGBDDistribution +from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import ( + FullPixelRGBDDistribution, + PixelRGBDDistribution, + is_unexplained, +) __all__ = [ "is_unexplained", "DEPTH_NONRETURN_VAL", - "FullPixelColorDistribution", - "FullPixelDepthDistribution", "MixturePixelColorDistribution", "MixturePixelDepthDistribution", "PixelColorDistribution", "PixelDepthDistribution", "PixelRGBDDistribution", + "FullPixelRGBDDistribution", "UnexplainedPixelDepthDistribution", ] diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py index 7c7f7a9b..e9ae524d 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py @@ -23,22 +23,6 @@ COLOR_MAX_VAL: float = 1.0 -def is_unexplained(latent_value: FloatArray) -> bool: - """ - Check if a given `latent_value` value given to a pixel - indicates that no latent point hits a pixel. - This is done by checking if any of the latent color values - are negative. - - Args: - latent_value (FloatArray): The latent color of the pixel. - - Returns: - bool: True is none of the latent point hits the pixel, False otherwise. - """ - return jnp.any(latent_value < 0.0) - - @Pytree.dataclass class PixelColorDistribution(genjax.ExactDensity): """ @@ -258,77 +242,3 @@ def logpdf_per_channel( ) return jnp.logaddexp(*logprobs) - - -@Pytree.dataclass -class FullPixelColorDistribution(PixelColorDistribution): - """A distribution that generates the color of the pixel according to the - following rule: - - if no latent point hits the pixel: - color ~ uniform(0, 1) - else: - color ~ mixture( - [uniform(0, 1), truncated_laplace(latent_color; color_scale)], - [occluded_prob, 1 - occluded_prob] - ) - - Constructor args: - - Distribution args: - - `latent_color`: 3-array. If no latent point hits the pixel, should contain - 3 negative values. If a latent point hits the pixel, should contain the point's - color as an RGB value in [0, 1]^3. - - color_scale: float. The scale of the truncated Laplace distribution - centered around the latent color used for inlier color observations. - - `color_visibility_prob`: float. If a latent point hits the pixel, should contain - the probability associated with that point that the generated color is - visible (non-occluded). If no latent point hits the pixel, this value is ignored. - - Distribution support: - - An RGB value in [0, 1]^3. - """ - - @property - def _color_from_latent(self) -> PixelColorDistribution: - return MixturePixelColorDistribution() - - @property - def _unexplained_color(self) -> PixelColorDistribution: - return UniformPixelColorDistribution() - - def sample( - self, - key: PRNGKey, - latent_color: FloatArray, - color_scale: FloatArray, - visibility_prob: FloatArray, - ) -> FloatArray: - return jax.lax.cond( - is_unexplained(latent_color), - self._unexplained_color.sample, # if no point hits current pixel - self._color_from_latent.sample, # if pixel is being hit by a latent point - # sample args - key, - latent_color, - color_scale, - visibility_prob, - ) - - def logpdf_per_channel( - self, - observed_color: FloatArray, - latent_color: FloatArray, - color_scale: FloatArray, - visibility_prob: float, - ) -> FloatArray: - return jax.lax.cond( - is_unexplained(latent_color), - self._unexplained_color.logpdf_per_channel, # if no point hits current pixel - self._color_from_latent.logpdf_per_channel, # if pixel is being hit by a latent point - # logpdf args - observed_color, - latent_color, - color_scale, - visibility_prob, - ) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py index 9d4e4adf..1c1a0365 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py @@ -2,13 +2,11 @@ from typing import TYPE_CHECKING, Any import genjax -import jax import jax.numpy as jnp from genjax import Pytree from genjax.typing import FloatArray, PRNGKey from tensorflow_probability.substrates import jax as tfp -from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import is_unexplained from b3d.modeling_utils import ( _FIXED_DEPTH_UNIFORM_WINDOW, PythonMixtureDistribution, @@ -316,76 +314,3 @@ def logpdf( **kwargs, ) -> float: return self._mixture_dist.logpdf(observed_depth, self._mix_ratio, [(), ()]) - - -@Pytree.dataclass -class FullPixelDepthDistribution(PixelDepthDistribution): - """A distribution that generates the depth of the pixel according to the - following rule: - - if no latent point hits the pixel: - depth ~ mixture( - [delta(DEPTH_NONRETURN_VAL), uniform(near, far)], - [unexplained_depth_nonreturn_prob, 1 - unexplained_depth_nonreturn_prob] - ) - else: - mixture( - [delta(DEPTH_NONRETURN_VAL), uniform(near, far), laplace(latent_depth; depth_scale)], - [depth_nonreturn_prob, (1 - depth_nonreturn_prob) * (1 - visibility_prob), remaining_prob] - ) - """ - - near: float = Pytree.static() - far: float = Pytree.static() - - @property - def _depth_from_latent(self) -> PixelDepthDistribution: - return MixturePixelDepthDistribution(self.near, self.far) - - @property - def _unexplained_depth(self) -> PixelDepthDistribution: - return UnexplainedPixelDepthDistribution(self.near, self.far) - - def sample( - self, - key: PRNGKey, - latent_depth: FloatArray, - depth_scale: FloatArray, - visibility_prob: FloatArray, - depth_nonreturn_prob: float, - *args, - **kwargs, - ) -> FloatArray: - return jax.lax.cond( - is_unexplained(latent_depth), - self._unexplained_depth.sample, # if no point hits current pixel - self._depth_from_latent.sample, # if pixel is being hit by a latent point - # sample args - key, - latent_depth, - depth_scale, - visibility_prob, - depth_nonreturn_prob, - ) - - def logpdf( - self, - observed_depth: FloatArray, - latent_depth: FloatArray, - depth_scale: FloatArray, - visibility_prob: float, - depth_nonreturn_prob: float, - *args, - **kwargs, - ) -> FloatArray: - return jax.lax.cond( - is_unexplained(latent_depth), - self._unexplained_depth.logpdf, # if no point hits current pixel - self._depth_from_latent.logpdf, # if pixel is being hit by a latent point - # logpdf args - observed_depth, - latent_depth, - depth_scale, - visibility_prob, - depth_nonreturn_prob, - ) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py index af0f0506..c81322ba 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py @@ -1,5 +1,6 @@ +from abc import abstractmethod + import genjax -import jax import jax.numpy as jnp from genjax import Pytree from genjax.typing import FloatArray, PRNGKey @@ -8,6 +9,22 @@ from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import PixelDepthDistribution +def is_unexplained(latent_value: FloatArray) -> bool: + """ + Check if a given `latent_value` value given to a pixel + indicates that no latent point hits a pixel. + This is done by checking if any of the latent color values + are negative. + + Args: + latent_value (FloatArray): The latent color of the pixel. + + Returns: + bool: True is none of the latent point hits the pixel, False otherwise. + """ + return jnp.any(latent_value < 0.0) + + @Pytree.dataclass class PixelRGBDDistribution(genjax.ExactDensity): """ @@ -24,8 +41,48 @@ class PixelRGBDDistribution(genjax.ExactDensity): pixel is observed, the logpdf will return -inf. """ - color_kernel: PixelColorDistribution - depth_kernel: PixelDepthDistribution + @abstractmethod + def sample( + self, + key: PRNGKey, + latent_rgbd: FloatArray, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, + ) -> FloatArray: + raise NotImplementedError + + @abstractmethod + def logpdf( + self, + observed_rgbd: FloatArray, + latent_rgbd: FloatArray, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, + ) -> float: + raise NotImplementedError + + +@Pytree.dataclass +class FullPixelRGBDDistribution(PixelRGBDDistribution): + """ + Args: + - latent_rgbd: 4-array: RGBD value. (a value of [-1, -1, -1, -1] indicates no point hits here.) + - color_scale: float + - depth_scale: float + - visibility_prob: float + + The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). + """ + + inlier_color_distribution: PixelColorDistribution + outlier_color_distribution: PixelColorDistribution + + inlier_depth_distribution: PixelDepthDistribution + outlier_depth_distribution: PixelDepthDistribution def sample( self, @@ -36,14 +93,8 @@ def sample( visibility_prob: float, depth_nonreturn_prob: float, ) -> FloatArray: - keys = jax.random.split(key, 2) - observed_color = self.color_kernel.sample( - keys[0], latent_rgbd[:3], color_scale, visibility_prob - ) - observed_depth = self.depth_kernel.sample( - keys[1], latent_rgbd[3], depth_scale, visibility_prob, depth_nonreturn_prob - ) - return jnp.append(observed_color, observed_depth) + # TODO: Implement this + return jnp.ones((4,)) * 0.5 def logpdf( self, @@ -54,14 +105,50 @@ def logpdf( visibility_prob: float, depth_nonreturn_prob: float, ) -> float: - color_logpdf = self.color_kernel.logpdf( - observed_rgbd[:3], latent_rgbd[:3], color_scale, visibility_prob + total_log_prob = 0.0 + + is_depth_non_return = observed_rgbd[3] == 0.0 + + # Is visible + total_visible_log_prob = 0.0 + # color term + total_visible_log_prob += self.inlier_color_distribution.logpdf( + observed_rgbd[:3], latent_rgbd[:3], color_scale + ) + # depth term + total_visible_log_prob += jnp.where( + is_depth_non_return, + jnp.log(depth_nonreturn_prob), + jnp.log(1 - depth_nonreturn_prob) + + self.inlier_depth_distribution.logpdf( + observed_rgbd[3], latent_rgbd[3], depth_scale + ), + ) + + # Is not visible + total_not_visible_log_prob = 0.0 + # color term + outlier_color_log_prob = self.outlier_color_distribution.logpdf( + observed_rgbd[:3], latent_rgbd[:3], color_scale + ) + outlier_depth_log_prob = self.outlier_depth_distribution.logpdf( + observed_rgbd[3], latent_rgbd[3], depth_scale + ) + + total_not_visible_log_prob += outlier_color_log_prob + # depth term + total_not_visible_log_prob += jnp.where( + is_depth_non_return, + jnp.log(depth_nonreturn_prob), + jnp.log(1 - depth_nonreturn_prob) + outlier_depth_log_prob, + ) + + total_log_prob += jnp.logaddexp( + jnp.log(visibility_prob) + total_visible_log_prob, + jnp.log(1 - visibility_prob) + total_not_visible_log_prob, ) - depth_logpdf = self.depth_kernel.logpdf( - observed_rgbd[3], - latent_rgbd[3], - depth_scale, - visibility_prob, - depth_nonreturn_prob, + return jnp.where( + jnp.any(is_unexplained(latent_rgbd)), + outlier_color_log_prob + outlier_depth_log_prob, + total_log_prob, ) - return color_logpdf + depth_logpdf diff --git a/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py b/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py index 4af3e1db..55455fdb 100644 --- a/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py +++ b/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py @@ -1,32 +1,32 @@ -import b3d.chisight.gen3d.inference_moves as im -import b3d.chisight.gen3d.transition_kernels as transition_kernels -import jax -import jax.numpy as jnp -import jax.random as r -from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( - FullPixelDepthDistribution, -) +# import b3d.chisight.gen3d.inference_moves as im +# import b3d.chisight.gen3d.transition_kernels as transition_kernels +# import jax +# import jax.numpy as jnp +# import jax.random as r +# from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( +# FullPixelDepthDistribution, +# ) -near, far = 0.001, 1.0 +# near, far = 0.001, 1.0 -dnrp_transition_kernel = transition_kernels.DiscreteFlipKernel( - resample_probability=0.05, support=jnp.array([0.01, 0.99]) -) +# dnrp_transition_kernel = transition_kernels.DiscreteFlipKernel( +# resample_probability=0.05, support=jnp.array([0.01, 0.99]) +# ) -def propose_val(k): - return im._propose_vertex_depth_nonreturn_prob( - k, - observed_depth=0.8, - latent_depth=1.0, - visibility_prob=1.0, - depth_scale=0.00001, - previous_dnrp=0.01, - dnrp_transition_kernel=dnrp_transition_kernel, - obs_depth_kernel=FullPixelDepthDistribution(near, far), - ) +# def propose_val(k): +# return im._propose_vertex_depth_nonreturn_prob( +# k, +# observed_depth=0.8, +# latent_depth=1.0, +# visibility_prob=1.0, +# depth_scale=0.00001, +# previous_dnrp=0.01, +# dnrp_transition_kernel=dnrp_transition_kernel, +# obs_depth_kernel=FullPixelDepthDistribution(near, far), +# ) -values, log_qs, _ = jax.vmap(propose_val)(r.split(r.PRNGKey(0), 1000)) -n_01 = jnp.sum((values == 0.01).astype(jnp.int32)) -assert n_01 >= 950 +# values, log_qs, _ = jax.vmap(propose_val)(r.split(r.PRNGKey(0), 1000)) +# n_01 = jnp.sum((values == 0.01).astype(jnp.int32)) +# assert n_01 >= 950 diff --git a/tests/gen3d/test_pixel_color_kernels.py b/tests/gen3d/test_pixel_color_kernels.py index 10505756..2ca53ffd 100644 --- a/tests/gen3d/test_pixel_color_kernels.py +++ b/tests/gen3d/test_pixel_color_kernels.py @@ -6,7 +6,6 @@ from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( COLOR_MAX_VAL, COLOR_MIN_VAL, - FullPixelColorDistribution, MixturePixelColorDistribution, RenormalizedGaussianPixelColorDistribution, RenormalizedLaplacePixelColorDistribution, @@ -47,13 +46,6 @@ def generate_color_grid(n_grid_steps: int): 0.5, ), ), - ( - FullPixelColorDistribution(), - ( - 0.5, - 1 - 0.3, - ), - ), ] @@ -88,31 +80,31 @@ def test_sample_in_valid_color_range(kernel_spec, latent_color): assert jnp.all(colors <= 1) -def test_relative_logpdf(): - kernel = FullPixelColorDistribution() - scale = 0.01 - obs_color = jnp.array([0.0, 0.0, 1.0]) # a blue pixel - - # case 1: no color hit the pixel - latent_color = -jnp.ones(3) # use -1 to denote invalid pixel - logpdf_1 = kernel.logpdf(obs_color, latent_color, scale, 0.8) - logpdf_2 = kernel.logpdf(obs_color, latent_color, scale, 0.2) - # the logpdf should be the same because the occluded probability is not used - # in the case when no color hit the pixel - assert jnp.allclose(logpdf_1, logpdf_2) - - # case 2: a color hit the pixel, but the color is not close to the observed color - latent_color = jnp.array([1.0, 0.5, 0.0]) - logpdf_3 = kernel.logpdf(obs_color, latent_color, scale, 0.8) - logpdf_4 = kernel.logpdf(obs_color, latent_color, scale, 0.2) - # the pixel should be more likely to be an occluded - assert logpdf_3 < logpdf_4 - - # case 3: a color hit the pixel, and the color is close to the observed color - latent_color = jnp.array([0.0, 0.0, 0.9]) - logpdf_5 = kernel.logpdf(obs_color, latent_color, 0.01, 0.8) - logpdf_6 = kernel.logpdf(obs_color, latent_color, scale, 0.2) - # the pixel should be more likely to be an inlier - assert logpdf_5 > logpdf_6 - # the score of the pixel should be higher when the color is closer - assert logpdf_5 > logpdf_3 +# def test_relative_logpdf(): +# kernel = FullPixelColorDistribution() +# scale = 0.01 +# obs_color = jnp.array([0.0, 0.0, 1.0]) # a blue pixel + +# # case 1: no color hit the pixel +# latent_color = -jnp.ones(3) # use -1 to denote invalid pixel +# logpdf_1 = kernel.logpdf(obs_color, latent_color, scale, 0.8) +# logpdf_2 = kernel.logpdf(obs_color, latent_color, scale, 0.2) +# # the logpdf should be the same because the occluded probability is not used +# # in the case when no color hit the pixel +# assert jnp.allclose(logpdf_1, logpdf_2) + +# # case 2: a color hit the pixel, but the color is not close to the observed color +# latent_color = jnp.array([1.0, 0.5, 0.0]) +# logpdf_3 = kernel.logpdf(obs_color, latent_color, scale, 0.8) +# logpdf_4 = kernel.logpdf(obs_color, latent_color, scale, 0.2) +# # the pixel should be more likely to be an occluded +# assert logpdf_3 < logpdf_4 + +# # case 3: a color hit the pixel, and the color is close to the observed color +# latent_color = jnp.array([0.0, 0.0, 0.9]) +# logpdf_5 = kernel.logpdf(obs_color, latent_color, 0.01, 0.8) +# logpdf_6 = kernel.logpdf(obs_color, latent_color, scale, 0.2) +# # the pixel should be more likely to be an inlier +# assert logpdf_5 > logpdf_6 +# # the score of the pixel should be higher when the color is closer +# assert logpdf_5 > logpdf_3 diff --git a/tests/gen3d/test_pixel_depth_kernels.py b/tests/gen3d/test_pixel_depth_kernels.py index 4c4aceac..19a5d9fe 100644 --- a/tests/gen3d/test_pixel_depth_kernels.py +++ b/tests/gen3d/test_pixel_depth_kernels.py @@ -3,8 +3,6 @@ import pytest from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( DEPTH_NONRETURN_VAL, - UNEXPLAINED_DEPTH_NONRETURN_PROB, - FullPixelDepthDistribution, MixturePixelDepthDistribution, RenormalizedGaussianPixelDepthDistribution, RenormalizedLaplacePixelDepthDistribution, @@ -31,14 +29,6 @@ 0.23, # depth_nonreturn_prob ), ), - ( - FullPixelDepthDistribution(near, far), - ( - 0.5, # scale - 1 - 0.3, # visibility_prob - 0.1, # depth_nonreturn_prob - ), - ), ] @@ -80,34 +70,34 @@ def test_sample_in_valid_depth_range(kernel_spec, latent_depth): assert jnp.all((depths <= far) | (depths == DEPTH_NONRETURN_VAL)) -def test_relative_logpdf(): - kernel = FullPixelDepthDistribution(near, far) - scale = 0.1 +# def test_relative_logpdf(): +# kernel = FullPixelDepthDistribution(near, far) +# scale = 0.1 - # case 1: depth is missing in observation (nonreturn) - obs_depth = DEPTH_NONRETURN_VAL - latent_depth = DEPTH_NONRETURN_VAL - depth_nonreturn_prob = 0.2 - logpdf_1 = kernel.logpdf(obs_depth, latent_depth, scale, 0.8, depth_nonreturn_prob) - assert logpdf_1 == jnp.log(depth_nonreturn_prob) +# # case 1: depth is missing in observation (nonreturn) +# obs_depth = DEPTH_NONRETURN_VAL +# latent_depth = DEPTH_NONRETURN_VAL +# depth_nonreturn_prob = 0.2 +# logpdf_1 = kernel.logpdf(obs_depth, latent_depth, scale, 0.8, depth_nonreturn_prob) +# assert logpdf_1 == jnp.log(depth_nonreturn_prob) - latent_depth = -1.0 # no depth information from latent - logpdf_2 = kernel.logpdf(obs_depth, latent_depth, scale, 0.8, depth_nonreturn_prob) - # nonreturn obs cannot be generates from latent that is not nonreturn - assert logpdf_2 == jnp.log(UNEXPLAINED_DEPTH_NONRETURN_PROB) +# latent_depth = -1.0 # no depth information from latent +# logpdf_2 = kernel.logpdf(obs_depth, latent_depth, scale, 0.8, depth_nonreturn_prob) +# # nonreturn obs cannot be generates from latent that is not nonreturn +# assert logpdf_2 == jnp.log(UNEXPLAINED_DEPTH_NONRETURN_PROB) - # case 2: valid depth is observed, but latent depth is far from the observed depth - obs_depth = 10.0 - latent_depth = 0.01 - logpdf_3 = kernel.logpdf(obs_depth, latent_depth, scale, 0.1, depth_nonreturn_prob) - logpdf_4 = kernel.logpdf(obs_depth, latent_depth, scale, 0.9, depth_nonreturn_prob) - # the pixel should be more likely to be an occluded - assert logpdf_3 > logpdf_4 +# # case 2: valid depth is observed, but latent depth is far from the observed depth +# obs_depth = 10.0 +# latent_depth = 0.01 +# logpdf_3 = kernel.logpdf(obs_depth, latent_depth, scale, 0.1, depth_nonreturn_prob) +# logpdf_4 = kernel.logpdf(obs_depth, latent_depth, scale, 0.9, depth_nonreturn_prob) +# # the pixel should be more likely to be an occluded +# assert logpdf_3 > logpdf_4 - # case 3: valid depth is observed, but latent depth is close from the observed depth - obs_depth = 6.0 - latent_depth = 6.01 - logpdf_5 = kernel.logpdf(obs_depth, latent_depth, scale, 0.1, depth_nonreturn_prob) - logpdf_6 = kernel.logpdf(obs_depth, latent_depth, scale, 0.9, depth_nonreturn_prob) - # the pixel should be more likely to be an inliner - assert logpdf_5 < logpdf_6 +# # case 3: valid depth is observed, but latent depth is close from the observed depth +# obs_depth = 6.0 +# latent_depth = 6.01 +# logpdf_5 = kernel.logpdf(obs_depth, latent_depth, scale, 0.1, depth_nonreturn_prob) +# logpdf_6 = kernel.logpdf(obs_depth, latent_depth, scale, 0.9, depth_nonreturn_prob) +# # the pixel should be more likely to be an inliner +# assert logpdf_5 < logpdf_6 diff --git a/tests/gen3d/test_pixel_rgbd_kernels.py b/tests/gen3d/test_pixel_rgbd_kernels.py index 704e623a..606edf64 100644 --- a/tests/gen3d/test_pixel_rgbd_kernels.py +++ b/tests/gen3d/test_pixel_rgbd_kernels.py @@ -3,9 +3,15 @@ import pytest from b3d.chisight.gen3d.pixel_kernels import ( DEPTH_NONRETURN_VAL, - FullPixelColorDistribution, - FullPixelDepthDistribution, - PixelRGBDDistribution, + FullPixelRGBDDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( + TruncatedLaplacePixelColorDistribution, + UniformPixelColorDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( + TruncatedLaplacePixelDepthDistribution, + UniformPixelDepthDistribution, ) near = 0.01 @@ -13,9 +19,11 @@ sample_kernels_to_test = [ ( - PixelRGBDDistribution( - FullPixelColorDistribution(), - FullPixelDepthDistribution(near, far), + FullPixelRGBDDistribution( + TruncatedLaplacePixelColorDistribution(), + UniformPixelColorDistribution(), + TruncatedLaplacePixelDepthDistribution(near, far), + UniformPixelDepthDistribution(near, far), ), ( 0.01, # color_scale From 6ab90c2c1b74279e52a3d3f4567fcf3ffd8fe12c Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Thu, 12 Sep 2024 09:03:09 -0400 Subject: [PATCH 12/37] Inference Unit Tests - Part 1 (#163) Co-authored-by: George Matheos --- .../bayes3d_paper/run_ycbv_evaluation.py | 298 +++++------------- src/b3d/chisight/gen3d/inference_moves.py | 8 +- src/b3d/chisight/gen3d/model.py | 3 + src/b3d/utils.py | 22 +- tests/gen3d/test_inference.py | 265 ++++++++++++++++ 5 files changed, 370 insertions(+), 226 deletions(-) create mode 100644 tests/gen3d/test_inference.py diff --git a/notebooks/bayes3d_paper/run_ycbv_evaluation.py b/notebooks/bayes3d_paper/run_ycbv_evaluation.py index b04bd93a..caf5b9e5 100644 --- a/notebooks/bayes3d_paper/run_ycbv_evaluation.py +++ b/notebooks/bayes3d_paper/run_ycbv_evaluation.py @@ -7,10 +7,18 @@ def run_tracking(scene=None, object=None, debug=False): import os import b3d + import b3d.chisight.gen3d.image_kernel as image_kernel + import b3d.chisight.gen3d.transition_kernels as transition_kernels import genjax import jax import jax.numpy as jnp from b3d import Mesh, Pose + from b3d.chisight.gen3d.model import ( + dynamic_object_generative_model, + make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, + make_visibility_prob_choicemap, + ) from genjax import Pytree from tqdm import tqdm @@ -32,6 +40,27 @@ def run_tracking(scene=None, object=None, debug=False): elif isinstance(scene, list): scenes = scene + hyperparams = { + "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.1), + "color_kernel": transition_kernels.LaplaceNotTruncatedColorDriftKernel( + scale=0.15 + ), + "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.05, possible_values=jnp.array([0.01, 0.99]) + ), + "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.05, possible_values=jnp.array([0.01, 0.99]) + ), + "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.05, possible_values=jnp.array([0.0025, 0.01, 0.02]) + ), + "color_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.05, possible_values=jnp.array([0.05, 0.1, 0.15]) + ), + "image_likelihood": image_kernel.SimpleNoRenderImageLikelihood(), + } + info_from_trace = hyperparams["image_likelihood"].info_from_trace + for scene_id in scenes: print(f"Scene {scene_id}") num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id) @@ -61,98 +90,9 @@ def run_tracking(scene=None, object=None, debug=False): 4.0, ) - def grid_outlier_prob(trace, values): - return jax.vmap( - lambda x: info_from_trace( - b3d.update_choices(trace, Pytree.const(("outlier_probability",)), x) - )["scores"] - )(values) - - @jax.jit - def update_pose_and_color(trace, address, pose): - trace = b3d.update_choices(trace, address, pose) - info = info_from_trace(trace) - current_outlier_probabilities = trace.get_choices()["outlier_probability"] - model_rgbd, observed_rgbd = ( - info["model_rgbd"], - info["corresponding_observed_rgbd"], - ) - deltas = (observed_rgbd - model_rgbd)[..., :3] - deltas_clipped = jnp.clip(deltas, -0.1, 0.1) - - mesh = trace.get_args()[0]["meshes"][0] - is_inlier = current_outlier_probabilities == outlier_probability_sweep[0] - mesh.vertex_attributes = ( - mesh.vertex_attributes + deltas_clipped * is_inlier[..., None] - ) - - trace, _ = importance_jit( - jax.random.PRNGKey(2), - trace.get_choices(), - ( - { - "num_objects": Pytree.const(1), - "meshes": [mesh], - "likelihood_args": likelihood_args, - }, - ), - ) - return trace.get_score() - - def _gvmf_and_select_best_move( - trace, key, variance, concentration, address, number - ): - test_poses = Pose.concatenate_poses( - [ - jax.vmap( - Pose.sample_gaussian_vmf_pose, in_axes=(0, None, None, None) - )( - jax.random.split(key, number), - trace.get_choices()[address.const], - variance, - concentration, - ), - trace.get_choices()[address.const][None, ...], - ] - ) - scores = jax.vmap(update_pose_and_color, in_axes=(None, None, 0))( - trace, address, test_poses - ) - trace = b3d.update_choices( - trace, - address, - test_poses[scores.argmax()], - ) - key = jax.random.split(key, 2)[-1] - return trace, key - - gvmf_and_select_best_move = jax.jit( - _gvmf_and_select_best_move, static_argnames=["number"] - ) - - from b3d.chisight.dense.likelihoods.simplified_rendering_laplace_likelihood import ( - simplified_rendering_laplace_likelihood, - ) - - model, viz_trace, info_from_trace = ( - b3d.chisight.dense.dense_model.make_dense_multiobject_model( - None, simplified_rendering_laplace_likelihood - ) - ) - importance_jit = jax.jit(model.importance) - # initial_camera_pose = all_data[0]["camera_pose"] initial_object_poses = all_data[0]["object_poses"] - likelihood_args = { - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - "image_height": Pytree.const(image_height), - "image_width": Pytree.const(image_width), - } - object_indices = ( [object] if object is not None else range(len(initial_object_poses)) ) @@ -178,140 +118,76 @@ def _gvmf_and_select_best_move( * (xyz_observed[..., 2] > 0) * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) ) - mesh = Mesh( - vertices=template_pose.inv().apply(xyz_rendered[mask]), - faces=jnp.zeros((0, 3), dtype=jnp.int32), - vertex_attributes=all_data[T]["rgbd"][..., :3][mask], - ) - - outlier_probability_sweep = jnp.array([0.05, 1.0]) - - choicemap = genjax.ChoiceMap.d( - { - "rgbd": all_data[T]["rgbd"], - "camera_pose": Pose.identity(), - "object_pose_0": template_pose, - "outlier_probability": jnp.ones(len(mesh.vertices)) - * outlier_probability_sweep[0], - "color_noise_variance": 0.05, - "depth_noise_variance": 0.01, - } - ) - - trace0, _ = importance_jit( - jax.random.PRNGKey(2), - choicemap, - ( + model_vertices = template_pose.inv().apply(xyz_rendered[mask]) + model_colors = all_data[T]["rgbd"][..., :3][mask] + + subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[ + : min(10000, len(model_vertices)) + ] + model_vertices = model_vertices[subset] + model_colors = model_colors[subset] + + num_vertices = model_vertices.shape[0] + previous_state = { + "pose": template_pose, + "colors": model_colors, + "visibility_prob": jnp.ones(num_vertices) + * hyperparams["visibility_prob_kernel"].possible_values[-1], + "depth_nonreturn_prob": jnp.ones(num_vertices) + * hyperparams["depth_nonreturn_prob_kernel"].possible_values[0], + "depth_scale": hyperparams["depth_scale_kernel"].possible_values[0], + "color_scale": hyperparams["color_scale_kernel"].possible_values[0], + } + + hyperparams["vertices"] = model_vertices + hyperparams["fx"] = fx + hyperparams["fy"] = fy + hyperparams["cx"] = cx + hyperparams["cy"] = cy + hyperparams["image_height"] = Pytree.const(image_height) + hyperparams["image_width"] = Pytree.const(image_width) + choicemap = ( + genjax.ChoiceMap.d( { - "num_objects": Pytree.const(1), - "meshes": [mesh], - "likelihood_args": likelihood_args, - }, - ), + "pose": previous_state["pose"], + "color_scale": previous_state["color_scale"], + "depth_scale": previous_state["depth_scale"], + "rgbd": all_data[T]["rgbd"], + } + ) + ^ make_visibility_prob_choicemap(previous_state["visibility_prob"]) + ^ make_colors_choicemap(previous_state["colors"]) + ^ make_depth_nonreturn_prob_choicemap( + previous_state["depth_nonreturn_prob"] + ) ) - key = jax.random.PRNGKey(100) + key = jax.random.PRNGKey(0) - trace = trace0 tracking_results = {} - for T in tqdm(range(len(all_data))): - trace = b3d.update_choices( - trace, - Pytree.const(("rgbd",)), - all_data[T]["rgbd"], - ) + trace = dynamic_object_generative_model.importance( + key, choicemap, (hyperparams, previous_state) + )[0] - for _ in range(5): - trace, key = gvmf_and_select_best_move( - trace, - key, - 0.01, - 1000.0, - Pytree.const(("object_pose_0",)), - 10000, - ) - trace, key = gvmf_and_select_best_move( - trace, - key, - 0.005, - 2000.0, - Pytree.const(("object_pose_0",)), - 10000, - ) - # viz_trace(trace, T) + from b3d.chisight.gen3d.inference import inference_step - if T % 1 == 0: - trace = b3d.bayes3d.enumerative_proposals.enumerate_and_select_best( - trace, - Pytree.const(("color_noise_variance",)), - jnp.linspace(0.05, 0.1, 10), - ) - trace = b3d.bayes3d.enumerative_proposals.enumerate_and_select_best( - trace, - Pytree.const(("depth_noise_variance",)), - jnp.linspace(0.005, 0.01, 10), - ) + ### Run inference ### + for T in tqdm(range(len(all_data))): + key = b3d.split_key(key) + trace = inference_step(trace, key, all_data[T]["rgbd"]) + tracking_results[T] = trace - current_outlier_probabilities = trace.get_choices()[ - "outlier_probability" - ] - scores = grid_outlier_prob( - trace, - outlier_probability_sweep[..., None] - * jnp.ones_like(current_outlier_probabilities), - ) - trace = b3d.update_choices( + if debug: + b3d.chisight.gen3d.model.viz_trace( trace, - Pytree.const(("outlier_probability",)), - outlier_probability_sweep[jnp.argmax(scores, axis=0)], - ) - - current_outlier_probabilities = trace.get_choices()[ - "outlier_probability" - ] - # b3d.rr_log_cloud( - # mesh.vertices, - # colors=colors[1 * (current_outlier_probabilities == outlier_probability_sweep[0])], - # channel="cloud/outlier_probabilities" - # ) - - info = info_from_trace(trace) - current_outlier_probabilities = trace.get_choices()[ - "outlier_probability" - ] - model_rgbd, observed_rgbd = ( - info["model_rgbd"], - info["corresponding_observed_rgbd"], + T, + ground_truth_vertices=meshes[OBJECT_INDEX].vertices, + ground_truth_pose=all_data[T]["camera_pose"].inv() + @ all_data[T]["object_poses"][OBJECT_INDEX], ) - deltas = observed_rgbd - model_rgbd - deltas_clipped = jnp.clip(deltas, -0.05, 0.05) - new_model_rgbd = model_rgbd + deltas_clipped - - mesh = trace.get_args()[0]["meshes"][0] - is_inlier = ( - current_outlier_probabilities == outlier_probability_sweep[0] - ) - mesh.vertex_attributes = mesh.vertex_attributes.at[is_inlier].set( - new_model_rgbd[is_inlier, :3] - ) - - trace, _ = importance_jit( - jax.random.PRNGKey(2), - trace.get_choices(), - ( - { - "num_objects": Pytree.const(1), - "meshes": [mesh], - "likelihood_args": likelihood_args, - }, - ), - ) - tracking_results[T] = trace - if debug: - viz_trace(trace, T) inferred_poses = Pose.stack_poses( [ - tracking_results[t].get_choices()["object_pose_0"] + tracking_results[t].get_choices()["pose"] for t in range(len(all_data)) ] ) diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index ce90429e..5d5f0ba6 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -141,7 +141,7 @@ def propose_a_points_attributes( """ return _propose_a_points_attributes( key, - observed_rgbd=observed_rgbd_for_point, + observed_rgbd_for_point=observed_rgbd_for_point, latent_depth=new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2], previous_color=prev_state["colors"][vertex_index], previous_visibility_prob=prev_state["visibility_prob"][vertex_index], @@ -158,7 +158,7 @@ def propose_a_points_attributes( def _propose_a_points_attributes( key, - observed_rgbd, + observed_rgbd_for_point, latent_depth, previous_color, previous_visibility_prob, @@ -181,7 +181,7 @@ def score_attribute_assignment(color, visprob, dnrprob): dnrprob_transition_score = dnrp_transition_kernel.logpdf(dnrprob, previous_dnrp) color_transition_score = color_kernel.logpdf(color, previous_color) likelihood_score = obs_rgbd_kernel.logpdf( - observed_rgbd=observed_rgbd, + observed_rgbd=observed_rgbd_for_point, latent_rgbd=jnp.append(color, latent_depth), color_scale=color_scale, depth_scale=depth_scale, @@ -209,7 +209,7 @@ def score_attribute_assignment(color, visprob, dnrprob): key=k, visprob=visprob_dnrprob_pair[0], dnrprob=visprob_dnrprob_pair[1], - observed_rgb=observed_rgbd[:3], + observed_rgb=observed_rgbd_for_point[:3], score_attribute_assignment=score_attribute_assignment, previous_rgb=previous_color, color_scale=color_scale, diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index 901f206d..79facb52 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -181,3 +181,6 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): ground_truth_pose.apply(ground_truth_vertices), "scene/ground_truth_object_mesh", ) + + b3d.rr_log_pose(ground_truth_pose, "scene/ground_truth_pose") + b3d.rr_log_pose(trace.get_choices()["pose"], "scene/inferred_pose") diff --git a/src/b3d/utils.py b/src/b3d/utils.py index 798064a5..3c268faa 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -597,17 +597,6 @@ def nn_background_segmentation(images): return masks -def rr_log_pose(channel, pose, scale=0.1): - origins = jnp.tile(pose.pos[None, ...], (3, 1)) - colors = jnp.eye(3) - rr.log( - channel, - rr.Arrows3D( - origins=origins, vectors=pose.as_matrix()[:3, :3].T * scale, colors=colors - ), - ) - - def rr_init(name="demo"): rr.init(name) rr.connect("127.0.0.1:8812") @@ -640,6 +629,17 @@ def rr_log_cloud(cloud, channel="cloud", colors=None): rr.log(channel, rr.Points3D(cloud.reshape(-1, 3), colors=colors.reshape(-1, 3))) +def rr_log_pose(pose, channel="pose", scale=0.1): + origins = jnp.tile(pose.pos[None, ...], (3, 1)) + colors = jnp.eye(3) + rr.log( + channel, + rr.Arrows3D( + origins=origins, vectors=pose.as_matrix()[:3, :3].T * scale, colors=colors + ), + ) + + def rr_set_time(t=0): rr.set_time_sequence("step", t) diff --git a/tests/gen3d/test_inference.py b/tests/gen3d/test_inference.py new file mode 100644 index 00000000..9536e300 --- /dev/null +++ b/tests/gen3d/test_inference.py @@ -0,0 +1,265 @@ +import b3d.chisight.gen3d.image_kernel as image_kernel +import b3d.chisight.gen3d.inference as inference +import b3d.chisight.gen3d.inference_moves as inference_moves +import b3d.chisight.gen3d.transition_kernels as transition_kernels +import jax +import jax.numpy as jnp +import pytest + + +@pytest.fixture +def hyperparams_and_inference_hyperparams(): + near, far, image_height, image_width = 0.001, 5.0, 480, 640 + img_model = image_kernel.NoOcclusionPerVertexImageKernel( + near, far, image_height, image_width + ) + color_transiton_scale = 0.05 + p_resample_color = 0.005 + + # This parameter is needed for the inference hyperparameters. + # See the `InferenceHyperparams` docstring in `inference.py` for details. + effective_color_transition_scale = color_transiton_scale + p_resample_color * 1 / 2 + inference_hyperparams = inference.InferenceHyperparams( + n_poses=6000, + pose_proposal_std=0.04, + pose_proposal_conc=1000.0, + effective_color_transition_scale=effective_color_transition_scale, + ) + + hyperparams = { + "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.1), + "color_kernel": transition_kernels.MixtureDriftKernel( + [ + transition_kernels.LaplaceNotTruncatedColorDriftKernel( + scale=color_transiton_scale + ), + transition_kernels.UniformDriftKernel( + max_shift=0.15, min_val=jnp.zeros(3), max_val=jnp.ones(3) + ), + ], + jnp.array([1 - p_resample_color, p_resample_color]), + ), + "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, support=jnp.array([0.01, 0.99]) + ), + "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, support=jnp.array([0.01, 0.99]) + ), + "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, + support=jnp.array([0.0025, 0.01, 0.02, 0.1, 0.4, 1.0]), + ), + "color_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15, 0.3, 0.8]) + ), + "image_kernel": img_model, + } + return hyperparams, inference_hyperparams + + +def test_visibility_prob_inference(hyperparams_and_inference_hyperparams): + hyperparams, inference_hyperparams = hyperparams_and_inference_hyperparams + + color_scale = 0.01 + depth_scale = 0.001 + + depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + color_kernel = hyperparams["color_kernel"] + obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() + + previous_color = jnp.array([0.1, 0.2, 0.3]) + previous_dnrp = depth_nonreturn_prob_kernel.support[0] + latent_depth = 1.0 + + def get_visibility_prob_sample( + key, observed_rgbd_for_point, previous_visibility_prob + ): + _, visibility_prob, _, _, _ = inference_moves._propose_a_points_attributes( + key, + observed_rgbd_for_point, + latent_depth, + previous_color, + previous_visibility_prob, + previous_dnrp, + depth_nonreturn_prob_kernel, + visibility_prob_kernel, + color_kernel, + obs_rgbd_kernel, + color_scale, + depth_scale, + inference_hyperparams, + return_metadata=True, + ) + return visibility_prob + + get_visibility_prob_samples = jax.vmap( + get_visibility_prob_sample, in_axes=(0, None, None) + ) + + keys = jax.random.split(jax.random.PRNGKey(0), 1000) + + # Verify that when the color matches exactly but the depth change drasticaly, the visibility prob switches to low. + previous_visibility_prob = visibility_prob_kernel.support[-1] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 4.0]) + visibility_prob_samples = get_visibility_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_visibility_prob + ) + assert visibility_prob_samples.mean() < 0.15 + + # Verify that when the color matches exactly but the depth change drasticaly, the visibility prob stays low. + previous_visibility_prob = visibility_prob_kernel.support[0] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 4.0]) + visibility_prob_samples = get_visibility_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_visibility_prob + ) + assert visibility_prob_samples.mean() < 0.03 + + # Verify that when the color matches exactly and the depth is close, the visibility prob switches to being high. + previous_visibility_prob = visibility_prob_kernel.support[0] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 1.0]) + visibility_prob_samples = get_visibility_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_visibility_prob + ) + assert visibility_prob_samples.mean() > 0.85 + + # Verify that when the color matches exactly and the depth is close, the visibility prob stays high. + previous_visibility_prob = visibility_prob_kernel.support[-1] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 1.0]) + visibility_prob_samples = get_visibility_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_visibility_prob + ) + assert visibility_prob_samples.mean() > 0.97 + + +def test_depth_nonreturn_prob_inference(hyperparams_and_inference_hyperparams): + hyperparams, inference_hyperparams = hyperparams_and_inference_hyperparams + + color_scale = 0.01 + depth_scale = 0.001 + + depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + color_kernel = hyperparams["color_kernel"] + obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() + + previous_color = jnp.array([0.1, 0.2, 0.3]) + previous_visibility_prob = visibility_prob_kernel.support[-1] + latent_depth = 1.0 + + def get_dnr_prob_sample(key, observed_rgbd_for_point, previous_dnrp): + _, _, dnr_prob, _, _ = inference_moves._propose_a_points_attributes( + key, + observed_rgbd_for_point, + latent_depth, + previous_color, + previous_visibility_prob, + previous_dnrp, + depth_nonreturn_prob_kernel, + visibility_prob_kernel, + color_kernel, + obs_rgbd_kernel, + color_scale, + depth_scale, + inference_hyperparams, + return_metadata=True, + ) + return dnr_prob + + get_dnr_prob_samples = jax.vmap(get_dnr_prob_sample, in_axes=(0, None, None)) + + keys = jax.random.split(jax.random.PRNGKey(0), 1000) + + # If depth is nonreturn, the depth nonreturn prob should stay high. + previous_dnrp = depth_nonreturn_prob_kernel.support[-1] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 0.0]) + dnr_prob_samples = get_dnr_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_dnrp + ) + assert dnr_prob_samples.mean() > 0.95 + + # If depth is nonreturn, the depth nonreturn prob should become high. + previous_dnrp = depth_nonreturn_prob_kernel.support[0] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 0.0]) + dnr_prob_samples = get_dnr_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_dnrp + ) + assert dnr_prob_samples.mean() < 0.90 + + # If depth is valid, the depth nonreturn prob should become low. + previous_dnrp = depth_nonreturn_prob_kernel.support[-1] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 1.0]) + dnr_prob_samples = get_dnr_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_dnrp + ) + assert dnr_prob_samples.mean() < 0.15 + + # If depth is valid, the depth nonreturn prob should stay low. + previous_dnrp = depth_nonreturn_prob_kernel.support[0] + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 1.0]) + dnr_prob_samples = get_dnr_prob_samples( + keys, observed_rgbd_for_this_vertex, previous_dnrp + ) + assert dnr_prob_samples.mean() < 0.1 + + +def test_color_prob_inference(hyperparams_and_inference_hyperparams): + hyperparams, inference_hyperparams = hyperparams_and_inference_hyperparams + + color_scale = 0.01 + depth_scale = 0.001 + + depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + color_kernel = hyperparams["color_kernel"] + obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() + + previous_visibility_prob = visibility_prob_kernel.support[-1] + previous_dnrp = depth_nonreturn_prob_kernel.support[0] + latent_depth = 1.0 + + def get_color_sample(key, observed_rgbd_for_point, previous_color): + rgb, _, _, _, _ = inference_moves._propose_a_points_attributes( + key, + observed_rgbd_for_point, + latent_depth, + previous_color, + previous_visibility_prob, + previous_dnrp, + depth_nonreturn_prob_kernel, + visibility_prob_kernel, + color_kernel, + obs_rgbd_kernel, + color_scale, + depth_scale, + inference_hyperparams, + return_metadata=True, + ) + return rgb + + get_color_samples = jax.vmap(get_color_sample, in_axes=(0, None, None)) + + keys = jax.random.split(jax.random.PRNGKey(0), 1000) + + # If depth match and colors match, the color should stay the same. + previous_color = jnp.array([0.1, 0.2, 0.3]) + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, latent_depth]) + color_samples = get_color_samples( + keys, observed_rgbd_for_this_vertex, previous_color + ) + assert jnp.max(jnp.abs(color_samples - previous_color)) < 0.02 + + # # If depths match and colors slightly change, then the color should move. + previous_color = jnp.array([0.15, 0.25, 0.35]) + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, latent_depth]) + color_samples = get_color_samples( + keys, observed_rgbd_for_this_vertex, previous_color + ) + assert ( + jnp.max( + jnp.abs( + jnp.median(color_samples, axis=0) - observed_rgbd_for_this_vertex[:3] + ) + ) + < 0.03 + ) From 335514f1b2d3b0fdb52b47e32c22c9f966be6e8e Mon Sep 17 00:00:00 2001 From: georgematheos Date: Thu, 12 Sep 2024 16:07:01 -0400 Subject: [PATCH 13/37] Fix bugs in inference (#164) @nishadgothoskar this seems to remove the NaN bugs. Inference seems like it works alright, but it does get off eventually -- and I think it isn't honing in closely enough to the right pose. So I think it is a good next step to do as you suggested and add several coarse-to-fine steps. --- notebooks/bayes3d_paper/tester.ipynb | 50 +++++++++----- src/b3d/chisight/gen3d/inference.py | 71 ++++++++++++++++---- src/b3d/chisight/gen3d/inference_moves.py | 79 +++++++++++++++++++++-- 3 files changed, 166 insertions(+), 34 deletions(-) diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 5e05220e..890f1738 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -51,7 +51,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 13.52it/s]\n", + "100%|██████████| 49/49 [00:03<00:00, 13.44it/s]\n", "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", " warnings.warn(\n" @@ -310,7 +310,16 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "### Single timestep test ###" + ] + }, + { + "cell_type": "code", + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -322,30 +331,31 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(43455.8, dtype=float32)" + "Array(9702.458, dtype=float32)" ] }, - "execution_count": 40, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "inference_hyperparams = InferenceHyperparams(\n", - " n_poses=6000,\n", - " pose_proposal_std=0.04,\n", - " pose_proposal_conc=1000.,\n", + " n_poses=3000,\n", + " pose_proposal_std=0.02,\n", + " pose_proposal_conc=2000.,\n", " effective_color_transition_scale=effective_color_transition_scale\n", ")\n", "\n", - "trace, step_weight, metadata = i.inference_step(\n", + "trace, step_weight = i.inference_step_using_sequential_proposals(\n", " jax.random.PRNGKey(21),\n", + " 4, # propose 3000 poses 4 times, and resample among all these options\n", " trace,\n", " all_data[0][\"rgbd\"],\n", " inference_hyperparams\n", @@ -355,7 +365,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -365,21 +375,30 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "### Run against video ###" + ] + }, + { + "cell_type": "code", + "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/49 [00:00 Date: Thu, 12 Sep 2024 16:09:34 -0400 Subject: [PATCH 14/37] Improve jitting, add first draft of c2f (#165) --- notebooks/bayes3d_paper/tester.ipynb | 696 ++++++++++++++++++++-- scratch.py | 0 src/b3d/chisight/gen3d/image_kernel.py | 8 +- src/b3d/chisight/gen3d/inference.py | 111 +++- src/b3d/chisight/gen3d/inference_moves.py | 41 +- src/b3d/chisight/gen3d/model.py | 31 +- src/b3d/utils.py | 17 + 7 files changed, 827 insertions(+), 77 deletions(-) create mode 100644 scratch.py diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 890f1738..13ee3ab1 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -32,7 +32,7 @@ "metadata": {}, "outputs": [], "source": [ - "b3d.rr_init(\"inference_test\")" + "b3d.rr_init(\"inference_test2\")" ] }, { @@ -51,7 +51,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 13.44it/s]\n", + "100%|██████████| 49/49 [00:03<00:00, 13.38it/s]\n", "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", " warnings.warn(\n" @@ -174,15 +174,15 @@ "metadata": {}, "outputs": [], "source": [ - "color_transiton_scale = 0.001\n", - "p_resample_color = 0.005\n", + "color_transiton_scale = 0.04\n", + "p_resample_color = 0.01\n", "\n", "# This parameter is needed for the inference hyperparameters.\n", "# See the `InferenceHyperparams` docstring in `inference.py` for details.\n", "effective_color_transition_scale = color_transiton_scale + p_resample_color * 1/2\n", "\n", "hyperparams = {\n", - " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", + " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=1.0),\n", " \"color_kernel\": transition_kernels.MixtureDriftKernel(\n", " [\n", " transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=color_transiton_scale),\n", @@ -193,16 +193,16 @@ " jnp.array([1-p_resample_color, p_resample_color])\n", " ),\n", " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", + " resample_probability=0.05, support=jnp.array([0.0, 0.998])\n", " ),\n", " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", + " resample_probability=0.05, support=jnp.array([0.002, 0.998])\n", " ),\n", " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02, .1, .4, 1.])\n", + " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02, .1])#, .1, .4, 1.])\n", " ),\n", " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.05, 0.1, 0.15, .3, .8])\n", + " resample_probability=0.05, support=jnp.array([0.01, 0.05, 0.1, .3])#, 0.15, .3, .8])\n", " ),\n", "\n", " \"image_kernel\": img_model,\n", @@ -274,7 +274,7 @@ { "data": { "text/plain": [ - "Array(158884.22, dtype=float32)" + "Array(120035.86, dtype=float32)" ] }, "execution_count": 13, @@ -284,7 +284,8 @@ ], "source": [ "key = jax.random.PRNGKey(0)\n", - "trace, weight = dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", + "og_trace, weight = dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", + "trace = og_trace\n", "weight" ] }, @@ -296,7 +297,7 @@ { "data": { "text/plain": [ - "Array(158884.22, dtype=float32)" + "Array(120035.86, dtype=float32)" ] }, "execution_count": 14, @@ -313,13 +314,45 @@ "execution_count": 15, "metadata": {}, "outputs": [], + "source": [ + "# My TODOs:\n", + "# 1. Coarse to fine\n", + "# 1.5 Fix JITTING\n", + "# 2. Rerun blueprint to improve debugging workflow\n", + "# 3. Set up Nishad's suggested test\n", + "## Nishad's suggestion - debug with inference only over color, visibility probs, and pose.\n", + "## He will send me hyperparams he had used for this." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], "source": [ "### Single timestep test ###" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "def gt_pose(T):\n", + " return all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]" + ] + }, + { + "cell_type": "code", + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -331,51 +364,99 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "T = 0\n", + "b3d.rr_init(\"inference9\")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.chisight.gen3d.model.viz_trace(og_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" + ] + }, + { + "cell_type": "code", + "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(9702.458, dtype=float32)" + "Array(71066.09, dtype=float32)" ] }, - "execution_count": 25, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "inference_hyperparams = InferenceHyperparams(\n", - " n_poses=3000,\n", - " pose_proposal_std=0.02,\n", - " pose_proposal_conc=2000.,\n", + "inference_hyperparams = i.InferenceHyperparams(\n", + " n_poses=1500,\n", + " do_stochastic_color_proposals=False,\n", + " pose_proposal_std=0.04,\n", + " pose_proposal_conc=1000.,\n", " effective_color_transition_scale=effective_color_transition_scale\n", ")\n", "\n", - "trace, step_weight = i.inference_step_using_sequential_proposals(\n", - " jax.random.PRNGKey(21),\n", - " 4, # propose 3000 poses 4 times, and resample among all these options\n", - " trace,\n", - " all_data[0][\"rgbd\"],\n", - " inference_hyperparams\n", + "trace, step_weight, metadata = i.inference_step(\n", + " jax.random.PRNGKey(24),\n", + " og_trace,\n", + " all_data[1][\"rgbd\"],\n", + " inference_hyperparams,\n", + " gt_pose = gt_pose(1),\n", + " get_metadata=True\n", ")\n", "step_weight" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ - "T = 0\n", + "T = 1\n", "b3d.chisight.gen3d.model.viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['chosen_pose_index', 'log_q_nonpose_latents', 'log_q_poses', 'other_latents_metadata', 'p_scores', 'proposed_poses'])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metadata.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -384,39 +465,572 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init(\"inference_test7\")" + ] + }, + { + "cell_type": "code", + "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/20 [00:00 PixelRGBDDistribution: # they don't expect observed_rgbd to be invalid, so we need to handle # that manually. return FullPixelRGBDDistribution( - TruncatedLaplacePixelColorDistribution(), + RenormalizedLaplacePixelColorDistribution(), UniformPixelColorDistribution(), - TruncatedLaplacePixelDepthDistribution(self.near, self.far), + RenormalizedLaplacePixelDepthDistribution(self.near, self.far), UniformPixelDepthDistribution(self.near, self.far), ) diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 125e3b34..6ceb0aa9 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -1,15 +1,15 @@ from functools import partial, wraps -from typing import NamedTuple import jax import jax.numpy as jnp import jax.random from genjax import ChoiceMapBuilder as C -from genjax import Diff +from genjax import Diff, Pytree from genjax import UpdateProblemBuilder as U from jax.random import split from b3d.chisight.gen3d.inference_moves import ( + get_pose_proposal_density, propose_other_latents_given_pose, propose_pose, ) @@ -19,11 +19,15 @@ ) -# Use namedtuple rather than dict so we can hash this, and use it as a static arg to a jitted function. -class InferenceHyperparams(NamedTuple): +@Pytree.dataclass +class InferenceHyperparams(Pytree): """ Parameters for the inference algorithm. - n_poses: Number of poses to propose at each timestep. + - do_stochastic_color_proposals: If true, the color proposal will be + absolutely continuous w.r.t. the Lebesgue measure on [0, 1]^3. + If false, the color proposal will consider returning exactly the + old color, and exactly the new color. - pose_proposal_std: Standard deviation of the position distribution for the pose. - pose_proposal_conc: Concentration parameter for the orientation distribution for the pose. - effective_color_transition_scale: This parameter is used in the color proposal. @@ -35,7 +39,8 @@ class InferenceHyperparams(NamedTuple): we conducted in the laplace case.) """ - n_poses: int + n_poses: int = Pytree.static() + do_stochastic_color_proposals: bool = Pytree.static() pose_proposal_std: float pose_proposal_conc: float effective_color_transition_scale: float @@ -64,43 +69,98 @@ def advance_time(key, trace, observed_rgbd): return trace +DEFAULT_C2F_SEQ = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] + + +def inference_step_c2f( + key, n_seq, n_poses_per_sequential_step, old_trace, observed_rgbd, *args, **kwargs +): + k1, k2 = split(key) + trace = advance_time(k1, old_trace, observed_rgbd) + return infer_latents_c2f( + k2, n_seq, n_poses_per_sequential_step, trace, *args, **kwargs + ) + + +def infer_latents_c2f( + key, + n_seq, + n_poses_per_sequential_step, + trace, + effective_color_transition_scale, + do_stochastic_color_proposals=True, + pose_proposal_std_conc_seq=DEFAULT_C2F_SEQ, +): + for std, conc in pose_proposal_std_conc_seq: + inference_hyperparams = InferenceHyperparams( + n_poses=n_poses_per_sequential_step, + do_stochastic_color_proposals=do_stochastic_color_proposals, + pose_proposal_std=std, + pose_proposal_conc=conc, + effective_color_transition_scale=effective_color_transition_scale, + ) + key, _ = split(key) + trace, _ = infer_latents_using_sequential_proposals( + key, n_seq, trace, inference_hyperparams + ) + + return trace + + def inference_step_using_sequential_proposals( key, n_seq, old_trace, observed_rgbd, inference_hyperparams ): + k1, k2 = split(key) + trace = advance_time(k1, old_trace, observed_rgbd) + return infer_latents_using_sequential_proposals( + k2, n_seq, trace, inference_hyperparams + ) + + +def infer_latents_using_sequential_proposals(key, n_seq, trace, inference_hyperparams): """ Like `inference_step`, but does `n_seq` sequential proposals of `inference_hyperparams.n_poses` poses and other latents, and resamples one among all of these. Returns `(trace, weight)`. """ - shared_args = (old_trace, observed_rgbd, inference_hyperparams) + shared_args = (trace, inference_hyperparams) def get_weight(key): - return inference_step(key, *shared_args, get_trace=False, get_metadata=False)[0] + return infer_latents(key, *shared_args, get_trace=False, get_metadata=False)[0] k1, k2 = split(key) ks = split(k1, n_seq) - weights = [] - for k in ks: - weights.append(get_weight(k)) + weights = [get_weight(k) for k in ks] + print("weights: ", weights) normalized_logps = jax.nn.log_softmax(jnp.array(weights)) chosen_idx = jax.random.categorical(k2, normalized_logps) - trace, _ = inference_step(ks[chosen_idx], *shared_args, get_metadata=False) + trace, _ = infer_latents(ks[chosen_idx], *shared_args, get_metadata=False) overall_weight = jax.scipy.special.logsumexp(jnp.array(weights)) return trace, overall_weight -@partial(jax.jit, static_argnums=(3, 4, 5, 6)) def inference_step( + key, old_trace, observed_rgbd, inference_hyperparams, *args, **kwargs +): + k1, k2 = split(key) + trace = advance_time(k1, old_trace, observed_rgbd) + return infer_latents(k2, trace, inference_hyperparams, *args, **kwargs) + + +@partial(jax.jit, static_argnums=(3, 4, 5, 6)) +def infer_latents( key, - old_trace, - observed_rgbd, + trace, inference_hyperparams, get_trace=True, get_weight=True, get_metadata=True, + # If this is included, we guarantee that this is one of the + # poses in the grid. + gt_pose=None, ): """ Perform over the latent state at time T, given the observed @@ -108,27 +168,38 @@ def inference_step( Also returns an estimate of the marginal likelihood of the observed rgbd, given the latent state from time T-1. - """ - k1, k2, k3, k4 = split(key, 4) - trace = advance_time(k1, old_trace, observed_rgbd) + If `gt_pose` is not None, this will force the pose sampled at index 0 + in the sampling step to be `gt_pose`. (That is, this will do inference + as would occur given that the ground truth pose was the first sampled + pose.) + """ + _, k2, k3, _ = split(key, 4) pose_generation_keys = split(k2, inference_hyperparams.n_poses) proposed_poses, log_q_poses = jax.vmap(propose_pose, in_axes=(0, None, None))( pose_generation_keys, trace, inference_hyperparams ) + if gt_pose is not None: + proposed_poses = jax.tree.map( + lambda x, y: x.at[0].set(y), proposed_poses, gt_pose + ) + log_q_poses = log_q_poses.at[0].set( + get_pose_proposal_density(gt_pose, trace, inference_hyperparams) + ) + param_generation_keys = split(k3, inference_hyperparams.n_poses) proposed_traces, log_q_nonpose_latents, other_latents_metadata = jax.vmap( propose_other_latents_given_pose, in_axes=(0, None, 0, None) )(param_generation_keys, trace, proposed_poses, inference_hyperparams) p_scores = jax.vmap(lambda tr: tr.get_score())(proposed_traces) - scores = p_scores - log_q_poses - log_q_nonpose_latents - chosen_index = jax.random.categorical(k4, scores) + scores = p_scores # - log_q_poses - log_q_nonpose_latents + chosen_index = jnp.argmax(scores) # jax.random.categorical(k4, scores) new_trace = jax.tree.map(lambda x: x[chosen_index], proposed_traces) - weight = logmeanexp(scores) + weight = jnp.max(scores) # logmeanexp(scores) metadata = { "proposed_poses": proposed_poses, "chosen_pose_index": chosen_index, diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index 29ed3e14..64a8d25d 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -36,7 +36,7 @@ def propose_pose(key, advanced_trace, inference_hyperparams): Propose a random pose near the previous timestep's pose. Returns (proposed_pose, log_proposal_density). """ - previous_pose = get_prev_state(advanced_trace)["pose"] + previous_pose = get_new_state(advanced_trace)["pose"] ih = inference_hyperparams pose = Pose.sample_gaussian_vmf_pose( key, previous_pose, ih.pose_proposal_std, ih.pose_proposal_conc @@ -47,6 +47,17 @@ def propose_pose(key, advanced_trace, inference_hyperparams): return pose, log_q +def get_pose_proposal_density(pose, advanced_trace, inference_hyperparams): + """ + Returns the log proposal density of the given pose, conditional upon the previous pose. + """ + previous_pose = get_prev_state(advanced_trace)["pose"] + ih = inference_hyperparams + return Pose.logpdf_gaussian_vmf_pose( + pose, previous_pose, ih.pose_proposal_std, ih.pose_proposal_conc + ) + + def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperparams): """ Proposes all latents other than the pose, conditional upon the pose and observed RGBD @@ -73,8 +84,6 @@ def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperp ["colors", "visibility_prob", "depth_nonreturn_prob"], [colors, visibility_probs, depth_nonreturn_probs], ) - # TODO: debug these scores -- right now they are causing bad behavior - # log_q_point_attributes = 0.0 k3a, k3b = split(k3) depth_scale, log_q_ds = propose_depth_scale(k3a, trace) @@ -228,7 +237,7 @@ def score_attribute_assignment(color, visprob, dnrprob): in_axes=(0, 0), )(all_visprob_dnrprob_pairs, rgbs) - log_weights = log_pscores - log_qs_rgb + log_weights = log_pscores # - log_qs_rgb log_normalized_scores = normalize_log_scores(log_weights) index = jax.random.categorical(k2, log_normalized_scores) @@ -274,7 +283,9 @@ def propose_vertex_color_given_other_attributes( inference_hyperparams, ) ) - value_if_observed_is_invalid = color_kernel.sample(key, previous_rgb) + value_if_observed_is_invalid = jnp.zeros( + 3 + ) # color_kernel.sample(key, previous_rgb) log_q_if_invalid = color_kernel.logpdf(value_if_observed_is_invalid, previous_rgb) isvalid = ~jnp.any(observed_rgb < 0) @@ -342,7 +353,10 @@ def propose_vertex_color_given_other_attributes_for_valid_observed_rgb( ## Proposal 1: near the previous value. min_rgbs1 = jnp.maximum(0.0, previous_rgb - diffs / 10 - 2 * d) max_rgbs1 = jnp.minimum(1.0, previous_rgb + diffs / 10 + 2 * d) - proposed_rgb_1 = uniform.sample(k1, min_rgbs1, max_rgbs1) + if inference_hyperparams.do_stochastic_color_proposals: + proposed_rgb_1 = uniform.sample(k1, min_rgbs1, max_rgbs1) + else: + proposed_rgb_1 = previous_rgb log_q_rgb_1 = uniform.logpdf(proposed_rgb_1, min_rgbs1, max_rgbs1) metadata["min_rgbs1"] = min_rgbs1 metadata["max_rgbs1"] = max_rgbs1 @@ -350,7 +364,10 @@ def propose_vertex_color_given_other_attributes_for_valid_observed_rgb( ## Proposal 2: near the observed value. min_rgbs2 = jnp.maximum(0.0, observed_rgb - diffs / 10 - 2 * d) max_rgbs2 = jnp.minimum(1.0, observed_rgb + diffs / 10 + 2 * d) - proposed_rgb_2 = uniform.sample(k2, min_rgbs2, max_rgbs2) + if inference_hyperparams.do_stochastic_color_proposals: + proposed_rgb_2 = uniform.sample(k2, min_rgbs2, max_rgbs2) + else: + proposed_rgb_2 = observed_rgb log_q_rgb_2 = uniform.logpdf(proposed_rgb_2, min_rgbs2, max_rgbs2) metadata["min_rgbs2"] = min_rgbs2 metadata["max_rgbs2"] = max_rgbs2 @@ -359,7 +376,10 @@ def propose_vertex_color_given_other_attributes_for_valid_observed_rgb( mean_rgb = (previous_rgb + observed_rgb) / 2 min_rgbs3 = jnp.maximum(0.0, mean_rgb - 8 / 10 * diffs - 2 * d) max_rgbs3 = jnp.minimum(1.0, mean_rgb + 8 / 10 * diffs + 2 * d) - proposed_rgb_3 = uniform.sample(k3, min_rgbs3, max_rgbs3) + if inference_hyperparams.do_stochastic_color_proposals: + proposed_rgb_3 = uniform.sample(k3, min_rgbs3, max_rgbs3) + else: + proposed_rgb_3 = mean_rgb log_q_rgb_3 = uniform.logpdf(proposed_rgb_3, min_rgbs3, max_rgbs3) metadata["min_rgbs3"] = min_rgbs3 metadata["max_rgbs3"] = max_rgbs3 @@ -375,7 +395,7 @@ def propose_vertex_color_given_other_attributes_for_valid_observed_rgb( jax.vmap(lambda rgb: score_attribute_assignment(rgb, visprob, dnrprob))( proposed_rgbs ) - - log_qs + # - log_qs ) normalized_scores = normalize_log_scores(scores) sampled_index = jax.random.categorical(key, normalized_scores) @@ -412,7 +432,8 @@ def propose_vertex_color_given_other_attributes_for_valid_observed_rgb( metadata["log_L_score"] = log_L_score ## Compute the overall estimate of the marginal density of proposing `sampled_rgb`. - overall_score = log_K_score - log_L_score + # overall_score = log_K_score - log_L_score + overall_score = normalized_scores[sampled_index] # + log_qs["sampled_index"] metadata["overall_score"] = overall_score ## Return diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index 79facb52..5714a6b9 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -2,6 +2,7 @@ import jax import jax.numpy as jnp import rerun as rr +import rerun.blueprint as rrb from genjax import ChoiceMapBuilder as C import b3d @@ -95,6 +96,8 @@ def get_observed_rgbd(trace): ### Visualization Code ### + + def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): b3d.rr_set_time(t) hyperparams, _ = trace.get_args() @@ -133,8 +136,8 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): ), ) - rr.log("color_scale", rr.Scalar(new_state["color_scale"])) - rr.log("depth_scale", rr.Scalar(new_state["depth_scale"])) + # rr.log("color_scale", rr.Scalar(new_state["color_scale"])) + # rr.log("depth_scale", rr.Scalar(new_state["depth_scale"])) vertices_transformed = pose.apply(vertices) b3d.rr_log_cloud( @@ -184,3 +187,27 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): b3d.rr_log_pose(ground_truth_pose, "scene/ground_truth_pose") b3d.rr_log_pose(trace.get_choices()["pose"], "scene/inferred_pose") + + if not b3d.get_blueprint_logged(): + rr.send_blueprint(get_blueprint()) + b3d.set_blueprint_logged(True) + + +def get_blueprint(): + return rrb.Blueprint( + rrb.Vertical( + rrb.Horizontal( + rrb.Spatial3DView(origin="scene/"), + rrb.Horizontal( + rrb.Spatial2DView(origin="image/rgb/observed"), + rrb.Spatial2DView(origin="image/depth/observed"), + ), + ), + rrb.Horizontal( + rrb.Spatial3DView(origin="object/model"), + rrb.Spatial3DView(origin="object/visibility_prob"), + rrb.Spatial3DView(origin="object/depth_nonreturn_prob"), + rrb.TextDocumentView(origin="info"), + ), + ) + ) diff --git a/src/b3d/utils.py b/src/b3d/utils.py index 3c268faa..7d214537 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -597,7 +597,24 @@ def nn_background_segmentation(images): return masks +# This variable can be used to know whether a rerun blueprint +# has been logged since this rerun session was initialized. +_blueprint_logged = False + + +def get_blueprint_logged(): + global _blueprint_logged + return _blueprint_logged + + +def set_blueprint_logged(val): + global _blueprint_logged + _blueprint_logged = val + + def rr_init(name="demo"): + global _blueprint_logged + _blueprint_logged = False rr.init(name) rr.connect("127.0.0.1:8812") From 2674fdf43a673c61d1a128b41d1288b891e2b09f Mon Sep 17 00:00:00 2001 From: georgematheos Date: Thu, 12 Sep 2024 16:52:03 -0400 Subject: [PATCH 15/37] simplify vertex color proposal (#166) --- notebooks/bayes3d_paper/tester.ipynb | 579 ++++------------------ src/b3d/chisight/gen3d/inference.py | 23 +- src/b3d/chisight/gen3d/inference_moves.py | 107 ++-- src/b3d/modeling_utils.py | 18 +- 4 files changed, 155 insertions(+), 572 deletions(-) diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 13ee3ab1..8c4ca222 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -352,7 +352,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 86, "metadata": {}, "outputs": [], "source": [ @@ -364,17 +364,17 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 87, "metadata": {}, "outputs": [], "source": [ "T = 0\n", - "b3d.rr_init(\"inference9\")" + "b3d.rr_init(\"inference92\")" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 88, "metadata": {}, "outputs": [], "source": [ @@ -383,43 +383,51 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 89, + "metadata": {}, + "outputs": [], + "source": [ + "inference_hyperparams = i.InferenceHyperparams(\n", + " n_poses=1500,\n", + " do_stochastic_color_proposals=False,\n", + " pose_proposal_std=0.04,\n", + " pose_proposal_conc=1000.,\n", + " prev_color_proposal_laplace_scale=0.001,\n", + " obs_color_proposal_laplace_scale=0.001,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 90, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(71066.09, dtype=float32)" + "Array(71180.67, dtype=float32)" ] }, - "execution_count": 21, + "execution_count": 90, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "inference_hyperparams = i.InferenceHyperparams(\n", - " n_poses=1500,\n", - " do_stochastic_color_proposals=False,\n", - " pose_proposal_std=0.04,\n", - " pose_proposal_conc=1000.,\n", - " effective_color_transition_scale=effective_color_transition_scale\n", - ")\n", - "\n", "trace, step_weight, metadata = i.inference_step(\n", " jax.random.PRNGKey(24),\n", " og_trace,\n", " all_data[1][\"rgbd\"],\n", " inference_hyperparams,\n", - " gt_pose = gt_pose(1),\n", - " get_metadata=True\n", + " get_metadata=True,\n", + " gt_pose=gt_pose(1),\n", ")\n", "step_weight" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 91, "metadata": {}, "outputs": [], "source": [ @@ -429,7 +437,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 78, "metadata": {}, "outputs": [ { @@ -438,7 +446,7 @@ "dict_keys(['chosen_pose_index', 'log_q_nonpose_latents', 'log_q_poses', 'other_latents_metadata', 'p_scores', 'proposed_poses'])" ] }, - "execution_count": 23, + "execution_count": 78, "metadata": {}, "output_type": "execute_result" } @@ -456,7 +464,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 92, "metadata": {}, "outputs": [], "source": [ @@ -465,7 +473,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 93, "metadata": {}, "outputs": [], "source": [ @@ -474,7 +482,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 94, "metadata": {}, "outputs": [ { @@ -488,7 +496,50 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [02:49<00:00, 16.99s/it]\n" + " 80%|████████ | 8/10 [02:20<00:35, 17.56s/it]\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[94], line 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\u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m args_flat:\n\u001b[1;32m 174\u001b[0m dispatch\u001b[38;5;241m.\u001b[39mcheck_arg(arg)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:598\u001b[0m, in \u001b[0;36m_infer_params\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 591\u001b[0m in_type \u001b[38;5;241m=\u001b[39m in_avals \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(avals)\n\u001b[1;32m 593\u001b[0m in_shardings_flat, in_layouts_flat \u001b[38;5;241m=\u001b[39m _process_in_axis_resources(\n\u001b[1;32m 594\u001b[0m in_shardings_treedef, in_shardings_leaves,\n\u001b[1;32m 595\u001b[0m in_layouts_treedef, in_layouts_leaves,\n\u001b[1;32m 596\u001b[0m in_avals, in_tree, dbg, device_or_backend_set, have_kwargs)\n\u001b[0;32m--> 598\u001b[0m jaxpr, consts, out_shardings_flat, out_layouts_flat, attrs_tracked \u001b[38;5;241m=\u001b[39m 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\u001b[49m\u001b[43mclosure\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 602\u001b[0m \u001b[43m \u001b[49m\u001b[43mHashableFunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43mres_paths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclosure\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minline\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 604\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(explicit_args) \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mlen\u001b[39m(in_shardings_flat) \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mlen\u001b[39m(in_layouts_flat)\n\u001b[1;32m 606\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m config\u001b[38;5;241m.\u001b[39mdynamic_shapes\u001b[38;5;241m.\u001b[39mvalue:\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:1206\u001b[0m, in \u001b[0;36m_pjit_jaxpr\u001b[0;34m(fun, out_shardings_treedef, out_shardings_leaves, out_layouts_treedef, out_layouts_leaves, in_type, debug_info, device_or_backend_set, out_tree, result_paths, inline)\u001b[0m\n\u001b[1;32m 1203\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_pjit_jaxpr\u001b[39m(fun, out_shardings_treedef, out_shardings_leaves,\n\u001b[1;32m 1204\u001b[0m out_layouts_treedef, out_layouts_leaves, in_type, debug_info,\n\u001b[1;32m 1205\u001b[0m device_or_backend_set, out_tree, result_paths, inline):\n\u001b[0;32m-> 1206\u001b[0m jaxpr, final_consts, out_type, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43m_create_pjit_jaxpr\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1207\u001b[0m \u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug_info\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mresult_paths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mIgnoreKey\u001b[49m\u001b[43m(\u001b[49m\u001b[43minline\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1208\u001b[0m canonicalized_out_shardings_flat, out_layouts_flat \u001b[38;5;241m=\u001b[39m _check_and_canonicalize_out_shardings(\n\u001b[1;32m 1209\u001b[0m out_shardings_treedef, out_shardings_leaves, out_layouts_treedef,\n\u001b[1;32m 1210\u001b[0m out_layouts_leaves, out_tree, \u001b[38;5;28mtuple\u001b[39m(out_type),\n\u001b[1;32m 1211\u001b[0m jaxpr\u001b[38;5;241m.\u001b[39mjaxpr\u001b[38;5;241m.\u001b[39mdebug_info, device_or_backend_set)\n\u001b[1;32m 1212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (jaxpr, final_consts, canonicalized_out_shardings_flat,\n\u001b[1;32m 1213\u001b[0m out_layouts_flat, attrs_tracked)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/linear_util.py:350\u001b[0m, in \u001b[0;36mcache..memoized_fun\u001b[0;34m(fun, *args)\u001b[0m\n\u001b[1;32m 348\u001b[0m fun\u001b[38;5;241m.\u001b[39mpopulate_stores(stores)\n\u001b[1;32m 349\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 350\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[43mcall\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 351\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m explain \u001b[38;5;129;01mand\u001b[39;00m config\u001b[38;5;241m.\u001b[39mexplain_cache_misses\u001b[38;5;241m.\u001b[39mvalue:\n\u001b[1;32m 352\u001b[0m explain(fun\u001b[38;5;241m.\u001b[39mf, cache \u001b[38;5;129;01mis\u001b[39;00m new_cache, cache, key, ans)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:1154\u001b[0m, in \u001b[0;36m_create_pjit_jaxpr\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 1152\u001b[0m attrs_tracked \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 1153\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1154\u001b[0m jaxpr, global_out_avals, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43mpe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrace_to_jaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1155\u001b[0m \u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpe_debug\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1157\u001b[0m \u001b[38;5;66;03m# TODO(dougalm,mattjj): enable debug info with attrs_tracked\u001b[39;00m\n\u001b[1;32m 1158\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m config\u001b[38;5;241m.\u001b[39mdynamic_shapes\u001b[38;5;241m.\u001b[39mvalue \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m attrs_tracked:\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/profiler.py:335\u001b[0m, in \u001b[0;36mannotate_function..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 332\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(func)\n\u001b[1;32m 333\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 334\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m TraceAnnotation(name, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mdecorator_kwargs):\n\u001b[0;32m--> 335\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 336\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wrapper\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2326\u001b[0m, in \u001b[0;36mtrace_to_jaxpr_dynamic\u001b[0;34m(fun, in_avals, debug_info, keep_inputs)\u001b[0m\n\u001b[1;32m 2324\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m core\u001b[38;5;241m.\u001b[39mnew_main(DynamicJaxprTrace, dynamic\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m main: \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m 2325\u001b[0m main\u001b[38;5;241m.\u001b[39mjaxpr_stack \u001b[38;5;241m=\u001b[39m () \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[0;32m-> 2326\u001b[0m jaxpr, out_avals, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43mtrace_to_subjaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2327\u001b[0m \u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmain\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkeep_inputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeep_inputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdebug_info\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2328\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m main, fun\n\u001b[1;32m 2329\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m jaxpr, out_avals, consts, attrs_tracked\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2348\u001b[0m, in \u001b[0;36mtrace_to_subjaxpr_dynamic\u001b[0;34m(fun, main, in_avals, keep_inputs, debug_info)\u001b[0m\n\u001b[1;32m 2346\u001b[0m in_tracers \u001b[38;5;241m=\u001b[39m _input_type_to_tracers(trace\u001b[38;5;241m.\u001b[39mnew_arg, in_avals)\n\u001b[1;32m 2347\u001b[0m in_tracers_ \u001b[38;5;241m=\u001b[39m [t \u001b[38;5;28;01mfor\u001b[39;00m t, keep \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(in_tracers, keep_inputs) \u001b[38;5;28;01mif\u001b[39;00m keep]\n\u001b[0;32m-> 2348\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[43mfun\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_wrapped\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43min_tracers_\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2349\u001b[0m out_tracers \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmap\u001b[39m(trace\u001b[38;5;241m.\u001b[39mfull_raise, ans)\n\u001b[1;32m 2350\u001b[0m jaxpr, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m frame\u001b[38;5;241m.\u001b[39mto_jaxpr(out_tracers)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/linear_util.py:192\u001b[0m, in \u001b[0;36mWrappedFun.call_wrapped\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 189\u001b[0m gen \u001b[38;5;241m=\u001b[39m gen_static_args \u001b[38;5;241m=\u001b[39m out_store \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 191\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 192\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mdict\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 193\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m 194\u001b[0m \u001b[38;5;66;03m# Some transformations yield from inside context managers, so we have to\u001b[39;00m\n\u001b[1;32m 195\u001b[0m \u001b[38;5;66;03m# interrupt them before reraising the exception. Otherwise they will only\u001b[39;00m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;66;03m# get garbage-collected at some later time, running their cleanup tasks\u001b[39;00m\n\u001b[1;32m 197\u001b[0m \u001b[38;5;66;03m# only after this exception is handled, which can corrupt the global\u001b[39;00m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;66;03m# state.\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m stack:\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference.py:184\u001b[0m, in \u001b[0;36minfer_latents\u001b[0;34m(key, trace, inference_hyperparams, get_trace, get_weight, get_metadata, gt_pose)\u001b[0m\n\u001b[1;32m 179\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m gt_pose \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 180\u001b[0m proposed_poses \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mtree\u001b[38;5;241m.\u001b[39mmap(\n\u001b[1;32m 181\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m x, y: x\u001b[38;5;241m.\u001b[39mat[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset(y), proposed_poses, gt_pose\n\u001b[1;32m 182\u001b[0m )\n\u001b[1;32m 183\u001b[0m log_q_poses \u001b[38;5;241m=\u001b[39m log_q_poses\u001b[38;5;241m.\u001b[39mat[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset(\n\u001b[0;32m--> 184\u001b[0m \u001b[43mget_pose_proposal_density\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgt_pose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 185\u001b[0m )\n\u001b[1;32m 187\u001b[0m param_generation_keys \u001b[38;5;241m=\u001b[39m split(k3, inference_hyperparams\u001b[38;5;241m.\u001b[39mn_poses)\n\u001b[1;32m 188\u001b[0m proposed_traces, log_q_nonpose_latents, other_latents_metadata \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mvmap(\n\u001b[1;32m 189\u001b[0m propose_other_latents_given_pose, in_axes\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m0\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 190\u001b[0m )(param_generation_keys, trace, proposed_poses, inference_hyperparams)\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference_moves.py:56\u001b[0m, in \u001b[0;36mget_pose_proposal_density\u001b[0;34m(pose, advanced_trace, inference_hyperparams)\u001b[0m\n\u001b[1;32m 54\u001b[0m previous_pose \u001b[38;5;241m=\u001b[39m get_prev_state(advanced_trace)[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpose\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 55\u001b[0m ih \u001b[38;5;241m=\u001b[39m inference_hyperparams\n\u001b[0;32m---> 56\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mPose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlogpdf_gaussian_vmf_pose\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 57\u001b[0m \u001b[43m \u001b[49m\u001b[43mpose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprevious_pose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mih\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpose_proposal_std\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mih\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpose_proposal_conc\u001b[49m\n\u001b[1;32m 58\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/src/b3d/pose/core.py:119\u001b[0m, in \u001b[0;36mlogpdf_gaussian_vmf_pose\u001b[0;34m(pose, mean_pose, std, concentration)\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlogpdf_gaussian_vmf_pose\u001b[39m(pose, mean_pose, std, concentration):\n\u001b[1;32m 114\u001b[0m translation_score \u001b[38;5;241m=\u001b[39m tfp\u001b[38;5;241m.\u001b[39mdistributions\u001b[38;5;241m.\u001b[39mMultivariateNormalDiag(\n\u001b[1;32m 115\u001b[0m mean_pose\u001b[38;5;241m.\u001b[39mpos, jnp\u001b[38;5;241m.\u001b[39mones(\u001b[38;5;241m3\u001b[39m) \u001b[38;5;241m*\u001b[39m std\n\u001b[1;32m 116\u001b[0m )\u001b[38;5;241m.\u001b[39mlog_prob(pose\u001b[38;5;241m.\u001b[39mpos)\n\u001b[1;32m 117\u001b[0m quaternion_score \u001b[38;5;241m=\u001b[39m \u001b[43mtfp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdistributions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mVonMisesFisher\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 118\u001b[0m \u001b[43m \u001b[49m\u001b[43mmean_pose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquat\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mjnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlinalg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnorm\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmean_pose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquat\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconcentration\u001b[49m\n\u001b[0;32m--> 119\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquat\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m translation_score \u001b[38;5;241m+\u001b[39m quaternion_score\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/distribution.py:1287\u001b[0m, in \u001b[0;36mDistribution.log_prob\u001b[0;34m(self, value, name, **kwargs)\u001b[0m\n\u001b[1;32m 1275\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlog_prob\u001b[39m(\u001b[38;5;28mself\u001b[39m, value, name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlog_prob\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 1276\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Log probability density/mass function.\u001b[39;00m\n\u001b[1;32m 1277\u001b[0m \n\u001b[1;32m 1278\u001b[0m \u001b[38;5;124;03m Args:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1285\u001b[0m \u001b[38;5;124;03m values of type `self.dtype`.\u001b[39;00m\n\u001b[1;32m 1286\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1287\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_log_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/distribution.py:1269\u001b[0m, in \u001b[0;36mDistribution._call_log_prob\u001b[0;34m(self, value, name, **kwargs)\u001b[0m\n\u001b[1;32m 1267\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_name_and_control_scope(name, value, kwargs):\n\u001b[1;32m 1268\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_log_prob\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[0;32m-> 1269\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_log_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1270\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_prob\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m 1271\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prob(value, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs))\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/von_mises_fisher.py:197\u001b[0m, in \u001b[0;36mVonMisesFisher._log_prob\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 194\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_log_prob\u001b[39m(\u001b[38;5;28mself\u001b[39m, x):\n\u001b[1;32m 195\u001b[0m concentration \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconcentration)\n\u001b[1;32m 196\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_log_unnormalized_prob(x, concentration\u001b[38;5;241m=\u001b[39mconcentration) \u001b[38;5;241m-\u001b[39m\n\u001b[0;32m--> 197\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_log_normalization\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconcentration\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconcentration\u001b[49m\u001b[43m)\u001b[49m)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/von_mises_fisher.py:218\u001b[0m, in \u001b[0;36mVonMisesFisher._log_normalization\u001b[0;34m(self, concentration)\u001b[0m\n\u001b[1;32m 213\u001b[0m event_dim \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mcast(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_event_shape_tensor()[\u001b[38;5;241m0\u001b[39m], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdtype)\n\u001b[1;32m 214\u001b[0m safe_conc \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mwhere(concentration \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, concentration,\n\u001b[1;32m 215\u001b[0m tf\u001b[38;5;241m.\u001b[39mones_like(concentration))\n\u001b[1;32m 216\u001b[0m safe_lognorm \u001b[38;5;241m=\u001b[39m ((event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m) \u001b[38;5;241m*\u001b[39m tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mlog(safe_conc) \u001b[38;5;241m-\u001b[39m\n\u001b[1;32m 217\u001b[0m (event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m) \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mpi) \u001b[38;5;241m-\u001b[39m\n\u001b[0;32m--> 218\u001b[0m \u001b[43mbessel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_bessel_ive\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevent_dim\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msafe_conc\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m-\u001b[39m\n\u001b[1;32m 219\u001b[0m tf\u001b[38;5;241m.\u001b[39mabs(safe_conc))\n\u001b[1;32m 220\u001b[0m log_nsphere_surface_area \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 221\u001b[0m np\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m2.\u001b[39m) \u001b[38;5;241m+\u001b[39m (event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m) \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mlog(np\u001b[38;5;241m.\u001b[39mpi) \u001b[38;5;241m-\u001b[39m\n\u001b[1;32m 222\u001b[0m tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mlgamma(tf\u001b[38;5;241m.\u001b[39mcast(event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdtype)))\n\u001b[1;32m 223\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tf\u001b[38;5;241m.\u001b[39mwhere(concentration \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m-\u001b[39msafe_lognorm,\n\u001b[1;32m 224\u001b[0m log_nsphere_surface_area)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:1219\u001b[0m, in \u001b[0;36mlog_bessel_ive\u001b[0;34m(v, z, name)\u001b[0m\n\u001b[1;32m 1217\u001b[0m v \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(v, dtype\u001b[38;5;241m=\u001b[39mdtype)\n\u001b[1;32m 1218\u001b[0m z \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(z, dtype\u001b[38;5;241m=\u001b[39mdtype)\n\u001b[0;32m-> 1219\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_log_bessel_ive_custom_gradient\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n", + " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/custom_derivatives.py:261\u001b[0m, in \u001b[0;36mcustom_jvp.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 258\u001b[0m flat_fun, out_type1 \u001b[38;5;241m=\u001b[39m _flatten_fun_nokwargs(f_, in_tree)\n\u001b[1;32m 259\u001b[0m flat_jvp, out_type2 \u001b[38;5;241m=\u001b[39m _flatten_jvp(jvp, primal_name, jvp_name, in_tree,\n\u001b[1;32m 260\u001b[0m out_type1)\n\u001b[0;32m--> 261\u001b[0m out_flat \u001b[38;5;241m=\u001b[39m \u001b[43mcustom_jvp_call_p\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbind\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflat_jvp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs_flat\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 262\u001b[0m \u001b[43m \u001b[49m\u001b[43msymbolic_zeros\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msymbolic_zeros\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 263\u001b[0m _, (out_tree, _) \u001b[38;5;241m=\u001b[39m lu\u001b[38;5;241m.\u001b[39mmerge_linear_aux(out_type1, out_type2)\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tree_unflatten(out_tree, out_flat)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/custom_derivatives.py:363\u001b[0m, in \u001b[0;36mCustomJVPCallPrimitive.bind\u001b[0;34m(self, fun, jvp, symbolic_zeros, *args)\u001b[0m\n\u001b[1;32m 360\u001b[0m jvp, env_trace_todo2 \u001b[38;5;241m=\u001b[39m process_env_traces(\n\u001b[1;32m 361\u001b[0m jvp, \u001b[38;5;28mself\u001b[39m, top_trace \u001b[38;5;129;01mand\u001b[39;00m top_trace\u001b[38;5;241m.\u001b[39mlevel, \u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 362\u001b[0m tracers \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmap\u001b[39m(top_trace\u001b[38;5;241m.\u001b[39mfull_raise, args) \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[0;32m--> 363\u001b[0m outs \u001b[38;5;241m=\u001b[39m \u001b[43mtop_trace\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprocess_custom_jvp_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjvp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtracers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m 364\u001b[0m \u001b[43m \u001b[49m\u001b[43msymbolic_zeros\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msymbolic_zeros\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m 365\u001b[0m _, env_trace_todo \u001b[38;5;241m=\u001b[39m lu\u001b[38;5;241m.\u001b[39mmerge_linear_aux(env_trace_todo1, env_trace_todo2)\n\u001b[1;32m 366\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m core\u001b[38;5;241m.\u001b[39mapply_todos(env_trace_todo, \u001b[38;5;28mmap\u001b[39m(core\u001b[38;5;241m.\u001b[39mfull_lower, outs))\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2120\u001b[0m, in \u001b[0;36mDynamicJaxprTrace.process_custom_jvp_call\u001b[0;34m(self, prim, fun, jvp, tracers, symbolic_zeros)\u001b[0m\n\u001b[1;32m 2118\u001b[0m in_avals \u001b[38;5;241m=\u001b[39m [t\u001b[38;5;241m.\u001b[39maval \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m tracers]\n\u001b[1;32m 2119\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m core\u001b[38;5;241m.\u001b[39mnew_sublevel():\n\u001b[0;32m-> 2120\u001b[0m fun_jaxpr, out_avals, consts, () \u001b[38;5;241m=\u001b[39m \u001b[43mtrace_to_subjaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmain\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2121\u001b[0m closed_fun_jaxpr \u001b[38;5;241m=\u001b[39m core\u001b[38;5;241m.\u001b[39mClosedJaxpr(convert_constvars_jaxpr(fun_jaxpr), ())\n\u001b[1;32m 2122\u001b[0m main_ \u001b[38;5;241m=\u001b[39m ref(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmain)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2348\u001b[0m, in \u001b[0;36mtrace_to_subjaxpr_dynamic\u001b[0;34m(fun, main, in_avals, keep_inputs, debug_info)\u001b[0m\n\u001b[1;32m 2346\u001b[0m in_tracers \u001b[38;5;241m=\u001b[39m _input_type_to_tracers(trace\u001b[38;5;241m.\u001b[39mnew_arg, in_avals)\n\u001b[1;32m 2347\u001b[0m in_tracers_ \u001b[38;5;241m=\u001b[39m [t \u001b[38;5;28;01mfor\u001b[39;00m t, keep \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(in_tracers, keep_inputs) \u001b[38;5;28;01mif\u001b[39;00m keep]\n\u001b[0;32m-> 2348\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[43mfun\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_wrapped\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43min_tracers_\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2349\u001b[0m out_tracers \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmap\u001b[39m(trace\u001b[38;5;241m.\u001b[39mfull_raise, ans)\n\u001b[1;32m 2350\u001b[0m jaxpr, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m frame\u001b[38;5;241m.\u001b[39mto_jaxpr(out_tracers)\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/linear_util.py:192\u001b[0m, in \u001b[0;36mWrappedFun.call_wrapped\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 189\u001b[0m gen \u001b[38;5;241m=\u001b[39m gen_static_args \u001b[38;5;241m=\u001b[39m out_store \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 191\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 192\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mdict\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 193\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m 194\u001b[0m \u001b[38;5;66;03m# Some transformations yield from inside context managers, so we have to\u001b[39;00m\n\u001b[1;32m 195\u001b[0m \u001b[38;5;66;03m# interrupt them before reraising the exception. Otherwise they will only\u001b[39;00m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;66;03m# get garbage-collected at some later time, running their cleanup tasks\u001b[39;00m\n\u001b[1;32m 197\u001b[0m \u001b[38;5;66;03m# only after this exception is handled, which can corrupt the global\u001b[39;00m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;66;03m# state.\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m stack:\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:1190\u001b[0m, in \u001b[0;36m_log_bessel_ive_custom_gradient\u001b[0;34m(v, z)\u001b[0m\n\u001b[1;32m 1185\u001b[0m \u001b[38;5;129m@tfp_custom_gradient\u001b[39m\u001b[38;5;241m.\u001b[39mcustom_gradient(\n\u001b[1;32m 1186\u001b[0m vjp_fwd\u001b[38;5;241m=\u001b[39m_log_bessel_ive_fwd,\n\u001b[1;32m 1187\u001b[0m vjp_bwd\u001b[38;5;241m=\u001b[39m_log_bessel_ive_bwd,\n\u001b[1;32m 1188\u001b[0m jvp_fn\u001b[38;5;241m=\u001b[39m_log_bessel_ive_jvp)\n\u001b[1;32m 1189\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_log_bessel_ive_custom_gradient\u001b[39m(v, z):\n\u001b[0;32m-> 1190\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_log_bessel_ive_naive\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:1136\u001b[0m, in \u001b[0;36m_log_bessel_ive_naive\u001b[0;34m(v, z)\u001b[0m\n\u001b[1;32m 1135\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_log_bessel_ive_naive\u001b[39m(v, z):\n\u001b[0;32m-> 1136\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_bessel_ive_shared\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mz\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moutput_log_space\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:895\u001b[0m, in \u001b[0;36m_bessel_ive_shared\u001b[0;34m(v, z, output_log_space)\u001b[0m\n\u001b[1;32m 892\u001b[0m small_v \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mwhere(tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mabs(v_abs) \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m50.\u001b[39m, v_abs, numpy_dtype(\u001b[38;5;241m0.1\u001b[39m))\n\u001b[1;32m 893\u001b[0m large_v \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mwhere(tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mabs(v_abs) \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m50.\u001b[39m, v_abs, numpy_dtype(\u001b[38;5;241m1000.\u001b[39m))\n\u001b[0;32m--> 895\u001b[0m olver_ive, _ 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\u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:473\u001b[0m, in \u001b[0;36m_olver_asymptotic_uniform\u001b[0;34m(v, z, output_log_space, name)\u001b[0m\n\u001b[1;32m 471\u001b[0m coeff \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.\u001b[39m\n\u001b[1;32m 472\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m _ASYMPTOTIC_OLVER_EXPANSION_COEFFICIENTS[i]:\n\u001b[0;32m--> 473\u001b[0m coeff \u001b[38;5;241m=\u001b[39m \u001b[43mcoeff\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m \u001b[38;5;241m+\u001b[39m c\n\u001b[1;32m 474\u001b[0m term \u001b[38;5;241m=\u001b[39m coeff \u001b[38;5;241m/\u001b[39m divisor\n\u001b[1;32m 475\u001b[0m ive_sum \u001b[38;5;241m=\u001b[39m ive_sum \u001b[38;5;241m+\u001b[39m term\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/numpy/array_methods.py:739\u001b[0m, in \u001b[0;36m_forward_operator_to_aval..op\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 738\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mop\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs):\n\u001b[0;32m--> 739\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43maval\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mname\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/numpy/array_methods.py:265\u001b[0m, in \u001b[0;36m_defer_to_unrecognized_arg..deferring_binary_op\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 263\u001b[0m args \u001b[38;5;241m=\u001b[39m (other, \u001b[38;5;28mself\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m swap \u001b[38;5;28;01melse\u001b[39;00m (\u001b[38;5;28mself\u001b[39m, other)\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, _accepted_binop_types):\n\u001b[0;32m--> 265\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mbinary_op\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 266\u001b[0m \u001b[38;5;66;03m# Note: don't use isinstance here, because we don't want to raise for\u001b[39;00m\n\u001b[1;32m 267\u001b[0m \u001b[38;5;66;03m# subclasses, e.g. NamedTuple objects that may override operators.\u001b[39;00m\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(other) \u001b[38;5;129;01min\u001b[39;00m _rejected_binop_types:\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], @@ -532,498 +583,46 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 99, "metadata": {}, "outputs": [], "source": [ - "b3d.rr_init(\"inference_test_c2f_5\")" + "b3d.rr_init(\"inference_test_c2f_7\")" ] }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 100, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/29 [00:00 Date: Thu, 12 Sep 2024 17:18:14 -0400 Subject: [PATCH 16/37] Visualization of Attribute Proposals (#167) --- .../gen3d/interactive_visualization.ipynb | 122 ++++++++++ src/b3d/chisight/gen3d/visualization.py | 226 ++++++++++++++++++ 2 files changed, 348 insertions(+) create mode 100644 notebooks/gen3d/interactive_visualization.ipynb create mode 100644 src/b3d/chisight/gen3d/visualization.py diff --git a/notebooks/gen3d/interactive_visualization.ipynb b/notebooks/gen3d/interactive_visualization.ipynb new file mode 100644 index 00000000..84ec2c7e --- /dev/null +++ b/notebooks/gen3d/interactive_visualization.ipynb @@ -0,0 +1,122 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d.chisight.gen3d.image_kernel as image_kernel\n", + "import b3d.chisight.gen3d.inference as inference\n", + "import b3d.chisight.gen3d.inference_moves as inference_moves\n", + "import b3d.chisight.gen3d.transition_kernels as transition_kernels\n", + "import jax\n", + "import b3d\n", + "import jax.numpy as jnp\n", + "import pytest\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "near, far, image_height, image_width = 0.001, 1.0, 480, 640\n", + "img_model = image_kernel.NoOcclusionPerVertexImageKernel(\n", + " near, far, image_height, image_width\n", + ")\n", + "\n", + "inference_hyperparams = inference.InferenceHyperparams(\n", + " n_poses=1500,\n", + " do_stochastic_color_proposals=True,\n", + " pose_proposal_std=0.04,\n", + " pose_proposal_conc=1000.,\n", + " prev_color_proposal_laplace_scale=0.001,\n", + " obs_color_proposal_laplace_scale=0.001,\n", + ")\n", + "\n", + "hyperparams = {\n", + " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", + " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(\n", + " scale= 0.05\n", + " ),\n", + " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.1, support=jnp.array([0.01, 0.99])\n", + " ),\n", + " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.1, support=jnp.array([0.01, 0.99])\n", + " ),\n", + " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.1,\n", + " support=jnp.array([0.0025, 0.01, 0.02, 0.1, 0.4, 1.0]),\n", + " ),\n", + " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.1, support=jnp.array([0.002, 0.01, 0.025, 0.05, 0.1, 0.15, 0.3, 0.8])\n", + " ),\n", + " \"image_kernel\": img_model,\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e43892100b2c48e9898f4c3e89e22554", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(ToggleButtons(description='Prev Vis Prob:', options=('0.01', '0.99'), value='0.01'), Tog…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from b3d.chisight.gen3d.visualization import create_interactive_visualization\n", + "b3d.reload(b3d.chisight.gen3d.visualization)\n", + "observed_rgbd_for_point = jnp.array([0.1, 0.2, 0.3, 0.4])\n", + "create_interactive_visualization(\n", + " observed_rgbd_for_point,\n", + " hyperparams,\n", + " inference_hyperparams,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "b3d", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/src/b3d/chisight/gen3d/visualization.py b/src/b3d/chisight/gen3d/visualization.py new file mode 100644 index 00000000..06ac2a0b --- /dev/null +++ b/src/b3d/chisight/gen3d/visualization.py @@ -0,0 +1,226 @@ +import ipywidgets as widgets +import jax +import jax.numpy as jnp +import matplotlib.pyplot as plt +from ipywidgets import interact +from matplotlib.gridspec import GridSpec + +import b3d.chisight.gen3d.inference_moves as inference_moves + + +@jax.jit +def get_sample( + key, + observed_rgbd_for_point, + previous_visibility_prob, + previous_color, + latent_depth, + previous_dnrp, + color_scale, + depth_scale, + hyperparams, + inference_hyperparams, +): + depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + color_kernel = hyperparams["color_kernel"] + obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() + rgb, visibility_prob, dnr_prob = inference_moves._propose_a_points_attributes( + key, + observed_rgbd_for_point, + latent_depth, + previous_color, + previous_visibility_prob, + previous_dnrp, + depth_nonreturn_prob_kernel, + visibility_prob_kernel, + color_kernel, + obs_rgbd_kernel, + color_scale, + depth_scale, + inference_hyperparams, + return_metadata=False, + )[:3] + return rgb, visibility_prob, dnr_prob + + +get_samples = jax.vmap( + get_sample, in_axes=(0, None, None, None, None, None, None, None, None, None) +) + + +def plot_samples(samples, observed_rgbd_for_point, previous_color, latent_depth): + fig = plt.figure(layout="constrained", figsize=(10, 10)) + gs = GridSpec(3, 3, figure=fig) + + fig.suptitle(f"Observed RGBD: {observed_rgbd_for_point}", fontsize=16) + rgb, visibility_prob, dnr_prob = samples + + ax = fig.add_subplot(gs[0, 0]) + values, counts = jnp.unique(visibility_prob, return_counts=True) + ax.bar(values, counts) + ax.set_xticks(values) + ax.set_title("Visibility Probability Samples") + + ax = fig.add_subplot(gs[0, 1]) + values, counts = jnp.unique(dnr_prob, return_counts=True) + ax.bar(values, counts) + ax.set_xticks(values) + ax.set_title("Depth Nonreturn Probability Samples") + + ax = fig.add_subplot(gs[0, 2]) + ax.set_xlim(0.0, 2.0) + ax.set_title("Depth") + ax.axvline( + x=observed_rgbd_for_point[3], color="black", linestyle="--", label="Observed" + ) + ax.axvline(x=latent_depth, color="black", linestyle="dotted", label="Latent") + ax.legend() + + ax = fig.add_subplot(gs[1, 0]) + ax.hist(rgb[:, 0], jnp.linspace(0, 1, 100), color="r") + ax.set_title("R Samples") + ax.axvline(x=observed_rgbd_for_point[0], color="black", linestyle="--") + ax.axvline(x=previous_color[0], color="black", linestyle="dotted") + + ax = fig.add_subplot(gs[1, 1]) + ax.hist(rgb[:, 1], jnp.linspace(0, 1, 100), color="g") + ax.set_title("G Samples") + ax.axvline(x=observed_rgbd_for_point[1], color="black", linestyle="--") + ax.axvline(x=previous_color[1], color="black", linestyle="dotted") + + ax = fig.add_subplot(gs[1, 2]) + ax.hist(rgb[:, 2], jnp.linspace(0, 1, 100), color="b") + ax.set_title("B Samples") + ax.axvline( + x=observed_rgbd_for_point[2], color="black", linestyle="--", label="Observed" + ) + ax.axvline(x=previous_color[2], color="black", linestyle="dotted", label="Previous") + ax.legend() + + +def create_interactive_visualization( + observed_rgbd_for_point, hyperparams, inference_hyperparams +): + key = jax.random.PRNGKey(0) + keys = jax.random.split(key, 1000) + + depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + color_scale_kernel = hyperparams["color_scale_kernel"] + depth_scale_kernel = hyperparams["depth_scale_kernel"] + + def f( + previous_visibility_prob, + previous_dnrp, + latent_depth, + previous_r, + previous_g, + previous_b, + color_scale, + depth_scale, + ): + previous_color = jnp.array([previous_r, previous_g, previous_b]) + previous_visibility_prob = float(previous_visibility_prob) + previous_dnrp = float(previous_dnrp) + samples = get_samples( + keys, + observed_rgbd_for_point, + previous_visibility_prob, + previous_color, + latent_depth, + previous_dnrp, + color_scale, + depth_scale, + hyperparams, + inference_hyperparams, + ) + plot_samples(samples, observed_rgbd_for_point, previous_color, latent_depth) + + interact( + f, + previous_visibility_prob=widgets.ToggleButtons( + options=[f"{x:.2f}" for x in visibility_prob_kernel.support], + description="Prev Vis Prob:", + disabled=False, + button_style="", # 'success', 'info', 'warning', 'danger' or '' + ), + previous_dnrp=widgets.ToggleButtons( + options=[f"{x:.2f}" for x in depth_nonreturn_prob_kernel.support], + description="Prev DNR Prob:", + disabled=False, + button_style="", # 'success', 'info', 'warning', 'danger' or '' + ), + latent_depth=widgets.FloatSlider( + value=observed_rgbd_for_point[3], + min=-1.0, + max=1.0, + step=0.01, + description="Latent Depth:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), + previous_r=widgets.FloatSlider( + value=observed_rgbd_for_point[0], + min=0.0, + max=1.0, + step=0.01, + description="Previous R:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), + previous_g=widgets.FloatSlider( + value=observed_rgbd_for_point[1], + min=0.0, + max=1.0, + step=0.01, + description="Previous G:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), + previous_b=widgets.FloatSlider( + value=observed_rgbd_for_point[2], + min=0.0, + max=1.0, + step=0.01, + description="Previous B:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), + color_scale=widgets.FloatSlider( + value=color_scale_kernel.support.min(), + min=color_scale_kernel.support.min(), + max=color_scale_kernel.support.max(), + step=0.001, + description="Color Scale:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".4f", + ), + depth_scale=widgets.FloatSlider( + value=depth_scale_kernel.support.min(), + min=depth_scale_kernel.support.min(), + max=depth_scale_kernel.support.max(), + step=0.0005, + description="Depth Scale:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".4f", + ), + ) From 5c036a331b66ae819bd4042a08a59ced5fe1611e Mon Sep 17 00:00:00 2001 From: georgematheos Date: Thu, 12 Sep 2024 18:03:45 -0400 Subject: [PATCH 17/37] fix test_inference.py (#168) --- tests/gen3d/test_inference.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/tests/gen3d/test_inference.py b/tests/gen3d/test_inference.py index 9536e300..423f9220 100644 --- a/tests/gen3d/test_inference.py +++ b/tests/gen3d/test_inference.py @@ -18,12 +18,13 @@ def hyperparams_and_inference_hyperparams(): # This parameter is needed for the inference hyperparameters. # See the `InferenceHyperparams` docstring in `inference.py` for details. - effective_color_transition_scale = color_transiton_scale + p_resample_color * 1 / 2 inference_hyperparams = inference.InferenceHyperparams( n_poses=6000, pose_proposal_std=0.04, pose_proposal_conc=1000.0, - effective_color_transition_scale=effective_color_transition_scale, + do_stochastic_color_proposals=True, + prev_color_proposal_laplace_scale=0.001, + obs_color_proposal_laplace_scale=0.001, ) hyperparams = { @@ -40,10 +41,10 @@ def hyperparams_and_inference_hyperparams(): jnp.array([1 - p_resample_color, p_resample_color]), ), "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.01, 0.99]) + resample_probability=0.1, support=jnp.array([0.001, 0.999]) ), "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.01, 0.99]) + resample_probability=0.1, support=jnp.array([0.001, 0.999]) ), "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( resample_probability=0.1, @@ -184,7 +185,7 @@ def get_dnr_prob_sample(key, observed_rgbd_for_point, previous_dnrp): dnr_prob_samples = get_dnr_prob_samples( keys, observed_rgbd_for_this_vertex, previous_dnrp ) - assert dnr_prob_samples.mean() < 0.90 + assert dnr_prob_samples.mean() > 0.90 # If depth is valid, the depth nonreturn prob should become low. previous_dnrp = depth_nonreturn_prob_kernel.support[-1] @@ -192,7 +193,7 @@ def get_dnr_prob_sample(key, observed_rgbd_for_point, previous_dnrp): dnr_prob_samples = get_dnr_prob_samples( keys, observed_rgbd_for_this_vertex, previous_dnrp ) - assert dnr_prob_samples.mean() < 0.15 + assert dnr_prob_samples.mean() < 0.10 # If depth is valid, the depth nonreturn prob should stay low. previous_dnrp = depth_nonreturn_prob_kernel.support[0] From b68cab67915e9583d89f66ba109b04f717edb7a2 Mon Sep 17 00:00:00 2001 From: georgematheos Date: Thu, 12 Sep 2024 19:23:50 -0400 Subject: [PATCH 18/37] Docstrings; Add back Log Q scores; Notebook Cleanup (#169) This adds back in the logq scores in the inference algorithm. It seems to work pretty well! Interestingly, on the dataset in the tester.ipynb notebook, having the logq scores changes the qualitative behavior at frame ~23, when the camera exposure changes. Without the logq scores, the tracking works okay through this period, while with the logq scores, the algorithm loses track of the object. This warrants further debugging, since it probably indicates the math is wrong somewehre. I suspect it may have to do with the fact that we are currently not including scores for pixels that are unobserved. I wonder if this makes the algorithm too likely to want to resample poses that have many points off the screen, since the scoring doesn't realize how much extra randomness this induces. (Put another way, if we include this score, we should lower the P scores of poses with many points off screen, since we will have a log(1/(far - near)) term for each pixel that no point is hitting, and there are more of these for poses where many points are off screen.) --- notebooks/bayes3d_paper/tester.ipynb | 1700 ++------------------- src/b3d/chisight/gen3d/inference.py | 108 +- src/b3d/chisight/gen3d/inference_moves.py | 1 - 3 files changed, 206 insertions(+), 1603 deletions(-) diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 8c4ca222..e1f5ce90 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -10,6 +10,13 @@ "%autoreload 2" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup" + ] + }, { "cell_type": "code", "execution_count": 2, @@ -30,15 +37,6 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], - "source": [ - "b3d.rr_init(\"inference_test2\")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, "outputs": [ { "name": "stdout", @@ -51,7 +49,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 13.38it/s]\n", + "100%|██████████| 49/49 [00:03<00:00, 13.47it/s]\n", "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", " warnings.warn(\n" @@ -65,7 +63,7 @@ "" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -100,7 +98,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -128,7 +126,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -137,7 +135,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -159,7 +157,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -170,7 +168,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -218,17 +216,15 @@ ] }, { - "cell_type": "code", - "execution_count": 10, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "from b3d.chisight.gen3d.inference import InferenceHyperparams" + "## Generate initial trace (/ initial state)" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -247,7 +243,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -268,7 +264,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -277,7 +273,7 @@ "Array(120035.86, dtype=float32)" ] }, - "execution_count": 13, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -291,7 +287,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -300,7 +296,7 @@ "Array(120035.86, dtype=float32)" ] }, - "execution_count": 14, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -309,21 +305,6 @@ "trace.get_score()" ] }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "# My TODOs:\n", - "# 1. Coarse to fine\n", - "# 1.5 Fix JITTING\n", - "# 2. Rerun blueprint to improve debugging workflow\n", - "# 3. Set up Nishad's suggested test\n", - "## Nishad's suggestion - debug with inference only over color, visibility probs, and pose.\n", - "## He will send me hyperparams he had used for this." - ] - }, { "cell_type": "code", "execution_count": null, @@ -332,17 +313,15 @@ "source": [] }, { - "cell_type": "code", - "execution_count": 16, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "### Single timestep test ###" + "## Single timestep test + get metadata for debugging" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -352,7 +331,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -364,17 +343,17 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "T = 0\n", - "b3d.rr_init(\"inference92\")" + "b3d.rr_init(\"inference_1step\")" ] }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -383,39 +362,47 @@ }, { "cell_type": "code", - "execution_count": 89, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "inference_hyperparams = i.InferenceHyperparams(\n", " n_poses=1500,\n", - " do_stochastic_color_proposals=False,\n", + " do_stochastic_color_proposals=True,\n", " pose_proposal_std=0.04,\n", " pose_proposal_conc=1000.,\n", - " prev_color_proposal_laplace_scale=0.001,\n", - " obs_color_proposal_laplace_scale=0.001,\n", + " prev_color_proposal_laplace_scale=0.04,\n", + " obs_color_proposal_laplace_scale=0.01,\n", ")" ] }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 18, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/georgematheos/b3d/src/b3d/modeling_utils.py:86: UserWarning: RenormalizedLaplace sampling is currently not implemented perfectly.\n", + " warnings.warn(\n" + ] + }, { "data": { "text/plain": [ - "Array(71180.67, dtype=float32)" + "Array(-871.44604, dtype=float32)" ] }, - "execution_count": 90, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "trace, step_weight, metadata = i.inference_step(\n", - " jax.random.PRNGKey(24),\n", + " jax.random.PRNGKey(26),\n", " og_trace,\n", " all_data[1][\"rgbd\"],\n", " inference_hyperparams,\n", @@ -427,7 +414,7 @@ }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -436,125 +423,88 @@ ] }, { - "cell_type": "code", - "execution_count": 78, + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys(['chosen_pose_index', 'log_q_nonpose_latents', 'log_q_poses', 'other_latents_metadata', 'p_scores', 'proposed_poses'])" - ] - }, - "execution_count": 78, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "metadata.keys()" + "## Run against video, using a pose proposal that is guaranteed to propose the ground truth pose at least once" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "b3d.rr_init(\"inference_given_gtpose_4\")" + ] }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ - "### Run against video ###" + "b3d.reload(i)" ] }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ - "b3d.rr_init(\"inference_test7\")" + "inference_hyperparams = i.InferenceHyperparams(\n", + " n_poses=1500,\n", + " do_stochastic_color_proposals=False,\n", + " pose_proposal_std=0.04,\n", + " pose_proposal_conc=1000.,\n", + " prev_color_proposal_laplace_scale=.04,\n", + " obs_color_proposal_laplace_scale=.01,\n", + ")" ] }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/10 [00:00 5\u001b[0m trace, _ \u001b[38;5;241m=\u001b[39m \u001b[43mi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minference_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43mjax\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrandom\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPRNGKey\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m21\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43mall_data\u001b[49m\u001b[43m[\u001b[49m\u001b[43mT\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrgbd\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mgt_pose\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mgt_pose\u001b[49m\u001b[43m(\u001b[49m\u001b[43mT\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43mget_metadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\n\u001b[1;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 13\u001b[0m b3d\u001b[38;5;241m.\u001b[39mchisight\u001b[38;5;241m.\u001b[39mgen3d\u001b[38;5;241m.\u001b[39mmodel\u001b[38;5;241m.\u001b[39mviz_trace(\n\u001b[1;32m 14\u001b[0m trace,\n\u001b[1;32m 15\u001b[0m T,\n\u001b[1;32m 16\u001b[0m ground_truth_vertices\u001b[38;5;241m=\u001b[39mmeshes[OBJECT_INDEX]\u001b[38;5;241m.\u001b[39mvertices,\n\u001b[1;32m 17\u001b[0m ground_truth_pose\u001b[38;5;241m=\u001b[39mall_data[T][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcamera_pose\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39minv() \u001b[38;5;241m@\u001b[39m all_data[T][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mobject_poses\u001b[39m\u001b[38;5;124m\"\u001b[39m][OBJECT_INDEX]\n\u001b[1;32m 18\u001b[0m )\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference.py:145\u001b[0m, in \u001b[0;36minference_step\u001b[0;34m(key, old_trace, observed_rgbd, inference_hyperparams, *args, **kwargs)\u001b[0m\n\u001b[1;32m 143\u001b[0m k1, k2 \u001b[38;5;241m=\u001b[39m split(key)\n\u001b[1;32m 144\u001b[0m trace \u001b[38;5;241m=\u001b[39m advance_time(k1, old_trace, observed_rgbd)\n\u001b[0;32m--> 145\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minfer_latents\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk2\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:304\u001b[0m, in \u001b[0;36m_cpp_pjit..cache_miss\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 302\u001b[0m \u001b[38;5;129m@api_boundary\u001b[39m\n\u001b[1;32m 303\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcache_miss\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 304\u001b[0m outs, out_flat, out_tree, args_flat, jaxpr, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43m_python_pjit_helper\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 305\u001b[0m \u001b[43m \u001b[49m\u001b[43mjit_info\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 306\u001b[0m executable \u001b[38;5;241m=\u001b[39m _read_most_recent_pjit_call_executable(jaxpr)\n\u001b[1;32m 307\u001b[0m maybe_fastpath_data \u001b[38;5;241m=\u001b[39m _get_fastpath_data(\n\u001b[1;32m 308\u001b[0m executable, out_tree, args_flat, out_flat, attrs_tracked, jaxpr\u001b[38;5;241m.\u001b[39meffects,\n\u001b[1;32m 309\u001b[0m jaxpr\u001b[38;5;241m.\u001b[39mconsts, jit_info\u001b[38;5;241m.\u001b[39mabstracted_axes)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:171\u001b[0m, in \u001b[0;36m_python_pjit_helper\u001b[0;34m(jit_info, *args, **kwargs)\u001b[0m\n\u001b[1;32m 169\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_python_pjit_helper\u001b[39m(jit_info, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 170\u001b[0m (args_flat, _, params, _, out_tree, _, arg_names,\n\u001b[0;32m--> 171\u001b[0m attrs_tracked) \u001b[38;5;241m=\u001b[39m \u001b[43m_infer_params\u001b[49m\u001b[43m(\u001b[49m\u001b[43mjit_info\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 173\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m args_flat:\n\u001b[1;32m 174\u001b[0m dispatch\u001b[38;5;241m.\u001b[39mcheck_arg(arg)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:598\u001b[0m, in \u001b[0;36m_infer_params\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 591\u001b[0m in_type \u001b[38;5;241m=\u001b[39m in_avals \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(avals)\n\u001b[1;32m 593\u001b[0m in_shardings_flat, in_layouts_flat \u001b[38;5;241m=\u001b[39m _process_in_axis_resources(\n\u001b[1;32m 594\u001b[0m in_shardings_treedef, in_shardings_leaves,\n\u001b[1;32m 595\u001b[0m in_layouts_treedef, in_layouts_leaves,\n\u001b[1;32m 596\u001b[0m in_avals, in_tree, dbg, device_or_backend_set, have_kwargs)\n\u001b[0;32m--> 598\u001b[0m jaxpr, consts, out_shardings_flat, out_layouts_flat, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43m_pjit_jaxpr\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 599\u001b[0m \u001b[43m \u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mout_shardings_treedef\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mout_shardings_leaves\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 600\u001b[0m \u001b[43m \u001b[49m\u001b[43mout_layouts_treedef\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mout_layouts_leaves\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdbg\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 601\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_or_backend_set\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mHashableFunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43mout_tree\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclosure\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 602\u001b[0m \u001b[43m \u001b[49m\u001b[43mHashableFunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43mres_paths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclosure\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minline\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 604\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(explicit_args) \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mlen\u001b[39m(in_shardings_flat) \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mlen\u001b[39m(in_layouts_flat)\n\u001b[1;32m 606\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m config\u001b[38;5;241m.\u001b[39mdynamic_shapes\u001b[38;5;241m.\u001b[39mvalue:\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:1206\u001b[0m, in \u001b[0;36m_pjit_jaxpr\u001b[0;34m(fun, out_shardings_treedef, out_shardings_leaves, out_layouts_treedef, out_layouts_leaves, in_type, debug_info, device_or_backend_set, out_tree, result_paths, inline)\u001b[0m\n\u001b[1;32m 1203\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_pjit_jaxpr\u001b[39m(fun, out_shardings_treedef, out_shardings_leaves,\n\u001b[1;32m 1204\u001b[0m out_layouts_treedef, out_layouts_leaves, in_type, debug_info,\n\u001b[1;32m 1205\u001b[0m device_or_backend_set, out_tree, result_paths, inline):\n\u001b[0;32m-> 1206\u001b[0m jaxpr, final_consts, out_type, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43m_create_pjit_jaxpr\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1207\u001b[0m \u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug_info\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mresult_paths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mIgnoreKey\u001b[49m\u001b[43m(\u001b[49m\u001b[43minline\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1208\u001b[0m canonicalized_out_shardings_flat, out_layouts_flat \u001b[38;5;241m=\u001b[39m _check_and_canonicalize_out_shardings(\n\u001b[1;32m 1209\u001b[0m out_shardings_treedef, out_shardings_leaves, out_layouts_treedef,\n\u001b[1;32m 1210\u001b[0m out_layouts_leaves, out_tree, \u001b[38;5;28mtuple\u001b[39m(out_type),\n\u001b[1;32m 1211\u001b[0m jaxpr\u001b[38;5;241m.\u001b[39mjaxpr\u001b[38;5;241m.\u001b[39mdebug_info, device_or_backend_set)\n\u001b[1;32m 1212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (jaxpr, final_consts, canonicalized_out_shardings_flat,\n\u001b[1;32m 1213\u001b[0m out_layouts_flat, attrs_tracked)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/linear_util.py:350\u001b[0m, in \u001b[0;36mcache..memoized_fun\u001b[0;34m(fun, *args)\u001b[0m\n\u001b[1;32m 348\u001b[0m fun\u001b[38;5;241m.\u001b[39mpopulate_stores(stores)\n\u001b[1;32m 349\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 350\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[43mcall\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 351\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m explain \u001b[38;5;129;01mand\u001b[39;00m config\u001b[38;5;241m.\u001b[39mexplain_cache_misses\u001b[38;5;241m.\u001b[39mvalue:\n\u001b[1;32m 352\u001b[0m explain(fun\u001b[38;5;241m.\u001b[39mf, cache \u001b[38;5;129;01mis\u001b[39;00m new_cache, cache, key, ans)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/pjit.py:1154\u001b[0m, in \u001b[0;36m_create_pjit_jaxpr\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 1152\u001b[0m attrs_tracked \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 1153\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1154\u001b[0m jaxpr, global_out_avals, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43mpe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrace_to_jaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1155\u001b[0m \u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpe_debug\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1157\u001b[0m \u001b[38;5;66;03m# TODO(dougalm,mattjj): enable debug info with attrs_tracked\u001b[39;00m\n\u001b[1;32m 1158\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m config\u001b[38;5;241m.\u001b[39mdynamic_shapes\u001b[38;5;241m.\u001b[39mvalue \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m attrs_tracked:\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/profiler.py:335\u001b[0m, in \u001b[0;36mannotate_function..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 332\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(func)\n\u001b[1;32m 333\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 334\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m TraceAnnotation(name, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mdecorator_kwargs):\n\u001b[0;32m--> 335\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 336\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wrapper\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2326\u001b[0m, in \u001b[0;36mtrace_to_jaxpr_dynamic\u001b[0;34m(fun, in_avals, debug_info, keep_inputs)\u001b[0m\n\u001b[1;32m 2324\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m core\u001b[38;5;241m.\u001b[39mnew_main(DynamicJaxprTrace, dynamic\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mas\u001b[39;00m main: \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m 2325\u001b[0m main\u001b[38;5;241m.\u001b[39mjaxpr_stack \u001b[38;5;241m=\u001b[39m () \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[0;32m-> 2326\u001b[0m jaxpr, out_avals, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m \u001b[43mtrace_to_subjaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2327\u001b[0m \u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmain\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkeep_inputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkeep_inputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdebug_info\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdebug_info\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2328\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m main, fun\n\u001b[1;32m 2329\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m jaxpr, out_avals, consts, attrs_tracked\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2348\u001b[0m, in \u001b[0;36mtrace_to_subjaxpr_dynamic\u001b[0;34m(fun, main, in_avals, keep_inputs, debug_info)\u001b[0m\n\u001b[1;32m 2346\u001b[0m in_tracers \u001b[38;5;241m=\u001b[39m _input_type_to_tracers(trace\u001b[38;5;241m.\u001b[39mnew_arg, in_avals)\n\u001b[1;32m 2347\u001b[0m in_tracers_ \u001b[38;5;241m=\u001b[39m [t \u001b[38;5;28;01mfor\u001b[39;00m t, keep \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(in_tracers, keep_inputs) \u001b[38;5;28;01mif\u001b[39;00m keep]\n\u001b[0;32m-> 2348\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[43mfun\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_wrapped\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43min_tracers_\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2349\u001b[0m out_tracers \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmap\u001b[39m(trace\u001b[38;5;241m.\u001b[39mfull_raise, ans)\n\u001b[1;32m 2350\u001b[0m jaxpr, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m frame\u001b[38;5;241m.\u001b[39mto_jaxpr(out_tracers)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/linear_util.py:192\u001b[0m, in \u001b[0;36mWrappedFun.call_wrapped\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 189\u001b[0m gen \u001b[38;5;241m=\u001b[39m gen_static_args \u001b[38;5;241m=\u001b[39m out_store \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 191\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 192\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mdict\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 193\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m 194\u001b[0m \u001b[38;5;66;03m# Some transformations yield from inside context managers, so we have to\u001b[39;00m\n\u001b[1;32m 195\u001b[0m \u001b[38;5;66;03m# interrupt them before reraising the exception. Otherwise they will only\u001b[39;00m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;66;03m# get garbage-collected at some later time, running their cleanup tasks\u001b[39;00m\n\u001b[1;32m 197\u001b[0m \u001b[38;5;66;03m# only after this exception is handled, which can corrupt the global\u001b[39;00m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;66;03m# state.\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m stack:\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference.py:184\u001b[0m, in \u001b[0;36minfer_latents\u001b[0;34m(key, trace, inference_hyperparams, get_trace, get_weight, get_metadata, gt_pose)\u001b[0m\n\u001b[1;32m 179\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m gt_pose \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 180\u001b[0m proposed_poses \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mtree\u001b[38;5;241m.\u001b[39mmap(\n\u001b[1;32m 181\u001b[0m \u001b[38;5;28;01mlambda\u001b[39;00m x, y: x\u001b[38;5;241m.\u001b[39mat[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset(y), proposed_poses, gt_pose\n\u001b[1;32m 182\u001b[0m )\n\u001b[1;32m 183\u001b[0m log_q_poses \u001b[38;5;241m=\u001b[39m log_q_poses\u001b[38;5;241m.\u001b[39mat[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset(\n\u001b[0;32m--> 184\u001b[0m \u001b[43mget_pose_proposal_density\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgt_pose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 185\u001b[0m )\n\u001b[1;32m 187\u001b[0m param_generation_keys \u001b[38;5;241m=\u001b[39m split(k3, inference_hyperparams\u001b[38;5;241m.\u001b[39mn_poses)\n\u001b[1;32m 188\u001b[0m proposed_traces, log_q_nonpose_latents, other_latents_metadata \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mvmap(\n\u001b[1;32m 189\u001b[0m propose_other_latents_given_pose, in_axes\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m0\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 190\u001b[0m )(param_generation_keys, trace, proposed_poses, inference_hyperparams)\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference_moves.py:56\u001b[0m, in \u001b[0;36mget_pose_proposal_density\u001b[0;34m(pose, advanced_trace, inference_hyperparams)\u001b[0m\n\u001b[1;32m 54\u001b[0m previous_pose \u001b[38;5;241m=\u001b[39m get_prev_state(advanced_trace)[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpose\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 55\u001b[0m ih \u001b[38;5;241m=\u001b[39m inference_hyperparams\n\u001b[0;32m---> 56\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mPose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlogpdf_gaussian_vmf_pose\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 57\u001b[0m \u001b[43m \u001b[49m\u001b[43mpose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprevious_pose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mih\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpose_proposal_std\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mih\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpose_proposal_conc\u001b[49m\n\u001b[1;32m 58\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/b3d/src/b3d/pose/core.py:119\u001b[0m, in \u001b[0;36mlogpdf_gaussian_vmf_pose\u001b[0;34m(pose, mean_pose, std, concentration)\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlogpdf_gaussian_vmf_pose\u001b[39m(pose, mean_pose, std, concentration):\n\u001b[1;32m 114\u001b[0m translation_score \u001b[38;5;241m=\u001b[39m tfp\u001b[38;5;241m.\u001b[39mdistributions\u001b[38;5;241m.\u001b[39mMultivariateNormalDiag(\n\u001b[1;32m 115\u001b[0m mean_pose\u001b[38;5;241m.\u001b[39mpos, jnp\u001b[38;5;241m.\u001b[39mones(\u001b[38;5;241m3\u001b[39m) \u001b[38;5;241m*\u001b[39m std\n\u001b[1;32m 116\u001b[0m )\u001b[38;5;241m.\u001b[39mlog_prob(pose\u001b[38;5;241m.\u001b[39mpos)\n\u001b[1;32m 117\u001b[0m quaternion_score \u001b[38;5;241m=\u001b[39m \u001b[43mtfp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdistributions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mVonMisesFisher\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 118\u001b[0m \u001b[43m \u001b[49m\u001b[43mmean_pose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquat\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mjnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlinalg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnorm\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmean_pose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquat\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconcentration\u001b[49m\n\u001b[0;32m--> 119\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpose\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquat\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m translation_score \u001b[38;5;241m+\u001b[39m quaternion_score\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/distribution.py:1287\u001b[0m, in \u001b[0;36mDistribution.log_prob\u001b[0;34m(self, value, name, **kwargs)\u001b[0m\n\u001b[1;32m 1275\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlog_prob\u001b[39m(\u001b[38;5;28mself\u001b[39m, value, name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlog_prob\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 1276\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Log probability density/mass function.\u001b[39;00m\n\u001b[1;32m 1277\u001b[0m \n\u001b[1;32m 1278\u001b[0m \u001b[38;5;124;03m Args:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1285\u001b[0m \u001b[38;5;124;03m values of type `self.dtype`.\u001b[39;00m\n\u001b[1;32m 1286\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1287\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_log_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/distribution.py:1269\u001b[0m, in \u001b[0;36mDistribution._call_log_prob\u001b[0;34m(self, value, name, **kwargs)\u001b[0m\n\u001b[1;32m 1267\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_name_and_control_scope(name, value, kwargs):\n\u001b[1;32m 1268\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_log_prob\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[0;32m-> 1269\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_log_prob\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1270\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_prob\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m 1271\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prob(value, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs))\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/von_mises_fisher.py:197\u001b[0m, in \u001b[0;36mVonMisesFisher._log_prob\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m 194\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_log_prob\u001b[39m(\u001b[38;5;28mself\u001b[39m, x):\n\u001b[1;32m 195\u001b[0m concentration \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconcentration)\n\u001b[1;32m 196\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_log_unnormalized_prob(x, concentration\u001b[38;5;241m=\u001b[39mconcentration) \u001b[38;5;241m-\u001b[39m\n\u001b[0;32m--> 197\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_log_normalization\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconcentration\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconcentration\u001b[49m\u001b[43m)\u001b[49m)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/distributions/von_mises_fisher.py:218\u001b[0m, in \u001b[0;36mVonMisesFisher._log_normalization\u001b[0;34m(self, concentration)\u001b[0m\n\u001b[1;32m 213\u001b[0m event_dim \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mcast(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_event_shape_tensor()[\u001b[38;5;241m0\u001b[39m], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdtype)\n\u001b[1;32m 214\u001b[0m safe_conc \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mwhere(concentration \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, concentration,\n\u001b[1;32m 215\u001b[0m tf\u001b[38;5;241m.\u001b[39mones_like(concentration))\n\u001b[1;32m 216\u001b[0m safe_lognorm \u001b[38;5;241m=\u001b[39m ((event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m) \u001b[38;5;241m*\u001b[39m tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mlog(safe_conc) \u001b[38;5;241m-\u001b[39m\n\u001b[1;32m 217\u001b[0m (event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m) \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mpi) \u001b[38;5;241m-\u001b[39m\n\u001b[0;32m--> 218\u001b[0m \u001b[43mbessel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog_bessel_ive\u001b[49m\u001b[43m(\u001b[49m\u001b[43mevent_dim\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msafe_conc\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m-\u001b[39m\n\u001b[1;32m 219\u001b[0m tf\u001b[38;5;241m.\u001b[39mabs(safe_conc))\n\u001b[1;32m 220\u001b[0m log_nsphere_surface_area \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 221\u001b[0m np\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m2.\u001b[39m) \u001b[38;5;241m+\u001b[39m (event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m) \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mlog(np\u001b[38;5;241m.\u001b[39mpi) \u001b[38;5;241m-\u001b[39m\n\u001b[1;32m 222\u001b[0m tf\u001b[38;5;241m.\u001b[39mmath\u001b[38;5;241m.\u001b[39mlgamma(tf\u001b[38;5;241m.\u001b[39mcast(event_dim \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m2\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdtype)))\n\u001b[1;32m 223\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tf\u001b[38;5;241m.\u001b[39mwhere(concentration \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m-\u001b[39msafe_lognorm,\n\u001b[1;32m 224\u001b[0m log_nsphere_surface_area)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:1219\u001b[0m, in \u001b[0;36mlog_bessel_ive\u001b[0;34m(v, z, name)\u001b[0m\n\u001b[1;32m 1217\u001b[0m v \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(v, dtype\u001b[38;5;241m=\u001b[39mdtype)\n\u001b[1;32m 1218\u001b[0m z \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(z, dtype\u001b[38;5;241m=\u001b[39mdtype)\n\u001b[0;32m-> 1219\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_log_bessel_ive_custom_gradient\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n", - " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/custom_derivatives.py:261\u001b[0m, in \u001b[0;36mcustom_jvp.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 258\u001b[0m flat_fun, out_type1 \u001b[38;5;241m=\u001b[39m _flatten_fun_nokwargs(f_, in_tree)\n\u001b[1;32m 259\u001b[0m flat_jvp, out_type2 \u001b[38;5;241m=\u001b[39m _flatten_jvp(jvp, primal_name, jvp_name, in_tree,\n\u001b[1;32m 260\u001b[0m out_type1)\n\u001b[0;32m--> 261\u001b[0m out_flat \u001b[38;5;241m=\u001b[39m \u001b[43mcustom_jvp_call_p\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbind\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflat_jvp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs_flat\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 262\u001b[0m \u001b[43m \u001b[49m\u001b[43msymbolic_zeros\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msymbolic_zeros\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 263\u001b[0m _, (out_tree, _) \u001b[38;5;241m=\u001b[39m lu\u001b[38;5;241m.\u001b[39mmerge_linear_aux(out_type1, out_type2)\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tree_unflatten(out_tree, out_flat)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/custom_derivatives.py:363\u001b[0m, in \u001b[0;36mCustomJVPCallPrimitive.bind\u001b[0;34m(self, fun, jvp, symbolic_zeros, *args)\u001b[0m\n\u001b[1;32m 360\u001b[0m jvp, env_trace_todo2 \u001b[38;5;241m=\u001b[39m process_env_traces(\n\u001b[1;32m 361\u001b[0m jvp, \u001b[38;5;28mself\u001b[39m, top_trace \u001b[38;5;129;01mand\u001b[39;00m top_trace\u001b[38;5;241m.\u001b[39mlevel, \u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 362\u001b[0m tracers \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmap\u001b[39m(top_trace\u001b[38;5;241m.\u001b[39mfull_raise, args) \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[0;32m--> 363\u001b[0m outs \u001b[38;5;241m=\u001b[39m \u001b[43mtop_trace\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprocess_custom_jvp_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjvp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtracers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# type: ignore\u001b[39;49;00m\n\u001b[1;32m 364\u001b[0m \u001b[43m \u001b[49m\u001b[43msymbolic_zeros\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msymbolic_zeros\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m 365\u001b[0m _, env_trace_todo \u001b[38;5;241m=\u001b[39m lu\u001b[38;5;241m.\u001b[39mmerge_linear_aux(env_trace_todo1, env_trace_todo2)\n\u001b[1;32m 366\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m core\u001b[38;5;241m.\u001b[39mapply_todos(env_trace_todo, \u001b[38;5;28mmap\u001b[39m(core\u001b[38;5;241m.\u001b[39mfull_lower, outs))\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2120\u001b[0m, in \u001b[0;36mDynamicJaxprTrace.process_custom_jvp_call\u001b[0;34m(self, prim, fun, jvp, tracers, symbolic_zeros)\u001b[0m\n\u001b[1;32m 2118\u001b[0m in_avals \u001b[38;5;241m=\u001b[39m [t\u001b[38;5;241m.\u001b[39maval \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m tracers]\n\u001b[1;32m 2119\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m core\u001b[38;5;241m.\u001b[39mnew_sublevel():\n\u001b[0;32m-> 2120\u001b[0m fun_jaxpr, out_avals, consts, () \u001b[38;5;241m=\u001b[39m \u001b[43mtrace_to_subjaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmain\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2121\u001b[0m closed_fun_jaxpr \u001b[38;5;241m=\u001b[39m core\u001b[38;5;241m.\u001b[39mClosedJaxpr(convert_constvars_jaxpr(fun_jaxpr), ())\n\u001b[1;32m 2122\u001b[0m main_ \u001b[38;5;241m=\u001b[39m ref(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmain)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/interpreters/partial_eval.py:2348\u001b[0m, in \u001b[0;36mtrace_to_subjaxpr_dynamic\u001b[0;34m(fun, main, in_avals, keep_inputs, debug_info)\u001b[0m\n\u001b[1;32m 2346\u001b[0m in_tracers \u001b[38;5;241m=\u001b[39m _input_type_to_tracers(trace\u001b[38;5;241m.\u001b[39mnew_arg, in_avals)\n\u001b[1;32m 2347\u001b[0m in_tracers_ \u001b[38;5;241m=\u001b[39m [t \u001b[38;5;28;01mfor\u001b[39;00m t, keep \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(in_tracers, keep_inputs) \u001b[38;5;28;01mif\u001b[39;00m keep]\n\u001b[0;32m-> 2348\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[43mfun\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_wrapped\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43min_tracers_\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2349\u001b[0m out_tracers \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmap\u001b[39m(trace\u001b[38;5;241m.\u001b[39mfull_raise, ans)\n\u001b[1;32m 2350\u001b[0m jaxpr, consts, attrs_tracked \u001b[38;5;241m=\u001b[39m frame\u001b[38;5;241m.\u001b[39mto_jaxpr(out_tracers)\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/linear_util.py:192\u001b[0m, in \u001b[0;36mWrappedFun.call_wrapped\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 189\u001b[0m gen \u001b[38;5;241m=\u001b[39m gen_static_args \u001b[38;5;241m=\u001b[39m out_store \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 191\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 192\u001b[0m ans \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mdict\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 193\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m 194\u001b[0m \u001b[38;5;66;03m# Some transformations yield from inside context managers, so we have to\u001b[39;00m\n\u001b[1;32m 195\u001b[0m \u001b[38;5;66;03m# interrupt them before reraising the exception. Otherwise they will only\u001b[39;00m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;66;03m# get garbage-collected at some later time, running their cleanup tasks\u001b[39;00m\n\u001b[1;32m 197\u001b[0m \u001b[38;5;66;03m# only after this exception is handled, which can corrupt the global\u001b[39;00m\n\u001b[1;32m 198\u001b[0m \u001b[38;5;66;03m# state.\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m stack:\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:1190\u001b[0m, in \u001b[0;36m_log_bessel_ive_custom_gradient\u001b[0;34m(v, z)\u001b[0m\n\u001b[1;32m 1185\u001b[0m \u001b[38;5;129m@tfp_custom_gradient\u001b[39m\u001b[38;5;241m.\u001b[39mcustom_gradient(\n\u001b[1;32m 1186\u001b[0m vjp_fwd\u001b[38;5;241m=\u001b[39m_log_bessel_ive_fwd,\n\u001b[1;32m 1187\u001b[0m vjp_bwd\u001b[38;5;241m=\u001b[39m_log_bessel_ive_bwd,\n\u001b[1;32m 1188\u001b[0m jvp_fn\u001b[38;5;241m=\u001b[39m_log_bessel_ive_jvp)\n\u001b[1;32m 1189\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_log_bessel_ive_custom_gradient\u001b[39m(v, z):\n\u001b[0;32m-> 1190\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_log_bessel_ive_naive\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:1136\u001b[0m, in \u001b[0;36m_log_bessel_ive_naive\u001b[0;34m(v, z)\u001b[0m\n\u001b[1;32m 1135\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_log_bessel_ive_naive\u001b[39m(v, z):\n\u001b[0;32m-> 1136\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_bessel_ive_shared\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mz\u001b[49m\u001b[43m,\u001b[49m\u001b[43m 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\u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/tensorflow_probability/substrates/jax/math/bessel.py:473\u001b[0m, in \u001b[0;36m_olver_asymptotic_uniform\u001b[0;34m(v, z, output_log_space, name)\u001b[0m\n\u001b[1;32m 471\u001b[0m coeff \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.\u001b[39m\n\u001b[1;32m 472\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m _ASYMPTOTIC_OLVER_EXPANSION_COEFFICIENTS[i]:\n\u001b[0;32m--> 473\u001b[0m coeff \u001b[38;5;241m=\u001b[39m \u001b[43mcoeff\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m \u001b[38;5;241m+\u001b[39m c\n\u001b[1;32m 474\u001b[0m term \u001b[38;5;241m=\u001b[39m coeff \u001b[38;5;241m/\u001b[39m divisor\n\u001b[1;32m 475\u001b[0m ive_sum \u001b[38;5;241m=\u001b[39m ive_sum \u001b[38;5;241m+\u001b[39m term\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/numpy/array_methods.py:739\u001b[0m, in \u001b[0;36m_forward_operator_to_aval..op\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 738\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mop\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs):\n\u001b[0;32m--> 739\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43maval\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mname\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/jax/_src/numpy/array_methods.py:265\u001b[0m, in \u001b[0;36m_defer_to_unrecognized_arg..deferring_binary_op\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 263\u001b[0m args \u001b[38;5;241m=\u001b[39m (other, \u001b[38;5;28mself\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m swap \u001b[38;5;28;01melse\u001b[39;00m (\u001b[38;5;28mself\u001b[39m, other)\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(other, _accepted_binop_types):\n\u001b[0;32m--> 265\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mbinary_op\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 266\u001b[0m \u001b[38;5;66;03m# Note: don't use isinstance here, because we don't want to raise for\u001b[39;00m\n\u001b[1;32m 267\u001b[0m \u001b[38;5;66;03m# subclasses, e.g. NamedTuple objects that may override operators.\u001b[39;00m\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(other) \u001b[38;5;129;01min\u001b[39;00m _rejected_binop_types:\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + "/home/georgematheos/b3d/src/b3d/modeling_utils.py:86: UserWarning: RenormalizedLaplace sampling is currently not implemented perfectly.\n", + " warnings.warn(\n", + "100%|██████████| 30/30 [00:32<00:00, 1.09s/it]\n" ] } ], "source": [ - "### Run inference ###\n", + "### Run inference, giving the ground truth pose as a option in the pose proposal grid ###\n", "trace = og_trace\n", - "for T in tqdm(range(10)):\n", + "key = jax.random.PRNGKey(21)\n", + "for T in tqdm(range(30)):\n", " key = b3d.split_key(key)\n", " trace, _ = i.inference_step(\n", - " jax.random.PRNGKey(21),\n", + " key,\n", " trace,\n", " all_data[T][\"rgbd\"],\n", " inference_hyperparams,\n", + " use_gt_pose=True,\n", " gt_pose = gt_pose(T),\n", - " get_metadata=False\n", + " get_metadata=False,\n", + " include_qscores_in_outer_resample=True\n", " )\n", " b3d.chisight.gen3d.model.viz_trace(\n", " trace,\n", @@ -571,55 +521,62 @@ "outputs": [], "source": [] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Real inference: run against video without ground truth information" + ] + }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "### Run inference without GT pose ###\n", "b3d.reload(i)" ] }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ - "b3d.rr_init(\"inference_test_c2f_7\")" + "b3d.rr_init(\"real_inference2\")" ] }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/10 [00:00" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": 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", 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" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 77, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "i = jnp.argmax(metadata[\"p_scores\"])\n", - "metadata[\"p_scores\"][i-3:i+3]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array([[0, 5],\n", - " [0, 6],\n", - " [0, 7],\n", - " [1, 5],\n", - " [1, 6],\n", - " [1, 7],\n", - " [2, 5],\n", - " [2, 6],\n", - " [2, 7],\n", - " [3, 5],\n", - " [3, 6],\n", - " [3, 7]], dtype=int32)" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def all_pairs_2(X, Y):\n", - " return jnp.swapaxes(jnp.stack(jnp.meshgrid(X, Y), axis=-1), 0, 1).reshape(-1, 2)\n", - "\n", - "all_pairs_2(jnp.arange(0, 4), jnp.arange(5, 8))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 84, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# get the 10 largest values in p_scores\n", - "jnp.sort(metadata[\"p_scores\"])[-10:]" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 80, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jnp.max(metadata[\"log_q_poses\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 91, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jnp.min(jnp.nan_to_num(metadata[\"log_q_nonpose_latents\"], -jnp.inf))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "dict_keys(['chosen_pose_index', 'other_latents_metadata', 'proposed_poses'])" - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "metadata.keys()" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "{'depth_nonreturn_proposal': {'index': ,\n", - " 'latent_depth': ,\n", - " 'likelihood_score': \n", - " >,\n", - " 'log_normalized_scores': \n", - " >,\n", - " 'observed_depth': ,\n", - " 'prev_dnrp': ,\n", - " 'support': \n", - " >,\n", - " 'transition_score': \n", - " >},\n", - " 'dnrps': }" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "md = jax.tree.map(lambda x: x[metadata['chosen_pose_index']], metadata['other_latents_metadata'])\n", - "jax.tree.map(lambda x: x[0], md)" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def sample(key):\n", - " return jax.random.categorical(key, jnp.array([-1.01509 , -0.44999695]))\n", - "\n", - "key = jax.random.PRNGKey(0)\n", - "jax.vmap(sample)(jax.random.split(key, 100))" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jnp.exp(jnp.array([-1.01509 , -0.44999695]))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "b3d.reload(b3d.chisight.gen3d.projection)\n", - "from b3d.chisight.gen3d.projection import PixelsPointsAssociation\n", - "import b3d.chisight.gen3d.model as m\n", - "\n", - "obs_point_depths = PixelsPointsAssociation.from_hyperparams_and_pose(\n", - " m.get_hypers(trace), m.get_new_state(trace)[\"pose\"]\n", - ").get_point_depths(m.get_observed_rgbd(trace))\n", - "\n", - "true_point_depths = template_pose.apply(hyperparams[\"vertices\"])[:, 2]\n", - "\n", - "jnp.all(jnp.abs(obs_point_depths - true_point_depths) < 1e-3)" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jnp.any(jnp.abs(obs_point_depths - true_point_depths[0]) < 1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "true_point_colors = m.get_prev_state(trace)[\"colors\"]\n", - "obs_point_colors = PixelsPointsAssociation.from_hyperparams_and_pose(\n", - " m.get_hypers(trace), m.get_new_state(trace)[\"pose\"]\n", - ").get_point_rgbds(m.get_observed_rgbd(trace))[..., :3]\n", - "\n", - "true_point_colors - obs_point_colors" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "dict_keys(['chosen_pose_index', 'other_latents_metadata', 'proposed_poses'])" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "metadata.keys()" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jnp.all(stepped_trace.get_retval()[\"new_state\"][\"depth_nonreturn_prob\"] == metadata[\"other_latents_metadata\"][\"dnrps\"][metadata[\"chosen_pose_index\"]])" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "# jax.Array float32(100,) ≈0.68 ±0.46 [≥0.01, ≤0.99] nonzero:100\n", - " Array([0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01,\n", - " 0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.99, 0.99, 0.01, 0.99, 0.99,\n", - " 0.01, 0.01, 0.99, 0.01, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01,\n", - " 0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.01, 0.01, 0.99, 0.99,\n", - " 0.99, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99,\n", - " 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01,\n", - " 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01, 0.99, 0.99, 0.01, 0.99,\n", - " 0.99, 0.01, 0.99, 0.01, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.99,\n", - " 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.01, 0.99, 0.01, 0.99, 0.99,\n", - " 0.01], dtype=float32)\n" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "stepped_trace.get_retval()[\"new_state\"][\"depth_nonreturn_prob\"][:100]" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "T = 0\n", - "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "{'depth_nonreturn_proposal': {'index': \n", - " >,\n", - " 'log_normalized_scores': \n", - " >,\n", - " 'support': \n", - " >}}" - ] - }, - "execution_count": 75, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jax.tree.map(\n", - " lambda x: x[closest_pose_idx], metadata[\"other_latents_metadata\"]\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 65, - "metadata": {}, - "outputs": [], - "source": [ - "gt_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 66, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "metadata[\"proposed_poses\"].position" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 74, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "closest_pose_idx" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "closest_pose_idx = jnp.argmin(\n", - " jnp.linalg.norm(\n", - " metadata[\"proposed_poses\"].position - gt_pose.position, axis=-1\n", + "## Finish the run\n", + "for T in tqdm(range(20, len(all_data))):\n", + " key = b3d.split_key(key)\n", + " trace = i.inference_step_c2f(\n", + " key,\n", + " 1, # number of sequential iterations of the parallel pose proposal to consider\n", + " 5000, # number of poses to propose in parallel\n", + " # So the total number of poses considered at each step of C2F is 5000 * 1\n", + " trace, all_data[T][\"rgbd\"],\n", + " prev_color_proposal_laplace_scale=inference_hyperparams.prev_color_proposal_laplace_scale,\n", + " obs_color_proposal_laplace_scale=inference_hyperparams.obs_color_proposal_laplace_scale,\n", + " do_stochastic_color_proposals=True\n", " )\n", - ")\n", - "metadata[\"proposed_poses\"].quaternion[closest_pose_idx]" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "\n", - ">" - ] - }, - "execution_count": 73, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "gt_pose.quaternion" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [], - "source": [ - "T = 1\n", - "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[2024-09-10T18:07:03Z WARN re_log_types::path::parse_path] When parsing the entity path \"proposed positions\": Unescaped whitespace. The path will be interpreted as /proposed\\ positions\n" - ] - } - ], - "source": [ - "import rerun as rr\n", - "rr.log(\"proposed positions\", rr.Points3D(metadata[\"proposed_poses\"].position))" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 57, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jax.scipy.special.logsumexp(jnp.array([-jnp.inf, -.2, -1.]))" + " b3d.chisight.gen3d.model.viz_trace(\n", + " trace,\n", + " T,\n", + " ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", + " ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", + " )\n" ] }, { diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 8b356049..26c3a6a2 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -8,6 +8,7 @@ from genjax import UpdateProblemBuilder as U from jax.random import split +import b3d from b3d.chisight.gen3d.inference_moves import ( get_pose_proposal_density, propose_other_latents_given_pose, @@ -73,6 +74,27 @@ def advance_time(key, trace, observed_rgbd): def inference_step_c2f( key, n_seq, n_poses_per_sequential_step, old_trace, observed_rgbd, *args, **kwargs ): + """ + Take an inference step using a coarse-to-fine sweep of pose proposals. + At each step of C2F, we propose `n_seq * n_poses_per_sequential_step` poses, + for each pose, propose all the other latents, and then resample one among + these options. That pose is used as the center of the pose proposal + distribution for the next step of C2F. + The final trace is returned. + + Args: + - key: PRNGKey + - n_seq: For each step of C2F, how many parallel batches of poses to propose. + (This is provided so more poses can be considered than can fit into GPU memory.) + - n_poses_per_sequential_step: How many poses to propose in parallel at each step. + (So at each step of C2F, we propose n_seq * n_poses_per_sequential_step poses, + and resample one. Then at the next step of C2F, we propose that many poses + again, but with a narrower proposal distribution.) + - old_trace: The trace from the previous timestep. + - observed_rgbd: The observed RGBD image at the current timestep. + - **kwargs: Kwargs providing each field of InferenceHyperparams + other than `n_poses`, `pose_proposal_std`, and `pose_proposal_conc`. + """ k1, k2 = split(key) trace = advance_time(k1, old_trace, observed_rgbd) return infer_latents_c2f( @@ -106,6 +128,13 @@ def infer_latents_c2f( def inference_step_using_sequential_proposals( key, n_seq, old_trace, observed_rgbd, inference_hyperparams ): + """ + Like `inference_step`, but does `n_seq` sequential proposals + of `inference_hyperparams.n_poses` poses and other latents, + and resamples one among all of these. + Considers n_seq * inference_hyperparams.n_poses proposals in total. + Returns `(trace, weight)`. + """ k1, k2 = split(key) trace = advance_time(k1, old_trace, observed_rgbd) return infer_latents_using_sequential_proposals( @@ -114,12 +143,6 @@ def inference_step_using_sequential_proposals( def infer_latents_using_sequential_proposals(key, n_seq, trace, inference_hyperparams): - """ - Like `inference_step`, but does `n_seq` sequential proposals - of `inference_hyperparams.n_poses` poses and other latents, - and resamples one among all of these. - Returns `(trace, weight)`. - """ shared_args = (trace, inference_hyperparams) def get_weight(key): @@ -140,12 +163,22 @@ def get_weight(key): def inference_step( key, old_trace, observed_rgbd, inference_hyperparams, *args, **kwargs ): + """ + Perform over the latent state at time T, given the observed + rgbd at this timestep, and the old trace from time T-1. + + Also returns an estimate of the marginal likelihood of + the observed rgbd, given the latent state from time T-1. + + All arguments after `inference_hyperparams` are passed to + `infer_latents`; see `infer_latents` for details. + """ k1, k2 = split(key) trace = advance_time(k1, old_trace, observed_rgbd) return infer_latents(k2, trace, inference_hyperparams, *args, **kwargs) -@partial(jax.jit, static_argnums=(3, 4, 5, 6)) +@partial(jax.jit, static_argnums=(3, 4, 5)) def infer_latents( key, trace, @@ -155,34 +188,49 @@ def infer_latents( get_metadata=True, # If this is included, we guarantee that this is one of the # poses in the grid. - gt_pose=None, + use_gt_pose=False, + gt_pose=b3d.Pose.identity(), + # Useful for debugging: turn off - logq in the pose resampling + include_qscores_in_outer_resample=True, ): """ - Perform over the latent state at time T, given the observed - rgbd at this timestep, and the old trace from time T-1. - - Also returns an estimate of the marginal likelihood of - the observed rgbd, given the latent state from time T-1. - - If `gt_pose` is not None, this will force the pose sampled at index 0 - in the sampling step to be `gt_pose`. (That is, this will do inference - as would occur given that the ground truth pose was the first sampled - pose.) + Infer the latents at time `T`, given a trace `T` with arguments + containing the prev state (state at `T-1`). + Pose proposals are centered around the trace in the new state + in this trace. + + Args: + - key: PRNGKey + - trace: Partially inferred trace at time `T`. + (E.g. the output of `advance_time`.) + - inference_hyperparams: InferenceHyperparams + - get_trace: Controls whether the inferred trace is in the function's return value. + - get_weight: Controls whether the weight is in the function's return value. + - get_metadata: Controls whether the metadata is in the function's return value. + - use_gt_pose: If true, the value `gt_pose` will be placed as the first + proposed pose, in the pose proposal. (Ie. the function will act as though + it proposed this pose on the first step.) + - gt_pose: The ground truth pose at time T. """ - _, k2, k3, _ = split(key, 4) + _, k2, k3, k4 = split(key, 4) pose_generation_keys = split(k2, inference_hyperparams.n_poses) proposed_poses, log_q_poses = jax.vmap(propose_pose, in_axes=(0, None, None))( pose_generation_keys, trace, inference_hyperparams ) - if gt_pose is not None: - proposed_poses = jax.tree.map( - lambda x, y: x.at[0].set(y), proposed_poses, gt_pose - ) - log_q_poses = log_q_poses.at[0].set( - get_pose_proposal_density(gt_pose, trace, inference_hyperparams) + proposed_poses = jax.tree.map( + lambda x, y: x.at[0].set(jnp.where(use_gt_pose, y, x[0])), + proposed_poses, + gt_pose, + ) + log_q_poses = log_q_poses.at[0].set( + jnp.where( + use_gt_pose, + get_pose_proposal_density(gt_pose, trace, inference_hyperparams), + log_q_poses[0], ) + ) param_generation_keys = split(k3, inference_hyperparams.n_poses) proposed_traces, log_q_nonpose_latents, other_latents_metadata = jax.vmap( @@ -190,11 +238,15 @@ def infer_latents( )(param_generation_keys, trace, proposed_poses, inference_hyperparams) p_scores = jax.vmap(lambda tr: tr.get_score())(proposed_traces) - scores = p_scores # - log_q_poses - log_q_nonpose_latents - chosen_index = jnp.argmax(scores) # jax.random.categorical(k4, scores) + scores = jnp.where( + include_qscores_in_outer_resample, + p_scores - log_q_poses - log_q_nonpose_latents, + p_scores, + ) + chosen_index = jax.random.categorical(k4, scores) new_trace = jax.tree.map(lambda x: x[chosen_index], proposed_traces) - weight = jnp.max(scores) # logmeanexp(scores) + weight = logmeanexp(scores) metadata = { "proposed_poses": proposed_poses, "chosen_pose_index": chosen_index, diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index c465d169..58cce765 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -182,7 +182,6 @@ def _propose_a_points_attributes( color_scale, depth_scale, inference_hyperparams, - return_metadata=True, ): k1, k2 = split(key, 2) From d6faa72144f61a5e07299a26c6ee5577bf971f21 Mon Sep 17 00:00:00 2001 From: georgematheos Date: Fri, 13 Sep 2024 12:26:21 -0400 Subject: [PATCH 19/37] Inference bug fixes --- notebooks/bayes3d_paper/tester.ipynb | 47 ++- notebooks/bayes3d_paper/tester2.ipynb | 432 +++++++++++++++++++++++++ src/b3d/chisight/gen3d/image_kernel.py | 5 +- src/b3d/chisight/gen3d/inference.py | 7 +- 4 files changed, 470 insertions(+), 21 deletions(-) create mode 100644 notebooks/bayes3d_paper/tester2.ipynb diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index e1f5ce90..6a55c3fd 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -49,7 +49,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 13.47it/s]\n", + "100%|██████████| 49/49 [00:03<00:00, 13.41it/s]\n", "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", " warnings.warn(\n" @@ -440,7 +440,7 @@ "metadata": {}, "outputs": [], "source": [ - "b3d.rr_init(\"inference_given_gtpose_4\")" + "b3d.rr_init(\"inference_given_gtpose_5\")" ] }, { @@ -454,23 +454,23 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "inference_hyperparams = i.InferenceHyperparams(\n", " n_poses=1500,\n", - " do_stochastic_color_proposals=False,\n", + " do_stochastic_color_proposals=True,\n", " pose_proposal_std=0.04,\n", " pose_proposal_conc=1000.,\n", " prev_color_proposal_laplace_scale=.04,\n", - " obs_color_proposal_laplace_scale=.01,\n", + " obs_color_proposal_laplace_scale=.02,\n", ")" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 35, "metadata": {}, "outputs": [ { @@ -484,9 +484,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/georgematheos/b3d/src/b3d/modeling_utils.py:86: UserWarning: RenormalizedLaplace sampling is currently not implemented perfectly.\n", - " warnings.warn(\n", - "100%|██████████| 30/30 [00:32<00:00, 1.09s/it]\n" + "100%|██████████| 30/30 [00:09<00:00, 3.02it/s]\n" ] } ], @@ -539,11 +537,11 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ - "b3d.rr_init(\"real_inference2\")" + "b3d.rr_init(\"real_inference_3\")" ] }, { @@ -562,7 +560,11 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 20/20 [01:51<00:00, 5.57s/it]\n" + "/home/georgematheos/b3d/src/b3d/modeling_utils.py:86: UserWarning: RenormalizedLaplace sampling is currently not implemented perfectly.\n", + " warnings.warn(\n", + "/home/georgematheos/b3d/src/b3d/modeling_utils.py:86: UserWarning: RenormalizedLaplace sampling is currently not implemented perfectly.\n", + " warnings.warn(\n", + "100%|██████████| 20/20 [02:35<00:00, 7.75s/it]\n" ] } ], @@ -593,7 +595,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -607,12 +609,29 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 29/29 [02:40<00:00, 5.55s/it]\n" + " 14%|█▍ | 4/29 [00:40<04:16, 10.25s/it]\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[29], line 6\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m T \u001b[38;5;129;01min\u001b[39;00m tqdm(\u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m20\u001b[39m, \u001b[38;5;28mlen\u001b[39m(all_data))):\n\u001b[1;32m 5\u001b[0m key \u001b[38;5;241m=\u001b[39m b3d\u001b[38;5;241m.\u001b[39msplit_key(key)\n\u001b[0;32m----> 6\u001b[0m trace \u001b[38;5;241m=\u001b[39m \u001b[43mi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minference_step_c2f\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# number of sequential iterations of the parallel pose proposal to consider\u001b[39;49;00m\n\u001b[1;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m5000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# number of poses to propose in parallel\u001b[39;49;00m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# So the total number of poses considered at each step of C2F is 5000 * 1\u001b[39;49;00m\n\u001b[1;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mall_data\u001b[49m\u001b[43m[\u001b[49m\u001b[43mT\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrgbd\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[43mprev_color_proposal_laplace_scale\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minference_hyperparams\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprev_color_proposal_laplace_scale\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 13\u001b[0m \u001b[43m 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pose_proposal_std\u001b[38;5;241m=\u001b[39mstd,\n\u001b[1;32m 117\u001b[0m pose_proposal_conc\u001b[38;5;241m=\u001b[39mconc,\n\u001b[1;32m 118\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39minference_hyperparam_kwargs,\n\u001b[1;32m 119\u001b[0m )\n\u001b[1;32m 120\u001b[0m key, _ \u001b[38;5;241m=\u001b[39m split(key)\n\u001b[0;32m--> 121\u001b[0m trace, _ \u001b[38;5;241m=\u001b[39m \u001b[43minfer_latents_using_sequential_proposals\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 122\u001b[0m \u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_seq\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\n\u001b[1;32m 123\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m trace\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference.py:153\u001b[0m, in \u001b[0;36minfer_latents_using_sequential_proposals\u001b[0;34m(key, n_seq, trace, inference_hyperparams)\u001b[0m\n\u001b[1;32m 151\u001b[0m k1, k2 \u001b[38;5;241m=\u001b[39m split(key)\n\u001b[1;32m 152\u001b[0m ks \u001b[38;5;241m=\u001b[39m split(k1, n_seq)\n\u001b[0;32m--> 153\u001b[0m weights \u001b[38;5;241m=\u001b[39m [\u001b[43mget_weight\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m ks]\n\u001b[1;32m 155\u001b[0m normalized_logps \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mnn\u001b[38;5;241m.\u001b[39mlog_softmax(jnp\u001b[38;5;241m.\u001b[39marray(weights))\n\u001b[1;32m 156\u001b[0m chosen_idx \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mcategorical(k2, normalized_logps)\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference.py:149\u001b[0m, in \u001b[0;36minfer_latents_using_sequential_proposals..get_weight\u001b[0;34m(key)\u001b[0m\n\u001b[1;32m 148\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_weight\u001b[39m(key):\n\u001b[0;32m--> 149\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minfer_latents\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mshared_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mget_trace\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mget_metadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m[\u001b[38;5;241m0\u001b[39m]\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], "source": [ "## Finish the run\n", + "key = jax.random.PRNGKey(1234)\n", + "trace = trace_20\n", "for T in tqdm(range(20, len(all_data))):\n", " key = b3d.split_key(key)\n", " trace = i.inference_step_c2f(\n", diff --git a/notebooks/bayes3d_paper/tester2.ipynb b/notebooks/bayes3d_paper/tester2.ipynb new file mode 100644 index 00000000..cacadc3b --- /dev/null +++ b/notebooks/bayes3d_paper/tester2.ipynb @@ -0,0 +1,432 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d\n", + "import jax.numpy as jnp\n", + "import os\n", + "from tqdm import tqdm\n", + "from b3d import Mesh, Pose\n", + "import matplotlib.pyplot as plt\n", + "import genjax\n", + "# genjax.pretty()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Scene 49\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 49/49 [00:03<00:00, 13.40it/s]\n", + "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", + "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/jpeg": 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", 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", + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scene_id = 49\n", + "FRAME_RATE = 50\n", + "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", + "print(f\"Scene {scene_id}\")\n", + "b3d.reload(b3d.io.data_loader)\n", + "num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id)\n", + "\n", + "# image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE)\n", + "image_ids = range(1, num_scenes + 1, FRAME_RATE)\n", + "all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, image_ids)\n", + "\n", + "meshes = [\n", + " Mesh.from_obj_file(\n", + " os.path.join(ycb_dir, f'models/obj_{f\"{id + 1}\".rjust(6, \"0\")}.ply')\n", + " ).scale(0.001)\n", + " for id in all_data[0][\"object_types\"]\n", + "]\n", + "\n", + "image_height, image_width = all_data[0][\"rgbd\"].shape[:2]\n", + "fx,fy,cx,cy = all_data[0][\"camera_intrinsics\"]\n", + "scaling_factor = 1.0\n", + "renderer = b3d.renderer.renderer_original.RendererOriginal(\n", + " image_width * scaling_factor, image_height * scaling_factor, fx * scaling_factor, fy * scaling_factor, cx * scaling_factor, cy * scaling_factor, 0.01, 2.0\n", + ")\n", + "b3d.viz_rgb(all_data[0][\"rgbd\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d\n", + "import b3d.chisight.gen3d.model\n", + "b3d.reload(b3d.chisight.gen3d.model)\n", + "import b3d.chisight.gen3d.transition_kernels as transition_kernels\n", + "b3d.reload(b3d.chisight.gen3d.transition_kernels)\n", + "import b3d.chisight.gen3d.image_kernel as image_kernel\n", + "b3d.reload(b3d.chisight.gen3d.image_kernel)\n", + "import b3d.io.data_loader\n", + "import jax\n", + "import jax.numpy as jnp\n", + "from b3d import Mesh, Pose\n", + "from b3d.chisight.gen3d.model import (\n", + " make_colors_choicemap,\n", + " make_depth_nonreturn_prob_choicemap,\n", + " make_visibility_prob_choicemap,\n", + ")\n", + "from b3d.chisight.gen3d.model import dynamic_object_generative_model\n", + "from genjax import ChoiceMapBuilder as C\n", + "from genjax import Pytree\n", + "import genjax" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "near, far = 0.001, 10." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "T = 0\n", + "b3d.rr_set_time(T)\n", + "\n", + "OBJECT_INDEX = 2\n", + "\n", + "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", + "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", + "xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy)\n", + "\n", + "fx, fy, cx, cy = all_data[T][\"camera_intrinsics\"]\n", + "xyz_observed = b3d.xyz_from_depth(all_data[T][\"rgbd\"][..., 3], fx, fy, cx, cy)\n", + "mask = all_data[T][\"masks\"][OBJECT_INDEX] * (xyz_observed[..., 2] > 0) * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01)\n", + "model_vertices = template_pose.inv().apply(xyz_rendered[mask])\n", + "model_colors = vertex_attributes=all_data[T][\"rgbd\"][..., :3][mask]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "img_model = image_kernel.NoOcclusionPerVertexImageKernel(\n", + " near, far, image_height, image_width\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "color_transiton_scale = 0.04\n", + "p_resample_color = 0.01\n", + "\n", + "# This parameter is needed for the inference hyperparameters.\n", + "# See the `InferenceHyperparams` docstring in `inference.py` for details.\n", + "effective_color_transition_scale = color_transiton_scale + p_resample_color * 1/2\n", + "\n", + "hyperparams = {\n", + " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", + " \"color_kernel\": transition_kernels.MixtureDriftKernel(\n", + " [\n", + " transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=color_transiton_scale),\n", + " transition_kernels.UniformDriftKernel(\n", + " max_shift=0.15, min_val=jnp.zeros(3), max_val=jnp.ones(3)\n", + " )\n", + " ],\n", + " jnp.array([1-p_resample_color, p_resample_color])\n", + " ),\n", + " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.0, 0.998])\n", + " ),\n", + " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.2, support=jnp.array([0.002, 0.998])\n", + " ),\n", + " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02, .1])#, .1, .4, 1.])\n", + " ),\n", + " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.01, 0.05, 0.1, .3])#, 0.15, .3, .8])\n", + " ),\n", + "\n", + " \"image_kernel\": img_model,\n", + "\n", + " \"intrinsics\": {\n", + " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy\n", + " },\n", + " \"image_height\": Pytree.const(image_height),\n", + " \"image_width\": Pytree.const(image_width),\n", + " \n", + " \"vertices\": model_vertices\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "num_vertices = model_vertices.shape[0]\n", + "previous_state = {\n", + " \"pose\": template_pose,\n", + " \"colors\": model_colors,\n", + " \"visibility_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"visibility_prob_kernel\"].support[-1],\n", + " \"depth_nonreturn_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"depth_nonreturn_prob_kernel\"].support[0],\n", + " \"depth_scale\": hyperparams[\"depth_scale_kernel\"].support[0],\n", + " \"color_scale\": hyperparams[\"color_scale_kernel\"].support[0],\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "choicemap = (\n", + " genjax.ChoiceMap.d(\n", + " {\n", + " \"pose\": previous_state[\"pose\"],\n", + " \"color_scale\": previous_state[\"color_scale\"],\n", + " \"depth_scale\": previous_state[\"depth_scale\"],\n", + " \"rgbd\": all_data[T][\"rgbd\"],\n", + " }\n", + " ) ^ \n", + " make_visibility_prob_choicemap(previous_state[\"visibility_prob\"]) ^\n", + " make_colors_choicemap(previous_state[\"colors\"]) ^\n", + " make_depth_nonreturn_prob_choicemap(previous_state[\"depth_nonreturn_prob\"])\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array(67224.41, dtype=float32)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "key = jax.random.PRNGKey(0)\n", + "og_trace, weight = dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", + "trace = og_trace\n", + "weight" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d.chisight.gen3d.inference as i\n", + "\n", + "inference_hyperparams = i.InferenceHyperparams(\n", + " n_poses=1500,\n", + " do_stochastic_color_proposals=False,\n", + " pose_proposal_std=0.04,\n", + " pose_proposal_conc=1000.,\n", + " prev_color_proposal_laplace_scale=0.1,\n", + " obs_color_proposal_laplace_scale=0.1,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init(\"real_inference_7-2\")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.reload(i)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 0%| | 0/20 [00:00 PixelRGBDDistribution: # Note: The distributions were originally defined for per-pixel computation, diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 26c3a6a2..1a0cf3b6 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -14,10 +14,7 @@ propose_other_latents_given_pose, propose_pose, ) -from b3d.chisight.gen3d.model import ( - get_hypers, - get_prev_state, -) +from b3d.chisight.gen3d.model import get_hypers, get_new_state @Pytree.dataclass @@ -60,7 +57,7 @@ def advance_time(key, trace, observed_rgbd): U.g( ( Diff.no_change(get_hypers(trace)), - Diff.unknown_change(get_prev_state(trace)), + Diff.unknown_change(get_new_state(trace)), ), C.kw(rgbd=observed_rgbd), ), From c15ee4fb01e3e4de03073d5bcf295829ba927d04 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Fri, 13 Sep 2024 13:19:09 -0400 Subject: [PATCH 20/37] Old Inference updated (#171) --- notebooks/bayes3d_paper/online_hb.ipynb | 259 +++---------------- src/b3d/chisight/gen3d/image_kernel.py | 88 +++++++ src/b3d/chisight/gen3d/inference_old.py | 242 +++++++++++++++++ src/b3d/chisight/gen3d/transition_kernels.py | 27 +- tests/gen3d/test_inference.py | 3 - tests/gen3d/test_transition_kernels.py | 9 + 6 files changed, 404 insertions(+), 224 deletions(-) create mode 100644 src/b3d/chisight/gen3d/inference_old.py diff --git a/notebooks/bayes3d_paper/online_hb.ipynb b/notebooks/bayes3d_paper/online_hb.ipynb index 855ad3d1..2500161c 100644 --- a/notebooks/bayes3d_paper/online_hb.ipynb +++ b/notebooks/bayes3d_paper/online_hb.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -54,10 +54,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 13.19it/s]\n", - "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", - "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", - " warnings.warn(\n" + "100%|██████████| 49/49 [00:04<00:00, 12.22it/s]\n" ] }, { @@ -105,7 +102,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -132,19 +129,19 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 42, "metadata": {}, - "outputs": [], - "source": [ - "near, far = 0.001, 100." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "45277.63\n" + ] + } + ], "source": [ + "\n", "T = 0\n", "b3d.rr_set_time(T)\n", "OBJECT_INDEX = 1\n", @@ -167,69 +164,41 @@ " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.15),\n", " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, possible_values=jnp.array([0.01, 0.99])\n", + " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", " ),\n", " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, possible_values=jnp.array([0.01, 0.99])\n", + " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", " ),\n", " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, possible_values=jnp.array([0.0025, 0.01, 0.02])\n", + " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02])\n", " ),\n", " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, possible_values=jnp.array([0.05, 0.1, 0.15])\n", + " resample_probability=0.05, support=jnp.array([0.05, 0.1, 0.15])\n", " ),\n", "\n", - " \"image_likelihood\": image_kernel.NoOcclusionPerVertexImageKernel(\n", - " near, far, image_height, image_width\n", + " \"image_kernel\": image_kernel.OldNoOcclusionPerVertexImageKernel(\n", + " 0.001, 1.0, image_height, image_width\n", " ),\n", "\n", - " \"fx\": fx,\n", - " \"fy\": fy,\n", - " \"cx\": cx,\n", - " \"cy\": cy,\n", + " \"intrinsics\": {\n", + " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy\n", + " },\n", " \"image_height\": Pytree.const(image_height),\n", " \"image_width\": Pytree.const(image_width),\n", " \n", - " \"vertices\": model_vertices\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "82541.78\n" - ] - }, - { - "ename": "AttributeError", - "evalue": "'NoOcclusionPerVertexImageKernel' object has no attribute 'info_from_trace'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[6], line 30\u001b[0m\n\u001b[1;32m 28\u001b[0m trace\u001b[38;5;241m=\u001b[39m dynamic_object_generative_model\u001b[38;5;241m.\u001b[39mimportance(key, choicemap, (hyperparams, previous_state))[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 29\u001b[0m \u001b[38;5;28mprint\u001b[39m(trace\u001b[38;5;241m.\u001b[39mget_score())\n\u001b[0;32m---> 30\u001b[0m \u001b[43mb3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchisight\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mviz_trace\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 31\u001b[0m results \u001b[38;5;241m=\u001b[39m {}\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/model.py:125\u001b[0m, in \u001b[0;36mviz_trace\u001b[0;34m(trace, t, ground_truth_vertices, ground_truth_pose)\u001b[0m\n\u001b[1;32m 123\u001b[0m output \u001b[38;5;241m=\u001b[39m trace\u001b[38;5;241m.\u001b[39mget_retval()\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m output[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 125\u001b[0m info \u001b[38;5;241m=\u001b[39m \u001b[43mhyperparams\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mimage_likelihood\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minfo_from_trace\u001b[49m(trace)\n\u001b[1;32m 126\u001b[0m b3d\u001b[38;5;241m.\u001b[39mrr_log_rgb(output[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m][\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 127\u001b[0m b3d\u001b[38;5;241m.\u001b[39mrr_log_rgb(output[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m][\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage/rgb/observed\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mAttributeError\u001b[0m: 'NoOcclusionPerVertexImageKernel' object has no attribute 'info_from_trace'" - ] - } - ], - "source": [ + " \"vertices\":model_vertices\n", + "}\n", + "\n", "num_vertices = model_vertices.shape[0]\n", "previous_state = {\n", " \"pose\": template_pose,\n", " \"colors\": model_colors,\n", " \"visibility_prob\": jnp.ones(num_vertices)\n", - " * hyperparams[\"visibility_prob_kernel\"].possible_values[-1],\n", + " * hyperparams[\"visibility_prob_kernel\"].support[-1],\n", " \"depth_nonreturn_prob\": jnp.ones(num_vertices)\n", - " * hyperparams[\"depth_nonreturn_prob_kernel\"].possible_values[0],\n", - " \"depth_scale\": hyperparams[\"depth_scale_kernel\"].possible_values[0],\n", - " \"color_scale\": hyperparams[\"color_scale_kernel\"].possible_values[0],\n", + " * hyperparams[\"depth_nonreturn_prob_kernel\"].support[0],\n", + " \"depth_scale\": hyperparams[\"depth_scale_kernel\"].support[0],\n", + " \"color_scale\": hyperparams[\"color_scale_kernel\"].support[0],\n", "}\n", "\n", "choicemap = (\n", @@ -255,182 +224,40 @@ }, { "cell_type": "code", - "execution_count": 153, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/49 [00:00 PixelRGBDDistribution: RenormalizedLaplacePixelDepthDistribution(self.near, self.far), UniformPixelDepthDistribution(self.near, self.far), ) + + +@Pytree.dataclass +class OldNoOcclusionPerVertexImageKernel(ImageKernel): + near: float = Pytree.static() + far: float = Pytree.static() + image_height: int = Pytree.static() + image_width: int = Pytree.static() + + @jax.jit + def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: + return jnp.zeros( + ( + self.image_height, + self.image_width, + 4, + ) + ) + + @jax.jit + def logpdf( + self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping + ) -> FloatArray: + return self.info_func(observed_rgbd, state, hyperparams)["scores"].sum() + + def info_from_trace(self, trace): + return self.info_func( + trace.get_choices()["rgbd"], + trace.get_retval()["new_state"], + trace.get_args()[0], + ) + + def info_func(self, observed_rgbd, state, hyperparams): + transformed_points = state["pose"].apply(hyperparams["vertices"]) + projected_pixel_coordinates = jnp.rint( + b3d.xyz_to_pixel_coordinates( + transformed_points, + hyperparams["intrinsics"]["fx"], + hyperparams["intrinsics"]["fy"], + hyperparams["intrinsics"]["cx"], + hyperparams["intrinsics"]["cy"], + ) + ).astype(jnp.int32) + + observed_rgbd_masked = observed_rgbd[ + projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1] + ] + + color_visible_branch_score = jax.scipy.stats.laplace.logpdf( + observed_rgbd_masked[..., :3], state["colors"], state["color_scale"] + ).sum(axis=-1) + color_not_visible_score = jnp.log(1 / 1.0**3) + color_score = jnp.logaddexp( + color_visible_branch_score + jnp.log(state["visibility_prob"]), + color_not_visible_score + jnp.log(1 - state["visibility_prob"]), + ) + + depth_visible_branch_score = jax.scipy.stats.laplace.logpdf( + observed_rgbd_masked[..., 3], + transformed_points[..., 2], + state["depth_scale"], + ) + depth_not_visible_score = jnp.log(1 / 1.0) + _depth_score = jnp.logaddexp( + depth_visible_branch_score + jnp.log(state["visibility_prob"]), + depth_not_visible_score + jnp.log(1 - state["visibility_prob"]), + ) + is_depth_non_return = observed_rgbd_masked[..., 3] < 0.0001 + + non_return_probability = 0.05 + depth_score = jnp.where( + is_depth_non_return, jnp.log(non_return_probability), _depth_score + ) + + lmbda = 0.5 + scores = lmbda * color_score + (1.0 - lmbda) * depth_score + return { + "scores": scores, + "observed_rgbd_masked": observed_rgbd_masked, + } + + def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: + # Note: The distributions were originally defined for per-pixel computation, + # but they should work for per-vertex computation as well, except that + # they don't expect observed_rgbd to be invalid, so we need to handle + # that manually. + raise NotImplementedError diff --git a/src/b3d/chisight/gen3d/inference_old.py b/src/b3d/chisight/gen3d/inference_old.py new file mode 100644 index 00000000..2f800ed6 --- /dev/null +++ b/src/b3d/chisight/gen3d/inference_old.py @@ -0,0 +1,242 @@ +import jax +import jax.numpy as jnp +import jax.random +from genjax import ChoiceMapBuilder as C +from genjax import Diff +from genjax import UpdateProblemBuilder as U + +from b3d import Pose + +from .model import ( + make_colors_choicemap, + make_visibility_prob_choicemap, +) + + +@jax.jit +def advance_time(key, trace, observed_rgbd): + """ + Advance to the next timestep, setting the new latent state to the + same thing as the previous latent state, and setting the new + observed RGBD value. + + Returns a trace where previous_state (stored in the arguments) + and new_state (sampled in the choices and returned) are identical. + """ + hyperparams, _ = trace.get_args() + previous_state = trace.get_retval()["new_state"] + trace, _, _, _ = trace.update( + key, + U.g( + (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), + C.kw(rgbd=observed_rgbd), + ), + ) + return trace + + +@jax.jit +def propose_color_and_visibility(trace, key): + # color_outlier_probability_sweep is (k,) shape array + hyperparams, previous_state = trace.get_args() + previous_visibility = previous_state["visibility_prob"] + previous_colors = previous_state["colors"] + + visibility_values = hyperparams["visibility_prob_kernel"].support + + visibility_sweep = ( + visibility_values[..., None] # (num_outlier_grid_points, 1) + * jnp.ones_like(previous_visibility) # (num_vertices,) + ) # (num_outlier_grid_points, num_vertices) + + visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + + visibility_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( + visibility_prob_kernel.logpdf, + signature="(),()->()", + )(visibility_sweep, previous_visibility) + + info_from_trace = hyperparams["image_kernel"].info_from_trace + + # We will grid over color values, using a grid that mixes the old and observed + # colors in a set of exact proportions. + # We regard these as coming from uniform proposals where we sample the RGB + # values uniformly between the mixed R, G, and B values with mixtures between + # [0., .125], [.125, .5], [.5, .875], [.875, 1.]. + # So the q scores will be .125^3, .375^3, .375^3, .125^3. + # TODO: we really ought to add a small amount of proposal probability mass + # onto the points at the end, to capture the fact that the posterior could allow + # colors outside the considered interpolation window. + color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) + # num_color_grid_points = len(color_interpolations_per_proposal) + + observed_colors = info_from_trace(trace)["observed_rgbd_masked"][ + ..., :3 + ] # (num_vertices, 3) + color_sweep = observed_colors[None, ...] * color_interpolations_per_proposal[ + :, None, None + ] + previous_colors[None, ...] * ( + 1 - color_interpolations_per_proposal[:, None, None] + ) # (num_color_grid_points, num_vertices, 3) + + color_kernel = hyperparams["color_kernel"] + color_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( + color_kernel.logpdf, + signature="(3),(3)->()", + )(color_sweep, previous_colors) + + # Function takes in color and color outlier probabilities array of shapes (num_vertices,3) and (num_vertices,) respectively + # and gives scores for each vertex (num_vertices,) + def get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities( + colors, visibility + ): + return info_from_trace( + trace.update( + key, + make_colors_choicemap(colors) + ^ make_visibility_prob_choicemap(visibility), + )[0] + )["scores"] + + vmap_version = jax.vmap( + jax.vmap( + get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities, + in_axes=(None, 0), + ), + in_axes=(0, None), + ) + + # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep + likelihood_scores_per_sweep_point_and_vertex = vmap_version( + color_sweep, visibility_sweep + ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + scores_per_sweep_point_and_vertex = ( + likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + visibility_transition_scores_per_sweep_point_and_vertex[None, ...] + + color_transition_scores_per_sweep_point_and_vertex[:, None, ...] + ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) + + unraveled_scores = scores_per_sweep_point_and_vertex.reshape( + -1, scores_per_sweep_point_and_vertex.shape[-1] + ) + normalized_log_probabilities = jax.nn.log_softmax(unraveled_scores, axis=0) + sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) + + color_sweep_indices, visibility_sweep_indices = jnp.unravel_index( + sampled_indices, scores_per_sweep_point_and_vertex.shape[:2] + ) + + # color_sweep is (num_outlier_grid_points, num_vertices, 3) + # outlier_probability_sweep is (num_outlier_grid_points,) + # color_outlier_probabilities_sweep is (num_outlier_grid_points, num_vertices) + sampled_colors = color_sweep[color_sweep_indices, jnp.arange(color_sweep.shape[1])] + sampled_color_outlier_probabilities = visibility_values[visibility_sweep_indices] + + log_q_color_and_color_outlier_probability = normalized_log_probabilities[ + sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) + ].sum() + + # log_q = estimate of q(all these colors, all these outliers ; inputs) + # Only source of real randomness = sampling indices. Captured in log_q_color_and_color_outlier_probability. + # But we also want to be careful with the continuous values... + # (1) outlier probs. --> change the model to have discrete grid. [Do later.] + # (2) colors. --> 1/q() + # uniform(old r, 2/3 oldr + 1/3 newr) 0 | uniform(0, 0.1) + # uniform(1/3, 2/3) # .5 | uniform(.1, .9) + # uniform(2/3, 1) # 1 | uniform(.9, 1) + # + # q(c1) * q(c2) * q(c3) + # but we just output c2 + # q(the c values we output, marginalizing over the other choices) + # -> just output q(c2) + + # We will treat this like the case where each sweep is uniform, so the q scores + # are each (oldr - obsr)/3 * (oldg - obsg)/3 * (oldb - obsb)/3. + + hyperparams = trace.get_args()[0] + color_shift_scale = hyperparams["color_kernel"].scale + color_scale = trace.get_choices()["color_scale"] + + d = 1 / (1 / color_shift_scale + 1 / color_scale) + + q_prob_per_vertex = ( + 1.0 / ((jnp.abs(previous_colors - observed_colors) / 3) + 4 * d) + ).prod(-1) + log_q_for_the_color_proposal = jnp.log(q_prob_per_vertex).sum() + + return ( + sampled_colors, + sampled_color_outlier_probabilities, + log_q_color_and_color_outlier_probability + log_q_for_the_color_proposal, + scores_per_sweep_point_and_vertex, + ) + + +@jax.jit +def propose_update(trace, key, pose): + total_log_q = 0.0 + + # Update pose + # pose, log_q_pose = propose_pose( + # trace, key, pose_sample_variance, pose_sample_concentration + # ) + trace = trace.update(key, C["pose"].set(pose))[0] + + # Update color and color outlier probability + sampled_colors, sampled_visibility, log_q, _ = propose_color_and_visibility( + trace, key + ) + trace = trace.update( + key, + make_colors_choicemap(sampled_colors) + ^ make_visibility_prob_choicemap(sampled_visibility), + )[0] + total_log_q += log_q + + return trace, total_log_q + + +@jax.jit +def propose_update_get_score(trace, key, pose): + new_trace, log_q = propose_update(trace, key, pose) + # score is an estimate of P(data, pose | previous state) + return new_trace.get_score() - log_q + + +propose_update_get_score_vmap = jax.jit( + jax.vmap(propose_update_get_score, in_axes=(None, None, 0)) +) + + +def inference_step_without_advance(trace, key): + number = 15000 + current_pose = trace.get_choices()["pose"] + var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] + for var, conc in var_conc: + key = jax.random.split(key, 2)[-1] + keys = jax.random.split(key, number) + poses = Pose.concatenate_poses( + [ + Pose.sample_gaussian_vmf_pose_vmap(keys, current_pose, var, conc), + current_pose[None, ...], + ] + ) + pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( + poses, trace.get_choices()["pose"], var, conc + ) + scores = propose_update_get_score_vmap(trace, key, poses) + scores_pose_q_correction = ( + scores - pose_scores + ) # After this, scores are fair estimates of P(data | previous state) + # and can be used to resample the choice sets. + index = jax.random.categorical(key, scores) + current_pose = poses[index] + trace = propose_update(trace, key, current_pose)[0] + return trace, scores, scores_pose_q_correction + + +def inference_step(trace, key, observed_rgbd): + trace = advance_time(key, trace, observed_rgbd) + trace = inference_step_without_advance(trace, key)[0] + return trace diff --git a/src/b3d/chisight/gen3d/transition_kernels.py b/src/b3d/chisight/gen3d/transition_kernels.py index 08dbf88f..48571e18 100644 --- a/src/b3d/chisight/gen3d/transition_kernels.py +++ b/src/b3d/chisight/gen3d/transition_kernels.py @@ -378,10 +378,27 @@ def sample(self, key: PRNGKey, prev_value): ) def logpdf(self, new_value, prev_value): + # Write code to compute the logpdf of this flipping kernel. + + resample_probability = self.resample_probability + support = self.support + match = new_value == prev_value - return jnp.logaddexp( - jnp.log(1.0 - self.resample_probability) + jnp.log(1.0 * match), - jnp.log(self.resample_probability) - - jnp.log(len(self.support) - 1) - + jnp.log(1.0 * (1 - match)), + number_of_other_values = len(support) - 1 + + log_probability_of_non_matched_values = jnp.where( + number_of_other_values > 0.0, + jnp.log(resample_probability) - jnp.log(number_of_other_values), + jnp.log(0.0), + ) + log_total_probability_of_non_matched_values = ( + log_probability_of_non_matched_values + jnp.log(len(support) - 1) + ) + log_probability_of_match = jnp.log( + 1.0 - jnp.exp(log_total_probability_of_non_matched_values) + ) + logprob = jnp.logaddexp( + jnp.log(match) + log_probability_of_match, + log_probability_of_non_matched_values + jnp.log(1.0 - match), ) + return logprob diff --git a/tests/gen3d/test_inference.py b/tests/gen3d/test_inference.py index 423f9220..77891133 100644 --- a/tests/gen3d/test_inference.py +++ b/tests/gen3d/test_inference.py @@ -90,7 +90,6 @@ def get_visibility_prob_sample( color_scale, depth_scale, inference_hyperparams, - return_metadata=True, ) return visibility_prob @@ -163,7 +162,6 @@ def get_dnr_prob_sample(key, observed_rgbd_for_point, previous_dnrp): color_scale, depth_scale, inference_hyperparams, - return_metadata=True, ) return dnr_prob @@ -234,7 +232,6 @@ def get_color_sample(key, observed_rgbd_for_point, previous_color): color_scale, depth_scale, inference_hyperparams, - return_metadata=True, ) return rgb diff --git a/tests/gen3d/test_transition_kernels.py b/tests/gen3d/test_transition_kernels.py index 578ae03b..a153727d 100644 --- a/tests/gen3d/test_transition_kernels.py +++ b/tests/gen3d/test_transition_kernels.py @@ -20,3 +20,12 @@ def test_discrete_flip_kernel(): kernel.logpdf(possible_values[0], possible_values[-1]), jnp.log(flip_probability / (num_values - 1)), ) + + possible_values = jnp.array([0.01]) + flip_probability = 0.1 + kernel = transition_kernels.DiscreteFlipKernel( + resample_probability=flip_probability, support=possible_values + ) + assert jnp.isclose( + kernel.logpdf(possible_values[0], possible_values[0]), jnp.log(1.0) + ) From 277c0aabd4791652f0c85a50b793f57481b8be69 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Fri, 13 Sep 2024 16:18:45 -0400 Subject: [PATCH 21/37] Refactor out global hyperparameters (#172) --- .../bayes3d_paper/run_ycbv_evaluation.py | 42 ++- notebooks/bayes3d_paper/tester.ipynb | 156 +++++------- src/b3d/chisight/gen3d/image_kernel.py | 208 ++++++++------- src/b3d/chisight/gen3d/inference_moves.py | 3 + .../chisight/gen3d/pixel_kernels/__init__.py | 27 -- .../pixel_kernels/pixel_depth_kernels.py | 240 +++++------------- .../gen3d/pixel_kernels/pixel_rgbd_kernels.py | 25 +- src/b3d/chisight/gen3d/settings.py | 42 +++ tests/gen3d/test_inference.py | 61 +---- tests/gen3d/test_model.py | 42 ++- tests/gen3d/test_pixel_depth_kernels.py | 30 +-- tests/gen3d/test_pixel_rgbd_kernels.py | 77 +++++- 12 files changed, 416 insertions(+), 537 deletions(-) delete mode 100644 src/b3d/chisight/gen3d/pixel_kernels/__init__.py create mode 100644 src/b3d/chisight/gen3d/settings.py diff --git a/notebooks/bayes3d_paper/run_ycbv_evaluation.py b/notebooks/bayes3d_paper/run_ycbv_evaluation.py index caf5b9e5..09dd9110 100644 --- a/notebooks/bayes3d_paper/run_ycbv_evaluation.py +++ b/notebooks/bayes3d_paper/run_ycbv_evaluation.py @@ -1,36 +1,28 @@ #!/usr/bin/env python +import os + +import b3d +import b3d.chisight.gen3d.image_kernel as image_kernel +import b3d.chisight.gen3d.transition_kernels as transition_kernels import fire +import genjax +import jax +import jax.numpy as jnp +from b3d import Mesh, Pose +from b3d.chisight.gen3d.model import ( + dynamic_object_generative_model, + make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, + make_visibility_prob_choicemap, +) +from genjax import Pytree +from tqdm import tqdm def run_tracking(scene=None, object=None, debug=False): - import importlib - import os - - import b3d - import b3d.chisight.gen3d.image_kernel as image_kernel - import b3d.chisight.gen3d.transition_kernels as transition_kernels - import genjax - import jax - import jax.numpy as jnp - from b3d import Mesh, Pose - from b3d.chisight.gen3d.model import ( - dynamic_object_generative_model, - make_colors_choicemap, - make_depth_nonreturn_prob_choicemap, - make_visibility_prob_choicemap, - ) - from genjax import Pytree - from tqdm import tqdm - - importlib.reload(b3d.mesh) - importlib.reload(b3d.io.data_loader) - importlib.reload(b3d.utils) - importlib.reload(b3d.renderer.renderer_original) - FRAME_RATE = 50 ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") - b3d.rr_init("run_ycbv_evaluation") if scene is None: diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index 6a55c3fd..b430d694 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -6,8 +6,8 @@ "metadata": {}, "outputs": [], "source": [ - "%load_ext autoreload\n", - "%autoreload 2" + "# %load_ext autoreload\n", + "# %autoreload 2" ] }, { @@ -49,10 +49,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:03<00:00, 13.41it/s]\n", - "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n", - "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n", - " warnings.warn(\n" + "100%|██████████| 49/49 [00:04<00:00, 11.77it/s]\n" ] }, { @@ -118,6 +115,7 @@ " make_depth_nonreturn_prob_choicemap,\n", " make_visibility_prob_choicemap,\n", ")\n", + "b3d.reload(b3d.chisight.gen3d.model)\n", "from b3d.chisight.gen3d.model import dynamic_object_generative_model\n", "from genjax import ChoiceMapBuilder as C\n", "from genjax import Pytree\n", @@ -129,15 +127,6 @@ "execution_count": 5, "metadata": {}, "outputs": [], - "source": [ - "near, far = 0.001, 100." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], "source": [ "T = 0\n", "b3d.rr_set_time(T)\n", @@ -156,75 +145,38 @@ ] }, { - "cell_type": "code", - "execution_count": 7, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "img_model = image_kernel.NoOcclusionPerVertexImageKernel(\n", - " near, far, image_height, image_width\n", - ")" + "## Generate initial trace (/ initial state)" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ - "color_transiton_scale = 0.04\n", - "p_resample_color = 0.01\n", - "\n", - "# This parameter is needed for the inference hyperparameters.\n", - "# See the `InferenceHyperparams` docstring in `inference.py` for details.\n", - "effective_color_transition_scale = color_transiton_scale + p_resample_color * 1/2\n", - "\n", - "hyperparams = {\n", - " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=1.0),\n", - " \"color_kernel\": transition_kernels.MixtureDriftKernel(\n", - " [\n", - " transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=color_transiton_scale),\n", - " transition_kernels.UniformDriftKernel(\n", - " max_shift=0.15, min_val=jnp.zeros(3), max_val=jnp.ones(3)\n", - " )\n", - " ],\n", - " jnp.array([1-p_resample_color, p_resample_color])\n", - " ),\n", - " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.0, 0.998])\n", - " ),\n", - " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.002, 0.998])\n", - " ),\n", - " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02, .1])#, .1, .4, 1.])\n", - " ),\n", - " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.01, 0.05, 0.1, .3])#, 0.15, .3, .8])\n", - " ),\n", - "\n", - " \"image_kernel\": img_model,\n", - "\n", - " \"intrinsics\": {\n", - " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy\n", - " },\n", - " \"image_height\": Pytree.const(image_height),\n", - " \"image_width\": Pytree.const(image_width),\n", - " \n", - " \"vertices\": model_vertices\n", - "}" + "import b3d.chisight.gen3d.settings\n", + "hyperparams = b3d.chisight.gen3d.settings.hyperparams\n", + "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 7, "metadata": {}, + "outputs": [], "source": [ - "## Generate initial trace (/ initial state)" + "hyperparams[\"intrinsics\"] = {\n", + " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy, \"image_height\": image_height,\"image_width\": image_width,\n", + "}\n", + "hyperparams[\"vertices\"] = model_vertices" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -243,7 +195,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -264,23 +216,60 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "Array(120035.86, dtype=float32)" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" + "ename": "TypeError", + "evalue": "RenormalizedLaplacePixelDepthDistribution.__init__() missing 2 required positional arguments: 'near' and 'far'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[10], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m key \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mPRNGKey(\u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m----> 2\u001b[0m og_trace, weight \u001b[38;5;241m=\u001b[39m \u001b[43mb3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchisight\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdynamic_object_generative_model\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimportance\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mchoicemap\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mhyperparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprevious_state\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m trace \u001b[38;5;241m=\u001b[39m og_trace\n\u001b[1;32m 4\u001b[0m weight\n", + "File \u001b[0;32m<@beartype(genjax._src.core.generative.core.GenerativeFunction.importance) at 0x7f212c7d1620>:77\u001b[0m, in \u001b[0;36mimportance\u001b[0;34m(__beartype_object_139780457001344, __beartype_get_violation, __beartype_conf, __beartype_object_94027647930096, __beartype_object_94027647965088, __beartype_object_139780463811040, __beartype_object_139780456993088, __beartype_func, *args, **kwargs)\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:801\u001b[0m, in \u001b[0;36mGenerativeFunction.importance\u001b[0;34m(self, key, constraint, args)\u001b[0m\n\u001b[1;32m 759\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 760\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mimportance\u001b[39m(\n\u001b[1;32m 761\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 764\u001b[0m args: Arguments,\n\u001b[1;32m 765\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[Trace, Weight]:\n\u001b[1;32m 766\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 767\u001b[0m \u001b[38;5;124;03m Returns a properly weighted pair, a [`Trace`][genjax.core.Trace] and a [`Weight`][genjax.core.Weight], properly weighted for the target induced by the generative function for the provided constraint and arguments.\u001b[39;00m\n\u001b[1;32m 768\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 799\u001b[0m \u001b[38;5;124;03m Under the hood, creates an [`UpdateProblem`][genjax.core.UpdateProblem] which requests that the generative function respond with a move from the _empty_ trace (the only possible value for _empty_ target $\\\\delta_\\\\emptyset$) to the target induced by the generative function for constraint $C$ with arguments $a$.\u001b[39;00m\n\u001b[1;32m 800\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 801\u001b[0m tr, w, _, _ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 802\u001b[0m \u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 803\u001b[0m \u001b[43m \u001b[49m\u001b[43mEmptyTrace\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 804\u001b[0m \u001b[43m \u001b[49m\u001b[43mGenericProblem\u001b[49m\u001b[43m(\u001b[49m\u001b[43mDiff\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munknown_change\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mImportanceProblem\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconstraint\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 805\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 806\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tr, w\n", + " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", + "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.StaticGenerativeFunction.update) at 0x7f2120a34e00>:78\u001b[0m, in \u001b[0;36mupdate\u001b[0;34m(__beartype_object_139780457001344, __beartype_get_violation, __beartype_conf, __beartype_object_94027647965088, __beartype_object_94027647916672, __beartype_object_139780463811040, __beartype_object_139780456908416, __beartype_object_139780456993088, __beartype_func, *args, **kwargs)\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:595\u001b[0m, in \u001b[0;36mStaticGenerativeFunction.update\u001b[0;34m(self, key, trace, update_problem)\u001b[0m\n\u001b[1;32m 593\u001b[0m \u001b[38;5;28;01mmatch\u001b[39;00m update_problem:\n\u001b[1;32m 594\u001b[0m \u001b[38;5;28;01mcase\u001b[39;00m GenericProblem(argdiffs, subproblem):\n\u001b[0;32m--> 595\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate_change_target\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msubproblem\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margdiffs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 596\u001b[0m \u001b[38;5;28;01mcase\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01m_\u001b[39;00m:\n\u001b[1;32m 597\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mupdate(\n\u001b[1;32m 598\u001b[0m key,\n\u001b[1;32m 599\u001b[0m trace,\n\u001b[1;32m 600\u001b[0m GenericProblem(Diff\u001b[38;5;241m.\u001b[39mno_change(trace\u001b[38;5;241m.\u001b[39mget_args()), update_problem),\n\u001b[1;32m 601\u001b[0m )\n", + "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.StaticGenerativeFunction.update_change_target) at 0x7f2120a34cc0>:103\u001b[0m, in \u001b[0;36mupdate_change_target\u001b[0;34m(__beartype_object_139780457001344, __beartype_get_violation, __beartype_conf, __beartype_object_94027647965088, __beartype_object_94027647916672, __beartype_object_139780460630784, __beartype_object_139780463811040, __beartype_object_139780456908416, __beartype_object_139780456993088, __beartype_func, *args, **kwargs)\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:560\u001b[0m, in \u001b[0;36mStaticGenerativeFunction.update_change_target\u001b[0;34m(self, key, trace, update_problem, argdiffs)\u001b[0m\n\u001b[1;32m 536\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 537\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mupdate_change_target\u001b[39m(\n\u001b[1;32m 538\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 542\u001b[0m argdiffs: Argdiffs,\n\u001b[1;32m 543\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[Trace, Weight, Retdiff, UpdateProblem]:\n\u001b[1;32m 544\u001b[0m syntax_sugar_handled \u001b[38;5;241m=\u001b[39m push_trace_overload_stack(\n\u001b[1;32m 545\u001b[0m handler_trace_with_static, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msource\n\u001b[1;32m 546\u001b[0m )\n\u001b[1;32m 547\u001b[0m (\n\u001b[1;32m 548\u001b[0m (\n\u001b[1;32m 549\u001b[0m retval_diffs,\n\u001b[1;32m 550\u001b[0m weight,\n\u001b[1;32m 551\u001b[0m (\n\u001b[1;32m 552\u001b[0m arg_primals,\n\u001b[1;32m 553\u001b[0m retval_primals,\n\u001b[1;32m 554\u001b[0m address_visitor,\n\u001b[1;32m 555\u001b[0m address_traces,\n\u001b[1;32m 556\u001b[0m score,\n\u001b[1;32m 557\u001b[0m ),\n\u001b[1;32m 558\u001b[0m bwd_problems,\n\u001b[1;32m 559\u001b[0m ),\n\u001b[0;32m--> 560\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[43mupdate_transform\u001b[49m\u001b[43m(\u001b[49m\u001b[43msyntax_sugar_handled\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mupdate_problem\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margdiffs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 562\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mmake_bwd_problem\u001b[39m(visitor, subproblems):\n\u001b[1;32m 563\u001b[0m addresses \u001b[38;5;241m=\u001b[39m visitor\u001b[38;5;241m.\u001b[39mget_visited()\n", + "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.update_transform.wrapper) at 0x7f1b8cd8e480>:31\u001b[0m, in \u001b[0;36mwrapper\u001b[0;34m(__beartype_get_violation, __beartype_conf, __beartype_func, *args, **kwargs)\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:377\u001b[0m, in \u001b[0;36mupdate_transform..wrapper\u001b[0;34m(key, previous_trace, constraints, diffs)\u001b[0m\n\u001b[1;32m 375\u001b[0m diff_primals \u001b[38;5;241m=\u001b[39m Diff\u001b[38;5;241m.\u001b[39mtree_primal(diffs)\n\u001b[1;32m 376\u001b[0m diff_tangents \u001b[38;5;241m=\u001b[39m Diff\u001b[38;5;241m.\u001b[39mtree_tangent(diffs)\n\u001b[0;32m--> 377\u001b[0m retval_diffs \u001b[38;5;241m=\u001b[39m \u001b[43mincremental\u001b[49m\u001b[43m(\u001b[49m\u001b[43msource_fn\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 378\u001b[0m \u001b[43m \u001b[49m\u001b[43mstateful_handler\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdiff_primals\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdiff_tangents\u001b[49m\n\u001b[1;32m 379\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 380\u001b[0m retval_primals \u001b[38;5;241m=\u001b[39m Diff\u001b[38;5;241m.\u001b[39mtree_primal(retval_diffs)\n\u001b[1;32m 381\u001b[0m (\n\u001b[1;32m 382\u001b[0m score,\n\u001b[1;32m 383\u001b[0m weight,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 386\u001b[0m bwd_problems,\n\u001b[1;32m 387\u001b[0m ) \u001b[38;5;241m=\u001b[39m stateful_handler\u001b[38;5;241m.\u001b[39myield_state()\n", + "File \u001b[0;32m<@beartype(genjax._src.core.interpreters.incremental.incremental.wrapped) at 0x7f1b8cd8e5c0>:73\u001b[0m, in \u001b[0;36mwrapped\u001b[0;34m(__beartype_object_139756341382400, __beartype_get_violation, __beartype_conf, __beartype_func, *args, **kwargs)\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/incremental.py:316\u001b[0m, in \u001b[0;36mincremental..wrapped\u001b[0;34m(_stateful_handler, primals, tangents)\u001b[0m\n\u001b[1;32m 308\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(f)\n\u001b[1;32m 309\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 310\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 313\u001b[0m tangents: Tuple,\n\u001b[1;32m 314\u001b[0m ):\n\u001b[1;32m 315\u001b[0m interpreter \u001b[38;5;241m=\u001b[39m IncrementalInterpreter()\n\u001b[0;32m--> 316\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minterpreter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_interpreter\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 317\u001b[0m \u001b[43m \u001b[49m\u001b[43m_stateful_handler\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 318\u001b[0m \u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 319\u001b[0m \u001b[43m \u001b[49m\u001b[43mprimals\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 320\u001b[0m \u001b[43m \u001b[49m\u001b[43mtangents\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 321\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/incremental.py:291\u001b[0m, in \u001b[0;36mIncrementalInterpreter.run_interpreter\u001b[0;34m(self, _stateful_handler, fn, primals, tangents, **kwargs)\u001b[0m\n\u001b[1;32m 288\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_inner\u001b[39m(\u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 289\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 291\u001b[0m _closed_jaxpr, (flat_primals, _, out_tree) \u001b[38;5;241m=\u001b[39m \u001b[43mstage\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_inner\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprimals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 292\u001b[0m flat_tangents \u001b[38;5;241m=\u001b[39m jtu\u001b[38;5;241m.\u001b[39mtree_leaves(\n\u001b[1;32m 293\u001b[0m tangents, is_leaf\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mlambda\u001b[39;00m v: \u001b[38;5;28misinstance\u001b[39m(v, ChangeTangent)\n\u001b[1;32m 294\u001b[0m )\n\u001b[1;32m 295\u001b[0m _jaxpr, consts \u001b[38;5;241m=\u001b[39m _closed_jaxpr\u001b[38;5;241m.\u001b[39mjaxpr, _closed_jaxpr\u001b[38;5;241m.\u001b[39mliterals\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:125\u001b[0m, in \u001b[0;36mstage..wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 123\u001b[0m flat_fun, out_tree \u001b[38;5;241m=\u001b[39m api_util\u001b[38;5;241m.\u001b[39mflatten_fun_nokwargs(fun, in_tree)\n\u001b[1;32m 124\u001b[0m flat_avals \u001b[38;5;241m=\u001b[39m safe_map(get_shaped_aval, flat_args)\n\u001b[0;32m--> 125\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m \u001b[43mcached_stage_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mflat_avals\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr, (flat_args, in_tree, out_tree)\n", + " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:112\u001b[0m, in \u001b[0;36mcached_stage_dynamic\u001b[0;34m(flat_fun, in_avals)\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;129m@lu\u001b[39m\u001b[38;5;241m.\u001b[39mcache\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcached_stage_dynamic\u001b[39m(flat_fun, in_avals):\n\u001b[0;32m--> 112\u001b[0m jaxpr, _, consts \u001b[38;5;241m=\u001b[39m \u001b[43mpe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrace_to_jaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 113\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m jc\u001b[38;5;241m.\u001b[39mClosedJaxpr(jaxpr, consts)\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr\n", + " \u001b[0;31m[... skipping hidden 5 frame]\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/incremental.py:289\u001b[0m, in \u001b[0;36mIncrementalInterpreter.run_interpreter.._inner\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 288\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_inner\u001b[39m(\u001b[38;5;241m*\u001b[39margs):\n\u001b[0;32m--> 289\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:1604\u001b[0m, in \u001b[0;36mpush_trace_overload_stack..wrapped\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 1602\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 1603\u001b[0m GLOBAL_TRACE_OP_HANDLER_STACK\u001b[38;5;241m.\u001b[39mappend(handler)\n\u001b[0;32m-> 1604\u001b[0m ret \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1605\u001b[0m GLOBAL_TRACE_OP_HANDLER_STACK\u001b[38;5;241m.\u001b[39mpop()\n\u001b[1;32m 1606\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ret\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/pytree.py:496\u001b[0m, in \u001b[0;36mClosure.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 495\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 496\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdyn_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/model.py:51\u001b[0m, in \u001b[0;36mdynamic_object_generative_model\u001b[0;34m(hyperparams, previous_state)\u001b[0m\n\u001b[1;32m 49\u001b[0m rgbd \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 51\u001b[0m rgbd \u001b[38;5;241m=\u001b[39m \u001b[43mhyperparams\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mimage_kernel\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnew_state\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhyperparams\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m@\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrgbd\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m 53\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m {\n\u001b[1;32m 54\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnew_state\u001b[39m\u001b[38;5;124m\"\u001b[39m: new_state,\n\u001b[1;32m 55\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m: rgbd,\n\u001b[1;32m 56\u001b[0m }\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:1660\u001b[0m, in \u001b[0;36mGenerativeFunctionClosure.__matmul__\u001b[0;34m(self, addr)\u001b[0m\n\u001b[1;32m 1654\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m handle_off_trace_stack(\n\u001b[1;32m 1655\u001b[0m addr,\n\u001b[1;32m 1656\u001b[0m maybe_kwarged_gen_fn,\n\u001b[1;32m 1657\u001b[0m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkwargs),\n\u001b[1;32m 1658\u001b[0m )\n\u001b[1;32m 1659\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1660\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mhandle_off_trace_stack\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1661\u001b[0m \u001b[43m \u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1662\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1663\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1664\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:1594\u001b[0m, in \u001b[0;36mhandle_off_trace_stack\u001b[0;34m(addr, gen_fn, args)\u001b[0m\n\u001b[1;32m 1592\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m GLOBAL_TRACE_OP_HANDLER_STACK:\n\u001b[1;32m 1593\u001b[0m handler \u001b[38;5;241m=\u001b[39m GLOBAL_TRACE_OP_HANDLER_STACK[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m-> 1594\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mhandler\u001b[49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1595\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1596\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\n\u001b[1;32m 1597\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAttempting to invoke trace outside of a tracing context.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mIf you want to invoke the generative function closure, and recieve a return value,\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124minvoke it with a key.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1598\u001b[0m )\n", + "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.handler_trace_with_static) at 0x7f2120a347c0>:91\u001b[0m, in \u001b[0;36mhandler_trace_with_static\u001b[0;34m(__beartype_getrandbits, __beartype_get_violation, __beartype_conf, __beartype_object_94027648046928, __beartype_func, *args, **kwargs)\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:467\u001b[0m, in \u001b[0;36mhandler_trace_with_static\u001b[0;34m(addr, gen_fn, args)\u001b[0m\n\u001b[1;32m 461\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 462\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhandler_trace_with_static\u001b[39m(\n\u001b[1;32m 463\u001b[0m addr: StaticAddressComponent \u001b[38;5;241m|\u001b[39m StaticAddress,\n\u001b[1;32m 464\u001b[0m gen_fn: GenerativeFunction,\n\u001b[1;32m 465\u001b[0m args: Tuple,\n\u001b[1;32m 466\u001b[0m ):\n\u001b[0;32m--> 467\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtrace\u001b[49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.trace) at 0x7f2120a16700>:89\u001b[0m, in \u001b[0;36mtrace\u001b[0;34m(__beartype_getrandbits, __beartype_get_violation, __beartype_conf, __beartype_object_94027648046928, __beartype_func, *args, **kwargs)\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:178\u001b[0m, in \u001b[0;36mtrace\u001b[0;34m(addr, gen_fn, args)\u001b[0m\n\u001b[1;32m 170\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Invoke a generative function, binding its generative semantics with the current\u001b[39;00m\n\u001b[1;32m 171\u001b[0m \u001b[38;5;124;03mcaller.\u001b[39;00m\n\u001b[1;32m 172\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[38;5;124;03m gen_fn: A generative function invoked as a callee of `StaticGenerativeFunction`.\u001b[39;00m\n\u001b[1;32m 176\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 177\u001b[0m addr \u001b[38;5;241m=\u001b[39m Pytree\u001b[38;5;241m.\u001b[39mtree_const(addr)\n\u001b[0;32m--> 178\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minitial_style_bind\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace_p\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_abstract_gen_fn_call\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 179\u001b[0m \u001b[43m \u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 180\u001b[0m \u001b[43m \u001b[49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 181\u001b[0m \u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 182\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/forward.py:121\u001b[0m, in \u001b[0;36minitial_style_bind..bind..wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 119\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 120\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Runs a function and binds it to a call primitive.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 121\u001b[0m _jaxpr, (flat_args, in_tree, out_tree) \u001b[38;5;241m=\u001b[39m \u001b[43mstage\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 122\u001b[0m outs \u001b[38;5;241m=\u001b[39m prim\u001b[38;5;241m.\u001b[39mbind(\n\u001b[1;32m 123\u001b[0m \u001b[38;5;241m*\u001b[39mit\u001b[38;5;241m.\u001b[39mchain(_jaxpr\u001b[38;5;241m.\u001b[39mliterals, flat_args),\n\u001b[1;32m 124\u001b[0m _jaxpr\u001b[38;5;241m=\u001b[39m_jaxpr\u001b[38;5;241m.\u001b[39mjaxpr,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams,\n\u001b[1;32m 129\u001b[0m )\n\u001b[1;32m 130\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tree_util\u001b[38;5;241m.\u001b[39mtree_unflatten(out_tree(), outs)\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:125\u001b[0m, in \u001b[0;36mstage..wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 123\u001b[0m flat_fun, out_tree \u001b[38;5;241m=\u001b[39m api_util\u001b[38;5;241m.\u001b[39mflatten_fun_nokwargs(fun, in_tree)\n\u001b[1;32m 124\u001b[0m flat_avals \u001b[38;5;241m=\u001b[39m safe_map(get_shaped_aval, flat_args)\n\u001b[0;32m--> 125\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m \u001b[43mcached_stage_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mflat_avals\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr, (flat_args, in_tree, out_tree)\n", + " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:112\u001b[0m, in \u001b[0;36mcached_stage_dynamic\u001b[0;34m(flat_fun, in_avals)\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;129m@lu\u001b[39m\u001b[38;5;241m.\u001b[39mcache\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcached_stage_dynamic\u001b[39m(flat_fun, in_avals):\n\u001b[0;32m--> 112\u001b[0m jaxpr, _, consts \u001b[38;5;241m=\u001b[39m \u001b[43mpe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrace_to_jaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 113\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m jc\u001b[38;5;241m.\u001b[39mClosedJaxpr(jaxpr, consts)\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr\n", + " \u001b[0;31m[... skipping hidden 5 frame]\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:161\u001b[0m, in \u001b[0;36m_abstract_gen_fn_call\u001b[0;34m(_, gen_fn, args)\u001b[0m\n\u001b[1;32m 156\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_abstract_gen_fn_call\u001b[39m(\n\u001b[1;32m 157\u001b[0m _: Address,\n\u001b[1;32m 158\u001b[0m gen_fn: GenerativeFunction,\n\u001b[1;32m 159\u001b[0m args: Tuple,\n\u001b[1;32m 160\u001b[0m ):\n\u001b[0;32m--> 161\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mgen_fn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__abstract_call__\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/distributions/distribution.py:498\u001b[0m, in \u001b[0;36mExactDensity.__abstract_call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 496\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__abstract_call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 497\u001b[0m key \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mPRNGKey(\u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m--> 498\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msample\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/image_kernel.py:70\u001b[0m, in \u001b[0;36mNoOcclusionPerVertexImageKernel.sample\u001b[0;34m(self, key, state, hyperparams)\u001b[0m\n\u001b[1;32m 66\u001b[0m transformed_points \u001b[38;5;241m=\u001b[39m state[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpose\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mapply(hyperparams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvertices\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m 67\u001b[0m points_to_pixels \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_pixels_points_association(\n\u001b[1;32m 68\u001b[0m transformed_points, hyperparams\n\u001b[1;32m 69\u001b[0m )\n\u001b[0;32m---> 70\u001b[0m vertex_kernel \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_rgbd_vertex_kernel\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 72\u001b[0m \u001b[38;5;66;03m# assuming that at most one vertex hit the pixel, we can convert the\u001b[39;00m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;66;03m# per-vertex attributes into per-pixel attributes, then vmap the\u001b[39;00m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;66;03m# RGBD pixel kernel over the pixels to generate the image.\u001b[39;00m\n\u001b[1;32m 75\u001b[0m pixel_visibility_prob \u001b[38;5;241m=\u001b[39m points_to_pixels\u001b[38;5;241m.\u001b[39mget_pixel_attributes(\n\u001b[1;32m 76\u001b[0m state[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisibility_prob\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 77\u001b[0m )\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/image_kernel.py:140\u001b[0m, in \u001b[0;36mNoOcclusionPerVertexImageKernel.get_rgbd_vertex_kernel\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_rgbd_vertex_kernel\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m PixelRGBDDistribution:\n\u001b[1;32m 133\u001b[0m \u001b[38;5;66;03m# Note: The distributions were originally defined for per-pixel computation,\u001b[39;00m\n\u001b[1;32m 134\u001b[0m \u001b[38;5;66;03m# but they should work for per-vertex computation as well, except that\u001b[39;00m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;66;03m# they don't expect observed_rgbd to be invalid, so we need to handle\u001b[39;00m\n\u001b[1;32m 136\u001b[0m \u001b[38;5;66;03m# that manually.\u001b[39;00m\n\u001b[1;32m 137\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m FullPixelRGBDDistribution(\n\u001b[1;32m 138\u001b[0m RenormalizedLaplacePixelColorDistribution(),\n\u001b[1;32m 139\u001b[0m UniformPixelColorDistribution(),\n\u001b[0;32m--> 140\u001b[0m \u001b[43mRenormalizedLaplacePixelDepthDistribution\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m,\n\u001b[1;32m 141\u001b[0m UniformPixelDepthDistribution(),\n\u001b[1;32m 142\u001b[0m )\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/penzai/core/struct.py:423\u001b[0m, in \u001b[0;36mAbstractStructMetaclass.__call__\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m 416\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_pytree_dataclass_type(\u001b[38;5;28mcls\u001b[39m):\n\u001b[1;32m 417\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 418\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCan\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt instantiate abstract Struct subclass \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. Non-abstract\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 419\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m subclasses of penzai.Struct must be decorated with\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 420\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m @penzai.pytree_dataclass before they can be instantiated.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 421\u001b[0m )\n\u001b[0;32m--> 423\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__call__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[0;31mTypeError\u001b[0m: RenormalizedLaplacePixelDepthDistribution.__init__() missing 2 required positional arguments: 'near' and 'far'" + ] } ], "source": [ "key = jax.random.PRNGKey(0)\n", - "og_trace, weight = dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", + "og_trace, weight = b3d.chisight.gen3d.model.dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))\n", "trace = og_trace\n", "weight" ] @@ -365,16 +354,7 @@ "execution_count": 17, "metadata": {}, "outputs": [], - "source": [ - "inference_hyperparams = i.InferenceHyperparams(\n", - " n_poses=1500,\n", - " do_stochastic_color_proposals=True,\n", - " pose_proposal_std=0.04,\n", - " pose_proposal_conc=1000.,\n", - " prev_color_proposal_laplace_scale=0.04,\n", - " obs_color_proposal_laplace_scale=0.01,\n", - ")" - ] + "source": [] }, { "cell_type": "code", @@ -676,7 +656,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.5" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index b95db25a..2106b8f5 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -7,8 +7,6 @@ from genjax import Pytree from genjax.typing import FloatArray, PRNGKey -import b3d -from b3d.chisight.gen3d.pixel_kernels import is_unexplained from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( RenormalizedLaplacePixelColorDistribution, UniformPixelColorDistribution, @@ -20,6 +18,7 @@ from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import ( FullPixelRGBDDistribution, PixelRGBDDistribution, + is_unexplained, ) from b3d.chisight.gen3d.projection import PixelsPointsAssociation @@ -33,19 +32,14 @@ class ImageKernel(genjax.ExactDensity): The support of the distribution is [0, 1]^3 x [near, far]. """ - near: float = Pytree.static() - far: float = Pytree.static() - image_height: int = Pytree.static() - image_width: int = Pytree.static() - def get_pixels_points_association( self, transformed_points, hyperparams: Mapping ) -> PixelsPointsAssociation: return PixelsPointsAssociation.from_points_and_intrinsics( transformed_points, hyperparams["intrinsics"], - self.image_height, - self.image_width, + hyperparams["intrinsics"]["image_height"].const, + hyperparams["intrinsics"]["image_width"].const, ) @abstractmethod @@ -64,11 +58,6 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: @Pytree.dataclass class NoOcclusionPerVertexImageKernel(ImageKernel): - near: float = Pytree.static() - far: float = Pytree.static() - image_height: int = Pytree.static() - image_width: int = Pytree.static() - def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: """Generate latent RGBD image by projecting the vertices directly to the image plane, without checking for occlusions. @@ -96,10 +85,16 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr [pixel_latent_rgbd, pixel_latent_depth[..., None]], axis=-1 ) - keys = jax.random.split(key, (self.image_height, self.image_width)) + keys = jax.random.split( + key, + ( + hyperparams["intrinsics"]["image_height"].const, + hyperparams["intrinsics"]["image_width"].const, + ), + ) return jax.vmap( - jax.vmap(vertex_kernel.sample, in_axes=(0, 0, None, None, 0, 0)), - in_axes=(0, 0, None, None, 0, 0), + jax.vmap(vertex_kernel.sample, in_axes=(0, 0, None, None, 0, 0, None)), + in_axes=(0, 0, None, None, 0, 0, None), )( keys, pixel_latent_rgbd, @@ -107,6 +102,7 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr state["depth_scale"], pixel_visibility_prob, pixel_depth_nonreturn_prob, + hyperparams["intrinsics"], ) def logpdf( @@ -122,13 +118,14 @@ def logpdf( (state["colors"], transformed_points[..., 2, None]), axis=-1 ) - scores = jax.vmap(vertex_kernel.logpdf, in_axes=(0, 0, None, None, 0, 0))( + scores = jax.vmap(vertex_kernel.logpdf, in_axes=(0, 0, None, None, 0, 0, None))( observed_rgbd_per_point, latent_rgbd_per_point, state["color_scale"], state["depth_scale"], state["visibility_prob"], state["depth_nonreturn_prob"], + hyperparams["intrinsics"], ) # Points that don't hit the camera plane should not contribute to the score. scores = jnp.where(is_unexplained(observed_rgbd_per_point), 0.0, scores) @@ -146,93 +143,88 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: return FullPixelRGBDDistribution( RenormalizedLaplacePixelColorDistribution(), UniformPixelColorDistribution(), - RenormalizedLaplacePixelDepthDistribution(self.near, self.far), - UniformPixelDepthDistribution(self.near, self.far), - ) - - -@Pytree.dataclass -class OldNoOcclusionPerVertexImageKernel(ImageKernel): - near: float = Pytree.static() - far: float = Pytree.static() - image_height: int = Pytree.static() - image_width: int = Pytree.static() - - @jax.jit - def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: - return jnp.zeros( - ( - self.image_height, - self.image_width, - 4, - ) - ) - - @jax.jit - def logpdf( - self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping - ) -> FloatArray: - return self.info_func(observed_rgbd, state, hyperparams)["scores"].sum() - - def info_from_trace(self, trace): - return self.info_func( - trace.get_choices()["rgbd"], - trace.get_retval()["new_state"], - trace.get_args()[0], - ) - - def info_func(self, observed_rgbd, state, hyperparams): - transformed_points = state["pose"].apply(hyperparams["vertices"]) - projected_pixel_coordinates = jnp.rint( - b3d.xyz_to_pixel_coordinates( - transformed_points, - hyperparams["intrinsics"]["fx"], - hyperparams["intrinsics"]["fy"], - hyperparams["intrinsics"]["cx"], - hyperparams["intrinsics"]["cy"], - ) - ).astype(jnp.int32) - - observed_rgbd_masked = observed_rgbd[ - projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1] - ] - - color_visible_branch_score = jax.scipy.stats.laplace.logpdf( - observed_rgbd_masked[..., :3], state["colors"], state["color_scale"] - ).sum(axis=-1) - color_not_visible_score = jnp.log(1 / 1.0**3) - color_score = jnp.logaddexp( - color_visible_branch_score + jnp.log(state["visibility_prob"]), - color_not_visible_score + jnp.log(1 - state["visibility_prob"]), - ) - - depth_visible_branch_score = jax.scipy.stats.laplace.logpdf( - observed_rgbd_masked[..., 3], - transformed_points[..., 2], - state["depth_scale"], - ) - depth_not_visible_score = jnp.log(1 / 1.0) - _depth_score = jnp.logaddexp( - depth_visible_branch_score + jnp.log(state["visibility_prob"]), - depth_not_visible_score + jnp.log(1 - state["visibility_prob"]), - ) - is_depth_non_return = observed_rgbd_masked[..., 3] < 0.0001 - - non_return_probability = 0.05 - depth_score = jnp.where( - is_depth_non_return, jnp.log(non_return_probability), _depth_score - ) - - lmbda = 0.5 - scores = lmbda * color_score + (1.0 - lmbda) * depth_score - return { - "scores": scores, - "observed_rgbd_masked": observed_rgbd_masked, - } - - def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: - # Note: The distributions were originally defined for per-pixel computation, - # but they should work for per-vertex computation as well, except that - # they don't expect observed_rgbd to be invalid, so we need to handle - # that manually. - raise NotImplementedError + RenormalizedLaplacePixelDepthDistribution(), + UniformPixelDepthDistribution(), + ) + + +# @Pytree.dataclass +# class OldNoOcclusionPerVertexImageKernel(ImageKernel): +# @jax.jit +# def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: +# return jnp.zeros( +# ( +# hyperparams["intrinsics"]["image_height"].const, +# hyperparams["intrinsics"]["image_width"].const, +# 4, +# ) +# ) + +# @jax.jit +# def logpdf( +# self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping +# ) -> FloatArray: +# return self.info_func(observed_rgbd, state, hyperparams)["scores"].sum() + +# def info_from_trace(self, trace): +# return self.info_func( +# trace.get_choices()["rgbd"], +# trace.get_retval()["new_state"], +# trace.get_args()[0], +# ) + +# def info_func(self, observed_rgbd, state, hyperparams): +# transformed_points = state["pose"].apply(hyperparams["vertices"]) +# projected_pixel_coordinates = jnp.rint( +# b3d.xyz_to_pixel_coordinates( +# transformed_points, +# hyperparams["intrinsics"]["fx"], +# hyperparams["intrinsics"]["fy"], +# hyperparams["intrinsics"]["cx"], +# hyperparams["intrinsics"]["cy"], +# ) +# ).astype(jnp.int32) + +# observed_rgbd_masked = observed_rgbd[ +# projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1] +# ] + +# color_visible_branch_score = jax.scipy.stats.laplace.logpdf( +# observed_rgbd_masked[..., :3], state["colors"], state["color_scale"] +# ).sum(axis=-1) +# color_not_visible_score = jnp.log(1 / 1.0**3) +# color_score = jnp.logaddexp( +# color_visible_branch_score + jnp.log(state["visibility_prob"]), +# color_not_visible_score + jnp.log(1 - state["visibility_prob"]), +# ) + +# depth_visible_branch_score = jax.scipy.stats.laplace.logpdf( +# observed_rgbd_masked[..., 3], +# transformed_points[..., 2], +# state["depth_scale"], +# ) +# depth_not_visible_score = jnp.log(1 / 1.0) +# _depth_score = jnp.logaddexp( +# depth_visible_branch_score + jnp.log(state["visibility_prob"]), +# depth_not_visible_score + jnp.log(1 - state["visibility_prob"]), +# ) +# is_depth_non_return = observed_rgbd_masked[..., 3] < 0.0001 + +# non_return_probability = 0.05 +# depth_score = jnp.where( +# is_depth_non_return, jnp.log(non_return_probability), _depth_score +# ) + +# lmbda = 0.5 +# scores = lmbda * color_score + (1.0 - lmbda) * depth_score +# return { +# "scores": scores, +# "observed_rgbd_masked": observed_rgbd_masked, +# } + +# def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: +# # Note: The distributions were originally defined for per-pixel computation, +# # but they should work for per-vertex computation as well, except that +# # they don't expect observed_rgbd to be invalid, so we need to handle +# # that manually. +# raise NotImplementedError diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index 58cce765..fa75e555 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -164,6 +164,7 @@ def propose_a_points_attributes( obs_rgbd_kernel=hyperparams["image_kernel"].get_rgbd_vertex_kernel(), color_scale=new_state["color_scale"], depth_scale=new_state["depth_scale"], + intrinsics=hyperparams["intrinsics"], inference_hyperparams=inference_hyperparams, ) @@ -181,6 +182,7 @@ def _propose_a_points_attributes( obs_rgbd_kernel, color_scale, depth_scale, + intrinsics, inference_hyperparams, ): k1, k2 = split(key, 2) @@ -198,6 +200,7 @@ def score_attribute_assignment(color, visprob, dnrprob): depth_scale=depth_scale, visibility_prob=visprob, depth_nonreturn_prob=dnrprob, + intrinsics=intrinsics, ) return ( visprob_transition_score diff --git a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py b/src/b3d/chisight/gen3d/pixel_kernels/__init__.py deleted file mode 100644 index 307026aa..00000000 --- a/src/b3d/chisight/gen3d/pixel_kernels/__init__.py +++ /dev/null @@ -1,27 +0,0 @@ -from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( - MixturePixelColorDistribution, - PixelColorDistribution, -) -from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( - DEPTH_NONRETURN_VAL, - MixturePixelDepthDistribution, - PixelDepthDistribution, - UnexplainedPixelDepthDistribution, -) -from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import ( - FullPixelRGBDDistribution, - PixelRGBDDistribution, - is_unexplained, -) - -__all__ = [ - "is_unexplained", - "DEPTH_NONRETURN_VAL", - "MixturePixelColorDistribution", - "MixturePixelDepthDistribution", - "PixelColorDistribution", - "PixelDepthDistribution", - "PixelRGBDDistribution", - "FullPixelRGBDDistribution", - "UnexplainedPixelDepthDistribution", -] diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py index 1c1a0365..e87c9504 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_depth_kernels.py @@ -1,18 +1,15 @@ from abc import abstractmethod -from typing import TYPE_CHECKING, Any +from typing import TYPE_CHECKING import genjax -import jax.numpy as jnp -from genjax import Pytree -from genjax.typing import FloatArray, PRNGKey -from tensorflow_probability.substrates import jax as tfp - from b3d.modeling_utils import ( _FIXED_DEPTH_UNIFORM_WINDOW, - PythonMixtureDistribution, renormalized_laplace, truncated_laplace, ) +from genjax import Pytree +from genjax.typing import PRNGKey +from tensorflow_probability.substrates import jax as tfp if TYPE_CHECKING: import tensorflow_probability.python.distributions.distribution as dist @@ -36,12 +33,26 @@ class PixelDepthDistribution(genjax.ExactDensity): """ @abstractmethod - def sample(self, key: PRNGKey, latent_depth: float, *args, **kwargs) -> float: + def sample( + self, + key: PRNGKey, + latent_depth: float, + near: float, + far: float, + *args, + **kwargs, + ) -> float: raise NotImplementedError @abstractmethod def logpdf( - self, observed_depth: float, latent_depth: float, *args, **kwargs + self, + observed_depth: float, + latent_depth: float, + near: float, + far: float, + *args, + **kwargs, ) -> float: raise NotImplementedError @@ -53,26 +64,30 @@ class RenormalizedGaussianPixelDepthDistribution(PixelDepthDistribution): by depth_scale. The support of the distribution is [near, far]. """ - near: float = Pytree.static() - far: float = Pytree.static() - def sample( - self, key: PRNGKey, latent_depth: float, depth_scale: float, *args, **kwargs + self, + key: PRNGKey, + latent_depth: float, + depth_scale: float, + near: float, + far: float, + *args, + **kwargs, ) -> float: - return genjax.truncated_normal.sample( - key, latent_depth, depth_scale, self.near, self.far - ) + return genjax.truncated_normal.sample(key, latent_depth, depth_scale, near, far) def logpdf( self, observed_depth: float, latent_depth: float, depth_scale: float, + near: float, + far: float, *args, **kwargs, ) -> float: return genjax.truncated_normal.logpdf( - observed_depth, latent_depth, depth_scale, self.near, self.far + observed_depth, latent_depth, depth_scale, near, far ) @@ -83,26 +98,30 @@ class RenormalizedLaplacePixelDepthDistribution(PixelDepthDistribution): by depth_scale. The support of the distribution is [near, far]. """ - near: float = Pytree.static() - far: float = Pytree.static() - def sample( - self, key: PRNGKey, latent_depth: float, depth_scale: float, *args, **kwargs + self, + key: PRNGKey, + latent_depth: float, + depth_scale: float, + near: float, + far: float, + *args, + **kwargs, ) -> float: - return renormalized_laplace.sample( - key, latent_depth, depth_scale, self.near, self.far - ) + return renormalized_laplace.sample(key, latent_depth, depth_scale, near, far) def logpdf( self, observed_depth: float, latent_depth: float, depth_scale: float, + near: float, + far: float, *args, **kwargs, ) -> float: return renormalized_laplace.logpdf( - observed_depth, latent_depth, depth_scale, self.near, self.far + observed_depth, latent_depth, depth_scale, near, far ) @@ -113,21 +132,26 @@ class TruncatedLaplacePixelDepthDistribution(PixelDepthDistribution): controlled by depth_scale. The support of the distribution is [near, far]. """ - near: float = Pytree.static() - far: float = Pytree.static() # the uniform window is used to wrapped the truncated laplace distribution # to ensure that the depth generated is within the range of [near, far] uniform_window_size: float = Pytree.static(default=_FIXED_DEPTH_UNIFORM_WINDOW) def sample( - self, key: PRNGKey, latent_depth: float, depth_scale: float, *args, **kwargs + self, + key: PRNGKey, + latent_depth: float, + depth_scale: float, + near: float, + far: float, + *args, + **kwargs, ) -> float: return truncated_laplace.sample( key, latent_depth, depth_scale, - self.near, - self.far, + near, + far, self.uniform_window_size, ) @@ -136,6 +160,8 @@ def logpdf( observed_depth: float, latent_depth: float, depth_scale: float, + near: float, + far: float, *args, **kwargs, ) -> float: @@ -143,8 +169,8 @@ def logpdf( observed_depth, latent_depth, depth_scale, - self.near, - self.far, + near, + far, self.uniform_window_size, ) @@ -154,163 +180,29 @@ class UniformPixelDepthDistribution(PixelDepthDistribution): """A distribution that generates the depth of a pixel from a uniform from [near, far].""" - near: float = Pytree.static() - far: float = Pytree.static() - - @property - def _base_dist(self) -> "dist.Distribution": - return tfp.distributions.Uniform(self.near, self.far) - - def sample(self, key: PRNGKey, *args, **kwargs) -> float: - return self._base_dist.sample(seed=key) - - def logpdf(self, observed_depth: float, *args, **kwargs) -> float: - return self._base_dist.log_prob(observed_depth) - - -@Pytree.dataclass -class DeltaDistribution(genjax.ExactDensity): - """ - Degenerate discrete distribution (a single point). It assigns probability one - to the single element in its support. - """ - - value: Any - - def sample(self, key: PRNGKey, *args, **kwargs) -> Any: - return self.value - - def logpdf(self, sampled_val: Any, *args, **kwargs) -> float: - return jnp.log(sampled_val == self.value) - - -@Pytree.dataclass -class MixturePixelDepthDistribution(PixelDepthDistribution): - """A distribution that generates the depth of a pixel from - mixture( - [delta(DEPTH_NONRETURN_VAL), uniform(near, far), laplace(latent_depth; depth_scale)], - [depth_nonreturn_prob, (1 - depth_nonreturn_prob) * occluded_prob, remaining_prob] - ) - - The support of the distribution is [near, far] ∪ { "nonreturn" }. - """ - - near: float = Pytree.static() - far: float = Pytree.static() - - @property - def _nonreturn_dist(self) -> PixelDepthDistribution: - return DeltaDistribution(DEPTH_NONRETURN_VAL) - - @property - def _occluded_dist(self) -> PixelDepthDistribution: - return UniformPixelDepthDistribution(self.near, self.far) - - @property - def _inlier_dist(self) -> PixelDepthDistribution: - return TruncatedLaplacePixelDepthDistribution(self.near, self.far) - - @property - def _mixture_dist(self) -> PythonMixtureDistribution: - return PythonMixtureDistribution( - (self._nonreturn_dist, self._occluded_dist, self._inlier_dist) - ) - - def _get_mix_ratio( - self, visibility_prob: float, depth_nonreturn_prob: float - ) -> FloatArray: - return jnp.array( - ( - depth_nonreturn_prob, - (1 - depth_nonreturn_prob) * (1 - visibility_prob), - (1 - depth_nonreturn_prob) * visibility_prob, - ) - ) + def _base_dist(self, near, far) -> "dist.Distribution": + return tfp.distributions.Uniform(near, far) def sample( self, key: PRNGKey, latent_depth: float, depth_scale: float, - visibility_prob: float, - depth_nonreturn_prob: float, + near: float, + far: float, *args, **kwargs, ) -> float: - return self._mixture_dist.sample( - key, - self._get_mix_ratio(visibility_prob, depth_nonreturn_prob), - [(), (), (latent_depth, depth_scale)], - ) + return self._base_dist(near, far).sample(seed=key) def logpdf( self, observed_depth: float, latent_depth: float, depth_scale: float, - visibility_prob: float, - depth_nonreturn_prob: float, - *args, - **kwargs, - ) -> float: - return self._mixture_dist.logpdf( - observed_depth, - self._get_mix_ratio(visibility_prob, depth_nonreturn_prob), - [(), (), (latent_depth, depth_scale)], - ) - - -@Pytree.dataclass -class UnexplainedPixelDepthDistribution(PixelDepthDistribution): - """A distribution that generates the depth of a pixel from - mixture( - [delta(DEPTH_NONRETURN_VAL), uniform(near, far)], - [unexplained_depth_nonreturn_prob, 1 - unexplained_depth_nonreturn_prob] - ), - for pixels that are not explained by the latent points. - - The support of the distribution is [near, far] ∪ { "nonreturn" }. - """ - - near: float = Pytree.static() - far: float = Pytree.static() - unexplained_depth_nonreturn_prob: float = Pytree.static( - default=UNEXPLAINED_DEPTH_NONRETURN_PROB - ) - - @property - def _nonreturn_dist(self) -> PixelDepthDistribution: - return DeltaDistribution(DEPTH_NONRETURN_VAL) - - @property - def _uniform_dist(self) -> PixelDepthDistribution: - return UniformPixelDepthDistribution(self.near, self.far) - - @property - def _mixture_dist(self) -> PythonMixtureDistribution: - return PythonMixtureDistribution((self._nonreturn_dist, self._uniform_dist)) - - @property - def _mix_ratio(self) -> FloatArray: - return jnp.array( - ( - self.unexplained_depth_nonreturn_prob, - 1 - self.unexplained_depth_nonreturn_prob, - ) - ) - - def sample( - self, - key: PRNGKey, - *args, - **kwargs, - ) -> float: - return self._mixture_dist.sample(key, self._mix_ratio, [(), ()]) - - def logpdf( - self, - observed_depth: float, + near: float, + far: float, *args, **kwargs, ) -> float: - return self._mixture_dist.logpdf(observed_depth, self._mix_ratio, [(), ()]) + return self._base_dist(near, far).log_prob(observed_depth) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py index c81322ba..934aca67 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py @@ -2,11 +2,10 @@ import genjax import jax.numpy as jnp -from genjax import Pytree -from genjax.typing import FloatArray, PRNGKey - from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import PixelColorDistribution from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import PixelDepthDistribution +from genjax import Pytree +from genjax.typing import FloatArray, PRNGKey def is_unexplained(latent_value: FloatArray) -> bool: @@ -50,6 +49,7 @@ def sample( depth_scale: float, visibility_prob: float, depth_nonreturn_prob: float, + intrinsics: dict, ) -> FloatArray: raise NotImplementedError @@ -62,6 +62,7 @@ def logpdf( depth_scale: float, visibility_prob: float, depth_nonreturn_prob: float, + intrinsics: dict, ) -> float: raise NotImplementedError @@ -92,6 +93,7 @@ def sample( depth_scale: float, visibility_prob: float, depth_nonreturn_prob: float, + intrinsics: dict, ) -> FloatArray: # TODO: Implement this return jnp.ones((4,)) * 0.5 @@ -104,6 +106,7 @@ def logpdf( depth_scale: float, visibility_prob: float, depth_nonreturn_prob: float, + intrinsics: dict, ) -> float: total_log_prob = 0.0 @@ -121,7 +124,11 @@ def logpdf( jnp.log(depth_nonreturn_prob), jnp.log(1 - depth_nonreturn_prob) + self.inlier_depth_distribution.logpdf( - observed_rgbd[3], latent_rgbd[3], depth_scale + observed_rgbd[3], + latent_rgbd[3], + depth_scale, + intrinsics["near"], + intrinsics["far"], ), ) @@ -129,10 +136,16 @@ def logpdf( total_not_visible_log_prob = 0.0 # color term outlier_color_log_prob = self.outlier_color_distribution.logpdf( - observed_rgbd[:3], latent_rgbd[:3], color_scale + observed_rgbd[:3], + latent_rgbd[:3], + color_scale, ) outlier_depth_log_prob = self.outlier_depth_distribution.logpdf( - observed_rgbd[3], latent_rgbd[3], depth_scale + observed_rgbd[3], + latent_rgbd[3], + depth_scale, + intrinsics["near"], + intrinsics["far"], ) total_not_visible_log_prob += outlier_color_log_prob diff --git a/src/b3d/chisight/gen3d/settings.py b/src/b3d/chisight/gen3d/settings.py new file mode 100644 index 00000000..364265e7 --- /dev/null +++ b/src/b3d/chisight/gen3d/settings.py @@ -0,0 +1,42 @@ +import jax.numpy as jnp + +import b3d.chisight.gen3d.image_kernel as image_kernel +import b3d.chisight.gen3d.inference as inference +import b3d.chisight.gen3d.transition_kernels as transition_kernels + +p_resample_color = 0.005 +hyperparams = { + "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.2), + "color_kernel": transition_kernels.MixtureDriftKernel( + [ + transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.05), + transition_kernels.UniformDriftKernel( + max_shift=0.15, min_val=jnp.zeros(3), max_val=jnp.ones(3) + ), + ], + jnp.array([1 - p_resample_color, p_resample_color]), + ), + "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, support=jnp.array([0.001, 0.999]) + ), + "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, support=jnp.array([0.001, 0.999]) + ), + "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, + support=jnp.array([0.0025, 0.01, 0.02, 0.1, 0.4, 1.0]), + ), + "color_scale_kernel": transition_kernels.DiscreteFlipKernel( + resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15, 0.3, 0.8]) + ), + "image_kernel": image_kernel.NoOcclusionPerVertexImageKernel(), +} + +inference_hyperparams = inference.InferenceHyperparams( + n_poses=6000, + pose_proposal_std=0.04, + pose_proposal_conc=1000.0, + do_stochastic_color_proposals=True, + prev_color_proposal_laplace_scale=0.001, + obs_color_proposal_laplace_scale=0.001, +) diff --git a/tests/gen3d/test_inference.py b/tests/gen3d/test_inference.py index 77891133..877dde7c 100644 --- a/tests/gen3d/test_inference.py +++ b/tests/gen3d/test_inference.py @@ -1,60 +1,24 @@ -import b3d.chisight.gen3d.image_kernel as image_kernel -import b3d.chisight.gen3d.inference as inference import b3d.chisight.gen3d.inference_moves as inference_moves -import b3d.chisight.gen3d.transition_kernels as transition_kernels +import b3d.chisight.gen3d.settings import jax import jax.numpy as jnp import pytest +from genjax import Pytree @pytest.fixture def hyperparams_and_inference_hyperparams(): near, far, image_height, image_width = 0.001, 5.0, 480, 640 - img_model = image_kernel.NoOcclusionPerVertexImageKernel( - near, far, image_height, image_width - ) - color_transiton_scale = 0.05 - p_resample_color = 0.005 - - # This parameter is needed for the inference hyperparameters. - # See the `InferenceHyperparams` docstring in `inference.py` for details. - inference_hyperparams = inference.InferenceHyperparams( - n_poses=6000, - pose_proposal_std=0.04, - pose_proposal_conc=1000.0, - do_stochastic_color_proposals=True, - prev_color_proposal_laplace_scale=0.001, - obs_color_proposal_laplace_scale=0.001, - ) - - hyperparams = { - "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.1), - "color_kernel": transition_kernels.MixtureDriftKernel( - [ - transition_kernels.LaplaceNotTruncatedColorDriftKernel( - scale=color_transiton_scale - ), - transition_kernels.UniformDriftKernel( - max_shift=0.15, min_val=jnp.zeros(3), max_val=jnp.ones(3) - ), - ], - jnp.array([1 - p_resample_color, p_resample_color]), - ), - "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.001, 0.999]) - ), - "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.001, 0.999]) - ), - "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, - support=jnp.array([0.0025, 0.01, 0.02, 0.1, 0.4, 1.0]), - ), - "color_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15, 0.3, 0.8]) - ), - "image_kernel": img_model, + intrinsics = { + "image_height": Pytree.const(image_height), + "image_width": Pytree.const(image_width), + "near": near, + "far": far, } + + hyperparams = b3d.chisight.gen3d.settings.hyperparams + inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams + hyperparams["intrinsics"] = intrinsics return hyperparams, inference_hyperparams @@ -89,6 +53,7 @@ def get_visibility_prob_sample( obs_rgbd_kernel, color_scale, depth_scale, + hyperparams["intrinsics"], inference_hyperparams, ) return visibility_prob @@ -161,6 +126,7 @@ def get_dnr_prob_sample(key, observed_rgbd_for_point, previous_dnrp): obs_rgbd_kernel, color_scale, depth_scale, + hyperparams["intrinsics"], inference_hyperparams, ) return dnr_prob @@ -231,6 +197,7 @@ def get_color_sample(key, observed_rgbd_for_point, previous_color): obs_rgbd_kernel, color_scale, depth_scale, + hyperparams["intrinsics"], inference_hyperparams, ) return rgb diff --git a/tests/gen3d/test_model.py b/tests/gen3d/test_model.py index 6932de89..1b6bcaef 100644 --- a/tests/gen3d/test_model.py +++ b/tests/gen3d/test_model.py @@ -3,7 +3,7 @@ import b3d import b3d.chisight.gen3d.model -import b3d.chisight.gen3d.transition_kernels as transition_kernels +import b3d.chisight.gen3d.settings import b3d.io.data_loader import jax import jax.numpy as jnp @@ -14,11 +14,12 @@ make_visibility_prob_choicemap, ) from genjax import ChoiceMapBuilder as C +from genjax import Pytree b3d.rr_init("test_gen3d_model") -def test_model_no_likelihood(): +def test_model(): importance = b3d.chisight.gen3d.model.dynamic_object_generative_model.importance # num_vertices = 100 @@ -39,22 +40,19 @@ def test_model_no_likelihood(): num_vertices = vertices.shape[0] key = jax.random.PRNGKey(0) - hyperparams = { - "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.1), - "color_kernel": transition_kernels.LaplaceColorDriftKernel(scale=0.05), - "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.01, 0.99]) - ), - "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.01, 0.99]) - ), - "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.005, 0.01, 0.02]) - ), - "color_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15]) - ), - "vertices": vertices, + + hyperparams = b3d.chisight.gen3d.settings.hyperparams + + hyperparams["vertices"] = vertices + hyperparams["intrinsics"] = { + "image_height": Pytree.const(480), + "image_width": Pytree.const(640), + "fx": 1066.778, + "fy": 1067.487, + "cx": 312.9869, + "cy": 241.3109, + "near": 0.1, + "far": 10.0, } previous_state = { @@ -76,7 +74,7 @@ def test_model_no_likelihood(): hyperparams, previous_state = trace.get_args() traces = [trace] - for t in range(100): + for t in range(10): key = b3d.split_key(key) previous_state = trace.get_retval()["new_state"] trace, _ = importance(key, C.n(), (hyperparams, previous_state)) @@ -95,7 +93,7 @@ def test_model_no_likelihood(): fig.suptitle( f""" pose_kernel max_shift: {hyperparams['pose_kernel'].max_shift}, -color_kernel scale: {hyperparams['color_kernel'].scale}, +color_kernel scale: FILL IN, visibility_prob_kernel resample_probability: {hyperparams['visibility_prob_kernel'].resample_probability}, depth_nonreturn_prob_kernel resample_probability: {hyperparams['depth_nonreturn_prob_kernel'].resample_probability}, depth_scale_kernel resample_probability: {hyperparams['depth_scale_kernel'].resample_probability}, @@ -153,7 +151,3 @@ def test_model_no_likelihood(): assert jnp.allclose( new_trace.get_choices()["depth_nonreturn_prob", ...], new_depth_nonreturn_prob ) - - -if __name__ == "__main__": - test_model_no_likelihood() diff --git a/tests/gen3d/test_pixel_depth_kernels.py b/tests/gen3d/test_pixel_depth_kernels.py index 19a5d9fe..ebf30144 100644 --- a/tests/gen3d/test_pixel_depth_kernels.py +++ b/tests/gen3d/test_pixel_depth_kernels.py @@ -2,12 +2,9 @@ import jax.numpy as jnp import pytest from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( - DEPTH_NONRETURN_VAL, - MixturePixelDepthDistribution, RenormalizedGaussianPixelDepthDistribution, RenormalizedLaplacePixelDepthDistribution, TruncatedLaplacePixelDepthDistribution, - UnexplainedPixelDepthDistribution, UniformPixelDepthDistribution, ) @@ -16,19 +13,10 @@ # each kernel specs is a tuple of (kernel, additional_args) sample_kernels_to_test = [ - (UniformPixelDepthDistribution(near, far), ()), - (TruncatedLaplacePixelDepthDistribution(near, far), (0.25,)), - (UnexplainedPixelDepthDistribution(near, far), ()), - (RenormalizedLaplacePixelDepthDistribution(near, far), (0.25,)), - (RenormalizedGaussianPixelDepthDistribution(near, far), (0.25,)), - ( - MixturePixelDepthDistribution(near, far), - ( - 0.15, # scale - 0.5, # visibility_prob - 0.23, # depth_nonreturn_prob - ), - ), + (UniformPixelDepthDistribution(), (0.25, near, far)), + (TruncatedLaplacePixelDepthDistribution(), (0.25, near, far)), + (RenormalizedLaplacePixelDepthDistribution(), (0.25, near, far)), + (RenormalizedGaussianPixelDepthDistribution(), (0.25, near, far)), ] @@ -47,12 +35,6 @@ def test_logpdf_sum_to_1(kernel_spec, latent_depth: float): + jnp.log(far - near) - jnp.log(n_grid_steps) ) - # compute the mass in { "nonreturn" } - log_nonreturn_mass = kernel.logpdf( - DEPTH_NONRETURN_VAL, latent_depth, *additional_args - ) - log_pmass = jnp.logaddexp(log_pmass, log_nonreturn_mass) - assert jnp.isclose(log_pmass, 0.0, atol=1e-3) @@ -66,8 +48,8 @@ def test_sample_in_valid_depth_range(kernel_spec, latent_depth): keys ) assert depths.shape == (num_samples,) - assert jnp.all((depths >= near) | (depths == DEPTH_NONRETURN_VAL)) - assert jnp.all((depths <= far) | (depths == DEPTH_NONRETURN_VAL)) + assert jnp.all((depths >= near)) + assert jnp.all((depths <= far)) # def test_relative_logpdf(): diff --git a/tests/gen3d/test_pixel_rgbd_kernels.py b/tests/gen3d/test_pixel_rgbd_kernels.py index 606edf64..82498cb1 100644 --- a/tests/gen3d/test_pixel_rgbd_kernels.py +++ b/tests/gen3d/test_pixel_rgbd_kernels.py @@ -1,35 +1,48 @@ import jax import jax.numpy as jnp import pytest -from b3d.chisight.gen3d.pixel_kernels import ( - DEPTH_NONRETURN_VAL, - FullPixelRGBDDistribution, -) from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( TruncatedLaplacePixelColorDistribution, UniformPixelColorDistribution, ) from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( + DEPTH_NONRETURN_VAL, TruncatedLaplacePixelDepthDistribution, UniformPixelDepthDistribution, ) +from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import ( + FullPixelRGBDDistribution, +) +from genjax import Pytree near = 0.01 far = 20.0 +intrinsics = { + "image_height": Pytree.const(480), + "image_width": Pytree.const(640), + "fx": 1066.778, + "fy": 1067.487, + "cx": 312.9869, + "cy": 241.3109, + "near": near, + "far": far, +} + sample_kernels_to_test = [ ( FullPixelRGBDDistribution( TruncatedLaplacePixelColorDistribution(), UniformPixelColorDistribution(), - TruncatedLaplacePixelDepthDistribution(near, far), - UniformPixelDepthDistribution(near, far), + TruncatedLaplacePixelDepthDistribution(), + UniformPixelDepthDistribution(), ), ( 0.01, # color_scale 0.01, # depth_scale 1 - 0.3, # visibility_prob 0.1, # depth_nonreturn_prob + intrinsics, ), ) ] @@ -66,10 +79,22 @@ def test_relative_logpdf(kernel_spec): # case 1: no vertex hit the pixel latent_rgbd = -jnp.ones(4) # use -1 to denote invalid pixel logpdf_1 = kernel.logpdf( - obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.8, depth_nonreturn_prob=0.1 + obs_rgbd, + latent_rgbd, + 0.01, + 0.01, + visibility_prob=0.8, + depth_nonreturn_prob=0.1, + intrinsics=intrinsics, ) logpdf_2 = kernel.logpdf( - obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.2, depth_nonreturn_prob=0.1 + obs_rgbd, + latent_rgbd, + 0.01, + 0.01, + visibility_prob=0.2, + depth_nonreturn_prob=0.1, + intrinsics=intrinsics, ) # the logpdf should be the same because the occluded probability is not used # in the case when no vertex hit the pixel @@ -78,10 +103,22 @@ def test_relative_logpdf(kernel_spec): # case 2: a vertex hit the pixel, but the rgbd is not close to the observed rgbd latent_rgbd = jnp.array([1.0, 0.5, 0.0, 12.0]) logpdf_3 = kernel.logpdf( - obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.8, depth_nonreturn_prob=0.1 + obs_rgbd, + latent_rgbd, + 0.01, + 0.01, + visibility_prob=0.8, + depth_nonreturn_prob=0.1, + intrinsics=intrinsics, ) logpdf_4 = kernel.logpdf( - obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.2, depth_nonreturn_prob=0.1 + obs_rgbd, + latent_rgbd, + 0.01, + 0.01, + visibility_prob=0.2, + depth_nonreturn_prob=0.1, + intrinsics=intrinsics, ) # the pixel should be more likely to be an occluded assert logpdf_3 < logpdf_4 @@ -89,10 +126,22 @@ def test_relative_logpdf(kernel_spec): # case 3: a vertex hit the pixel, and the rgbd is close to the observed rgbd latent_rgbd = jnp.array([0.0, 0.0, 0.95, 0.022]) logpdf_5 = kernel.logpdf( - obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.8, depth_nonreturn_prob=0.1 + obs_rgbd, + latent_rgbd, + 0.01, + 0.01, + visibility_prob=0.8, + depth_nonreturn_prob=0.1, + intrinsics=intrinsics, ) logpdf_6 = kernel.logpdf( - obs_rgbd, latent_rgbd, 0.01, 0.01, visibility_prob=0.2, depth_nonreturn_prob=0.1 + obs_rgbd, + latent_rgbd, + 0.01, + 0.01, + visibility_prob=0.2, + depth_nonreturn_prob=0.1, + intrinsics=intrinsics, ) # the pixel should be more likely to be an inlier assert logpdf_5 > logpdf_6 @@ -116,10 +165,10 @@ def test_invalid_pixel(kernel_spec): assert logpdf_1 == logpdf_2 logpdf_3 = kernel.logpdf( - jnp.array([1.0, 0.5, 0.2, 4.0]), latent_rgbd, 0.1, 0.4, 0.2, 0.1 + jnp.array([1.0, 0.5, 0.2, 4.0]), latent_rgbd, 0.1, 0.4, 0.2, 0.1, intrinsics ) logpdf_4 = kernel.logpdf( - jnp.array([0.0, 0.0, 0.0, 0.02]), latent_rgbd, 0.3, 0.5, 0.4, 0.2 + jnp.array([0.0, 0.0, 0.0, 0.02]), latent_rgbd, 0.3, 0.5, 0.4, 0.2, intrinsics ) # and the values of the parameters doesn't matter either assert logpdf_2 == logpdf_3 From 4b7cd6d7c0349b088effc4d00e03e9f2b8fa3c8e Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Fri, 13 Sep 2024 21:55:41 +0000 Subject: [PATCH 22/37] projection --- src/b3d/chisight/gen3d/projection.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index 7899316f..bdfcd767 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -27,8 +27,8 @@ def from_hyperparams_and_pose(cls, hyperparams, pose_CO): return cls.from_points_and_intrinsics( vertices_C, hyperparams["intrinsics"], - hyperparams["image_height"].const, - hyperparams["image_width"].const, + hyperparams["intrinsics"]["image_height"].const, + hyperparams["intrinsics"]["image_width"].const, ) @classmethod From 83d40b488a49807ada736a34e72fbf9f6ccaced0 Mon Sep 17 00:00:00 2001 From: georgematheos Date: Fri, 13 Sep 2024 18:11:15 -0400 Subject: [PATCH 23/37] Upgrade to GenJAX 0.6.1 (#173) --- notebooks/aug1demos/slam_color_room.ipynb | 2 +- notebooks/bayes3d_paper/interactive.ipynb | 8 +- notebooks/bayes3d_paper/tester.ipynb | 126 +- notebooks/bayes3d_paper/ycbv.ipynb | 2 +- notebooks/integration.ipynb | 2 +- pixi.lock | 1326 +++++++++-------- pyproject.toml | 2 +- src/b3d/chisight/dense/dense_model.py | 6 +- .../likelihoods/blur_likelihood_gaussian.py | 2 +- src/b3d/chisight/gen3d/image_kernel.py | 12 +- src/b3d/chisight/gen3d/projection.py | 4 +- src/b3d/chisight/particle_system.py | 24 +- src/b3d/chisight/patch_tracking.py | 8 +- src/b3d/utils.py | 10 +- .../solver/importance.py | 4 +- tests/test_chisight_dense_gps.py | 4 +- 16 files changed, 770 insertions(+), 772 deletions(-) diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb index 0c0f059d..a8273e85 100644 --- a/notebooks/aug1demos/slam_color_room.ipynb +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -1621,7 +1621,7 @@ "# convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", "# convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", "def intermediate_likelihood_func(observed_rgbd, latent_rgbd, likelihood_args):\n", - " k = likelihood_args[\"k\"].const\n", + " k = likelihood_args[\"k\"].unwrap()\n", " fx = likelihood_args[\"fx\"]\n", " fy = likelihood_args[\"fy\"]\n", "\n", diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index b4724748..670fbde8 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -169,7 +169,7 @@ "# def sample_likelihood_func()\n", "\n", "def intermediate_likelihood_func(observed_rgbd, latent_rgbd, likelihood_args):\n", - " k = likelihood_args[\"k\"].const\n", + " k = likelihood_args[\"k\"].unwrap()\n", " fx = likelihood_args[\"fx\"]\n", " fy = likelihood_args[\"fy\"]\n", " \n", @@ -628,16 +628,16 @@ " rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[IDX].transform(pose))\n", " rendered_color_space_d = convert_rgbd_to_color_space(rendered_rgbd)\n", "\n", - " k = likelihood_args[\"k\"].const\n", + " k = likelihood_args[\"k\"].unwrap()\n", " image_height, image_width = rendered_color_space_d.shape[0], rendered_color_space_d.shape[1]\n", " image_height = Pytree.const(image_height)\n", " image_width = Pytree.const(image_width)\n", "\n", " row_coordinates = genjax.categorical.vmap(in_axes=(0,))(\n", - " jnp.ones((k, image_height.const))\n", + " jnp.ones((k, image_height.unwrap()))\n", " ) @ \"row_coordinates\"\n", " column_coordinates = genjax.categorical.vmap(in_axes=(0,))(\n", - " jnp.ones((k, image_width.const))\n", + " jnp.ones((k, image_width.unwrap()))\n", " ) @ \"column_coordinates\"\n", "\n", "\n", diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb index b430d694..9b373c03 100644 --- a/notebooks/bayes3d_paper/tester.ipynb +++ b/notebooks/bayes3d_paper/tester.ipynb @@ -49,7 +49,17 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 49/49 [00:04<00:00, 11.77it/s]\n" + " 0%| | 0/49 [00:00 2\u001b[0m og_trace, weight \u001b[38;5;241m=\u001b[39m \u001b[43mb3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mchisight\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdynamic_object_generative_model\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimportance\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mchoicemap\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mhyperparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprevious_state\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m trace \u001b[38;5;241m=\u001b[39m og_trace\n\u001b[1;32m 4\u001b[0m weight\n", - "File \u001b[0;32m<@beartype(genjax._src.core.generative.core.GenerativeFunction.importance) at 0x7f212c7d1620>:77\u001b[0m, in \u001b[0;36mimportance\u001b[0;34m(__beartype_object_139780457001344, __beartype_get_violation, __beartype_conf, __beartype_object_94027647930096, __beartype_object_94027647965088, __beartype_object_139780463811040, __beartype_object_139780456993088, __beartype_func, *args, **kwargs)\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:801\u001b[0m, in \u001b[0;36mGenerativeFunction.importance\u001b[0;34m(self, key, constraint, args)\u001b[0m\n\u001b[1;32m 759\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 760\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mimportance\u001b[39m(\n\u001b[1;32m 761\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 764\u001b[0m args: Arguments,\n\u001b[1;32m 765\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[Trace, Weight]:\n\u001b[1;32m 766\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 767\u001b[0m \u001b[38;5;124;03m Returns a properly weighted pair, a [`Trace`][genjax.core.Trace] and a [`Weight`][genjax.core.Weight], properly weighted for the target induced by the generative function for the provided constraint and arguments.\u001b[39;00m\n\u001b[1;32m 768\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 799\u001b[0m \u001b[38;5;124;03m Under the hood, creates an [`UpdateProblem`][genjax.core.UpdateProblem] which requests that the generative function respond with a move from the _empty_ trace (the only possible value for _empty_ target $\\\\delta_\\\\emptyset$) to the target induced by the generative function for constraint $C$ with arguments $a$.\u001b[39;00m\n\u001b[1;32m 800\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 801\u001b[0m tr, w, _, _ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 802\u001b[0m \u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 803\u001b[0m \u001b[43m \u001b[49m\u001b[43mEmptyTrace\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 804\u001b[0m \u001b[43m \u001b[49m\u001b[43mGenericProblem\u001b[49m\u001b[43m(\u001b[49m\u001b[43mDiff\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munknown_change\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mImportanceProblem\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconstraint\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 805\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 806\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tr, w\n", - " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", - "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.StaticGenerativeFunction.update) at 0x7f2120a34e00>:78\u001b[0m, in \u001b[0;36mupdate\u001b[0;34m(__beartype_object_139780457001344, __beartype_get_violation, __beartype_conf, __beartype_object_94027647965088, __beartype_object_94027647916672, __beartype_object_139780463811040, __beartype_object_139780456908416, __beartype_object_139780456993088, __beartype_func, *args, **kwargs)\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:595\u001b[0m, in \u001b[0;36mStaticGenerativeFunction.update\u001b[0;34m(self, key, trace, update_problem)\u001b[0m\n\u001b[1;32m 593\u001b[0m \u001b[38;5;28;01mmatch\u001b[39;00m update_problem:\n\u001b[1;32m 594\u001b[0m \u001b[38;5;28;01mcase\u001b[39;00m GenericProblem(argdiffs, subproblem):\n\u001b[0;32m--> 595\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate_change_target\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msubproblem\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margdiffs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 596\u001b[0m \u001b[38;5;28;01mcase\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01m_\u001b[39;00m:\n\u001b[1;32m 597\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mupdate(\n\u001b[1;32m 598\u001b[0m key,\n\u001b[1;32m 599\u001b[0m trace,\n\u001b[1;32m 600\u001b[0m GenericProblem(Diff\u001b[38;5;241m.\u001b[39mno_change(trace\u001b[38;5;241m.\u001b[39mget_args()), update_problem),\n\u001b[1;32m 601\u001b[0m )\n", - "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.StaticGenerativeFunction.update_change_target) at 0x7f2120a34cc0>:103\u001b[0m, in \u001b[0;36mupdate_change_target\u001b[0;34m(__beartype_object_139780457001344, __beartype_get_violation, __beartype_conf, __beartype_object_94027647965088, __beartype_object_94027647916672, __beartype_object_139780460630784, __beartype_object_139780463811040, __beartype_object_139780456908416, __beartype_object_139780456993088, __beartype_func, *args, **kwargs)\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:560\u001b[0m, in \u001b[0;36mStaticGenerativeFunction.update_change_target\u001b[0;34m(self, key, trace, update_problem, argdiffs)\u001b[0m\n\u001b[1;32m 536\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 537\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mupdate_change_target\u001b[39m(\n\u001b[1;32m 538\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 542\u001b[0m argdiffs: Argdiffs,\n\u001b[1;32m 543\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[Trace, Weight, Retdiff, UpdateProblem]:\n\u001b[1;32m 544\u001b[0m syntax_sugar_handled \u001b[38;5;241m=\u001b[39m push_trace_overload_stack(\n\u001b[1;32m 545\u001b[0m handler_trace_with_static, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msource\n\u001b[1;32m 546\u001b[0m )\n\u001b[1;32m 547\u001b[0m (\n\u001b[1;32m 548\u001b[0m (\n\u001b[1;32m 549\u001b[0m retval_diffs,\n\u001b[1;32m 550\u001b[0m weight,\n\u001b[1;32m 551\u001b[0m (\n\u001b[1;32m 552\u001b[0m arg_primals,\n\u001b[1;32m 553\u001b[0m retval_primals,\n\u001b[1;32m 554\u001b[0m address_visitor,\n\u001b[1;32m 555\u001b[0m address_traces,\n\u001b[1;32m 556\u001b[0m score,\n\u001b[1;32m 557\u001b[0m ),\n\u001b[1;32m 558\u001b[0m bwd_problems,\n\u001b[1;32m 559\u001b[0m ),\n\u001b[0;32m--> 560\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[43mupdate_transform\u001b[49m\u001b[43m(\u001b[49m\u001b[43msyntax_sugar_handled\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mupdate_problem\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margdiffs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 562\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mmake_bwd_problem\u001b[39m(visitor, subproblems):\n\u001b[1;32m 563\u001b[0m addresses \u001b[38;5;241m=\u001b[39m visitor\u001b[38;5;241m.\u001b[39mget_visited()\n", - "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.update_transform.wrapper) at 0x7f1b8cd8e480>:31\u001b[0m, in \u001b[0;36mwrapper\u001b[0;34m(__beartype_get_violation, __beartype_conf, __beartype_func, *args, **kwargs)\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:377\u001b[0m, in \u001b[0;36mupdate_transform..wrapper\u001b[0;34m(key, previous_trace, constraints, diffs)\u001b[0m\n\u001b[1;32m 375\u001b[0m diff_primals \u001b[38;5;241m=\u001b[39m Diff\u001b[38;5;241m.\u001b[39mtree_primal(diffs)\n\u001b[1;32m 376\u001b[0m diff_tangents \u001b[38;5;241m=\u001b[39m Diff\u001b[38;5;241m.\u001b[39mtree_tangent(diffs)\n\u001b[0;32m--> 377\u001b[0m retval_diffs \u001b[38;5;241m=\u001b[39m \u001b[43mincremental\u001b[49m\u001b[43m(\u001b[49m\u001b[43msource_fn\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 378\u001b[0m \u001b[43m \u001b[49m\u001b[43mstateful_handler\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdiff_primals\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdiff_tangents\u001b[49m\n\u001b[1;32m 379\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 380\u001b[0m retval_primals \u001b[38;5;241m=\u001b[39m Diff\u001b[38;5;241m.\u001b[39mtree_primal(retval_diffs)\n\u001b[1;32m 381\u001b[0m (\n\u001b[1;32m 382\u001b[0m score,\n\u001b[1;32m 383\u001b[0m weight,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 386\u001b[0m bwd_problems,\n\u001b[1;32m 387\u001b[0m ) \u001b[38;5;241m=\u001b[39m stateful_handler\u001b[38;5;241m.\u001b[39myield_state()\n", - "File \u001b[0;32m<@beartype(genjax._src.core.interpreters.incremental.incremental.wrapped) at 0x7f1b8cd8e5c0>:73\u001b[0m, in \u001b[0;36mwrapped\u001b[0;34m(__beartype_object_139756341382400, __beartype_get_violation, __beartype_conf, __beartype_func, *args, **kwargs)\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/incremental.py:316\u001b[0m, in \u001b[0;36mincremental..wrapped\u001b[0;34m(_stateful_handler, primals, tangents)\u001b[0m\n\u001b[1;32m 308\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(f)\n\u001b[1;32m 309\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 310\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 313\u001b[0m tangents: Tuple,\n\u001b[1;32m 314\u001b[0m ):\n\u001b[1;32m 315\u001b[0m interpreter \u001b[38;5;241m=\u001b[39m IncrementalInterpreter()\n\u001b[0;32m--> 316\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minterpreter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_interpreter\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 317\u001b[0m \u001b[43m \u001b[49m\u001b[43m_stateful_handler\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 318\u001b[0m \u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 319\u001b[0m \u001b[43m \u001b[49m\u001b[43mprimals\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 320\u001b[0m \u001b[43m \u001b[49m\u001b[43mtangents\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 321\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/incremental.py:291\u001b[0m, in \u001b[0;36mIncrementalInterpreter.run_interpreter\u001b[0;34m(self, _stateful_handler, fn, primals, tangents, **kwargs)\u001b[0m\n\u001b[1;32m 288\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_inner\u001b[39m(\u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 289\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m fn(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 291\u001b[0m _closed_jaxpr, (flat_primals, _, out_tree) \u001b[38;5;241m=\u001b[39m \u001b[43mstage\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_inner\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mprimals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 292\u001b[0m flat_tangents \u001b[38;5;241m=\u001b[39m jtu\u001b[38;5;241m.\u001b[39mtree_leaves(\n\u001b[1;32m 293\u001b[0m tangents, is_leaf\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mlambda\u001b[39;00m v: \u001b[38;5;28misinstance\u001b[39m(v, ChangeTangent)\n\u001b[1;32m 294\u001b[0m )\n\u001b[1;32m 295\u001b[0m _jaxpr, consts \u001b[38;5;241m=\u001b[39m _closed_jaxpr\u001b[38;5;241m.\u001b[39mjaxpr, _closed_jaxpr\u001b[38;5;241m.\u001b[39mliterals\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:125\u001b[0m, in \u001b[0;36mstage..wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 123\u001b[0m flat_fun, out_tree \u001b[38;5;241m=\u001b[39m api_util\u001b[38;5;241m.\u001b[39mflatten_fun_nokwargs(fun, in_tree)\n\u001b[1;32m 124\u001b[0m flat_avals \u001b[38;5;241m=\u001b[39m safe_map(get_shaped_aval, flat_args)\n\u001b[0;32m--> 125\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m \u001b[43mcached_stage_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mflat_avals\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr, (flat_args, in_tree, out_tree)\n", - " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:112\u001b[0m, in \u001b[0;36mcached_stage_dynamic\u001b[0;34m(flat_fun, in_avals)\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;129m@lu\u001b[39m\u001b[38;5;241m.\u001b[39mcache\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcached_stage_dynamic\u001b[39m(flat_fun, in_avals):\n\u001b[0;32m--> 112\u001b[0m jaxpr, _, consts \u001b[38;5;241m=\u001b[39m \u001b[43mpe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrace_to_jaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 113\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m jc\u001b[38;5;241m.\u001b[39mClosedJaxpr(jaxpr, consts)\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr\n", - " \u001b[0;31m[... skipping hidden 5 frame]\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/incremental.py:289\u001b[0m, in \u001b[0;36mIncrementalInterpreter.run_interpreter.._inner\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 288\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_inner\u001b[39m(\u001b[38;5;241m*\u001b[39margs):\n\u001b[0;32m--> 289\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:1604\u001b[0m, in \u001b[0;36mpush_trace_overload_stack..wrapped\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 1602\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 1603\u001b[0m GLOBAL_TRACE_OP_HANDLER_STACK\u001b[38;5;241m.\u001b[39mappend(handler)\n\u001b[0;32m-> 1604\u001b[0m ret \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1605\u001b[0m GLOBAL_TRACE_OP_HANDLER_STACK\u001b[38;5;241m.\u001b[39mpop()\n\u001b[1;32m 1606\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ret\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/pytree.py:496\u001b[0m, in \u001b[0;36mClosure.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 495\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 496\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdyn_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/model.py:51\u001b[0m, in \u001b[0;36mdynamic_object_generative_model\u001b[0;34m(hyperparams, previous_state)\u001b[0m\n\u001b[1;32m 49\u001b[0m rgbd \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 51\u001b[0m rgbd \u001b[38;5;241m=\u001b[39m \u001b[43mhyperparams\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mimage_kernel\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnew_state\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhyperparams\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m@\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrgbd\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m 53\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m {\n\u001b[1;32m 54\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnew_state\u001b[39m\u001b[38;5;124m\"\u001b[39m: new_state,\n\u001b[1;32m 55\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m: rgbd,\n\u001b[1;32m 56\u001b[0m }\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:1660\u001b[0m, in \u001b[0;36mGenerativeFunctionClosure.__matmul__\u001b[0;34m(self, addr)\u001b[0m\n\u001b[1;32m 1654\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m handle_off_trace_stack(\n\u001b[1;32m 1655\u001b[0m addr,\n\u001b[1;32m 1656\u001b[0m maybe_kwarged_gen_fn,\n\u001b[1;32m 1657\u001b[0m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkwargs),\n\u001b[1;32m 1658\u001b[0m )\n\u001b[1;32m 1659\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1660\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mhandle_off_trace_stack\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1661\u001b[0m \u001b[43m \u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1662\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1663\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1664\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/generative/core.py:1594\u001b[0m, in \u001b[0;36mhandle_off_trace_stack\u001b[0;34m(addr, gen_fn, args)\u001b[0m\n\u001b[1;32m 1592\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m GLOBAL_TRACE_OP_HANDLER_STACK:\n\u001b[1;32m 1593\u001b[0m handler \u001b[38;5;241m=\u001b[39m GLOBAL_TRACE_OP_HANDLER_STACK[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n\u001b[0;32m-> 1594\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mhandler\u001b[49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1595\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1596\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\n\u001b[1;32m 1597\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAttempting to invoke trace outside of a tracing context.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124mIf you want to invoke the generative function closure, and recieve a return value,\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124minvoke it with a key.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1598\u001b[0m )\n", - "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.handler_trace_with_static) at 0x7f2120a347c0>:91\u001b[0m, in \u001b[0;36mhandler_trace_with_static\u001b[0;34m(__beartype_getrandbits, __beartype_get_violation, __beartype_conf, __beartype_object_94027648046928, __beartype_func, *args, **kwargs)\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:467\u001b[0m, in \u001b[0;36mhandler_trace_with_static\u001b[0;34m(addr, gen_fn, args)\u001b[0m\n\u001b[1;32m 461\u001b[0m \u001b[38;5;129m@typecheck\u001b[39m\n\u001b[1;32m 462\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhandler_trace_with_static\u001b[39m(\n\u001b[1;32m 463\u001b[0m addr: StaticAddressComponent \u001b[38;5;241m|\u001b[39m StaticAddress,\n\u001b[1;32m 464\u001b[0m gen_fn: GenerativeFunction,\n\u001b[1;32m 465\u001b[0m args: Tuple,\n\u001b[1;32m 466\u001b[0m ):\n\u001b[0;32m--> 467\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtrace\u001b[49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43misinstance\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m<@beartype(genjax._src.generative_functions.static.trace) at 0x7f2120a16700>:89\u001b[0m, in \u001b[0;36mtrace\u001b[0;34m(__beartype_getrandbits, __beartype_get_violation, __beartype_conf, __beartype_object_94027648046928, __beartype_func, *args, **kwargs)\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:178\u001b[0m, in \u001b[0;36mtrace\u001b[0;34m(addr, gen_fn, args)\u001b[0m\n\u001b[1;32m 170\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Invoke a generative function, binding its generative semantics with the current\u001b[39;00m\n\u001b[1;32m 171\u001b[0m \u001b[38;5;124;03mcaller.\u001b[39;00m\n\u001b[1;32m 172\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[38;5;124;03m gen_fn: A generative function invoked as a callee of `StaticGenerativeFunction`.\u001b[39;00m\n\u001b[1;32m 176\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 177\u001b[0m addr \u001b[38;5;241m=\u001b[39m Pytree\u001b[38;5;241m.\u001b[39mtree_const(addr)\n\u001b[0;32m--> 178\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minitial_style_bind\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace_p\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_abstract_gen_fn_call\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 179\u001b[0m \u001b[43m \u001b[49m\u001b[43maddr\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 180\u001b[0m \u001b[43m \u001b[49m\u001b[43mgen_fn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 181\u001b[0m \u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 182\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/forward.py:121\u001b[0m, in \u001b[0;36minitial_style_bind..bind..wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 119\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 120\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Runs a function and binds it to a call primitive.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 121\u001b[0m _jaxpr, (flat_args, in_tree, out_tree) \u001b[38;5;241m=\u001b[39m \u001b[43mstage\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 122\u001b[0m outs \u001b[38;5;241m=\u001b[39m prim\u001b[38;5;241m.\u001b[39mbind(\n\u001b[1;32m 123\u001b[0m \u001b[38;5;241m*\u001b[39mit\u001b[38;5;241m.\u001b[39mchain(_jaxpr\u001b[38;5;241m.\u001b[39mliterals, flat_args),\n\u001b[1;32m 124\u001b[0m _jaxpr\u001b[38;5;241m=\u001b[39m_jaxpr\u001b[38;5;241m.\u001b[39mjaxpr,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams,\n\u001b[1;32m 129\u001b[0m )\n\u001b[1;32m 130\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tree_util\u001b[38;5;241m.\u001b[39mtree_unflatten(out_tree(), outs)\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:125\u001b[0m, in \u001b[0;36mstage..wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 123\u001b[0m flat_fun, out_tree \u001b[38;5;241m=\u001b[39m api_util\u001b[38;5;241m.\u001b[39mflatten_fun_nokwargs(fun, in_tree)\n\u001b[1;32m 124\u001b[0m flat_avals \u001b[38;5;241m=\u001b[39m safe_map(get_shaped_aval, flat_args)\n\u001b[0;32m--> 125\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m \u001b[43mcached_stage_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mflat_avals\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr, (flat_args, in_tree, out_tree)\n", - " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/core/interpreters/staging.py:112\u001b[0m, in \u001b[0;36mcached_stage_dynamic\u001b[0;34m(flat_fun, in_avals)\u001b[0m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;129m@lu\u001b[39m\u001b[38;5;241m.\u001b[39mcache\n\u001b[1;32m 111\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcached_stage_dynamic\u001b[39m(flat_fun, in_avals):\n\u001b[0;32m--> 112\u001b[0m jaxpr, _, consts \u001b[38;5;241m=\u001b[39m \u001b[43mpe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrace_to_jaxpr_dynamic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mflat_fun\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_avals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 113\u001b[0m typed_jaxpr \u001b[38;5;241m=\u001b[39m jc\u001b[38;5;241m.\u001b[39mClosedJaxpr(jaxpr, consts)\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m typed_jaxpr\n", - " \u001b[0;31m[... skipping hidden 5 frame]\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/static.py:161\u001b[0m, in \u001b[0;36m_abstract_gen_fn_call\u001b[0;34m(_, gen_fn, args)\u001b[0m\n\u001b[1;32m 156\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_abstract_gen_fn_call\u001b[39m(\n\u001b[1;32m 157\u001b[0m _: Address,\n\u001b[1;32m 158\u001b[0m gen_fn: GenerativeFunction,\n\u001b[1;32m 159\u001b[0m args: Tuple,\n\u001b[1;32m 160\u001b[0m ):\n\u001b[0;32m--> 161\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mgen_fn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__abstract_call__\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/genjax/_src/generative_functions/distributions/distribution.py:498\u001b[0m, in \u001b[0;36mExactDensity.__abstract_call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 496\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__abstract_call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs):\n\u001b[1;32m 497\u001b[0m key \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mPRNGKey(\u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m--> 498\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msample\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/image_kernel.py:70\u001b[0m, in \u001b[0;36mNoOcclusionPerVertexImageKernel.sample\u001b[0;34m(self, key, state, hyperparams)\u001b[0m\n\u001b[1;32m 66\u001b[0m transformed_points \u001b[38;5;241m=\u001b[39m state[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpose\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mapply(hyperparams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvertices\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m 67\u001b[0m points_to_pixels \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_pixels_points_association(\n\u001b[1;32m 68\u001b[0m transformed_points, hyperparams\n\u001b[1;32m 69\u001b[0m )\n\u001b[0;32m---> 70\u001b[0m vertex_kernel \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_rgbd_vertex_kernel\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 72\u001b[0m \u001b[38;5;66;03m# assuming that at most one vertex hit the pixel, we can convert the\u001b[39;00m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;66;03m# per-vertex attributes into per-pixel attributes, then vmap the\u001b[39;00m\n\u001b[1;32m 74\u001b[0m \u001b[38;5;66;03m# RGBD pixel kernel over the pixels to generate the image.\u001b[39;00m\n\u001b[1;32m 75\u001b[0m pixel_visibility_prob \u001b[38;5;241m=\u001b[39m points_to_pixels\u001b[38;5;241m.\u001b[39mget_pixel_attributes(\n\u001b[1;32m 76\u001b[0m state[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisibility_prob\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 77\u001b[0m )\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/image_kernel.py:140\u001b[0m, in \u001b[0;36mNoOcclusionPerVertexImageKernel.get_rgbd_vertex_kernel\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_rgbd_vertex_kernel\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m PixelRGBDDistribution:\n\u001b[1;32m 133\u001b[0m \u001b[38;5;66;03m# Note: The distributions were originally defined for per-pixel computation,\u001b[39;00m\n\u001b[1;32m 134\u001b[0m \u001b[38;5;66;03m# but they should work for per-vertex computation as well, except that\u001b[39;00m\n\u001b[1;32m 135\u001b[0m \u001b[38;5;66;03m# they don't expect observed_rgbd to be invalid, so we need to handle\u001b[39;00m\n\u001b[1;32m 136\u001b[0m \u001b[38;5;66;03m# that manually.\u001b[39;00m\n\u001b[1;32m 137\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m FullPixelRGBDDistribution(\n\u001b[1;32m 138\u001b[0m RenormalizedLaplacePixelColorDistribution(),\n\u001b[1;32m 139\u001b[0m UniformPixelColorDistribution(),\n\u001b[0;32m--> 140\u001b[0m \u001b[43mRenormalizedLaplacePixelDepthDistribution\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m,\n\u001b[1;32m 141\u001b[0m UniformPixelDepthDistribution(),\n\u001b[1;32m 142\u001b[0m )\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/penzai/core/struct.py:423\u001b[0m, in \u001b[0;36mAbstractStructMetaclass.__call__\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m 416\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_pytree_dataclass_type(\u001b[38;5;28mcls\u001b[39m):\n\u001b[1;32m 417\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 418\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCan\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt instantiate abstract Struct subclass \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. Non-abstract\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 419\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m subclasses of penzai.Struct must be decorated with\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 420\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m @penzai.pytree_dataclass before they can be instantiated.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 421\u001b[0m )\n\u001b[0;32m--> 423\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__call__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[0;31mTypeError\u001b[0m: RenormalizedLaplacePixelDepthDistribution.__init__() missing 2 required positional arguments: 'near' and 'far'" - ] + "data": { + "text/plain": [ + "Array(91953.95, dtype=float32)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -276,16 +252,16 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(120035.86, dtype=float32)" + "Array(91953.95, dtype=float32)" ] }, - "execution_count": 12, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -310,7 +286,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -320,7 +296,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -332,7 +308,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ @@ -342,7 +318,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -358,26 +334,26 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 27, "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/georgematheos/b3d/src/b3d/modeling_utils.py:86: UserWarning: RenormalizedLaplace sampling is currently not implemented perfectly.\n", - " warnings.warn(\n" + "ename": "KeyError", + "evalue": "'image_height'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[27], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m trace, step_weight, metadata \u001b[38;5;241m=\u001b[39m \u001b[43mi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minference_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m 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\u001b[49m\u001b[43mgt_pose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgt_pose\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m 9\u001b[0m step_weight\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference.py:175\u001b[0m, in \u001b[0;36minference_step\u001b[0;34m(key, old_trace, observed_rgbd, inference_hyperparams, *args, **kwargs)\u001b[0m\n\u001b[1;32m 173\u001b[0m k1, k2 \u001b[38;5;241m=\u001b[39m split(key)\n\u001b[1;32m 174\u001b[0m trace \u001b[38;5;241m=\u001b[39m advance_time(k1, old_trace, observed_rgbd)\n\u001b[0;32m--> 175\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43minfer_latents\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk2\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + " \u001b[0;31m[... skipping hidden 11 frame]\u001b[0m\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference.py:233\u001b[0m, in \u001b[0;36minfer_latents\u001b[0;34m(key, trace, inference_hyperparams, get_trace, get_weight, get_metadata, use_gt_pose, gt_pose, include_qscores_in_outer_resample)\u001b[0m\n\u001b[1;32m 224\u001b[0m log_q_poses \u001b[38;5;241m=\u001b[39m log_q_poses\u001b[38;5;241m.\u001b[39mat[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mset(\n\u001b[1;32m 225\u001b[0m jnp\u001b[38;5;241m.\u001b[39mwhere(\n\u001b[1;32m 226\u001b[0m use_gt_pose,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 229\u001b[0m )\n\u001b[1;32m 230\u001b[0m )\n\u001b[1;32m 232\u001b[0m param_generation_keys \u001b[38;5;241m=\u001b[39m split(k3, inference_hyperparams\u001b[38;5;241m.\u001b[39mn_poses)\n\u001b[0;32m--> 233\u001b[0m proposed_traces, log_q_nonpose_latents, other_latents_metadata \u001b[38;5;241m=\u001b[39m \u001b[43mjax\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvmap\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 234\u001b[0m \u001b[43m \u001b[49m\u001b[43mpropose_other_latents_given_pose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_axes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 235\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparam_generation_keys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproposed_poses\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 236\u001b[0m p_scores \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mvmap(\u001b[38;5;28;01mlambda\u001b[39;00m tr: tr\u001b[38;5;241m.\u001b[39mget_score())(proposed_traces)\n\u001b[1;32m 238\u001b[0m scores \u001b[38;5;241m=\u001b[39m jnp\u001b[38;5;241m.\u001b[39mwhere(\n\u001b[1;32m 239\u001b[0m include_qscores_in_outer_resample,\n\u001b[1;32m 240\u001b[0m p_scores \u001b[38;5;241m-\u001b[39m log_q_poses \u001b[38;5;241m-\u001b[39m log_q_nonpose_latents,\n\u001b[1;32m 241\u001b[0m p_scores,\n\u001b[1;32m 242\u001b[0m )\n", + " \u001b[0;31m[... skipping hidden 3 frame]\u001b[0m\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference_moves.py:80\u001b[0m, in \u001b[0;36mpropose_other_latents_given_pose\u001b[0;34m(key, advanced_trace, pose, inference_hyperparams)\u001b[0m\n\u001b[1;32m 71\u001b[0m trace \u001b[38;5;241m=\u001b[39m update_field(k1, advanced_trace, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpose\u001b[39m\u001b[38;5;124m\"\u001b[39m, pose)\n\u001b[1;32m 73\u001b[0m k2a, k2b \u001b[38;5;241m=\u001b[39m split(k2)\n\u001b[1;32m 74\u001b[0m (\n\u001b[1;32m 75\u001b[0m colors,\n\u001b[1;32m 76\u001b[0m visibility_probs,\n\u001b[1;32m 77\u001b[0m depth_nonreturn_probs,\n\u001b[1;32m 78\u001b[0m log_q_point_attributes,\n\u001b[1;32m 79\u001b[0m point_proposal_metadata,\n\u001b[0;32m---> 80\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[43mpropose_all_pointlevel_attributes\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk2a\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 81\u001b[0m trace \u001b[38;5;241m=\u001b[39m update_vmapped_fields(\n\u001b[1;32m 82\u001b[0m k2b,\n\u001b[1;32m 83\u001b[0m trace,\n\u001b[1;32m 84\u001b[0m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcolors\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisibility_prob\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdepth_nonreturn_prob\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[1;32m 85\u001b[0m [colors, visibility_probs, depth_nonreturn_probs],\n\u001b[1;32m 86\u001b[0m )\n\u001b[1;32m 88\u001b[0m k3a, k3b \u001b[38;5;241m=\u001b[39m split(k3)\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference_moves.py:117\u001b[0m, in \u001b[0;36mpropose_all_pointlevel_attributes\u001b[0;34m(key, trace, inference_hyperparams)\u001b[0m\n\u001b[1;32m 107\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpropose_all_pointlevel_attributes\u001b[39m(key, trace, inference_hyperparams):\n\u001b[1;32m 108\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 109\u001b[0m \u001b[38;5;124;03m Propose a new color, visibility probability, and depth non-return probability\u001b[39;00m\n\u001b[1;32m 110\u001b[0m \u001b[38;5;124;03m for every vertex, conditioned upon the other values in `trace`.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 115\u001b[0m \u001b[38;5;124;03m the overall log proposal density, and metadata is a dict.\u001b[39;00m\n\u001b[1;32m 116\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 117\u001b[0m observed_rgbds_per_point \u001b[38;5;241m=\u001b[39m \u001b[43mPixelsPointsAssociation\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_hyperparams_and_pose\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 118\u001b[0m \u001b[43m \u001b[49m\u001b[43mget_hypers\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mget_new_state\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpose\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 119\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mget_point_rgbds(get_observed_rgbd(trace))\n\u001b[1;32m 121\u001b[0m colors, visibility_probs, depth_nonreturn_probs, log_qs, metadata \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mvmap(\n\u001b[1;32m 122\u001b[0m propose_a_points_attributes, in_axes\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 123\u001b[0m )(\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 130\u001b[0m inference_hyperparams,\n\u001b[1;32m 131\u001b[0m )\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m colors, visibility_probs, depth_nonreturn_probs, log_qs\u001b[38;5;241m.\u001b[39msum(), metadata\n", + "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/projection.py:30\u001b[0m, in \u001b[0;36mPixelsPointsAssociation.from_hyperparams_and_pose\u001b[0;34m(cls, hyperparams, pose_CO)\u001b[0m\n\u001b[1;32m 25\u001b[0m vertices_O \u001b[38;5;241m=\u001b[39m hyperparams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvertices\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 26\u001b[0m vertices_C \u001b[38;5;241m=\u001b[39m pose_CO\u001b[38;5;241m.\u001b[39mapply(vertices_O)\n\u001b[1;32m 27\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mfrom_points_and_intrinsics(\n\u001b[1;32m 28\u001b[0m vertices_C,\n\u001b[1;32m 29\u001b[0m hyperparams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mintrinsics\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[0;32m---> 30\u001b[0m \u001b[43mhyperparams\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mimage_height\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39munwrap(),\n\u001b[1;32m 31\u001b[0m hyperparams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage_width\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39munwrap(),\n\u001b[1;32m 32\u001b[0m )\n", + "\u001b[0;31mKeyError\u001b[0m: 'image_height'" ] - }, - { - "data": { - "text/plain": [ - "Array(-871.44604, dtype=float32)" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -656,7 +632,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.4" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/notebooks/bayes3d_paper/ycbv.ipynb b/notebooks/bayes3d_paper/ycbv.ipynb index b548b546..7355c2f7 100644 --- a/notebooks/bayes3d_paper/ycbv.ipynb +++ b/notebooks/bayes3d_paper/ycbv.ipynb @@ -346,7 +346,7 @@ "@genjax.gen\n", "def dense_multiobject_model(num_objects, meshes, likelihood_args):\n", " all_poses = []\n", - " for i in range(num_objects.const):\n", + " for i in range(num_objects.unwrap()):\n", " object_pose = (\n", " uniform_pose(jnp.ones(3) * -100.0, jnp.ones(3) * 100.0) @ f\"object_pose_{i}\"\n", " )\n", diff --git a/notebooks/integration.ipynb b/notebooks/integration.ipynb index a5d5344a..ec285ab3 100644 --- a/notebooks/integration.ipynb +++ b/notebooks/integration.ipynb @@ -534,7 +534,7 @@ "metadata": {}, "outputs": [], "source": [ - "scantr = ps.particle_system_state_step.scan(n=(num_timesteps.const - 1)).simulate(\n", + "scantr = ps.particle_system_state_step.scan(n=(num_timesteps.unwrap() - 1)).simulate(\n", " key, (state0, None)\n", ")" ] diff --git a/pixi.lock b/pixi.lock index a56e8dd2..a671ee25 100644 --- a/pixi.lock +++ b/pixi.lock @@ -23,19 +23,19 @@ environments: - conda: 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uniform_pose(jnp.ones(3) * -100.0, jnp.ones(3) * 100.0) @ f"object_pose_{i}" diff --git a/src/b3d/chisight/dense/likelihoods/blur_likelihood_gaussian.py b/src/b3d/chisight/dense/likelihoods/blur_likelihood_gaussian.py index 77a77467..2308131f 100644 --- a/src/b3d/chisight/dense/likelihoods/blur_likelihood_gaussian.py +++ b/src/b3d/chisight/dense/likelihoods/blur_likelihood_gaussian.py @@ -114,7 +114,7 @@ def likelihood_per_pixel(latent_rgbd: jnp.ndarray, blur): @jax.jit def blur_intermediate_likelihood_func(observed_rgbd, latent_rgbd, likelihood_args): - # k = likelihood_args["k"].const + # k = likelihood_args["k"].unwrap() color_variance = likelihood_args["color_variance_0"] depth_variance = likelihood_args["depth_variance_0"] outlier_probability = likelihood_args["outlier_probability_0"] diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index 2106b8f5..f4dd93cf 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -38,8 +38,8 @@ def get_pixels_points_association( return PixelsPointsAssociation.from_points_and_intrinsics( transformed_points, hyperparams["intrinsics"], - hyperparams["intrinsics"]["image_height"].const, - hyperparams["intrinsics"]["image_width"].const, + hyperparams["intrinsics"]["image_height"].unwrap(), + hyperparams["intrinsics"]["image_width"].unwrap(), ) @abstractmethod @@ -88,8 +88,8 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr keys = jax.random.split( key, ( - hyperparams["intrinsics"]["image_height"].const, - hyperparams["intrinsics"]["image_width"].const, + hyperparams["intrinsics"]["image_height"].unwrap(), + hyperparams["intrinsics"]["image_width"].unwrap(), ), ) return jax.vmap( @@ -154,8 +154,8 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: # def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: # return jnp.zeros( # ( -# hyperparams["intrinsics"]["image_height"].const, -# hyperparams["intrinsics"]["image_width"].const, +# hyperparams["intrinsics"]["image_height"].unwrap(), +# hyperparams["intrinsics"]["image_width"].unwrap(), # 4, # ) # ) diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index bdfcd767..484ae83c 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -27,8 +27,8 @@ def from_hyperparams_and_pose(cls, hyperparams, pose_CO): return cls.from_points_and_intrinsics( vertices_C, hyperparams["intrinsics"], - hyperparams["intrinsics"]["image_height"].const, - hyperparams["intrinsics"]["image_width"].const, + hyperparams["intrinsics"]["image_height"].unwrap(), + hyperparams["intrinsics"]["image_width"].unwrap(), ) @classmethod diff --git a/src/b3d/chisight/particle_system.py b/src/b3d/chisight/particle_system.py index 9b6790fd..f77fee5c 100644 --- a/src/b3d/chisight/particle_system.py +++ b/src/b3d/chisight/particle_system.py @@ -26,14 +26,14 @@ def initial_particle_system_state( ): relative_particle_poses = ( dummy_mapped_uniform_pose( - jnp.arange(num_particles.const), *relative_particle_poses_prior_params + jnp.arange(num_particles.unwrap()), *relative_particle_poses_prior_params ) @ "particle_poses" ) object_assignments = ( b3d.modeling_utils.categorical.vmap(in_axes=(0,))( - jnp.zeros((num_particles.const, num_clusters.const)) + jnp.zeros((num_particles.unwrap(), num_clusters.unwrap())) ) @ "object_assignments" ) @@ -41,7 +41,7 @@ def initial_particle_system_state( # Cluster pose in world coordinates initial_object_poses = ( dummy_mapped_uniform_pose( - jnp.arange(num_clusters.const), *initial_object_poses_prior_params + jnp.arange(num_clusters.unwrap()), *initial_object_poses_prior_params ) @ "object_poses" ) @@ -59,7 +59,7 @@ def initial_particle_system_state( # Initial visibility mask initial_vis_mask = ( b3d.modeling_utils.bernoulli.vmap(in_axes=(0,))( - jnp.repeat(jax.scipy.special.logit(0.5), num_particles.const) + jnp.repeat(jax.scipy.special.logit(0.5), num_particles.unwrap()) ) @ "initial_visibility" ) @@ -101,7 +101,7 @@ def particle_system_state_step(carried_state, _): # Visibility mask vis_mask = ( b3d.modeling_utils.bernoulli.vmap(in_axes=(0,))( - jnp.repeat(jax.scipy.special.logit(0.5), num_particles.const) + jnp.repeat(jax.scipy.special.logit(0.5), num_particles.unwrap()) ) @ "visibility" ) @@ -146,7 +146,7 @@ def latent_particle_model( ) final_state, scan_retvals = ( - particle_system_state_step.scan(n=(num_timesteps.const - 1))(state0, None) + particle_system_state_step.scan(n=(num_timesteps.unwrap() - 1))(state0, None) @ "states1+" ) @@ -164,7 +164,7 @@ def sparse_observation_model( ): # TODO: add visibility uv = b3d.camera.screen_from_world( - particle_absolute_poses.pos, camera_pose, instrinsics.const + particle_absolute_poses.pos, camera_pose, instrinsics.unwrap() ) uv_ = ( b3d.modeling_utils.normal(uv, jnp.tile(sigma, uv.shape)) @ "sensor_coordinates" @@ -248,7 +248,7 @@ def visualize_particle_system( camera_pose = particle_dynamics_summary["camera_pose"] object_assignments = static_state[0] - cluster_colors = jnp.array(b3d.distinct_colors(num_clusters.const)) + cluster_colors = jnp.array(b3d.distinct_colors(num_clusters.unwrap())) rr.log( f"{viz_prefix}/3D", @@ -266,7 +266,7 @@ def visualize_particle_system( timeless=True, ) - for t in range(num_timesteps.const): + for t in range(num_timesteps.unwrap()): rr.set_time_sequence("time", t) cam_pose = camera_pose[t] @@ -286,7 +286,7 @@ def visualize_particle_system( ), ) - for i in range(num_clusters.const): + for i in range(num_clusters.unwrap()): b3d.rr_log_pose(f"{viz_prefix}/3D/cluster/{i}", object_poses[t][i]) @@ -302,7 +302,7 @@ def particle_2d_pixel_coordinates_to_image(pixel_coords, image_height, image_wid def visualize_sparse_observation(sparse_model_args, observations): import rerun as rr - intrinsics = sparse_model_args[0].const + intrinsics = sparse_model_args[0].unwrap() for t in range(observations.shape[0]): rr.set_time_sequence("time", t) @@ -338,7 +338,7 @@ def visualize_dense_gps( timeless=True, ) - for t in range(num_timesteps.const): + for t in range(num_timesteps.unwrap()): rr.set_time_sequence("time", t) poses = particle_dynamics_summary["absolute_particle_poses"][t] for i in range(len(meshes)): diff --git a/src/b3d/chisight/patch_tracking.py b/src/b3d/chisight/patch_tracking.py index 94d8e889..9910d763 100644 --- a/src/b3d/chisight/patch_tracking.py +++ b/src/b3d/chisight/patch_tracking.py @@ -90,7 +90,7 @@ def get_adam_optimization_patch_tracker(model, patches, pose_WC=Pose.identity()) """ def allidx_chm(x): - return genjax.ChoiceMap.idx(jnp.arange(x.shape[0], dtype=int), x) + return C[jnp.arange(x.shape[0], dtype=int)].set(x) @jax.jit def importance_from_pos_quat(positions, quaternions, observed_rgbd): @@ -118,14 +118,14 @@ def importance_from_pos_quat(positions, quaternions, observed_rgbd): ) particle_poses = jax.tree.map( - lambda arr: jnp.tile(arr, (num_particles.const, 1)), Pose.identity() + lambda arr: jnp.tile(arr, (num_particles.unwrap(), 1)), Pose.identity() ) - object_assignments = jnp.arange(num_particles.const, dtype=int) + object_assignments = jnp.arange(num_particles.unwrap(), dtype=int) object_poses = jax.vmap( lambda pos, quat: Pose.from_vec(jnp.concatenate([pos, quat])), in_axes=(0, 0), )(positions, quaternions) - vis_mask = jnp.ones((num_particles.const,), dtype=int) + vis_mask = jnp.ones((num_particles.unwrap(),), dtype=int) constraints = C.d( { diff --git a/src/b3d/utils.py b/src/b3d/utils.py index 7d214537..bee6f67c 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -522,7 +522,7 @@ def multivmap(f, args=None): def update_choices(trace, addresses, *values): return trace.update( jax.random.PRNGKey(0), - genjax.ChoiceMap.d({addr: c for (addr, c) in zip(addresses.const, values)}), + genjax.ChoiceMap.from_mapping(zip(addresses.unwrap(), values)), )[0] @@ -560,13 +560,13 @@ def update_choices_get_score(trace, addr_const, *values): @jax.jit def grid_trace(trace, addresses_const, values): - if len(addresses_const.const) == 1: + if len(addresses_const.unwrap()) == 1: return grid1(trace, addresses_const, *values) - elif len(addresses_const.const) == 2: + elif len(addresses_const.unwrap()) == 2: return grid2(trace, addresses_const, *values) - elif len(addresses_const.const) == 3: + elif len(addresses_const.unwrap()) == 3: return grid3(trace, addresses_const, *values) - elif len(addresses_const.const) == 4: + elif len(addresses_const.unwrap()) == 4: return grid4(trace, addresses_const, *values) else: raise ValueError("Too many addresses") diff --git a/tests/dense_model_unit_tests/triangle_depth_posterior/solver/importance.py b/tests/dense_model_unit_tests/triangle_depth_posterior/solver/importance.py index 613ad101..911b4e04 100644 --- a/tests/dense_model_unit_tests/triangle_depth_posterior/solver/importance.py +++ b/tests/dense_model_unit_tests/triangle_depth_posterior/solver/importance.py @@ -67,8 +67,8 @@ def importance_sample_with_depth_in_partition( C.d( { "triangle_vertices": new_triangle_W, - "observed_rgbs": genjax.ChoiceMap.idx( - jnp.arange(T), C.n().at["observed_rgb"].set(task_input["video"]) + "observed_rgbs": C[jnp.arange(T), "observed_rgb"].set( + task_input["video"] ), } ), diff --git a/tests/test_chisight_dense_gps.py b/tests/test_chisight_dense_gps.py index 1274442c..418404b5 100644 --- a/tests/test_chisight_dense_gps.py +++ b/tests/test_chisight_dense_gps.py @@ -53,8 +53,8 @@ def cube_mesh_with_size_and_color(size, color): return mesh meshes = jax.vmap(cube_mesh_with_size_and_color)( - jnp.ones((num_particles.const, 3)) * jnp.array([[0.1, 0.1, 0.01]]), - jax.random.uniform(key, (num_particles.const, 3)), + jnp.ones((num_particles.unwrap(), 3)) * jnp.array([[0.1, 0.1, 0.01]]), + jax.random.uniform(key, (num_particles.unwrap(), 3)), ) likelihood = make_krays_image_observation_model(renderer) From 4196b30cbdf45489d0a6eec9b5503cee1930157d Mon Sep 17 00:00:00 2001 From: georgematheos Date: Fri, 13 Sep 2024 19:07:28 -0400 Subject: [PATCH 24/37] add unit test for full inference alg (#174) Unfortunately this pushes up the test time for the `tests/gen3d/` directory to 3 mins. --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- .../pixel_kernels/pixel_color_kernels.py | 9 +- src/b3d/chisight/gen3d/settings.py | 6 +- .../inference/test_full_inference_alg.py | 191 ++++++++++++++++++ .../test_point_attribute_inferences.py} | 0 4 files changed, 198 insertions(+), 8 deletions(-) create mode 100644 tests/gen3d/inference/test_full_inference_alg.py rename tests/gen3d/{test_inference.py => inference/test_point_attribute_inferences.py} (100%) diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py index e9ae524d..dc9a2f0f 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_color_kernels.py @@ -4,17 +4,16 @@ import genjax import jax import jax.numpy as jnp -from genjax import Pytree -from genjax.typing import FloatArray, PRNGKey -from jax.random import split -from tensorflow_probability.substrates import jax as tfp - from b3d.modeling_utils import ( _FIXED_COLOR_UNIFORM_WINDOW, PythonMixtureDistribution, renormalized_laplace, truncated_laplace, ) +from genjax import Pytree +from genjax.typing import FloatArray, PRNGKey +from jax.random import split +from tensorflow_probability.substrates import jax as tfp if TYPE_CHECKING: import tensorflow_probability.python.distributions.distribution as dist diff --git a/src/b3d/chisight/gen3d/settings.py b/src/b3d/chisight/gen3d/settings.py index 364265e7..b5248af8 100644 --- a/src/b3d/chisight/gen3d/settings.py +++ b/src/b3d/chisight/gen3d/settings.py @@ -36,7 +36,7 @@ n_poses=6000, pose_proposal_std=0.04, pose_proposal_conc=1000.0, - do_stochastic_color_proposals=True, - prev_color_proposal_laplace_scale=0.001, - obs_color_proposal_laplace_scale=0.001, + do_stochastic_color_proposals=False, + prev_color_proposal_laplace_scale=0.1, + obs_color_proposal_laplace_scale=0.1, ) diff --git a/tests/gen3d/inference/test_full_inference_alg.py b/tests/gen3d/inference/test_full_inference_alg.py new file mode 100644 index 00000000..01188253 --- /dev/null +++ b/tests/gen3d/inference/test_full_inference_alg.py @@ -0,0 +1,191 @@ +import os + +import b3d +import b3d.chisight.gen3d.inference as i +import b3d.chisight.gen3d.model +import b3d.chisight.gen3d.settings +import b3d.io.data_loader +import genjax +import jax +import jax.numpy as jnp +from b3d import Mesh +from b3d.chisight.gen3d.model import ( + get_new_state, + make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, + make_visibility_prob_choicemap, +) +from genjax import Pytree +from tqdm import tqdm + + +def test_inference_alg_runs_and_looks_ok(): + scene_id = 49 + FRAME_RATE = 50 + ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") + print(f"Scene {scene_id}") + b3d.reload(b3d.io.data_loader) + num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id) + image_ids = range(1, num_scenes + 1, FRAME_RATE) + all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, image_ids) + + meshes = [ + Mesh.from_obj_file( + os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') + ).scale(0.001) + for id in all_data[0]["object_types"] + ] + + image_height, image_width = all_data[0]["rgbd"].shape[:2] + fx, fy, cx, cy = all_data[0]["camera_intrinsics"] + scaling_factor = 1.0 + renderer = b3d.renderer.renderer_original.RendererOriginal( + image_width * scaling_factor, + image_height * scaling_factor, + fx * scaling_factor, + fy * scaling_factor, + cx * scaling_factor, + cy * scaling_factor, + 0.01, + 2.0, + ) + b3d.viz_rgb(all_data[0]["rgbd"]) + + T = 0 + b3d.rr_set_time(T) + + OBJECT_INDEX = 1 + + template_pose = ( + all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] + ) + rendered_rgbd = renderer.render_rgbd_from_mesh( + meshes[OBJECT_INDEX].transform(template_pose) + ) + xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy) + + fx, fy, cx, cy = all_data[T]["camera_intrinsics"] + xyz_observed = b3d.xyz_from_depth(all_data[T]["rgbd"][..., 3], fx, fy, cx, cy) + mask = ( + all_data[T]["masks"][OBJECT_INDEX] + * (xyz_observed[..., 2] > 0) + * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) + ) + model_vertices = template_pose.inv().apply(xyz_rendered[mask]) + model_colors = all_data[T]["rgbd"][..., :3][mask] + + ### Set up inference hyperparams ### + + hyperparams = b3d.chisight.gen3d.settings.hyperparams + inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams + + hyperparams["intrinsics"] = { + "fx": fx, + "fy": fy, + "cx": cx, + "cy": cy, + "image_height": Pytree.const(image_height), + "image_width": Pytree.const(image_width), + "near": 0.01, + "far": 10.0, + } + hyperparams["vertices"] = model_vertices + + num_vertices = model_vertices.shape[0] + previous_state = { + "pose": template_pose, + "colors": model_colors, + "visibility_prob": jnp.ones(num_vertices) + * hyperparams["visibility_prob_kernel"].support[-1], + "depth_nonreturn_prob": jnp.ones(num_vertices) + * hyperparams["depth_nonreturn_prob_kernel"].support[0], + "depth_scale": hyperparams["depth_scale_kernel"].support[0], + "color_scale": hyperparams["color_scale_kernel"].support[0], + } + + choicemap = ( + genjax.ChoiceMap.d( + { + "pose": previous_state["pose"], + "color_scale": previous_state["color_scale"], + "depth_scale": previous_state["depth_scale"], + "rgbd": all_data[T]["rgbd"], + } + ) + ^ make_visibility_prob_choicemap(previous_state["visibility_prob"]) + ^ make_colors_choicemap(previous_state["colors"]) + ^ make_depth_nonreturn_prob_choicemap(previous_state["depth_nonreturn_prob"]) + ) + + ### Test we can generate a trace ### + key = jax.random.PRNGKey(0) + og_trace, weight = ( + b3d.chisight.gen3d.model.dynamic_object_generative_model.importance( + key, choicemap, (hyperparams, previous_state) + ) + ) + trace = og_trace + assert weight == trace.get_score() + + ### Test one inference step ### + def gt_pose(T): + return ( + all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] + ) + + trace, _ = i.inference_step( + jax.random.PRNGKey(26), + og_trace, + all_data[0]["rgbd"], + inference_hyperparams, + get_metadata=False, + use_gt_pose=True, + gt_pose=gt_pose(0), + ) + + assert ( + jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(0).position) + < 0.004 + ) + + ### Run inference, giving the ground truth pose as a option in the pose proposal grid ### + trace = og_trace + key = jax.random.PRNGKey(21) + for T in tqdm(range(2)): + key = b3d.split_key(key) + trace, _ = i.inference_step( + key, + trace, + all_data[T]["rgbd"], + inference_hyperparams, + use_gt_pose=True, + gt_pose=gt_pose(T), + get_metadata=False, + include_qscores_in_outer_resample=True, + ) + assert ( + jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) + < 0.004 + ) + + ### Real inference run ### + key = jax.random.PRNGKey(123) + trace = og_trace + for T in tqdm(range(2)): + key = b3d.split_key(key) + trace = i.inference_step_c2f( + key, + 1, # number of sequential iterations of the parallel pose proposal to consider + 5000, # number of poses to propose in parallel + # So the total number of poses considered at each step of C2F is 5000 * 1 + trace, + all_data[T]["rgbd"], + prev_color_proposal_laplace_scale=inference_hyperparams.prev_color_proposal_laplace_scale, + obs_color_proposal_laplace_scale=inference_hyperparams.obs_color_proposal_laplace_scale, + do_stochastic_color_proposals=True, + ) + + assert ( + jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) + < 0.01 + ) diff --git a/tests/gen3d/test_inference.py b/tests/gen3d/inference/test_point_attribute_inferences.py similarity index 100% rename from tests/gen3d/test_inference.py rename to tests/gen3d/inference/test_point_attribute_inferences.py From 5e4c6ea369a8cfeeab1be8b3a8728958b1f451a0 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Sat, 14 Sep 2024 12:04:30 -0400 Subject: [PATCH 25/37] Visualize Latent RGBD (#175) --- src/b3d/chisight/gen3d/image_kernel.py | 6 +- src/b3d/chisight/gen3d/inference.py | 30 +++++++ src/b3d/chisight/gen3d/model.py | 30 +++++-- src/b3d/chisight/gen3d/projection.py | 14 +-- src/b3d/chisight/gen3d/settings.py | 4 +- tests/gen3d/test_visualization.py | 117 +++++++++++++++++++++++++ 6 files changed, 182 insertions(+), 19 deletions(-) create mode 100644 tests/gen3d/test_visualization.py diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index f4dd93cf..590d365d 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -38,8 +38,6 @@ def get_pixels_points_association( return PixelsPointsAssociation.from_points_and_intrinsics( transformed_points, hyperparams["intrinsics"], - hyperparams["intrinsics"]["image_height"].unwrap(), - hyperparams["intrinsics"]["image_width"].unwrap(), ) @abstractmethod @@ -77,12 +75,12 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr pixel_depth_nonreturn_prob = points_to_pixels.get_pixel_attributes( state["depth_nonreturn_prob"] ) - pixel_latent_rgbd = points_to_pixels.get_pixel_attributes(state["colors"]) + pixel_latent_rgb = points_to_pixels.get_pixel_attributes(state["colors"]) pixel_latent_depth = points_to_pixels.get_pixel_attributes( transformed_points[..., 2] ) pixel_latent_rgbd = jnp.concatenate( - [pixel_latent_rgbd, pixel_latent_depth[..., None]], axis=-1 + [pixel_latent_rgb, pixel_latent_depth[..., None]], axis=-1 ) keys = jax.random.split( diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 1a0cf3b6..86c44b69 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -7,6 +7,7 @@ from genjax import Diff, Pytree from genjax import UpdateProblemBuilder as U from jax.random import split +from tqdm import tqdm import b3d from b3d.chisight.gen3d.inference_moves import ( @@ -273,6 +274,35 @@ def inference_step_noweight(*args): return inference_step(*args)[0] +def run_inference_many_frames( + key, + trace, + all_data, + inference_hyperparams, + use_gt_pose=True, + gt_poses=None, + get_metadata=False, + include_qscores_in_outer_resample=True, +): + traces = [] + if gt_poses is None: + gt_poses = [b3d.Pose.identity()] * len(all_data) + for T in tqdm(len(all_data)): + key = b3d.split_key(key) + trace, _ = inference_step( + key, + trace, + all_data[T]["rgbd"], + inference_hyperparams, + use_gt_pose=use_gt_pose, + gt_pose=gt_poses[T], + get_metadata=get_metadata, + include_qscores_in_outer_resample=include_qscores_in_outer_resample, + ) + traces.append(trace) + return trace + + ### Utils ### diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index 5714a6b9..36541238 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -6,6 +6,7 @@ from genjax import ChoiceMapBuilder as C import b3d +from b3d.chisight.gen3d.projection import PixelsPointsAssociation # TODOs # 1. Tests of drift kernels @@ -148,9 +149,26 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): output = trace.get_retval() if output["rgbd"] is not None: - b3d.rr_log_rgb(output["rgbd"][..., :3], "image") - b3d.rr_log_rgb(output["rgbd"][..., :3], "image/rgb/observed") - b3d.rr_log_depth(output["rgbd"][..., 3], "image/depth/observed") + observed_rgbd = output["rgbd"] + b3d.rr_log_rgb(observed_rgbd[..., :3], "image") + b3d.rr_log_rgb(observed_rgbd[..., :3], "image/rgb/observed") + b3d.rr_log_depth(observed_rgbd[..., 3], "image/depth/observed") + + pixel_point_association = PixelsPointsAssociation.from_points_and_intrinsics( + vertices_transformed, + hyperparams["intrinsics"], + ) + pixel_latent_rgb = jnp.clip( + pixel_point_association.get_pixel_attributes(new_state["colors"]), 0.0, 1.0 + ) + pixel_latent_depth = jnp.clip( + pixel_point_association.get_pixel_attributes(vertices_transformed[..., 2]), + 0.0, + 10.0, + ) + + b3d.rr_log_rgb(pixel_latent_rgb, "image/rgb/latent") + b3d.rr_log_depth(pixel_latent_depth, "image/depth/latent") # TODO: should we add in a way to visualize a noise-free projection # of the points to the camera plane? @@ -188,9 +206,9 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): b3d.rr_log_pose(ground_truth_pose, "scene/ground_truth_pose") b3d.rr_log_pose(trace.get_choices()["pose"], "scene/inferred_pose") - if not b3d.get_blueprint_logged(): - rr.send_blueprint(get_blueprint()) - b3d.set_blueprint_logged(True) + # if not b3d.get_blueprint_logged(): + # rr.send_blueprint(get_blueprint()) + # b3d.set_blueprint_logged(True) def get_blueprint(): diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index 484ae83c..ce151662 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -27,17 +27,11 @@ def from_hyperparams_and_pose(cls, hyperparams, pose_CO): return cls.from_points_and_intrinsics( vertices_C, hyperparams["intrinsics"], - hyperparams["intrinsics"]["image_height"].unwrap(), - hyperparams["intrinsics"]["image_width"].unwrap(), ) @classmethod def from_points_and_intrinsics( - cls, - points: FloatArray, - intrinsics: dict, - image_height: int, - image_width: int, + cls, points: FloatArray, intrinsics: dict ) -> "PixelsPointsAssociation": """Create a PixelsPointsAssociation object from a set of 3D points and the camera intrinsics. @@ -58,6 +52,12 @@ def from_points_and_intrinsics( ) - 0.5 ) + + image_height, image_width = ( + intrinsics["image_height"].unwrap(), + intrinsics["image_width"].unwrap(), + ) + # handle NaN before converting to int (otherwise NaN will be converted # to 0) projected_coords = jnp.nan_to_num(projected_coords, nan=INVALID_IDX) diff --git a/src/b3d/chisight/gen3d/settings.py b/src/b3d/chisight/gen3d/settings.py index b5248af8..0b4c74c7 100644 --- a/src/b3d/chisight/gen3d/settings.py +++ b/src/b3d/chisight/gen3d/settings.py @@ -24,10 +24,10 @@ ), "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( resample_probability=0.1, - support=jnp.array([0.0025, 0.01, 0.02, 0.1, 0.4, 1.0]), + support=jnp.array([0.0025, 0.01, 0.02]), ), "color_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15, 0.3, 0.8]) + resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15]) ), "image_kernel": image_kernel.NoOcclusionPerVertexImageKernel(), } diff --git a/tests/gen3d/test_visualization.py b/tests/gen3d/test_visualization.py new file mode 100644 index 00000000..81e91c28 --- /dev/null +++ b/tests/gen3d/test_visualization.py @@ -0,0 +1,117 @@ +import os + +import b3d +import b3d.chisight.gen3d.model +import b3d.chisight.gen3d.settings +import b3d.io.data_loader +import genjax +import jax +import jax.numpy as jnp +from b3d import Mesh +from b3d.chisight.gen3d.model import ( + make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, + make_visibility_prob_choicemap, +) +from genjax import Pytree + + +def test_visualization(): + b3d.rr_init("test_visualization") + scene_id = 49 + ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") + all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, [1]) + OBJECT_INDEX = 0 + id = all_data[0]["object_types"][OBJECT_INDEX] + + mesh = Mesh.from_obj_file( + os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') + ).scale(0.001) + + image_height, image_width = all_data[0]["rgbd"].shape[:2] + fx, fy, cx, cy = all_data[0]["camera_intrinsics"] + scaling_factor = 1.0 + renderer = b3d.renderer.renderer_original.RendererOriginal( + image_width * scaling_factor, + image_height * scaling_factor, + fx * scaling_factor, + fy * scaling_factor, + cx * scaling_factor, + cy * scaling_factor, + 0.01, + 2.0, + ) + b3d.viz_rgb(all_data[0]["rgbd"]) + + T = 0 + b3d.rr_set_time(T) + + template_pose = ( + all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] + ) + rendered_rgbd = renderer.render_rgbd_from_mesh(mesh.transform(template_pose)) + xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy) + + fx, fy, cx, cy = all_data[T]["camera_intrinsics"] + xyz_observed = b3d.xyz_from_depth(all_data[T]["rgbd"][..., 3], fx, fy, cx, cy) + mask = ( + all_data[T]["masks"][OBJECT_INDEX] + * (xyz_observed[..., 2] > 0) + * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) + ) + model_vertices = template_pose.inv().apply(xyz_rendered[mask]) + model_colors = all_data[T]["rgbd"][..., :3][mask] + + ### Set up inference hyperparams ### + + hyperparams = b3d.chisight.gen3d.settings.hyperparams + + hyperparams["intrinsics"] = { + "fx": fx, + "fy": fy, + "cx": cx, + "cy": cy, + "image_height": Pytree.const(image_height), + "image_width": Pytree.const(image_width), + "near": 0.01, + "far": 10.0, + } + hyperparams["vertices"] = model_vertices + + num_vertices = model_vertices.shape[0] + previous_state = { + "pose": template_pose, + "colors": model_colors, + "visibility_prob": jnp.ones(num_vertices) + * hyperparams["visibility_prob_kernel"].support[-1], + "depth_nonreturn_prob": jnp.ones(num_vertices) + * hyperparams["depth_nonreturn_prob_kernel"].support[0], + "depth_scale": hyperparams["depth_scale_kernel"].support[0], + "color_scale": hyperparams["color_scale_kernel"].support[0], + } + + choicemap = ( + genjax.ChoiceMap.d( + { + "pose": previous_state["pose"], + "color_scale": previous_state["color_scale"], + "depth_scale": previous_state["depth_scale"], + "rgbd": all_data[T]["rgbd"], + } + ) + ^ make_visibility_prob_choicemap(previous_state["visibility_prob"]) + ^ make_colors_choicemap(previous_state["colors"]) + ^ make_depth_nonreturn_prob_choicemap(previous_state["depth_nonreturn_prob"]) + ) + + key = jax.random.PRNGKey(0) + trace, _ = b3d.chisight.gen3d.model.dynamic_object_generative_model.importance( + key, choicemap, (hyperparams, previous_state) + ) + b3d.chisight.gen3d.model.viz_trace( + trace, + T, + ground_truth_vertices=mesh.vertices, + ground_truth_pose=all_data[T]["camera_pose"].inv() + @ all_data[T]["object_poses"][OBJECT_INDEX], + ) From 8f05777b2ad53a3c56224ede46d0b56a5fdce5f0 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Sun, 15 Sep 2024 03:45:02 -0400 Subject: [PATCH 26/37] Tracking working on spam (#176) --- .../old_inference_algorithm.ipynb | 403 ++++++++++++++++++ notebooks/bayes3d_paper/online_hb.ipynb | 279 ------------ src/b3d/chisight/gen3d/image_kernel.py | 103 ++++- src/b3d/chisight/gen3d/inference_old.py | 295 ++++++------- src/b3d/chisight/gen3d/projection.py | 1 + src/b3d/chisight/gen3d/visualization.py | 152 ++----- 6 files changed, 648 insertions(+), 585 deletions(-) create mode 100644 notebooks/bayes3d_paper/old_inference_algorithm.ipynb delete mode 100644 notebooks/bayes3d_paper/online_hb.ipynb diff --git a/notebooks/bayes3d_paper/old_inference_algorithm.ipynb b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb new file mode 100644 index 00000000..0c201a52 --- /dev/null +++ b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb @@ -0,0 +1,403 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "### IMPORTS ###\n", + "\n", + "import b3d\n", + "import jax.numpy as jnp\n", + "import os\n", + "from b3d import Mesh, Pose\n", + "import jax\n", + "import genjax\n", + "from genjax import Pytree\n", + "import rerun as rr\n", + "from b3d.modeling_utils import uniform_discrete, uniform_pose, gaussian_vmf\n", + "import matplotlib.pyplot as plt\n", + "from functools import partial\n", + "import importlib\n", + "from ipywidgets import interact\n", + "import ipywidgets as widgets\n", + "from tqdm import tqdm\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from genjax import SelectionBuilder as S\n", + "from genjax import ChoiceMapBuilder as C\n", + "\n", + "b3d.rr_init(\"dynamics2\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "### Loading data ###\n", + "b3d.reload(b3d.io.data_loader)\n", + "scene_id = 49\n", + "FRAME_RATE = 50\n", + "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", + "print(f\"Scene {scene_id}\")\n", + "b3d.reload(b3d.io.data_loader)\n", + "num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id)\n", + "\n", + "# image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE)\n", + "image_ids = range(1, num_scenes + 1, FRAME_RATE)\n", + "all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, image_ids)\n", + "\n", + "meshes = [\n", + " Mesh.from_obj_file(\n", + " os.path.join(ycb_dir, f'models/obj_{f\"{id + 1}\".rjust(6, \"0\")}.ply')\n", + " ).scale(0.001)\n", + " for id in all_data[0][\"object_types\"]\n", + "]\n", + "\n", + "image_height, image_width = all_data[0][\"rgbd\"].shape[:2]\n", + "fx,fy,cx,cy = all_data[0][\"camera_intrinsics\"]\n", + "scaling_factor = 1.0\n", + "renderer = b3d.renderer.renderer_original.RendererOriginal(\n", + " image_width * scaling_factor, image_height * scaling_factor, fx * scaling_factor, fy * scaling_factor, cx * scaling_factor, cy * scaling_factor, 0.01, 2.0\n", + ")\n", + "b3d.viz_rgb(all_data[0][\"rgbd\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d\n", + "import b3d.chisight.gen3d.model\n", + "b3d.reload(b3d.chisight.gen3d.model)\n", + "import b3d.chisight.gen3d.transition_kernels as transition_kernels\n", + "b3d.reload(b3d.chisight.gen3d.transition_kernels)\n", + "import b3d.chisight.gen3d.image_kernel as image_kernel\n", + "b3d.reload(b3d.chisight.gen3d.image_kernel)\n", + "import b3d.io.data_loader\n", + "import jax\n", + "import jax.numpy as jnp\n", + "from b3d import Mesh, Pose\n", + "from b3d.chisight.gen3d.model import (\n", + " make_colors_choicemap,\n", + " make_depth_nonreturn_prob_choicemap,\n", + " make_visibility_prob_choicemap,\n", + ")\n", + "from b3d.chisight.gen3d.model import dynamic_object_generative_model\n", + "from genjax import ChoiceMapBuilder as C\n", + "from genjax import Pytree\n", + "from b3d.chisight.gen3d.projection import PixelsPointsAssociation\n", + "\n", + "p_resample_color = 0.005\n", + "hyperparams = {\n", + " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.2),\n", + " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.05),\n", + " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.001, 0.999])\n", + " ),\n", + " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.001, 0.999])\n", + " ),\n", + " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05,\n", + " support=jnp.array([0.0025, 0.005, 0.01, 0.02]),\n", + " ),\n", + " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", + " resample_probability=0.05, support=jnp.array([0.01])\n", + " ),\n", + " \"image_kernel\": image_kernel.NoOcclusionPerVertexImageKernel(image_kernel.OldOcclusionPixelRGBDDistribution()),\n", + "}\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-10053.277\n" + ] + } + ], + "source": [ + "\n", + "T = 0\n", + "b3d.rr_set_time(T)\n", + "OBJECT_INDEX = 2\n", + "\n", + "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", + "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", + "xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy)\n", + "\n", + "fx, fy, cx, cy = all_data[T][\"camera_intrinsics\"]\n", + "xyz_observed = b3d.xyz_from_depth(all_data[T][\"rgbd\"][..., 3], fx, fy, cx, cy)\n", + "mask = all_data[T][\"masks\"][OBJECT_INDEX] * (xyz_observed[..., 2] > 0) * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01)\n", + "model_vertices = template_pose.inv().apply(xyz_rendered[mask])\n", + "model_colors = vertex_attributes=all_data[T][\"rgbd\"][..., :3][mask]\n", + "\n", + "# subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[:len(model_vertices) // 2]\n", + "# model_vertices = model_vertices[subset]\n", + "# model_colors = model_colors[subset]\n", + "mesh = meshes[OBJECT_INDEX]\n", + "model_vertices = mesh.vertices\n", + "model_colors = mesh.vertex_attributes\n", + "\n", + "hyperparams[\"intrinsics\"] = {\n", + " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy,\n", + " \"image_height\": Pytree.const(image_height),\n", + " \"image_width\": Pytree.const(image_width),\n", + " \"near\": 0.01,\n", + " \"far\": 3.0,\n", + "}\n", + "hyperparams[\"vertices\"] = model_vertices\n", + "\n", + "\n", + "num_vertices = model_vertices.shape[0]\n", + "previous_state = {\n", + " \"pose\": template_pose,\n", + " \"colors\": model_colors,\n", + " \"visibility_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"visibility_prob_kernel\"].support[-1],\n", + " \"depth_nonreturn_prob\": jnp.ones(num_vertices)\n", + " * hyperparams[\"depth_nonreturn_prob_kernel\"].support[0],\n", + " \"depth_scale\": hyperparams[\"depth_scale_kernel\"].support[0],\n", + " \"color_scale\": hyperparams[\"color_scale_kernel\"].support[0],\n", + "}\n", + "\n", + "choicemap = (\n", + " genjax.ChoiceMap.d(\n", + " {\n", + " \"pose\": previous_state[\"pose\"],\n", + " \"color_scale\": previous_state[\"color_scale\"],\n", + " \"depth_scale\": previous_state[\"depth_scale\"],\n", + " \"rgbd\": all_data[T][\"rgbd\"],\n", + " }\n", + " ) ^ \n", + " make_visibility_prob_choicemap(previous_state[\"visibility_prob\"]) ^\n", + " make_colors_choicemap(previous_state[\"colors\"]) ^\n", + " make_depth_nonreturn_prob_choicemap(previous_state[\"depth_nonreturn_prob\"])\n", + ")\n", + "key = jax.random.PRNGKey(0)\n", + "\n", + "trace= dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))[0]\n", + "print(trace.get_score())\n", + "og_trace = trace\n", + "b3d.chisight.gen3d.model.viz_trace(trace, T,\n", + " ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", + " ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", + ")\n", + "results = {}" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d.chisight.gen3d.inference_old as inference\n", + "import b3d.chisight.gen3d.settings \n", + "b3d.reload(b3d.chisight.gen3d.inference_old)\n", + "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams\n", + "import b3d.chisight.gen3d.visualization as viz\n", + "b3d.reload(b3d.chisight.gen3d.visualization)\n", + "import b3d.chisight.gen3d.visualization as viz\n", + "import b3d.chisight.gen3d.image_kernel\n", + "b3d.reload(b3d.chisight.gen3d.image_kernel)" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [], + "source": [ + "# trace, _ = inference.update_vertex_attributes(key, trace, inference_hyperparams)\n", + "# b3d.chisight.gen3d.model.viz_trace(trace, 1,\n", + "# ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", + "# ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", + "# )\n", + "# choicemap_good = trace.get_choices()" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [], + "source": [ + "trace = trace.update(key, choicemap_good)[0]\n", + "b3d.chisight.gen3d.model.viz_trace(trace, 0,\n", + " ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", + " ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 141, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 49/49 [02:09<00:00, 2.65s/it]\n" + ] + } + ], + "source": [ + "for T in tqdm(range(len(all_data))):\n", + " trace = inference.advance_time(key, trace, all_data[T][\"rgbd\"])\n", + " trace = inference.inference_step(trace, key, inference_hyperparams)[0]\n", + " results[T] = trace\n", + "\n", + " b3d.chisight.gen3d.model.viz_trace(trace, T,\n", + " ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", + " ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array(0., dtype=float32)" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vertex_index = 2426\n", + "trace.get_retval()[\"new_state\"][\"visibility_prob\"][vertex_index]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for T in tqdm(range(len(all_data))):\n", + " trace = inference.advance_time(key, trace, all_data[T][\"rgbd\"])\n", + " trace = inference.inference_step(trace, key, inference_hyperparams)[0]\n", + " results[T] = trace\n", + "\n", + " b3d.chisight.gen3d.model.viz_trace(trace, T,\n", + " ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", + " ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "T = 1\n", + "trace = inference.advance_time(key, trace, all_data[T][\"rgbd\"])\n", + "trace = inference.inference_step(trace, key, inference_hyperparams)[0]\n", + "b3d.chisight.gen3d.model.viz_trace(trace, T)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.54117644 0.37647057 0.2352941 0.9140787 ] [0.54117644 0.37647057 0.2352941 0.851 ]\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a6a6bb735693451490d8a25f64893e94", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(FloatSlider(value=0.009999999776482582, continuous_update=False, description='Color Scal…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "b3d.reload(b3d.chisight.gen3d.visualization)\n", + "import b3d.chisight.gen3d.visualization as viz\n", + "\n", + "latent_rgbd_per_point, observed_rgbd_per_point = b3d.chisight.gen3d.image_kernel.get_latent_and_observed_correspondences(\n", + " trace.get_retval()[\"new_state\"], trace.get_args()[0], trace.get_choices()[\"rgbd\"]\n", + ")\n", + "previous_state = trace.get_args()[1]\n", + "vertex_index = 602\n", + "print(latent_rgbd_per_point[vertex_index], observed_rgbd_per_point[vertex_index])\n", + "previous_color = previous_state[\"colors\"][vertex_index]\n", + "previous_visibility_prob = previous_state[\"visibility_prob\"][vertex_index]\n", + "previous_dnrp = previous_state[\"depth_nonreturn_prob\"][vertex_index]\n", + "observed_rgbd_for_point = observed_rgbd_per_point[vertex_index]\n", + "latent_rgbd_for_point = latent_rgbd_per_point[vertex_index]\n", + "attribute_proposal_function = inference.attribute_proposal_only_color_and_visibility\n", + "viz.create_interactive_visualization(\n", + " observed_rgbd_for_point,\n", + " latent_rgbd_for_point,\n", + " hyperparams, inference_hyperparams,\n", + " previous_color,\n", + " previous_visibility_prob,\n", + " previous_dnrp,\n", + " attribute_proposal_function,\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/bayes3d_paper/online_hb.ipynb b/notebooks/bayes3d_paper/online_hb.ipynb deleted file mode 100644 index 2500161c..00000000 --- a/notebooks/bayes3d_paper/online_hb.ipynb +++ /dev/null @@ -1,279 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "### IMPORTS ###\n", - "\n", - "import b3d\n", - "import jax.numpy as jnp\n", - "import os\n", - "from b3d import Mesh, Pose\n", - "import jax\n", - "import genjax\n", - "from genjax import Pytree\n", - "import rerun as rr\n", - "from b3d.modeling_utils import uniform_discrete, uniform_pose, gaussian_vmf\n", - "import matplotlib.pyplot as plt\n", - "from functools import partial\n", - "import importlib\n", - "from ipywidgets import interact\n", - "import ipywidgets as widgets\n", - "from tqdm import tqdm\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "from genjax import SelectionBuilder as S\n", - "from genjax import ChoiceMapBuilder as C\n", - "\n", - "b3d.rr_init(\"dynamics2\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Scene 49\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/49 [00:00" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "### Loading data ###\n", - "b3d.reload(b3d.io.data_loader)\n", - "scene_id = 49\n", - "FRAME_RATE = 50\n", - "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", - "print(f\"Scene {scene_id}\")\n", - "b3d.reload(b3d.io.data_loader)\n", - "num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id)\n", - "\n", - "# image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE)\n", - "image_ids = range(1, num_scenes + 1, FRAME_RATE)\n", - "all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, image_ids)\n", - "\n", - "meshes = [\n", - " Mesh.from_obj_file(\n", - " os.path.join(ycb_dir, f'models/obj_{f\"{id + 1}\".rjust(6, \"0\")}.ply')\n", - " ).scale(0.001)\n", - " for id in all_data[0][\"object_types\"]\n", - "]\n", - "\n", - "image_height, image_width = all_data[0][\"rgbd\"].shape[:2]\n", - "fx,fy,cx,cy = all_data[0][\"camera_intrinsics\"]\n", - "scaling_factor = 1.0\n", - "renderer = b3d.renderer.renderer_original.RendererOriginal(\n", - " image_width * scaling_factor, image_height * scaling_factor, fx * scaling_factor, fy * scaling_factor, cx * scaling_factor, cy * scaling_factor, 0.01, 2.0\n", - ")\n", - "b3d.viz_rgb(all_data[0][\"rgbd\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "import b3d\n", - "import b3d.chisight.gen3d.model\n", - "b3d.reload(b3d.chisight.gen3d.model)\n", - "import b3d.chisight.gen3d.transition_kernels as transition_kernels\n", - "b3d.reload(b3d.chisight.gen3d.transition_kernels)\n", - "import b3d.chisight.gen3d.image_kernel as image_kernel\n", - "b3d.reload(b3d.chisight.gen3d.image_kernel)\n", - "import b3d.io.data_loader\n", - "import jax\n", - "import jax.numpy as jnp\n", - "from b3d import Mesh, Pose\n", - "from b3d.chisight.gen3d.model import (\n", - " make_colors_choicemap,\n", - " make_depth_nonreturn_prob_choicemap,\n", - " make_visibility_prob_choicemap,\n", - ")\n", - "from b3d.chisight.gen3d.model import dynamic_object_generative_model\n", - "from genjax import ChoiceMapBuilder as C\n", - "from genjax import Pytree" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "45277.63\n" - ] - } - ], - "source": [ - "\n", - "T = 0\n", - "b3d.rr_set_time(T)\n", - "OBJECT_INDEX = 1\n", - "\n", - "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", - "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", - "xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy)\n", - "\n", - "fx, fy, cx, cy = all_data[T][\"camera_intrinsics\"]\n", - "xyz_observed = b3d.xyz_from_depth(all_data[T][\"rgbd\"][..., 3], fx, fy, cx, cy)\n", - "mask = all_data[T][\"masks\"][OBJECT_INDEX] * (xyz_observed[..., 2] > 0) * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01)\n", - "model_vertices = template_pose.inv().apply(xyz_rendered[mask])\n", - "model_colors = vertex_attributes=all_data[T][\"rgbd\"][..., :3][mask]\n", - "\n", - "# subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[:len(model_vertices) // 2]\n", - "# model_vertices = model_vertices[subset]\n", - "# model_colors = model_colors[subset]\n", - "\n", - "hyperparams = {\n", - " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", - " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.15),\n", - " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", - " ),\n", - " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.01, 0.99])\n", - " ),\n", - " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.0025, 0.01, 0.02])\n", - " ),\n", - " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.05, 0.1, 0.15])\n", - " ),\n", - "\n", - " \"image_kernel\": image_kernel.OldNoOcclusionPerVertexImageKernel(\n", - " 0.001, 1.0, image_height, image_width\n", - " ),\n", - "\n", - " \"intrinsics\": {\n", - " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy\n", - " },\n", - " \"image_height\": Pytree.const(image_height),\n", - " \"image_width\": Pytree.const(image_width),\n", - " \n", - " \"vertices\":model_vertices\n", - "}\n", - "\n", - "num_vertices = model_vertices.shape[0]\n", - "previous_state = {\n", - " \"pose\": template_pose,\n", - " \"colors\": model_colors,\n", - " \"visibility_prob\": jnp.ones(num_vertices)\n", - " * hyperparams[\"visibility_prob_kernel\"].support[-1],\n", - " \"depth_nonreturn_prob\": jnp.ones(num_vertices)\n", - " * hyperparams[\"depth_nonreturn_prob_kernel\"].support[0],\n", - " \"depth_scale\": hyperparams[\"depth_scale_kernel\"].support[0],\n", - " \"color_scale\": hyperparams[\"color_scale_kernel\"].support[0],\n", - "}\n", - "\n", - "choicemap = (\n", - " genjax.ChoiceMap.d(\n", - " {\n", - " \"pose\": previous_state[\"pose\"],\n", - " \"color_scale\": previous_state[\"color_scale\"],\n", - " \"depth_scale\": previous_state[\"depth_scale\"],\n", - " \"rgbd\": all_data[T][\"rgbd\"],\n", - " }\n", - " ) ^ \n", - " make_visibility_prob_choicemap(previous_state[\"visibility_prob\"]) ^\n", - " make_colors_choicemap(previous_state[\"colors\"]) ^\n", - " make_depth_nonreturn_prob_choicemap(previous_state[\"depth_nonreturn_prob\"])\n", - ")\n", - "key = jax.random.PRNGKey(0)\n", - "\n", - "trace= dynamic_object_generative_model.importance(key, choicemap, (hyperparams, previous_state))[0]\n", - "print(trace.get_score())\n", - "b3d.chisight.gen3d.model.viz_trace(trace, 0)\n", - "results = {}" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [], - "source": [ - "import b3d.chisight.gen3d.inference_old as inference\n", - "b3d.reload(b3d.chisight.gen3d.inference_old)" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 49/49 [00:42<00:00, 1.14it/s]\n" - ] - } - ], - "source": [ - "### Run inference ###\n", - "for T in tqdm(range(len(all_data))):\n", - " key = b3d.split_key(key)\n", - " trace = inference.inference_step(trace, key, all_data[T][\"rgbd\"])\n", - " b3d.chisight.gen3d.model.viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])\n", - " results[T] = trace\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "b3d", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index 590d365d..0043f3cc 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -23,6 +23,18 @@ from b3d.chisight.gen3d.projection import PixelsPointsAssociation +def get_latent_and_observed_correspondences(state, hyperparams, observed_rgbd): + transformed_points = state["pose"].apply(hyperparams["vertices"]) + points_to_pixels = PixelsPointsAssociation.from_points_and_intrinsics( + transformed_points, hyperparams["intrinsics"] + ) + observed_rgbd_per_point = points_to_pixels.get_point_rgbds(observed_rgbd) + latent_rgbd_per_point = jnp.concatenate( + (state["colors"], transformed_points[..., 2, None]), axis=-1 + ) + return latent_rgbd_per_point, observed_rgbd_per_point + + @Pytree.dataclass class ImageKernel(genjax.ExactDensity): """An abstract class that defines the common interface for image kernels, @@ -56,10 +68,18 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: @Pytree.dataclass class NoOcclusionPerVertexImageKernel(ImageKernel): + rgbd_vertex_kernel: PixelRGBDDistribution = FullPixelRGBDDistribution( + RenormalizedLaplacePixelColorDistribution(), + UniformPixelColorDistribution(), + RenormalizedLaplacePixelDepthDistribution(), + UniformPixelDepthDistribution(), + ) + def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: """Generate latent RGBD image by projecting the vertices directly to the image plane, without checking for occlusions. """ + transformed_points = state["pose"].apply(hyperparams["vertices"]) points_to_pixels = self.get_pixels_points_association( transformed_points, hyperparams @@ -106,16 +126,10 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr def logpdf( self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping ) -> FloatArray: - transformed_points = state["pose"].apply(hyperparams["vertices"]) - points_to_pixels = self.get_pixels_points_association( - transformed_points, hyperparams + latent_rgbd_per_point, observed_rgbd_per_point = ( + get_latent_and_observed_correspondences(state, hyperparams, observed_rgbd) ) vertex_kernel = self.get_rgbd_vertex_kernel() - observed_rgbd_per_point = points_to_pixels.get_point_rgbds(observed_rgbd) - latent_rgbd_per_point = jnp.concatenate( - (state["colors"], transformed_points[..., 2, None]), axis=-1 - ) - scores = jax.vmap(vertex_kernel.logpdf, in_axes=(0, 0, None, None, 0, 0, None))( observed_rgbd_per_point, latent_rgbd_per_point, @@ -125,12 +139,12 @@ def logpdf( state["depth_nonreturn_prob"], hyperparams["intrinsics"], ) + # Points that don't hit the camera plane should not contribute to the score. scores = jnp.where(is_unexplained(observed_rgbd_per_point), 0.0, scores) score_for_pixels_with_points = scores.sum() # TODO: add scores for pixels that don't get a point - return score_for_pixels_with_points def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: @@ -138,12 +152,7 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: # but they should work for per-vertex computation as well, except that # they don't expect observed_rgbd to be invalid, so we need to handle # that manually. - return FullPixelRGBDDistribution( - RenormalizedLaplacePixelColorDistribution(), - UniformPixelColorDistribution(), - RenormalizedLaplacePixelDepthDistribution(), - UniformPixelDepthDistribution(), - ) + return self.rgbd_vertex_kernel # @Pytree.dataclass @@ -226,3 +235,67 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: # # they don't expect observed_rgbd to be invalid, so we need to handle # # that manually. # raise NotImplementedError + + +@Pytree.dataclass +class OldOcclusionPixelRGBDDistribution(PixelRGBDDistribution): + """ + Distribution args: + - latent_rgbd: 4-array: RGBD value. (a value of [-1, -1, -1, -1] indicates no point hits here.) + - color_scale: float + - depth_scale: float + - visibility_prob: float + - depth_nonreturn_prob: float + + The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). + + Note that this distribution expects the observed_rgbd to be valid. If an invalid + pixel is observed, the logpdf will return -inf. + """ + + def sample( + self, + key: PRNGKey, + latent_rgbd: FloatArray, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, + intrinsics: dict, + ) -> FloatArray: + return jnp.ones((4,)) * 0.5 + + def logpdf( + self, + observed_rgbd: FloatArray, + latent_rgbd: FloatArray, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, + intrinsics: dict, + ) -> float: + color_visible_branch_score = jax.scipy.stats.laplace.logpdf( + observed_rgbd[:3], latent_rgbd[:3], color_scale + ).sum(axis=-1) + color_not_visible_score = jnp.log(1 / 1.0**3) + color_score = jnp.logaddexp( + color_visible_branch_score + jnp.log(visibility_prob), + color_not_visible_score + jnp.log(1 - visibility_prob), + ) + + depth_visible_branch_score = jax.scipy.stats.laplace.logpdf( + observed_rgbd[3], latent_rgbd[3], depth_scale + ) + depth_not_visible_score = jnp.log(1 / 1.0) + _depth_score = jnp.logaddexp( + depth_visible_branch_score + jnp.log(visibility_prob), + depth_not_visible_score + jnp.log(1 - visibility_prob), + ) + is_depth_non_return = observed_rgbd[3] < 0.0001 + + depth_score = jnp.where( + is_depth_non_return, jnp.log(depth_nonreturn_prob), _depth_score + ) + + return color_score + depth_score diff --git a/src/b3d/chisight/gen3d/inference_old.py b/src/b3d/chisight/gen3d/inference_old.py index 2f800ed6..90e171f2 100644 --- a/src/b3d/chisight/gen3d/inference_old.py +++ b/src/b3d/chisight/gen3d/inference_old.py @@ -2,215 +2,175 @@ import jax.numpy as jnp import jax.random from genjax import ChoiceMapBuilder as C -from genjax import Diff -from genjax import UpdateProblemBuilder as U +import b3d from b3d import Pose from .model import ( make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, make_visibility_prob_choicemap, ) @jax.jit -def advance_time(key, trace, observed_rgbd): - """ - Advance to the next timestep, setting the new latent state to the - same thing as the previous latent state, and setting the new - observed RGBD value. - - Returns a trace where previous_state (stored in the arguments) - and new_state (sampled in the choices and returned) are identical. - """ - hyperparams, _ = trace.get_args() - previous_state = trace.get_retval()["new_state"] - trace, _, _, _ = trace.update( - key, - U.g( - (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), - C.kw(rgbd=observed_rgbd), - ), - ) - return trace - +def attribute_proposal_only_color_and_visibility( + key, + observed_rgbd_for_point, + latent_rgbd_for_point, + previous_color, + previous_visibility_prob, + previous_dnrp, + color_scale, + depth_scale, + hyperparams, + inference_hyperparams, +): + image_kernel = hyperparams["image_kernel"] + vertex_rgbd_kernel = image_kernel.get_rgbd_vertex_kernel() -@jax.jit -def propose_color_and_visibility(trace, key): # color_outlier_probability_sweep is (k,) shape array - hyperparams, previous_state = trace.get_args() - previous_visibility = previous_state["visibility_prob"] - previous_colors = previous_state["colors"] - - visibility_values = hyperparams["visibility_prob_kernel"].support + depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] + dnrp_values = depth_nonreturn_prob_kernel.support + + def likelihood_scorer(dnrp): + return vertex_rgbd_kernel.logpdf( + observed_rgbd_for_point, + latent_rgbd_for_point, + color_scale, + depth_scale, + previous_visibility_prob, + dnrp, + hyperparams["intrinsics"], + ) - visibility_sweep = ( - visibility_values[..., None] # (num_outlier_grid_points, 1) - * jnp.ones_like(previous_visibility) # (num_vertices,) - ) # (num_outlier_grid_points, num_vertices) + dnrp = dnrp_values[jnp.argmax(jax.vmap(likelihood_scorer)(dnrp_values))] + # color_outlier_probability_sweep is (k,) shape array + visibility_values = hyperparams["visibility_prob_kernel"].support visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - visibility_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( - visibility_prob_kernel.logpdf, - signature="(),()->()", - )(visibility_sweep, previous_visibility) - - info_from_trace = hyperparams["image_kernel"].info_from_trace - - # We will grid over color values, using a grid that mixes the old and observed - # colors in a set of exact proportions. - # We regard these as coming from uniform proposals where we sample the RGB - # values uniformly between the mixed R, G, and B values with mixtures between - # [0., .125], [.125, .5], [.5, .875], [.875, 1.]. - # So the q scores will be .125^3, .375^3, .375^3, .125^3. - # TODO: we really ought to add a small amount of proposal probability mass - # onto the points at the end, to capture the fact that the posterior could allow - # colors outside the considered interpolation window. - color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) - # num_color_grid_points = len(color_interpolations_per_proposal) + visbility_transition_scores = jax.vmap( + visibility_prob_kernel.logpdf, in_axes=(0, None) + )(visibility_values, previous_visibility_prob) - observed_colors = info_from_trace(trace)["observed_rgbd_masked"][ - ..., :3 - ] # (num_vertices, 3) - color_sweep = observed_colors[None, ...] * color_interpolations_per_proposal[ - :, None, None - ] + previous_colors[None, ...] * ( - 1 - color_interpolations_per_proposal[:, None, None] - ) # (num_color_grid_points, num_vertices, 3) + color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) + observed_color = observed_rgbd_for_point[:3] + color_sweep = ( + color_interpolations_per_proposal[..., None] * observed_color + + (1.0 - color_interpolations_per_proposal[..., None]) * previous_color + ) color_kernel = hyperparams["color_kernel"] - color_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( - color_kernel.logpdf, - signature="(3),(3)->()", - )(color_sweep, previous_colors) - - # Function takes in color and color outlier probabilities array of shapes (num_vertices,3) and (num_vertices,) respectively - # and gives scores for each vertex (num_vertices,) - def get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities( - colors, visibility - ): - return info_from_trace( - trace.update( - key, - make_colors_choicemap(colors) - ^ make_visibility_prob_choicemap(visibility), - )[0] - )["scores"] + color_transition_scores = jax.vmap(color_kernel.logpdf, in_axes=(0, None))( + color_sweep, previous_color + ) + + def likelihood_scorer(color, visibility_prob): + latent_rgbd_adjusted = latent_rgbd_for_point.at[:3].set(color) + return vertex_rgbd_kernel.logpdf( + observed_rgbd_for_point, + latent_rgbd_adjusted, + color_scale, + depth_scale, + visibility_prob, + dnrp, + hyperparams["intrinsics"], + ) vmap_version = jax.vmap( jax.vmap( - get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities, + likelihood_scorer, in_axes=(None, 0), ), in_axes=(0, None), ) - # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep likelihood_scores_per_sweep_point_and_vertex = vmap_version( - color_sweep, visibility_sweep - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - scores_per_sweep_point_and_vertex = ( - likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points, num_vertices) - + visibility_transition_scores_per_sweep_point_and_vertex[None, ...] - + color_transition_scores_per_sweep_point_and_vertex[:, None, ...] - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - unraveled_scores = scores_per_sweep_point_and_vertex.reshape( - -1, scores_per_sweep_point_and_vertex.shape[-1] + color_sweep, visibility_values ) - normalized_log_probabilities = jax.nn.log_softmax(unraveled_scores, axis=0) - sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) - color_sweep_indices, visibility_sweep_indices = jnp.unravel_index( - sampled_indices, scores_per_sweep_point_and_vertex.shape[:2] - ) + scores_color_and_visibility = ( + likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points) + + color_transition_scores[:, None, ...] + + visbility_transition_scores[None, ...] + ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - # color_sweep is (num_outlier_grid_points, num_vertices, 3) - # outlier_probability_sweep is (num_outlier_grid_points,) - # color_outlier_probabilities_sweep is (num_outlier_grid_points, num_vertices) - sampled_colors = color_sweep[color_sweep_indices, jnp.arange(color_sweep.shape[1])] - sampled_color_outlier_probabilities = visibility_values[visibility_sweep_indices] - - log_q_color_and_color_outlier_probability = normalized_log_probabilities[ - sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) - ].sum() - - # log_q = estimate of q(all these colors, all these outliers ; inputs) - # Only source of real randomness = sampling indices. Captured in log_q_color_and_color_outlier_probability. - # But we also want to be careful with the continuous values... - # (1) outlier probs. --> change the model to have discrete grid. [Do later.] - # (2) colors. --> 1/q() - # uniform(old r, 2/3 oldr + 1/3 newr) 0 | uniform(0, 0.1) - # uniform(1/3, 2/3) # .5 | uniform(.1, .9) - # uniform(2/3, 1) # 1 | uniform(.9, 1) - # - # q(c1) * q(c2) * q(c3) - # but we just output c2 - # q(the c values we output, marginalizing over the other choices) - # -> just output q(c2) - - # We will treat this like the case where each sweep is uniform, so the q scores - # are each (oldr - obsr)/3 * (oldg - obsg)/3 * (oldb - obsb)/3. - - hyperparams = trace.get_args()[0] - color_shift_scale = hyperparams["color_kernel"].scale - color_scale = trace.get_choices()["color_scale"] - - d = 1 / (1 / color_shift_scale + 1 / color_scale) - - q_prob_per_vertex = ( - 1.0 / ((jnp.abs(previous_colors - observed_colors) / 3) + 4 * d) - ).prod(-1) - log_q_for_the_color_proposal = jnp.log(q_prob_per_vertex).sum() - - return ( - sampled_colors, - sampled_color_outlier_probabilities, - log_q_color_and_color_outlier_probability + log_q_for_the_color_proposal, - scores_per_sweep_point_and_vertex, + idx_color, idx_visibility = jnp.unravel_index( + jnp.argmax(scores_color_and_visibility.reshape(-1)), + scores_color_and_visibility.shape, ) + return { + "colors": color_sweep[idx_color], + "visibility_prob": visibility_values[idx_visibility], + "depth_nonreturn_prob": dnrp, + "scores": scores_color_and_visibility, + } @jax.jit -def propose_update(trace, key, pose): - total_log_q = 0.0 +def update_vertex_attributes(key, trace, inference_hyperparams): + hyperparams, previous_state = trace.get_args() - # Update pose - # pose, log_q_pose = propose_pose( - # trace, key, pose_sample_variance, pose_sample_concentration - # ) - trace = trace.update(key, C["pose"].set(pose))[0] + latent_rgbd_per_point, observed_rgbd_per_point = ( + b3d.chisight.gen3d.image_kernel.get_latent_and_observed_correspondences( + trace.get_retval()["new_state"], + trace.get_args()[0], + trace.get_choices()["rgbd"], + ) + ) - # Update color and color outlier probability - sampled_colors, sampled_visibility, log_q, _ = propose_color_and_visibility( - trace, key + previous_state = trace.get_args()[1] + previous_color = previous_state["colors"] + previous_visibility_prob = previous_state["visibility_prob"] + previous_dnrp = previous_state["depth_nonreturn_prob"] + color_scale = previous_state["color_scale"] + depth_scale = previous_state["depth_scale"] + + keys = jax.random.split(key, len(observed_rgbd_per_point)) + + sample = jax.vmap( + attribute_proposal_only_color_and_visibility, + in_axes=(0, 0, 0, 0, 0, 0, None, None, None, None), + )( + keys, + observed_rgbd_per_point, + latent_rgbd_per_point, + previous_color, + previous_visibility_prob, + previous_dnrp, + color_scale, + depth_scale, + hyperparams, + inference_hyperparams, ) trace = trace.update( key, - make_colors_choicemap(sampled_colors) - ^ make_visibility_prob_choicemap(sampled_visibility), + make_colors_choicemap(sample["colors"]) + ^ make_visibility_prob_choicemap(sample["visibility_prob"]) + ^ make_depth_nonreturn_prob_choicemap(sample["depth_nonreturn_prob"]), )[0] - total_log_q += log_q + return trace, {} - return trace, total_log_q +def update_all(key, trace, pose, inference_hyperparams): + trace = trace.update(key, C["pose"].set(pose))[0] + trace, _ = update_vertex_attributes(key, trace, inference_hyperparams) + return trace -@jax.jit -def propose_update_get_score(trace, key, pose): - new_trace, log_q = propose_update(trace, key, pose) - # score is an estimate of P(data, pose | previous state) - return new_trace.get_score() - log_q +def update_all_get_score(key, trace, pose, inference_hyperparams): + trace = update_all(key, trace, pose, inference_hyperparams) + return trace.get_score() -propose_update_get_score_vmap = jax.jit( - jax.vmap(propose_update_get_score, in_axes=(None, None, 0)) + +update_all_get_score_vmap = jax.jit( + jax.vmap(update_all_get_score, in_axes=(0, None, 0, None)) ) -def inference_step_without_advance(trace, key): - number = 15000 +def inference_step(trace, key, inference_hyperparams): + number = 20000 current_pose = trace.get_choices()["pose"] var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] for var, conc in var_conc: @@ -218,25 +178,18 @@ def inference_step_without_advance(trace, key): keys = jax.random.split(key, number) poses = Pose.concatenate_poses( [ - Pose.sample_gaussian_vmf_pose_vmap(keys, current_pose, var, conc), + Pose.sample_gaussian_vmf_pose_vmap(keys[:-1], current_pose, var, conc), current_pose[None, ...], ] ) pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( poses, trace.get_choices()["pose"], var, conc ) - scores = propose_update_get_score_vmap(trace, key, poses) + scores = update_all_get_score_vmap(keys, trace, poses, inference_hyperparams) scores_pose_q_correction = ( scores - pose_scores ) # After this, scores are fair estimates of P(data | previous state) # and can be used to resample the choice sets. - index = jax.random.categorical(key, scores) - current_pose = poses[index] - trace = propose_update(trace, key, current_pose)[0] + current_pose = poses[jnp.argmax(scores)] + trace = update_all(key, trace, current_pose, inference_hyperparams) return trace, scores, scores_pose_q_correction - - -def inference_step(trace, key, observed_rgbd): - trace = advance_time(key, trace, observed_rgbd) - trace = inference_step_without_advance(trace, key)[0] - return trace diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index ce151662..7a40a327 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -51,6 +51,7 @@ def from_points_and_intrinsics( intrinsics["cy"], ) - 0.5 + # ? (not sure if this is necessary) ?? ) image_height, image_width = ( diff --git a/src/b3d/chisight/gen3d/visualization.py b/src/b3d/chisight/gen3d/visualization.py index 06ac2a0b..26600126 100644 --- a/src/b3d/chisight/gen3d/visualization.py +++ b/src/b3d/chisight/gen3d/visualization.py @@ -5,56 +5,23 @@ from ipywidgets import interact from matplotlib.gridspec import GridSpec -import b3d.chisight.gen3d.inference_moves as inference_moves - -@jax.jit -def get_sample( - key, +def plot_samples( + samples, observed_rgbd_for_point, - previous_visibility_prob, + latent_rgbd_for_point, previous_color, - latent_depth, + previous_visibility_prob, previous_dnrp, color_scale, - depth_scale, - hyperparams, - inference_hyperparams, ): - depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] - visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - color_kernel = hyperparams["color_kernel"] - obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() - rgb, visibility_prob, dnr_prob = inference_moves._propose_a_points_attributes( - key, - observed_rgbd_for_point, - latent_depth, - previous_color, - previous_visibility_prob, - previous_dnrp, - depth_nonreturn_prob_kernel, - visibility_prob_kernel, - color_kernel, - obs_rgbd_kernel, - color_scale, - depth_scale, - inference_hyperparams, - return_metadata=False, - )[:3] - return rgb, visibility_prob, dnr_prob - - -get_samples = jax.vmap( - get_sample, in_axes=(0, None, None, None, None, None, None, None, None, None) -) - - -def plot_samples(samples, observed_rgbd_for_point, previous_color, latent_depth): fig = plt.figure(layout="constrained", figsize=(10, 10)) gs = GridSpec(3, 3, figure=fig) fig.suptitle(f"Observed RGBD: {observed_rgbd_for_point}", fontsize=16) - rgb, visibility_prob, dnr_prob = samples + rgb = samples["colors"] + visibility_prob = samples["visibility_prob"] + dnr_prob = samples["depth_nonreturn_prob"] ax = fig.add_subplot(gs[0, 0]) values, counts = jnp.unique(visibility_prob, return_counts=True) @@ -69,12 +36,14 @@ def plot_samples(samples, observed_rgbd_for_point, previous_color, latent_depth) ax.set_title("Depth Nonreturn Probability Samples") ax = fig.add_subplot(gs[0, 2]) - ax.set_xlim(0.0, 2.0) + # ax.set_xlim(0.0, 2.0) ax.set_title("Depth") ax.axvline( x=observed_rgbd_for_point[3], color="black", linestyle="--", label="Observed" ) - ax.axvline(x=latent_depth, color="black", linestyle="dotted", label="Latent") + ax.axvline( + x=latent_rgbd_for_point[3], color="black", linestyle="dotted", label="Latent" + ) ax.legend() ax = fig.add_subplot(gs[1, 0]) @@ -100,105 +69,48 @@ def plot_samples(samples, observed_rgbd_for_point, previous_color, latent_depth) def create_interactive_visualization( - observed_rgbd_for_point, hyperparams, inference_hyperparams + observed_rgbd_for_point, + latent_rgbd_for_point, + hyperparams, + inference_hyperparams, + previous_color, + previous_visibility_prob, + previous_dnrp, + attribute_proposal_function, ): key = jax.random.PRNGKey(0) - keys = jax.random.split(key, 1000) - depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] - visibility_prob_kernel = hyperparams["visibility_prob_kernel"] color_scale_kernel = hyperparams["color_scale_kernel"] depth_scale_kernel = hyperparams["depth_scale_kernel"] def f( - previous_visibility_prob, - previous_dnrp, - latent_depth, - previous_r, - previous_g, - previous_b, color_scale, depth_scale, ): - previous_color = jnp.array([previous_r, previous_g, previous_b]) - previous_visibility_prob = float(previous_visibility_prob) - previous_dnrp = float(previous_dnrp) - samples = get_samples( - keys, + samples = jax.vmap(attribute_proposal_function, in_axes=(0, *(None,) * 9))( + jax.random.split(key, 100), observed_rgbd_for_point, - previous_visibility_prob, + latent_rgbd_for_point, previous_color, - latent_depth, + previous_visibility_prob, previous_dnrp, color_scale, depth_scale, hyperparams, inference_hyperparams, ) - plot_samples(samples, observed_rgbd_for_point, previous_color, latent_depth) + plot_samples( + samples, + observed_rgbd_for_point, + latent_rgbd_for_point, + previous_color, + previous_visibility_prob, + previous_dnrp, + color_scale, + ) interact( f, - previous_visibility_prob=widgets.ToggleButtons( - options=[f"{x:.2f}" for x in visibility_prob_kernel.support], - description="Prev Vis Prob:", - disabled=False, - button_style="", # 'success', 'info', 'warning', 'danger' or '' - ), - previous_dnrp=widgets.ToggleButtons( - options=[f"{x:.2f}" for x in depth_nonreturn_prob_kernel.support], - description="Prev DNR Prob:", - disabled=False, - button_style="", # 'success', 'info', 'warning', 'danger' or '' - ), - latent_depth=widgets.FloatSlider( - value=observed_rgbd_for_point[3], - min=-1.0, - max=1.0, - step=0.01, - description="Latent Depth:", - disabled=False, - continuous_update=False, - orientation="horizontal", - readout=True, - readout_format=".2f", - ), - previous_r=widgets.FloatSlider( - value=observed_rgbd_for_point[0], - min=0.0, - max=1.0, - step=0.01, - description="Previous R:", - disabled=False, - continuous_update=False, - orientation="horizontal", - readout=True, - readout_format=".2f", - ), - previous_g=widgets.FloatSlider( - value=observed_rgbd_for_point[1], - min=0.0, - max=1.0, - step=0.01, - description="Previous G:", - disabled=False, - continuous_update=False, - orientation="horizontal", - readout=True, - readout_format=".2f", - ), - previous_b=widgets.FloatSlider( - value=observed_rgbd_for_point[2], - min=0.0, - max=1.0, - step=0.01, - description="Previous B:", - disabled=False, - continuous_update=False, - orientation="horizontal", - readout=True, - readout_format=".2f", - ), color_scale=widgets.FloatSlider( value=color_scale_kernel.support.min(), min=color_scale_kernel.support.min(), From e7775e3e5d39ae76937092606328a075c421dd76 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Sun, 15 Sep 2024 17:11:07 -0400 Subject: [PATCH 27/37] Fiddle with inference (#177) --- .../old_inference_algorithm.ipynb | 145 ++---------------- src/b3d/chisight/gen3d/inference_old.py | 4 +- src/b3d/chisight/gen3d/projection.py | 1 - src/b3d/utils.py | 4 +- 4 files changed, 21 insertions(+), 133 deletions(-) diff --git a/notebooks/bayes3d_paper/old_inference_algorithm.ipynb b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb index 0c201a52..b80edd63 100644 --- a/notebooks/bayes3d_paper/old_inference_algorithm.ipynb +++ b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb @@ -39,7 +39,7 @@ "source": [ "### Loading data ###\n", "b3d.reload(b3d.io.data_loader)\n", - "scene_id = 49\n", + "scene_id = 48\n", "FRAME_RATE = 50\n", "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", "print(f\"Scene {scene_id}\")\n", @@ -68,7 +68,7 @@ }, { "cell_type": "code", - "execution_count": 136, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -111,28 +111,19 @@ " resample_probability=0.05, support=jnp.array([0.01])\n", " ),\n", " \"image_kernel\": image_kernel.NoOcclusionPerVertexImageKernel(image_kernel.OldOcclusionPixelRGBDDistribution()),\n", - "}\n", - "\n" + "}" ] }, { "cell_type": "code", - "execution_count": 137, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-10053.277\n" - ] - } - ], + "outputs": [], "source": [ "\n", "T = 0\n", "b3d.rr_set_time(T)\n", - "OBJECT_INDEX = 2\n", + "OBJECT_INDEX = 0\n", "\n", "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", @@ -147,9 +138,9 @@ "# subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[:len(model_vertices) // 2]\n", "# model_vertices = model_vertices[subset]\n", "# model_colors = model_colors[subset]\n", - "mesh = meshes[OBJECT_INDEX]\n", - "model_vertices = mesh.vertices\n", - "model_colors = mesh.vertex_attributes\n", + "# mesh = meshes[OBJECT_INDEX]\n", + "# model_vertices = mesh.vertices\n", + "# model_colors = mesh.vertex_attributes\n", "\n", "hyperparams[\"intrinsics\"] = {\n", " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy,\n", @@ -200,12 +191,14 @@ }, { "cell_type": "code", - "execution_count": 138, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ - "import b3d.chisight.gen3d.inference_old as inference\n", + "import b3d.chisight.gen3d.inference as inference\n", + "import b3d.chisight.gen3d.inference_old as inference_old\n", "import b3d.chisight.gen3d.settings \n", + "b3d.reload(b3d.chisight.gen3d.inference)\n", "b3d.reload(b3d.chisight.gen3d.inference_old)\n", "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams\n", "import b3d.chisight.gen3d.visualization as viz\n", @@ -215,79 +208,6 @@ "b3d.reload(b3d.chisight.gen3d.image_kernel)" ] }, - { - "cell_type": "code", - "execution_count": 139, - "metadata": {}, - "outputs": [], - "source": [ - "# trace, _ = inference.update_vertex_attributes(key, trace, inference_hyperparams)\n", - "# b3d.chisight.gen3d.model.viz_trace(trace, 1,\n", - "# ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", - "# ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", - "# )\n", - "# choicemap_good = trace.get_choices()" - ] - }, - { - "cell_type": "code", - "execution_count": 140, - "metadata": {}, - "outputs": [], - "source": [ - "trace = trace.update(key, choicemap_good)[0]\n", - "b3d.chisight.gen3d.model.viz_trace(trace, 0,\n", - " ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", - " ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 141, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 49/49 [02:09<00:00, 2.65s/it]\n" - ] - } - ], - "source": [ - "for T in tqdm(range(len(all_data))):\n", - " trace = inference.advance_time(key, trace, all_data[T][\"rgbd\"])\n", - " trace = inference.inference_step(trace, key, inference_hyperparams)[0]\n", - " results[T] = trace\n", - "\n", - " b3d.chisight.gen3d.model.viz_trace(trace, T,\n", - " ground_truth_vertices=meshes[OBJECT_INDEX].vertices,\n", - " ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX] \n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array(0., dtype=float32)" - ] - }, - "execution_count": 84, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "vertex_index = 2426\n", - "trace.get_retval()[\"new_state\"][\"visibility_prob\"][vertex_index]" - ] - }, { "cell_type": "code", "execution_count": null, @@ -296,7 +216,7 @@ "source": [ "for T in tqdm(range(len(all_data))):\n", " trace = inference.advance_time(key, trace, all_data[T][\"rgbd\"])\n", - " trace = inference.inference_step(trace, key, inference_hyperparams)[0]\n", + " trace = inference_old.inference_step(trace, key, inference_hyperparams)[0]\n", " results[T] = trace\n", "\n", " b3d.chisight.gen3d.model.viz_trace(trace, T,\n", @@ -307,14 +227,12 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "T = 1\n", - "trace = inference.advance_time(key, trace, all_data[T][\"rgbd\"])\n", - "trace = inference.inference_step(trace, key, inference_hyperparams)[0]\n", - "b3d.chisight.gen3d.model.viz_trace(trace, T)" + "vertex_index = 2426\n", + "trace.get_retval()[\"new_state\"][\"visibility_prob\"][vertex_index]" ] }, { @@ -322,35 +240,6 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 72, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.54117644 0.37647057 0.2352941 0.9140787 ] [0.54117644 0.37647057 0.2352941 0.851 ]\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "a6a6bb735693451490d8a25f64893e94", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(FloatSlider(value=0.009999999776482582, continuous_update=False, description='Color Scal…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], "source": [ "b3d.reload(b3d.chisight.gen3d.visualization)\n", "import b3d.chisight.gen3d.visualization as viz\n", diff --git a/src/b3d/chisight/gen3d/inference_old.py b/src/b3d/chisight/gen3d/inference_old.py index 90e171f2..013a7508 100644 --- a/src/b3d/chisight/gen3d/inference_old.py +++ b/src/b3d/chisight/gen3d/inference_old.py @@ -104,7 +104,7 @@ def likelihood_scorer(color, visibility_prob): "colors": color_sweep[idx_color], "visibility_prob": visibility_values[idx_visibility], "depth_nonreturn_prob": dnrp, - "scores": scores_color_and_visibility, + # "scores": scores_color_and_visibility, } @@ -170,7 +170,7 @@ def update_all_get_score(key, trace, pose, inference_hyperparams): def inference_step(trace, key, inference_hyperparams): - number = 20000 + number = 10000 current_pose = trace.get_choices()["pose"] var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] for var, conc in var_conc: diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py index 7a40a327..ce151662 100644 --- a/src/b3d/chisight/gen3d/projection.py +++ b/src/b3d/chisight/gen3d/projection.py @@ -51,7 +51,6 @@ def from_points_and_intrinsics( intrinsics["cy"], ) - 0.5 - # ? (not sure if this is necessary) ?? ) image_height, image_width = ( diff --git a/src/b3d/utils.py b/src/b3d/utils.py index bee6f67c..3585df9a 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -133,8 +133,8 @@ def downsize_images(ims, k): @jax.jit def xyz_from_depth(z: rr.DepthImage, fx, fy, cx, cy): v, u = jnp.mgrid[: z.shape[0], : z.shape[1]] - x = (u - cx) / fx - y = (v - cy) / fy + x = (u + 0.5 - cx) / fx + y = (v + 0.5 - cy) / fy xyz = jnp.stack([x, y, jnp.ones_like(x)], axis=-1) * z[..., None] return xyz From 4b8e6feffd403338173b8dc35df1b8e8d7c77381 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Mon, 16 Sep 2024 13:59:21 -0400 Subject: [PATCH 28/37] Inference Move API (#178) --- .../old_inference_algorithm.ipynb | 237 ++++++++++-- .../bayes3d_paper/run_ycbv_evaluation.py | 75 ++-- .../gen3d/interactive_visualization.ipynb | 78 ++-- src/b3d/chisight/gen3d/image_kernel.py | 359 +++++++++--------- src/b3d/chisight/gen3d/inference_moves.py | 51 ++- src/b3d/chisight/gen3d/inference_old.py | 6 +- src/b3d/chisight/gen3d/model.py | 2 +- .../gen3d/pixel_kernels/pixel_rgbd_kernels.py | 131 +++++++ src/b3d/chisight/gen3d/settings.py | 20 +- src/b3d/chisight/gen3d/transition_kernels.py | 20 + src/b3d/chisight/gen3d/visualization.py | 59 ++- .../inference/test_full_inference_alg.py | 2 +- .../test_point_attribute_inferences.py | 51 +-- tests/gen3d/test_model.py | 2 +- 14 files changed, 760 insertions(+), 333 deletions(-) mode change 100644 => 100755 notebooks/bayes3d_paper/run_ycbv_evaluation.py diff --git a/notebooks/bayes3d_paper/old_inference_algorithm.ipynb b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb index b80edd63..78eb3652 100644 --- a/notebooks/bayes3d_paper/old_inference_algorithm.ipynb +++ b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb @@ -33,9 +33,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Scene 48\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 45/45 [00:05<00:00, 8.95it/s]\n" + ] + }, + { + "data": { + "image/jpeg": 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wGByeB9azQivaXLTRSymJXjRio2L8zY7+4oMiXFhHcW7iVRIGUkYwM81LBbR2luEjLRnIBOMkmo7iN4n86LaUYfvFJx5gx0HvV7sCd5pFuY0IVVYE5z1OKz5ZJJ2kDn93AOJF4LHuBVtVjmt4ik2yFhnDdc/0xS/LLAVeB3VWwoz1HrQgsJboyIWQB3YfePAU+lTQAhnMkarIOMr3FVoluioCLsbcSSxyPrVtItjMQcqe3fNEgKhvLmORS8JaJ2ADIPu/WrTAlmMgyM7Vx1GabKpdQ2xyFP3f71LKN8RiQ8kjJNDsIr2ly3mCB0PAxuAwvHbFSu8U0LruURowyAMYwc/lUM8I86MiJhFykhzgj0OfSq0kkbPujJa4KFNich8HB5p2Td0BdEgE6Mm10mYkk/w4Hai8CfKm5VZ2D5PfHbNZl2Z0jsNkMmPm8z5eB/vVYmBlihePAiYbmUDkYp8qutRGklwjBRuG8ru2rzTLiVfscpb5QQQpIzz2qPy0lDbo5I9yAk9x7VFNIkVlHESN24bVI5IB/wD1VHKugxxkFvbRrCFaQkZL8ckdfrVm3jCwJGMFV6k+vXj8ar3sMlw6ITtQEMP94dKkDGS62lWKxpnLLjJpvVAW6KhkdooSwUk/3QM1IjFkDEHJGcVFhjqKrq05uGBAEY6ZHX8asUgCimM0m4bEUrjqWx/SjEm8NuG3uv8A9egB9FHbmkIz3I+lAACCMg8UtIq7FC5zj1paACiiigAooooA+VFYhQxwB3I709yTtGcgLkYHSoEY/ZlZjkk8+mKliVQ7EDlQQG/pXm2u9T1Wxp4ABJJHrUhYOAvQsB9BULvtjL7dzAdQaNzO5OPkIwKUW2NkuWYAkA49+lQS7QyqUyh5yvapwwTaF4BGOOgFRSKoXJZgKuWpJG8m1k8tNwLYbPWmkl42QAZB3fKM4pFwrj5jyR1HT3oU7bmRoxlmOGbPahboNtR0kku7y1RSki5YkcrSMPLCrK446YHAp29CWDZCsMHA5pjcBUwXXB5JzTV7k7GbuUthiB853MRTvlN3bkNkMroD+v8ASkcrvbapxnHNNDKNQ0/AxmYjnn+E0+gr2NyCQtaxg9NoHNShwQd3SqVi4eyU4JIdvxwasK+doxwcj0rGSvqbXuWNwx0qTcOACSPcVWVz0zn0p4YB1I5OPWnFrqHkWA2RyefSnxytbuXgkZGPp/hVcMSW6KPX1qzaRC7naMzIm1d7NJ0wD04prpYOomo+MIdIMUF1bmWVxkFDgY9TTbHXpr6CRoEjt0Zum4M1aTWNq0ZX7ZFhhglYiSPzFUZbWysrZ3SdZ5lABYwhGPuSOK6I30RnJlTxDYzX3hzwzNKTI91fum5j15NZPiy0Fz4i1Nrl2EJEceYyN2FA/wAK6G/mL/D3wVOGxs1qRCM9Pnb/AArndbkWTU72SRmYGdsgnOR6Vpdtq4vd5bPz/Qnh8fahoOiQadY2dvLBbJhJZwSx57geleiaPqtz/wAISmt6kIhcNbtdP5Ywu3GV/TFeP3KxXXkWUVoTJczpEhLc8kV6j42K2fhOHSrdSizvHaqg4wi8kfkK6IS5pX7HPJWVkS/BXTXbXn1ZiEEVs5lBHJMh3E59sCtT4L6r9vuvF2phF8+61FbmdnJB8pt5GPpk1X8F6uuieJG0aMxxxNo73Mm/gmQsNozn0/nWT8GdROma59jwxW6KhyT3wwGaKlRpqL/r+rl+z5otvtp956PrhR9e1ArgExx44OT8opfiKCfhbqZBxiyf+VL4k51+64B/0dFye3Wm/EJkX4W6kGYDNk4GeOccCuKr/F+79DRL91A+edD+HdzrXh+11WLU7KCCUNmOR/3oKsVPGOemah13wHNpGmPqFrfPdeRhnCwldg/vZz2qTSNVuI9JsLZb5bZEV8rHGHcnecDvjitS8tNUn0TUrp7vUpIFt2UI0TKrZ46FRXQlJSbk7r8iHScqatEk8P8AxJ1mCxgM1xJciGLymV/m8wf7WTzx3qSW8TSNWtdWsQEt7e6juVhiHAjbG9B7YJrz7T2ktQ4eGcN2AQ10+n3LyQiOaG58p4duPIcgHJ9B6VtWq88Em9UTh6M07qL1PbNS0rw+lxImk6xp+k3DsJmhvrrKyI4yCFJyvOarHRLu1t/MbV9JvnPHl2j5Yd88k+lcTqr22s/BiK3Oko+vW0yW/miA+cyq33s4yQVq1riRtdaZbWG2CberzTKhUKu3GCenXtXNVjQklp7z+X9fqdEVXg3F7ea1OjBwx3DI96WPC/XPcdKhe80932/b7XAxx5o4wKU3NiW2/wBoWp47zrXncjTukdVnbVE3y8ZXjOTS5AOBkswz0qP7TalsC8tW+ki8CnrJGWGy4hYccBxQnZbC1HgYyrjlThR6+9A5CjkHmniM5c71PbqOKb5Uo+bJPPHFTfQVhQSW4HtmlBDDA4amjAIH3c/jmhPvAbT1qr6gOySeAck4HNJhhhSAcjv2xSjG0fL3yQaRThgCp4PrxQ9FoFyS25uExyM14Ux232okYLfbJeM9Pmr3e3XbOo3KMnjjBxXg+FN9fbu93L/Ou3C9TkxOqRLgYbkZFfQHwHe+PwwtEms1igWab7PL5oPnLvOTgdMNuXn+7mvn4c54pIPtlqhis9SvLWInd5UM7KoP0Brugk99Dz5p9D7HSTUDIBJbWyp3K3DE/lsH86fKjzI0ckMbIexkPP6V8bebqR+9reoHH/Tdun501vtpDKurXpHqZm/xq/Zw/m/AhKR9kv8Aan+U28BX184g/wDoNMlhkkh2G1gbBBAMp7e+2vjV4J2GHvrlvrKeaibToWwXkd/99icUuSP8w9T7S8lpMGa3iBDbsLISM/kKscBeQAK+JF0m3xzvyTnIPT2pw0y3PA3/AF3mrVKHWX4f8Eep9pvNaKuxpYVX0LAVG2o2Kkj7daqfeRf8a+MTp1sFGFYnOOXIpW0u25+Vvxc/403TopXu/uFqfX99r+lWdjMRrWk2spVvLeedAgbHBI3DIz71hJ4wsTYp5/jfwwt3/EYZ41Xr/tSNXy4NMtFOdrNjsXNKdOtMjEOeP7xqo+zj/SJlSc3e59HzeNWi2lPGXheXbzg6hGN3twvFaa/ELw0bRJH8QaDaXLKdyrcrOFP1G3NfL/2G13Y8lM49KPsVqAMwp+VXOdKa+HbtoZQoSg21Ju/fU+iU8faPC48/4kWEi+iWIH6jNC/EXQl8QwXH/Cf2Z0pEIktPsw3O56fNtyAOv4V88C0tQT+4Tr6UG0gwd1unOc8Ue0g3qvwj/kEMPy7P8ZP82fVbfETwao58U6b+FwpqFviT4Gz8/iPTnYdy+f6V8sCxtmxmFPw4p32S1wQIE/LpWThS6XN7SPqRvip4HXr4ks/w3H+lR/8AC2fAgBP/AAkdvx/sP/8AE18vi2tiB+5UcemKebS2xxEvUcetHs6Xn+Ae8fTLfGDwEvXxFF+EEp/9lqJvjR8PlOD4gH4Wk5/9kr5rNvb42+Uu30xSiGED/VgDqQKXJSt1DU+k/wDhdPw+/wChhH/gJP8A/EUh+NXw/A41/P0tJ/8A4ivm7yYwTtUfNyfWlCKGJwvTjNUoUez+9f5BqfRTfHDwEo41aU/S1k/+JqCT47+BU+7eXb/7ts39cV8+bVyMIAf50vAPOM9xiny0f5X94O6PfH+P3gpQSp1GTAzhbcf1YVH/AMNBeDc48nVf/AdP/i68GwuTkDB7YoG1QcDg+lC9jty/iDi31PeD+0D4QBAFprBJ6Yt05/8AH6hb9obwvjKaVrRHvDGP/aleG5UZ9zS7ugwOfai1L+X8RWfc9qb9ofR8ZTw/qrD1Owf1qu37RNkD8vhi/I9TKo/pXjjMMZ4o8zA5PSk1T/l/ELPueut+0UCf3fhK4YYJ+a8C/wDslR/8NFTnG3waxyM86jj/ANpV5QX9COlAY5OeOPzo5af8oWZsoFZSOCuMAAZ/CpogwjA46ZqMEKuRyADnikhYKvI56c14XK7anrpkr5LjG0KO3qaRzlSMkruxgilJ5GF5OOaRmUH7xwSADTQajtvybQ3Qce9IQxQAkAHr60gGZOnPY1G5dBIcFmLdxzSvqJEPloJ8uzeg54+tTbyJAwLb+5A601HJJJYEKeBt607dIdzFMHA4zirW2ggkbO5QCSWIJ9qaOXLZPQAA9BTXkkUqVQns2Wp7hidoPITOSadrkmXNnzCrDJDDNRTSbbqxyDgXIx35xVi4UCc5IOV5wcc1TuGJSE5I8udWx79P61orbB1Rr2rn7PtIwwkcHPB65qwG+cHgDJzntVSAhVlO7PzkZqbn5WIzzg47muZK10aIscgghwSB1AqQEMDheQKro2DgYxj1zUgIHzAnJIPWr0Wgk9CdTwNoBzzTrLUo7fUpGlhdLRYjvuT91SD0xUIzu6gA+9IUkuLW4sVjD+fGy8tjHOc1cF76TFKTZoa3Hf3JtprC6uEjAP8AqQPmY9N3tW5rENufhhd3pt4/tothmUdmBAY/zqhLKkUZ3ugVABgP6CsXUPGMQ0ebw7CqyLOrLJLuztDV0pNu72RMpJLfUpy3/wDxa7w2mfkt9acgd+5/rWHqt0W+2MG+YybiD1BzT2Yf8IBdWpcbrTUBKg7kMAM1m358y4njy25sHJ9+atRS2MZSeyNfwHbPq3jbT1bHl2m65fcf7o4/8e216H4id9T8X6XpwIKxRmVsf3nOBkfQGuc+EemtH/aeouoO4raxtnn1b/2Wta0vQNX8R6/wyWccmznIby1wv/j2a0pIhtrc5+01trj4n6rIv8Ra0iwONqYUfntz+Na/w1nEvjqW35JgiEqqDg7lfp+tcH4Ln8vxRbySsSrHe/PU5/8Ar11/gMy6d8anttpKzSTRgNxkfeH8qh6yuOE7RVz0TxP4lvtJRJYrN72e781mld8LEFPAJ6e34Vt6T498KXHguA+ItUs7m4MX+k2syBzu6bfLx/nvT3iiAuLd4opYw5DRumVJzyMGvKPiN4Ts4fGN8ukxRWaCGGYxKMICwOcfiM/nWV/38r7nfGEJ0lBrzv8A16m3r/xEn0zUp7TwfZaFaWCkeXc2lqu5sgE57dcjp2rDT4l+IWZjez3OoSHJ8svsjX3wg/wrin067hP7y6Ij56c/pUBFzDwLtwCM8cA1VZzqytHRdjvozo0o2Ude+jOmPjnVd7vHZ2qyOxYsYN7En3bNV38beJjgDULtCOAsWEH5AVz4ubtXyt049OaDfXuf+PiTP+9XO6Ukzd4hPv8AcjXl8TeIbmU773UnOMjMzVUm1rV7uPy5Jr2QnqGdmB/Cqa3+okEpcTcDJwxpq61qauGW9uAw77zmlyOxlLEpbyf3IlX7erhvs9xnsDGTn9KBb37dLG5JHXETf4ULrusyKc6nc/KM8ynmozruskYOpXf/AH9NCh6ESxPW7+7/AIJdi0rW7lPNi0q/dBxuWBsfnitSHwV4rmcBNImz1xJIqcfia5p9Z1l0MbanebG4K+ccGq7zXrj57qdgf7zk1rGnBrUx+t1L6XPQrf4deMMgPBaWqt1ebUY1wPoGzW5B4X1OycC8+I3h6yYYBjGo7yB9GxzXjypKwPzNx15rovBdpb3HjPSI7tVliabDpIoKkYPBz1rejGjf3l9xNTEV5K6/E920/RPD8GmPLceM11S5ZC0bwSxqufTaue/qay7YzNawtcLiUoDIo5Gf/wBdRzSWtrdzrHZSwQrIct9nZEHv0xUsM8dxCJYJFdDkqVOc15+JcXKyVrERUrOUne5MNu8NjryRQowBkkqSScdaQlt3HU9ttOACsMcD39awurBuSQFRNGRwA3SvCHIW+1DH3heSjr/tV7xB/r0JI+U5rwWQH+0tTyBxeS/zrrwq1Zy4nZD8EbvlPynrmo2uoI22tKinOD83NPGAoLZyfSvZfgz4f8M6x8NmutS0KwvbuO5lSSWe2V3PQj5iM4wa7rPocLaR4sL615/fJ7fNQdQtiAfPUcetfVw8BeEGjWb/AIRfRlVkGR9iQYH5VGvgbwihZYfDGmApwrG0VifzFNbiuup8oi/td+5pRk8dD0oOqWgyBJnB7Ka+rk8K+HLe68+Lw7pQYD94Pssf+HGKtxeHNDima4sdC0vkEuEtkBYn3xxSd+hV49z5HTVbTn52znj5TQuq2oPMhHvsNfXkNno8Nsg/smzidQVx9nT5T+VMt7KwhaS2SztkES5KtCPmHUnpVK/UTaex8ijVLQn7xJznhDR/a9t/eY57bTX1+NMa4t4ltUgtYgyklYlyy9T27jir9tbQ24EIgAjBJBKdOeKL6CvY+MF1RJB8kEzgcEqmalFzLIG8uxvHC9SsROK+0ZQyRFYQVPXhRiiISIjeYyE9cgYzVc/UVz4zj+3TNiLSdSkPbFuxqWK01eUb4vD+rOO5S0c/0r6/ubxreJXEagOMllbJz+VZq64rKdqS/L8uAwGaWrQOR8qmx1wYJ8OaxtbjP2N+f0pRpfiFpCg8M61vxkgWUmR+lfWEtzq/2uGIWa/Z/OUPIzAnbxk8VF9qnbVL0AktD9xV7jg0LmFzHywdF8SiWSP/AIRjWFeNcsDavkZ9sU+Pw34ullWJPCmrFjnAe2ZM/mK+nxdjz2u5WljS427QOxX0PTFaMuqxpcSW8ZeWdCAQIzxnnr9Kq0kgU0j5XXwh40ebyE8KX288YbA9+9Wv+FffEFunhacfWaMf1r6cl867QJHOkUse1mfHr2o1K8lttPFxG2dv3l7k9B/WhXbsDZ8xv8PfiBEiO/hdwG4H+kRZ/LdxQvw5+IkhCr4XcBuRunjH55avpppxLMjgMVXG0E9Scc1bW5YA+cdpxxjvRZoOY+YR8L/iOpUnw/EN3P8Ax8x8fk9Tx/CT4ikEjSbOME9GukJH5NX0b9vke3jnC8vMVjGeSuKSfUprM2sJi86RyPNKt9wE0e83ohXPnpfg18QXkCtBpajH32uOB+XNOX4K+P3ADDSFPq07f0FfS5f59pU4JwD6mq1vcpMJ/Kbdscgv9O1TztgfOX/CkvH20gyaOAP+m7f/ABNO/wCFHePPKDG80jIOAglc4Hr9yvogu89wEWQFVbcQOo9qsykLB8rEbemO/tSbasNSPnaL4C+MXwZdY0tDnOFLH/2WpH+AvilRubxBp+AcA7G/wr6DjkWSVjG4EaDnjg/jVWVQjxiZAyTYBbdwrDpgVoqje4nI8KX4BeIiC03iWzjQHqIWNSf8M/6n9pETeLYMDlsWpJHpxu/rXvWFdfs247wuT+dOlhMhYYG0gexJB9annC7toeEx/s7zyhvM8Z/MGxiOz4/9Gdas/wDDOg8o7fF9yX55+zcf+h17SLNAwJwHPPAqYhmmAyQgHbuaHUfT8hK58pxlQDsO4D+/1piS+YcHnjBOKcAGfAcNnkcYwaYjgsQ7MdqnJFeMmeq7dBwbaiFWJHfPGKmDgLtJ3j+tQDMnTBXA4PpUokGdmSuD3GKd3oFhSu5XAbHcc96aqs/+sYZxtIz/AFpQN0gJOVHXHekZxzuABAxQG+4kpIyQRtXgYPWo8hSXPr9eKk+ZyVxxwTxQWdmIZQATkAegqlcV+wkkXPl5Vtw3cHpUUyr5rszSKSoG0dKlwy7mJwD12nGaiZnMm7fgYyR13U9kC0KN0mJAApzjqD1FUbxlFnK2fukED8a0L9jldhCj2FZt8f8AQ7jI/wCWeQRWkdXoK7Wprx7QzrgBThuDkjipScDIfaB2A61WicmY7sEGNO3tU29X2gkjAycVi423GicP85O3rzT1IyGHQj86gRzuViSeOOKkQnoDhQOMDoarqOxOuMH86f8AbotMK3UucLkD39qgaXykMjHhQc+9ZlhD/blx595k2yybI48/fYetVBJ+89kQ29kU7Ro9Z1C4FvsihaYzTRM2C4J55NY91YBtRuvsJUwo5AJkH49etej3GkaaWBfTbZ3YAlmjGSax9TfRtNQD7HZ+YTtUJEDk/hXbCoo62uYSg7anN73NrcW+QfPjBIDZ5H/16zZ70MysAS4UA7u5Arfjjtr9l82eO3Xd+7jixux7jtWRLok7X4todr+ZMIo3z94k8VbtdtCalskes+EYv+Ee+GyXcqqjvHJdkk9Sw+T8xtrntbdtK+GSo2Fn1CdI3OfT52OfqAPxrqfFO2z0Gw0m2AKySRWwBbgIo5/lXHfEj95qGk6Um1Rb2pmYnjLO3T8lH50KSSbYNN+6jlvDbmHxDanAdSCMfQZ/pXa+ML5tN17RfEds7LE7JMAvYocMuR7GuJtbC80+4t75tvlRSq2fMHTPpXomkW1hIdX0XxDa288MDbrLD5KFsnHynI7cmlCpGzdwVOV7bHqiTR3du1zGdyTp5g54IODXG/EN418YurZDSWMITnjI3Vv+HIoYPDMMNqVMUSsiYYtgA9M1yvxRmWHxpDu43WEGWJ46yCubnviLHo0k+Ven+RwV4cO3zMcHv71TlcDaVKDaxwpXP5+1XLw4lb5QcgAkHrWZLk5BPGa1a1OuCTIWJD/LgdenvTSpI3jGOhpSxP4elIxIOBnHvU81tS7DYyyhiGxgY+tQsCCDwc+9TRyFGJGQahOM8VnKWhEkJg9fWlYlh16cD6UZpKnmJsLtGxTnk54pQpYqFyWJwAKVULKWGOPU0Z6Y4xQ2NRAL3rp/A8Ec3jfRDIR8k+8jH90bh/Kua4IwCcV0Pg9pYvFGnSpwCzrn1+U1dOXvWXkXKKUHc9Cn/aC1S1vnhvNAtvJ6eUd6sR9TkdPatXRvEHhf4gSj+xIxo3iLazfYnP7u5UDJC4wpOOc4B65BAyMnxPoNv4i8OSI0Qa+gh32sgGGJAzt/GvDrWWa2uEkhleKaJg6SIdrKQcggjoa0VaFZNTijypx5Je5ofRqnPyuroyna8bj5lYdjS9vu4OKq6VrcXinSINYCFJ5BsuV/6argMfx6/jVonJHOP615s6fJJxOuLutSa3x50bMDkmvBpB/xMtTG4Z+2SgD/AIFXvNsVNxGDnnGK8GkJGp6ntOCbyTj0+aurC9TkxXQf0IJJwVx06V7/APAGJP8AhV4zgB72Utz1+6P6V4BnPGcHHWvdvglPIPhfZRRJ8zX8oIx98dT/AE/Ku2Gt/wCux58j1J5miun3ugh2gBcHOajivmkwqREsDnHQAf41mXqn+1oxCzI/m5z1UnH9Km06RbQTS3NyWleQqx28Lzx0q7aCRctx5Jml8vCSynoO1OYwQQIYnVN7AgnocUlq0V1GDBcFWV8so5APcDNLMHljSGUhWyMnghqXUCG6tvtdtJEsiJLu3hiOMZzmoEvokjdJrjzbdjh5Gz3HY9xU/lyeRJhEjbBUjPDIaeLaCe2NlCVESKOAM7OegqugWIrJpbdTGsBCJwu7qfTB+laADux/eSAEZAIHFULK7m8tluFPnJwI2XbjHcnvkVdgE7RgvIDleCPU+tKegDUvUlYxxEyvgklVwB+JouLkxgZjDNkADvz1pCy26EjbAueuMhvc1Dd3bCW28kAxyE/MQQRSS1CxBeEmNSiBfKJO0nJIPoKowzsbK/EgxcRqmXZBjn0xU5tM3RFvcNChjJ3A5DHPfPSh7KaK3mJuUWL5TJvX+H2NaK1rCt1FG2SGwSC9kYwXK7yQV3g/w/rVaOJl1bULtJAzvuSMZ4DZx/SrMMYS0BtW82ViGRm/vZ681SmDPJbSXLBIkkYOo/iOM8/jTVle5PmWo7WQWMFuSrBFIb584yfWpA88OpyqVQrIm4ynAxgdaZNZyvp1mhR/NDNIEVeQM/8A1xUYgjluJTIzj90VBXJz0zQmmrjsSEmGOaRY3IJBUr0yR941J5iXUMMM6OCRw+eHPpUEt7PEblbe4U28UfyjAwCB61Itzdyx2UMKwgTRh/OPOeMnApsZJI8UEmfLIO75VT5ifw7VDcTTx6dd3GxopGYCFZBk47gUlpJ9puJufmWTllOMr6+1MtL03N83mIRCg2pubPfk/Wm0xF+GSG3soBGhKyAn5+SPWqt2kv2u1a2UgzsqvwOFB5NPu3t4rGCeV5lV5CgEYzjJP6cVlXVpFea/pksWuRiW2kQGEoQWGc7Rz1PNSvINiSQs/wAREUu+wAYQMcFhHnOOnQ1PoUjNaXh3EJ5zMQ3Bwecir0enWy67PqUpi89W+TZIScbAp3Dsap6Ro15a2l8LoqjzyAoFOdqg5/rTvFx+SG2T3c93Zabcz20cYmZ0MZk5GGIzn8KtR3866PFczNEZnODt+7nngflUGt2gv7KWNxOY2kj2+UMkY7/Tmql9ZT3ehafZWh2b7j53YYIUbifx4FRo43fcXoWPt0tgipIY2EnJ46VYvZYjZ25nTBZM4x0PHSs25mP2yxRU80shDOR8uB1PtWhqfmSTQbfmGP4fTIq+XVEl6G3NvDAFPzjhsnrmpPtEcchjchX4J9KV4vNlV2JCoQVHv60kjxvIIOGZuWA7AVhe+5RKARgdcd+9QxnbdPGv3QoZs9ye9PfeYnEbEt0BPalWNfPZ+rYA61IHyeNxi3YzzgcdaYCy5bp9BSR7sKjljzjGamcbDhV6+9eWeqwVFJO8HJXAwablxkZDYwCRS7jvQhyBjnvzTnLexPtxTbsFrDiGCEKepwDURzglmIb1/pUgJxsOOBn3pjBQdp7c0PsGwj7/ADItu3k/NzzinSFUlTBG/lQMYJpG4IPfAxxTZAkhRn5ZeVY8YpppaBbqObKQscO5Kk7QtRMApEqAncgGP/rVK0hRACzDA3YXmq7kRoZEWRVXkYGCaq2lhWW5WvVEalduSDng9zVC4Ba1ljzyUIxWjfgeUHzuHXjjFUGwyPyPumrjpsJ2ZZtDuEJOSfIXn14q0DlsADOPXNUbAAwW4B6x4P4VcAHT2xWc21Iq9iVGPJJ6cD2qRcDOC23P3sdahHJxTwM4GM4HOKqKuJtFDWJTcyW2mRsVaZhuI/u/5FbVsscLWyxosaRkYGeBWFKxbxraJjjy+Ae3ymp9SvpCv2aDZwCHk7IPer5eaKiiOZK7L2ta1LLcjT9MUM+3bI56D8a5+8sNOgdPtd27SAAgIcsfb0/Gr2m2dw8YECFLcHLSN8rSt7ZrAtY3GvMZ4dio5d0bnb1I+vaupWZhJtyXMX7FZNSv103SrGOOVxw7nlR1JJruNL8F21tqlpdXOrtcS25Eq24jwN47lu4z2rkfCiS/8JinzhRcK4Yr1C9f6V7F5FraxW1vAihurORknPqad256FpWTuc3rUjX3iy0tA4ItoTIQP77nABH0BrXudN8N6lqly0/g3ULyZdqtcpFNtfAA4xx27VneFon1bxhdXmVaM3RAP+zGuAfzzXtOmzSmIDdnn9KzxU/c5YuxrQbj7yPGNS8LeEb2IRtpmqaPt6jayAgc/wAYNddr3hbw18TITe2dtDb63B0VX2CZR2YgDt0PUcdq7rVZpVU7SG9iM1PpNjZS2/ni1hSbP+ujQKx/Ec1nhHZNSYYiXNBT6nmfg61jtPBwtoI3gSN5Mxu24rluRn61zPxfCf8ACSQy7/m/s+AIoHOS8lddoKPBpNzFKzOY7iaMsRywDnk/WuT+MEDv4gtHReP7KjJPqQ78D86bjbE2Xc6KMvdizzyR2cZOBhQKqSMCxPJp9rK0paPbnaM4pspMhLcgdgDWkpdUd0UV+gIHApCh5OD8vX2pxJ5HQe9IWXy8DO7qTWbtfUsjB+VuajPPpUi9yM471ERiov2MpbBS9BSU6MgSLkgc9SMgUhIQEY6U/tSdzjkUvYUPsXFDlyK2vDJI8RWGGAO5sZ7fKaxAea2PDR/4qOyIGeWOP+AmlD4kW3+7Z7NaMq+VuAztAH5V4B4isTpniS/tCu0JM20DsvVf0Ir3uI5iiBPO1eMe1eP/ABMRYvG1w68CSONz/wB8Af0pUf4jPMrr3dTpvhZcu9vqlkzkooSZF9DyCf5flXoAG7PY+46V5f8AC12XxDdLk4azY/iGWvTQx2jOWx2zWNaKTv3OhliDHnKB1z3rwecY1XUxk4F7Ln3+avd7cnz1YAdcnNeFXH/IV1Ug/wDL7LjH+9W+Gum7nFilohQeAdvavfPgFFG/w4t5JIgHjvJhE5PXOM4/WvA/xBGOcivffgIwb4Zwxunyfa5fm7da7orc4JPud0YEOtySSptUDPPPJ7/pTXiaITsk+wBwwi2ZyT6+lOlvmaSTYxMJ4WUp/qWB756iqcIP2p4pZJS0/wAzOeVIHvV6hYuWrvIUkOz5iNrRkYarrSSS2rSLEqsi8KecNnHasn7JPc3WIY/Lhh+USA/e9xWjZSRTukrzEzR5UsDgPjrkUN9RWHRlJIT9pABjxuZDn8OKqXFy63kMkbsLVXHyRjknHXHetZvMQfukXO/5gO4qlkwX+x7YmIkkOOg47ChO4IpWt+IbpJJZi0TsVzs/iJ7+laly0hicLEW2tgIWCg++apyKbqRI1hSB2f8AeRtzkDkH61psysrh+xAYdePpRJrTQLmZK0LOC4Zl2LuTdlEOassWeSHYowqlmIOSRxwKryQukAS0Ae3Zt5dsYjGemD1FXPLS4tovKYCM4Ksg5xnPXtQ2hERMc4jxGYxICwRl2seOhFZksEN3tJmWJB92I8EmrJae1u768niO3axjLAHGMAD2qFopp72ydIGBU5dwvy8D1qo3sBBJBJFPEYgrwkZI3Z5Hue9WLOKOO0ikSFZPMYySeaAec8EU944FgWOcK4BZsDg59fpRaeXdW/l+SVSIYU5zuXPUUwduhLeaibe7lYNHhIcqSM57nmk0h0k09bNkVJjEHYdQwbnP61IrQ2FmqpsaVgxXA/ix6VT0+0mWKG8a5Mm8Y2on3gTzknpStG1hEE6MLW1tBbl7aTEsxXqRnhR/U1qvHZvcQW7QSB41KxqqkLGCOeRxU0k6RJIqhQYyFQEeuKa0he3nYZMg4BxjbxxSu3qNWK9tb2drNG1odq/ccEH8P1qaTS1dUUzYK8EhQCaNPiksraOCRlYn5i3JJzSyR2yXPmkIMgjBH8XrQ276MRBqmim9t7SGGQIkEoZg2TuXnI+tRnSJ11OKaPYIFlDbQecAY5981bgeSS3lkiAQsRtIHBA+tWomfZukI69+MUryXUZi3OkudWe8O/AJMYjXnOO9WrZpLWFTPPJJczH5VYZAyegrS84ZYKQSvXnHbNZ/mu155jRKixrtVc5yT3FNSclZ9CWrDmuGe6mVJTEkWEXC5DMai1G4kttPijuJ186RipCj7456fhirss3kQIFI3McDeOvrxWZJp8ctx9okLSzt93ccCMfSiKTBsR1UTW8yMFO0IsbD+H1NX5mg+0pH5O89M+n0pgiSeUBWwIjks3OKsPAZJ1k3AxqMAKapyQWJ1ZjHkJg9gahhjW2L5JZ5DuOB1pyvOzkNDsAPB3A5+tNhkLysgOPLPz5HtxisgJEctJhk2nGQD2qIIkt5MrKpACnIPOeev5VMXCyOTwFUZNULO4jEsmF/eTPnIHAHbNCT1aB26nyzY+Z5WFfLdNxPJ/GpplBxubBAB6VFaqVABXHpn0qeUAjkNgjkA15V7nq76kAySGKjjHT+dL53l5Xad3QEc4qRclQyjCgY2n0pq7g259qEnk54o3eoJjI1jMqsCVYrgEcHFPJ6nYxX1zTfIikkDMAWUEqwOKdvC91wRgEHOKaasNrUXfgHgnHTjFIWB3HA2gd+1LgswQt05xTJGU5A528cDNCi+pOxHG5Jfao93zwBUc8jAxrGmSwyd3H41MruqHG0E9P/AK9MAOM+YCw4xVKzWgXILoN9nbgcYyRziqKgM+CvQZz61oTMsdvIBycZyfc1moxDbR0z+laReliR+mtusoMHgOwBP1NXSSWHyrx1rO04/wCiRqMllndeDx+NXxuyARyeoHNS17zSHF3VyVMAHbjPQipFbHU/XmoEbg4P4GpQd4Az+XFShvUoatbzLqVlqMDYdflc5Hyj1/U1QW4jvLz7PtZ/OIULnlmJxk1c1uG8mQNEQlsiZdt2D/8AXqvJokCQW6WuoSx6r5IkNqY23Mx5AVh3xzXTTty3vqYyum7LQ7HToSIbqB5ATbytECw/LH51wQWa1ub77SZvNWPanm8kgnr/AFr0C5YWmizRtLskMUYkx955MDP45rlNQYyXEEeCQc/LjuPrVp3dy+R3VzR8EaZfarrunXUDRbINyS7jg9D/AIivRdRvBaWN5dOV/cRMAegyBwK5b4d4stUucfdWUvjrk7RmtXxRMTp9vahwDe3aocjqoO5v0FVCzbZElaJrfD60lg04zuxWYQqCy9STy1ehaeHMZAuZhzgYxXN+H4Ps+ixcjdIzOB0wO1dLphwqqecnqK58V2R00PgbEv1uChIvpi2eSwXgflVnTNYawitbd4HmE84iMm4DZnvj0qK/ACnJ3CqiwvLBbFNgCXqcHOeo5rHDScdv61LqwjKnqU77Sn0PUry284TxXbSXUfy7SgLcqfWuK+MIYSWswJwdMUDHs5/xr0nxcG/tqAq2P9EYcj/arzn4zD/RdIkw3z2TJjtwwNdCTeJvcmg+aEPn+TPHLMs0r4JJ25NSMBnGcAevaorMFrjCttyvJNSynLGqjsehEic4UBSSO4prLkE7cYHJFO9cU3eVyBk7hyD0pSjqURjvTMnnHepFDc8HAGTxUXSs9bGchenFKVIzntTaOg60kSKKcM4pop2eaTLiOA+UnjrjrW14VG/xNp69cuwx/wABNYv1rc8HYHjDTCRkb24zj+E06fxJFS+BnrsWZBEOjEKNteM+PZxqPjO7MeW2MIRx3UAH9c17ELqKy057+fKw28HmtjrgDp9a8FEj3uqy3bEnc5kf6nJqKOknNnDUjzNQ7s7/AOGNvu1TUbrdxDAIseu4/wD2NehqCeB1HXNc34DsfsvhYSMpWS7lMgyMHaMAfyz+NdIPmjznr3FY1ZOUrG1R62JbfPnqeMZxmvC7kf8AE41QZxtv5f8A0KvdYCBLGMdxnPWvDbn/AJDOrf8AX/N/6FW+G3OHFapDTgE/LwRxXvPwJYR/Ct5ArErcyng9eleDDHPI/Kvevgg7R/CBn8svi5m2rnryP613rS5wS1O8nuLpBbzSouHGBFnCtkZ5+lRWULzhpkikSNiMxF9y+4XPaqts73Fvc+ap3zBfMHmZ+XGBtHYVY8q5htTLaFnCgDAOMY9jWnmCL9iVk/cM5CjOwLxjnkGo4YpG1HYI/KK4Z+4/D60lnfgRWrSxKGfILFgTGT1PuK0mRmjOUEhC/K4OCc9eal6MLkd7LNDb+aixiTeMZJxj3/WoBcvcOpML/J83/wBYUo3z2MscjE5X5VPUEdqhg3x29s8h+zrvyY8ZyB0FNLQRbkiEzxTmJhk4dcc+35VIghjXqDuOF3Nkk+nvQJljkVSr5mPUcgHFVrpIo5YjxHIz7VK9u3A96SV2IlSPJlG9o0lwqjHIwOaZZSLCv2Qo/mRHnA+Xn09aXcP3aQM2WJYuTnJp9yqTmCCSV4pGG5WThiQOQKfqBSmH2mwv4zch4WwqM3AHtTraZ9OtBFK4lnJG1B2XgDNLGVkCWqsJBtLJKf42BxyPaq99A81/9ojMUYICl853Y/z+lUo3dmLoT3VoGvPNddyspAAbsB0/nVfT7/Y0sjv5cEMeEgC5+Xsc/hSi8BaS22hSsZaOTOQT0JpmjN9msTHI0csjPmFW/iB7fzp201A0CYnsDOjlJJIjIpGOOM4zUFnG32a1E+/aAHVRzz68fWnl441MWREpTb5ZH+rJ7j2qOEXcbQq80SiPAJH8aetCWgFgTusbGSB5WLkcD3prJdRSCbHlxluY0OePU0hubXUHgSNZjksflO3A9/rQEkuIJoZXMQLqOGyQAfX3pbCJo7gF33tuVDknB4AqGMMgdnjAVmyjHuT61YQtbwFEwy/wOR396glnaQRoylpFGSFHJPrj0oWr0Hsi5uQMm/YMLnr0NVrkMy+dNlEjBbah61LOkESfvsBG5LEc59zVOe5t54hGJiqA/M+w8jtSiuqAWd2neNQcbh5jDGD04H61HJJb2o+9uJOFDNgk1Vvdak86NLKHzN8nl524L8cYz2qCGzAm827JaUk7kVu+e1XFPQTZct5nlvVuLrEYA+WM5Pl//rpxb7TdybSDuOd/UAD0NOnW4dAkNuwWTgupyPp61OYUt2hhjVlwoDHbgNT0BIJ1hcqkEOVLfM4OAfUVZlhKjcoGFI8tVH86hVTOMyt5JVjsVT+tMkuZlnSNB820BWZh8x+lZ6vYZKHIUCF5DI3LZwfr1qOOWbDSpjEhJdnHTA44p0KgJ+7uo1kx82ACM5pYnMcEysctvwSDnAPSmCK32h/spYy+bNccCPoV/wD1Vo2pjjjEaqFAAGe5NUrWxWG4aVpCz5zlh0+lTTbgq75cuW6LwcUNJuyJ8z5aUMk8sRYfu5GBPrzU5GOODkdhmoXYJqNyW5USk4Uc4qYEhC45yD8o614yWt2expYrKdkZhIJHIP40oJyy5ZsDuM0sjYfAA+brSlQ7DhlGc/LQ73uSMYb1+XCkjO4jkH3FJIbeP75yCeNopGjydxBXnnJ5xShY8jIViD3FNJvQEluRb0JIRsOMZBz0pyKBk4x2DA9qkDAgFiODjK0mX3kFVxuIz7etC+ELiBuVLENk/SoyQXcHsc4p3yYMasN2MjPX6UIu4glG3D7wzQiUluQzbWhYAjeOox2rMUgZ65zWrMUYOwU7sfMRyKycYPzEDJzW1PazFcSyx5coyf8Aj5Jx2wavk4OB0B4NZ9sfnudpxiRWx65q+zKSO3PSpm7MpbEikkNz0HFSxHOeeQO9V+CwJ6g1MgyeeD0+tJKTAfBpja7JcWaXSQrAEaVmGSQegA/CuqSx0CSRb+B3mu0UQ/a0YFiwGMnnAOOOKwvDGxdf1WLIJe3icfhwafosUkHhe9FqIzLFPI0a9Mntmt4QdrERmTXnh63uLx54p7oJITuDStw3fHtXMSWv2bWmtnkaZbY7txz1PNdjFH4idIvPgjjkYchZBgH865KN5JL/AFKaRizPIY8D1Bq4RS1HeydjpvBsYjvLho4jH5i7iCT19a0tSL3viuC0Qgra2u7H/TRyAP0B/OovCFpdJLcy3QUnaqIVPHHWrPhZP7S8QX+oOPkN2wTBzlYxtH5mtqS79zGerseixRJBBHCpxsQKPyrT0viMc9TnbjpWduLAM/DY71f0w/OSQcbux6VxYjV8zO6kvdLF7sCMRggcAY6VWibdYNtJYpdwk4/3xU98uVOeM1mf2Hca7BJa2Or3GmXAIdZYVDAleRuU8EZ7VjhU3IqpJRp3Zp+LwP7Wtzt3YtmyPT5hXnvxmiL6N4fkDdYpVOfTCmtrRdS13VtHguPETW8l4FkiV4F2+YitjcwHG7IPQD6Vk/GQF/DHh4qP4Z+fQbBXZJOGIt2MsMmoxXr+TPE7Mn7UOQNykVI/LALnrUFuxFwhBwQeKsTKS4APr260ou+56MdGQHvjvTCTjBNO+93ximnryaTsW7jQTzUZNSYx6Uw9ahmUthOlLxScd6PrSJFHWl7Ug60vBOaRSHda6XwRbibxbpmSc73GP+AGuZyc5rp/Bl7FYeJrCeZdyLJjHuQQP1NK9mjopQU7ryL3jrxTEdOi0PT2ZzGf9JkA6sDjZ7885rn/AA7oE+p3sdpGp3OQ08i8iNOuSfWtOLQkvNduv7Ozcy+c5e5uAY4IDnPDDv169fSuv02XSPDlgLaCaWaaQ5mlh2kse3PoKU5Rp+6ThsHVqNygrv8ABevmdIfLt1jjhULGiqiKp+6BxStJtU4V8DuVOPzxXNTeJAIiLazikUDlp1Bb8cGsm61m48iS4luZY4wQCkRPfvjNcbqq/qelTyKq1z1pcqPRtJt31W6nSG4td1uocqr7y3fA4rwm4ctreqt0/wBOlOO/LV0Hhvxqtn4psXiiEIaTY0mXPB6kjPNZmvWb2Xi3WIpVCebctPGB02Ody/oRxXfho2VpRszwM0o0Yvmw0+aK/D+tLFMDoSB789a91+Cwkl+FNpGqjaLuYtkcMN1eEg5OO45r3P4IiVvhYrTORbJdSFQoBJ5/xrvgtTxGdpZaetvP5sca28cSkDONox34q9YSQPZSukkhQMWfd1aqa3EoFostqoOzdIZMgAE0+2uzIjLZROrGQ4KjKsorSwlexqrDE0y3ChBbNH8nychjVSxivNNsgs02IlfnJyeT2Pf6UWUciWyStcNKPMZAWJwB9PqOtTwXTXEEh1BIsRt8hUHBx35qbW21Gx032eabzIJFjm3YfcuC49M0T5sZC8avIzcAFhjnvjr2qp5Kssks9tsB43PJtXHr9auX0Udym5p5FAxtZUyT34Ip2s7XIXmXHO8yeW+xlILHGSeP0rMvovLgtztKyIRtXd1IOeKtW4dsQyTHJTO/GGf3qrqEkRV0uQzD7qsvXpyaUVZ2GyeDzZI0E1uI037mZ3H5DFRX0tywiuIUUusuI4yf9YPY9qr2kJurO32yhUjJQLuxk+nvV+2iChRIGYwOdvzZzmqaSbEPFtZ20vneWUlWJjwSdg6mseK8a5k80uzHGT8gyq9h+NX555IZfLeMMCCztuAJzxjFU4v+PCe2ihKeZkhy2GOO9EE9x6bDVvLL7NdFiDJCw8wFcNHnpx6GpYIp7SeSPzlaPO6NuuDjoKxYHc3bWskShrnGWI3K23p9DW5YNHLJJKSMqhVzjgY749a0kiNRtzdTzSrauUDkFtzRghh6e1Otb2KTS4ri5EUbrujXA4Lf4VRvnhs4neQSP9p+aNgxyo9MdqbbwBtNR4CdkbAtgZ3P1x/9ela6tsN7mhBMiXZjmR7VQD8o4UDFRQv5kzShoQj87ZGI2qD1P9KmuWivmSVPOjfIJymRs7/SrEVvb/YHgLI6Ej58cnnvSvZXYWIbVvL3vcRTbZOVIOVA9QavS3I2BYoy7mMMuQORQ8vzhzEDDGGA2sCDUVoktzJLdzREp/y7xnA+XH+etZy11Yl2KAtZvMuJLgvKv3lLPlV9yKbOLm8a2+ysSrc+WcAAA9TTnufLSdPId5nOEgU+p6D6VZdp7aZ547ZZUC/O5k27AB0xWt2tRWRNY2aqqy53l8tuZfu+w9KyrZzeSLbxLiQvuYuOAuetX11XNvDHFCfNYZcA4EY+tRWamO4NtDG8LSEsZc7yOM1K5ldsZfD3FveLF5sbQlQFDDBBHaltLma6urnITyIn2KQc5OATVWysikk0N2y3AjbKux555qTR4Y5LZbwwGKSVmYDkYBPHH0rOXLbzGrlu82mIjYzuOVCjkH+lZMtzY3F3E8Eg85W+ffkAcda1mvLaKYxhszE8oi5YnHGR9PWqH2OS6ul+0wRKAm4ovU88ZPeiGm4pMZZ2Fu3mLBdbmRs71AOPrU08U1tBiaSN4CwDM3BGT/jTjbxTzzQxDy0EeH2rgZz/APrqlfwx2htbOFWLTyqWJbIAB5/nVr3pbk82hfVJWLzYypGE2jg/hUSQsjlGhaQA/Mcdc0+Jrlb2dFlLRxRqAHAxn/8AVT5tQe2VPNjVmf7oVsFj6AUXlshppny7ffJq91twDlTn1yKCW8vcj444JHIqXVcLqgOw8xL8xpi42uAcnHfnFeNJp6HseRXkyeGbcMdaRcgkcnHI5pztgbH2gnknrUbM4iBHRh346UuVCvoSAMF4B/2h7UEneSF/4EfUU1gjNlEYN3Pb3pDyh8zCn0FNO0hLYc7nI+5jGSR71GPM84HI2leAe9OZN6KrleDnAFNJJ+dsZ6ZApvV6jt1BgvCso3cYNMUspZZD+IFB5lB3Z57DrQzSCPedox1Dd6aVgtroKDKqDeQC7H7p7Vjnknv9a03yEDAdR09KzDuBPAHJwMVoui6k2GW//H3dr1ARCTV7BYA44z1rNjJ+3z5bgwA/rV/I2pk9QO1KcE2KLdtSZD2GMVIvPc557VCjAflwKkjbo2alK7GaHh4Z8WzAkbW07nn/AGxV7SBnTNYRcB1kcr6oe1Z3h0xjxOqkH99augPuCDj9K1NDQtfawhH35Dx7V0wbsS0rHno8Ta7JIqjU7jcTgYbFXyzwWWoTFzk4CFSQVbpn8zWFEuNURfSYDp71tbTeWq2SnabiYKp67mLcVq9DCmm4s7/wy0mk/Dxr+5lZpmSS5HmHJwfu8+/B/GtzwbaG10WN35dgu4g9z8zfzrL8QoLLRNM0e3P+smitsY52KMn9BXUWKiGKCMKAQMsD71VkloVFanQRtmPLHLYyPpWnpuVTcSA2eRjr71kxA+UCVzn17Vo6dJuLAcsOOelcWISex30i5ethNxx1zT/DJI1IjOcqRxUd4G8ok4J5/Wm+GTt1SPplg2cfSs8K3zirr90c7poBtJ4+dqXF4nXpidhisX4zZPgrw9ICQRO6EDvlD/hWjptxGE1pGkVRDq9+gyf+m7HHX3qj8YWEnw60Ob+D7aBnscxvj+VdE581fmRND4YN9/0Z4ZAP9IUY5zmrE/8ArMk4bPTFQRYFwhIB5qeY7J/lyPT2q0rNo9CJCSNgAABHUjvTKkY56daYRz0FKUVfcp7EZHzUw1ISSTk9KjrJqzM5ByKOaX+dFImwYpaSlpFIcOnWr2ksTq9kqn706D/x4VRrR0RGk1/TIkTe7XcQAHUkuKErtI1i3HVHtF3apPDcWUaJGjqflQYGSOv1rxy/168t5mtkQB0JDfMR04r27UdN1rTbt5bjSLjyR83nRYkUD32k4rxbxxZpYeJ5GQHZNiRc993X9c1nGknUtNGVHHVaFGXsJWvqR6Vq0kvnLcMfMABU59/8KmvLrfbSxA8uMdfcVgQ5F0ioQCzbTjj86uSypGCWYfgamrQiql0j1MHmlWrhHCpK/RtlCaL9yZFJyo//AF13njgf2lHo3iiN/wBzcwC2cFejr+Pfp+FcVAY7iNipO05U5GK37me4m8F6bD5zm2tbpleM8gMeh/n+dd9pNpnzinBRnB7P+kUFBPYYPqK96+BSW1p8LY7yQkBribfySD8wHT8K8E5CH5SeO1e8/BqeKL4V6Vb3CEJc3Fwqv2B3Hr+ordHmyR297/aU9xbzW2PshHzqzBQEzx9cipYLYyXKQRfLAqM0qKcHJPGD6GrciK0KxTKUWAhMqeCMVV+zytfRm3GxCm3B4BUd+PrVt6WJJ7O5a8YwTWiLCuNpB4B9PrUZWaS4UudpWbywmOGHr+FV7sTXl9FpaoCiOJLiRFKEehBz16VbeVbq5hukkcYV0WIfec9+expbMdio15AsLQ3cm8AlAvcHtUum3lojSR75FjZht3g8MOwqqLSyLGeIEgAKozuIOec1YihKyzzSiVU5bb9aqWw2uw2ys5DqFxLNKwQAFQwOASferN1MI4WeCFWjYmMtuyQe/H4VSF2tlN9oud5gdgWYNnHZQR3q1NFPJel1uZoicMroqtHjHQ03vqRZ9Co8ts8sLvKdyqAiBe2cA4HTmtW2iiaNnhywJIYOecis1Q9wLyM4XawkBU4GB1x7VJcX62JcWgLSsQS84yoGO2KJa7CtYmuLKx88TuxjmU7mOSceoBNR39tbyRrdu5lt4lLcnAPtx3pzyJHEtzLNFJIE+eN2AUt681Gf38LtO0H2UgEpG3X6Cmrq1wMue/8As91Yi305PInUMZE7e31qBh5s1xFChhmL5GTwwzzmrwh/0hvLVljGzajfdJHoPUVHaF/tDW0jExsx3FFyST0q79h8pXu4GV5IyqrtYYGSx/KtLTxtWS1uBiJcFW3YAIHTj1pt7B5UCXCSgXEagXBwCOmBkUkEii4SW0kD7SN6Y+8x6flRfmWhL0siWQu8UcdvGx8w/Mc8KKuYt9PJYyqWUAGPsaZcXkMdtOqgT+Wf9JZT03elYV/FGXjkheWSLI3yZwOB0rK+gzVtpje+ZfXLNHDFISYT0bA6kd6hvNd86zc26SpAygL5KFm/EDpVPR2a9SRLeXenm7jHIepA5x7VOIINMR9OJkhLjc0kRyMn9RiqaVxJdx3h65tLeF2AnjlMoVjcIclcdvStK6la5kItmEolYxFiMhOM54pLeNLSKRvNk2bBuabGDx2pscVtFaI1rmF5JlPykg+/H0pO1+YOXQdp1o1npDPKyi4k5dl6AZ4H5VUsIphfzXEc6iMA5fkrnHGa1Lnc7yOJggI2IuOuOvFZqy2cFvFH9pkzEdxjYYyx9fb2oje3qD7ItX1481gVgjL3BKeYkA3Ntzz9MjPWrln572hRYmtVHEfmEMwH06D86ybTVxAXAi4Y7laNMhz6H3rWsrmUWu68ARxgls9c9OP0rOcGugLcsW1sttFt3GSQ/flYDc59TgCuX0i6uJNXvd0UsUeHWNcknOeDXVyyCKMuSMAZOTisnTJGlu7hkIMS8bhx15ohs2wa2RU0u/1MQ6x9uK/6KoMZ2452kn69qq6bf6heWaavcQxuEU7Svy55x0rRmAt7TVGlOEcDaxP3sisqLU4joslvCBiMoNqDIHrmtY63aRNlsaOlahELHULuTe8jXBLxkZ25wFH0pC9ojy3xnkecgARgcKPRRUOnvNH4YabasaZLEtyx59PrTLaf7RoiSvl2MzAlRjOOfwqkldtegct1qeAasP8AS424K+XjPuDVVcPuHyqfUc1b1cF1tNoBOWDHFUoz+9QLyMEgjivCa6nsdbEYVQi4c4BI+amMwA5+6T9akZUESvtBxzyeT+FN3HDfKATyR6UKVw16CMTkBRgcd8UoOBl8uuc5HWoz8oUMcnOacmCmO5PAos2wdkKwUEsSRuPpkionZpVkiMoIK44449qfGzgsTjg4wRyKjbOShxt6fKOefem3ZbCQIuSpBOFGOvNMuJFigYgHJcKqgZLVJkcjtiozncGI+UDjvzThYV9SWSZwqMEy+ApwM1kS7hM/U5OSfTNaDuUTKZztzyelZs6hZG+YjcQTmtI6ahoQoobUCPlw0Rzn61fQ/KpIG0AcCs5Plv4+RyGA4q6n3QCx6c5oqNXQoolVyGJyMnpzU8UixuGkhNwAp2R7toz9aqjHPQGpAcHIP5mpjKwWL2mTyP4p0gtHDEN0o8uIcD5Dxk8mt/Stq+INTjx85UNz2rmLByniHSGJP+uZQceq4rp7MbPGd2g6NboPc9a3pu61/rUz1bZ5ltA8QOp4AuG/Qmt3wpanUPE2l25BMcMrTvjsFyR+ox+NY92vl+Kblc4xcvyPqa7j4Y2e64v71jjGIFJHvk/0rZPWxlC1nfudBebr/wAb20Cn91bW5fA/vucfXoD+ddBZyK95MygBQ21fcDpXK6de7IfEOuyOoEbusRI4wvyr+Zrf0QqLa3klcbgocn/axzVTdkaU9zq0bCYJYEnr61p2B3MxyeMYGMVk2cmUBbOQf4hjitLT5Ui8x5XACDJPp6VxV37tmdtJF+9I2Z/ixnPoai0Bwmpxu3yjJ696Y9/bXR8mJ2aQqSMoVFRaEVGrr5mCWJ2gdvSssJK9TQqtH93Zlrw14c0jR4tZ1NmS7nv9RuL1jKn+r3vwgHsAOepyaueLdCsvF/ga6tLl1YPEZoJE48uUA7SPx4I7gkVyFxf3ME01uztE6yEOg559xWSbOKaTzI7ueB1fecSMFz24zivVklFnnqldbnh0tvJaT+U+4Ohw6uCGU+hFTPLE+GDEHHIx3r1LXPBA1+7a7mvFW5kbczxgfN25rmbn4WaxEf8ARry3lH+3lf8AGuery87cNj1IVkkrnHvjPXP41GwzzkV0Mvw+8Swkj7NDIR/ck/xxUB8EeJ1yDpbfhIv+NZSlc0VaLMLcATkZ4ph5OK6IeCvEykg6QxJH/PReP1py+BPFBIA0ls/9dE/xqBOSfU5vtSnJ611KfDvxZIcLpJ/7+p/jV2D4U+L5x/x4wR+7zD+lILpLc4oA44FOCse1ehxfB3xSQPMl0yL/AHrg5/lWlF8HZYgW1HxTY2/PzBCG/mwqFJN2LU6dr3PMUgYjc3A65Nel/CfwRNe6lF4ouJxFZ2U+2FDHuaZ8dh2AJHNaMPw/8C6bOpv/ABHcXjoMsiY2nj0AJ/Wuq07xHoGh2MVjotneyxIxZVKFUDevNb0XGMrvdGdaqpQtDc61fEF9FLOJEVo1+4SuDXgfxOhvtW1yZ5Yo0W2tWmUr1KgjI49P616Xe+I9QvgQsEdsDyQDk4/GuOtLGTW/F1zcTPHLYCza1mbeCWZj04pzrX02RxqnGGqR45G4fDEVYiggDbimT2JqMWbx3V1ZlgHgdkPPUg44p9sSoIZtx7Gt3rZo5Lu2pb24TOGI9AK19Ff7bpOsWJ3fPCJkU9cr7fhWbbSqh+ZQ24dK09BuYrXWbeVDnLeW6g9QaUZWlfoXa6KMZV4gwBGVzX0H8BuPhfaGU/8ALzMI9zcY3dvTnNeC3Vq1nqF1ancPKlONx6g8g/rXvHwM8uT4U2izAELcThfX73b9a1tucjtc9MEUTN5gUNuAHTiq8NofsxSWRnYscNjlee35VnNGLe7hnS5WVWfcEK7QF6fjirM1zdWbuzOGiZiyggYjUe/vT5X0Yr9i7JCSmxAG3AAux9PpVdbdYbx5JD5krHeqrxiq/wDad3JZ73tY0lYgqhfdlc8MeAamlXddJPAfLnciOTPOV9R/jQovqK9wdSqp5cRCyNl1zgg++aZdWpmVZbdmUH5WR+e+RUfnSOTE7B1DYbzBjPYdKfYkx7pCQF37EwMAe5FW1ZFLuNezaWaVJSotxGBISvPrxVcMgkjS2t8WYUgAYzn1q5Lc3AnikMXkwsCGRxyTnHOKqOkZuiVuVaWEHCBcFsjoBQr2uwvcg2G0ZCsmC0DRAsvXJz0qK1eUMfMt92Cqo6tg57k0RNN9oggkmMlrISG3YDA+g707UINs6zWrARsMkHIAGMZ9etX6iSV7jLuxWWeCFrmSPe5fOzeH9QSaRLkWMKQuioQ+M5yMfUVvQ7pbSExuHdcgjPBHfNVZdJtnW5hmtg0T424ck/gPak530Ybu5nea1xqMGZIMoS0afxEd81Dpc4NvqhINvNbvtEmeoblT7elWpLK10iGRIGkllMe4FxkoPr2qjcrBYWHn3N2wE8irKET7xx39sd6L6XJF09Ly+nvoZkXaHRpGLffGOvuK0IDDp2k7cpIVcyEjJBY9PwqEyypZJa6bAJ2c4J258tO2T/Sorm9ZoJhAihXHlqiHinqxpFe5mkFtbyW58p5OZ1xu3D8fWnC/jkj8j7O4VcbdhGD7c9aIDvmmtpEeNpLfcqyZwGA7VI1otvp8PlHCq2A78HkdfwoXug1dlxb+zhS1g+zRxyyDcp28gfhzURvLQIJLm1Z7hiVzGNpdfXB/Cq8awWkgkWN5mXG5gmWI7nNTPeQai0VvsVEdWw5bMiY9KLdUDja1ywL+K5WKGKJhDvQOLgep5q8PMMFwjxRoY5C0fYBR3qotpEdPEM0chHnLiU8c9ifarUgBlhcMwcsIiA2QR3/lUvsFtLFmdzFOVRAGWJn3n156c+1Y6q8UEXniN5ZRuZgvI+oqzFcPG4mu41aWQmM46KB7VfRVSXMaq8mAuewGKSvERj26SN5hhCxQrIFV+o5GSabfPGyLNBKrBHXcWJBGPark1zBLNLZW1oB5LA7xhVL+g9aiSygmg8m6m8ickltnXB96tS6tCt0GajrMemW489WmvJgQFAyq4H8uaxYZtTVUZbsQ28i/vNiZOCOua6aDQoo5Z5FuZXEi7VLMCUPtVWfR7+JVWFoJ1BAO8bWYY7jpUqcE9BONzOuNKgvYbeK3vWuDxuLkjgdz71eh02az0+aK0hifMmWRDyQKrJaXy3d3G6lCsK5EIzuJ9KjhlNvaSs8jW7g4KueprRarRgWpJGtPDELSoyebNhlxkgEn/CqK3EMGk2gClEDyHB9zgVpLcyjQ7K5SRkdC2COcjPvWHPqt3qaIryxSxljyybcHjgY604X/ABEeLaw22K3cYH70jkcciqClDhAcYUn8zV3WUzZIRyY5Qx56CqPXDADa3Q5rwG+jPZurg6kx8kcelQ5wCc8kdqlJLxkHp3qMDgkADnGM1Ol7sTA5fk88UAhMEE00FjuTPB7g9qFbcgXbnac8jtVpsQON5+82c5yCOaTCjluCf50ZxzjGexFRliCF6DPAqkrK7D0FJ/eEjBHX6UibWyQegyQKay5A5CnOSB6UYaIPhMsBxzjJoWpNxWYNHkscAmsu5cmZnww6YrTV22cqobOfXNZly26ZsYIGO9XF3eoMgUsL61ZuNzHn8KuxsCnGMZI5qgCBd2z9/NAxnjBq7F/q3B5wzDntzVVEt9yV2Jhjd+H508AnJGMY5zUSk5JUDA7GndVB2/Nmsk9dCh0ZZNW0p/S8jAx9a6rp44DKR88IGD6gk1x8jlbywbccLdRtj8a7G5cL4wsmGNskRye/ftXRHuQtGef+JNsPi69bHy+du9OoB/rXoXhnfofw6mviAsjJJcDJ4JPC/ngVwnjKJpfF9xFCu5mKKqr3JA4FejeIIfs+j6To8XSeWG3cHrtQZP8AKt4/EmYxvZox9dV9N+G9lZg7Li8kQOhPUAbm5+pFddpMqLEBs42jbgd8dK4f4hlptTsrQW80i21rvfy4ycMx/wAAK7TSGDJGCpz/AHgPaoqv3kvI2p63Oqs3M218Y465yM+grXsVWZmSRQUb7wP1rNtkaOFVTaoAFadkMzlQxweTXPW2udVJ6lWBmtry4tmtpFAYssxBPy59f6VPoxCatGCT98bT+NatwP8AR1XO7IwRWJYIV1GLnaofOT2rDCLlmka1pc0Hc81+I2o6po3xH1s27EwPNDIEYblx5K56cjmsKx+I9x54gubEbWO0tG5J/Iiul+Mb3WifEz7RCyFNRtIpCpH93cmD/wB8/rXnkGo6dPqTfa9JTzCxJZXLAfh/9evqo01UpJ8iasvLbQ8aMkmkpWO6Xxzp6t88EyPnktER/KrSeONOkYhbkLjkAsQP1rkZbfSZ2zFfPbL1AaMjH51E2hW0ufK1PzARkBkQY/WueVCj1i0bxlUbaTR3P/CWWLOCb3AIznzQeaDr9m7DOpyNu44Zf05rzmTw5P5m0eS2BgHI/pUR8N37ZAtIR25bH9KyeHw/WX4Fc9SPS/zPRm1uEn/kKTqc9Vxmov7dhyB/bVzuzj7y5HtXnC+GdTWRtttCCBx+9FVX8O6lv4hiIPcSrUeww61U/wAA9rW/lPTm12I5H/CQXg5yQJFFMbxFYA5Ov3LnupuFx+PNeZf8I7qQxmFBn/bFINAvuAUjUnPBepWHw/8AN+YnXqreJ6Fc654eY5mufNPXDTEjP4VTbxN4TTj7NC5A6mFm/pXFpojA/vriKMd/mHH5kVJJpWmxbvN1MrjgAIDn8ialYWhurv5D9tWavdJep2DfEDR7cf6LZSkgcKkYRc/XOapTfE+/bi2sIkHbzJC36DFcusOjwv8ANcyzY9I+Cf0qVtQ02NwbfS1LA5VyxB/LmtY4aL1jTb/Az9rK13NItXPiXxLrUjRfa5Ujccxx/IuPr/ia7b4VAw+H9RBCgreY9eQq157Nrd/fSiKOQxI5wqJzjPv1r0T4VgjwzqQ/jF3/AOyrUY2jKFF6JLyClKMqqs2zlPiLp66f4zkmijCw3kayjaMDdjBx+Iz+Nc5G5WQKy4HrXqPxSsGufDVpfRqGaym+Y9wrYH/oW2vLTNuxI+ckA8Vy4eacLFVo2mzQiILrktgdcDtVkwR/akljYgId3y8E1nxyE8kmrHkyyRB0kIwSDhv1PtVtWFFm7rapLJZagOlzAEkIGfnX/wCtXtPwQIb4T2ge4MUazzEkgYxv7GvD7WVrjQJ4XwZrNxKoHTaeDXsfwbkmtvhPbShTOr3MoWEjp83ODWsLsxmrSPSNQNpJHbmTLIWEaSRnJAI6n8asq4itvsyKfMI2rvGcn1rCu0N/ZCGziRQxIO8kFXq8Ll3hfyZP3yxLu3jhSO+avk0RFhkGo2dxNIJow7kiGWQ5XHJwBU1xdrHqEAhVZFBEe4dcd6is7Z4kup5Jk2SsCUVc846ip4bdEIukDTNkYAXn3oVlq0DCKCSNJw7oUMhkUsMk+lI7XD3Nukew2bplzj7xHv2Ip8YaaGMMzwuhbAK54z3Aqs1yqRRJmT5gQrKOMdwB2o3C4+8vWi1KOGAgmQFmVumf8azihU+esaFi+3L87T3NMSRmnkBZZONyktjinGGS7IkSRR8oP3epHv61WwLQQLcK5UCMsoaWJSMn5eR+eKlvrpbmHTdSKN9mkjzJsGfmJAx+ec1LaxvDbtcmJWlPyqGOevWm28ZlEVs7LC8Z/dJgEYPUYoVrid2WZEMR1F4yYzLs6cAcYzV3R4zHbRArIzCPmR+rkn1rPvLx8SLPCsjBxGrL79asJqC21iWhullwu1RKMMG6AYpSTcREU80NxOZvIBd4+VZiQ2M4GKxNVIu7YvNbiNWcRqR/Cen5VoX89uIrWJ3QwJbgNjjBH8qytRsXvptOs0mV4ZpQHR+uF5JB9aaTSvEL2VzaspBomhQM5uJNnEixqCN3Ayx9OlJaiC51AiW1McxBYLgbTjoBj86qai5/e6fC8ibWEgjPO5emfp0rT0y18rUYpZVJLw/u85O0jGc+h5pyas31DpoFtGb9bSeT5XRWWQ4IIB7AGlEsUlolxHbtIisUCSYzx3Iqw6ywXDNuVlDZxv5P1FRblgV7iRQlvcAbo1blSR1/GpHdlWZzFp0qojEzY2leo5qJY7ayWCJlBlfdtcnhSeuasQFmkkR2OcgoFHJAqKxuJr68eSaFBauSqKUBb6k/hVbXC/cuC5lg0+LYEmiRcNn+I/41ZQIs8QkUK+AYQDjdxzUPm2zwCOWMRJGQygd8nsKUyW13dYidhIWwrnpwMnAPSofYLkkoYTyPGpZsKqIBkAHrT3l8qGZbRf3yFSyY9eoFVZA+ZGtWkc/3x1HtU6QzmECQlpGILfLQ0ragVNPcQxOZY2ijjYsMnlzV9JBs+0TKN8owkajmopJY/tLho90anDADgHsKh+3wpPHCodpZMhckfIaHrqNbitZ7BLI4IiCfu2zh8ntgUbromD7PduA4480feP4+1WJE+0eSskRLKCJDnOD9fenSOqwQvJFt2D5V3Zwen41N2OwyaWS3u2+zQLPcyqpcF9oQDgE+1VgtveXlvJdWayyFSrEjdGhHPAPX61be3k8iOSW5eB0zvKY+bnjPFZ2uahJaaTctaKVVQFWVSASeOlCSexPS9iTUJrFl+z20AeU4jIUELED3I6VIuhWcFtiSPcqLlivBrLsSyRQpPJiaWMPK+M4471WjuhPOBBFJIP8Anq5wp9a15GloyE09Tw7UudPuCR6Efn1rHBLRDrjOd1bWoAvYXKKNzGJsHPQ1hRMTEvyEdOteG3Y9dkoIIfkFeoGOlRMACV/HFPU/PjPygHvioudoYk4PrRJsLWsPXqOmD+lKQMk9AOMA0EhRjOe1K3+o5UDuPeq1vYTfcjcKGVQe3c5zTAo3dMLjHr+NPJw6Fsdewph3GTHPfpSg09AvoNbaWIPTrn1NOB3YyQDjGc9aZ9Oc+tIw+UhflINWt0xbD1IxuQAkHv1zWXdENNuBHPPHrWhuOMKxycjis65VIxgcjpgVcVYTZVlzuh7Depzj3q/uO5sdKzJwojboNpBxmtHGHbnkgEd6dRNJIUErskGQACo9jTtxBzwO3Wo1ZcgAckdKdkEYH6Vmo6aDZBfP5Vr5oPzo6sp981v6pr+mJ4gsbmO6V4YlKybOccdq5zUwGsSAehBrIfY1xKFTI3kj6V0UoaHPObUrHVaQV1/4iQTgnyhJ5wwD0Xp+oFd/ch77xxDCBujtbUyFuuHc4/kK5L4XWgfUr+/IYRpEIV9Dk5P/AKCPzrdt79otL8R64ZPLdjIkLA9No2Jj8a3jG+pKbtcwNT8R6FLqt7O15qzM77QkYXZgcfLz04ru/DqSzwQPlgjoGweMg9MmvAicnNd5qnhXxLJeaPbC/nvI9UQG1CuQCuAfu5x0NTPWV0VSqSatY9qZrO2X/Sr2wtwwwvmXGTn6ZqS11HTDeZOoWrJx8yuNvXtXinh221Pwj4g1TT7mzEWoiJcfaEyVXOcge+RW3JqGpTNufUZRnptCr/IVDp8yszeFe26Pb7zVNDjspANS06PAzkzKAMdyc1h6PJZz3cONTtLpfPAzFOuTk8jg815a2oalLp1/azStewy20imJ0XPI/hIGc15hmCRQIrJy3TO8nP5VNPC+zlzJhPEpLlX4ns/x588fETSycGEaepQ46HzHB/p+deUW5xqwweQ5Ga3tPF7P4Qmm1GS4k8qTZB57M2xABwuegyegrnoV3agm0DBfPTtX02Bf7m3a6PLmrSub0wDLng4HGBVaWKJg2UTPfjrVlwMggHIOetQP15zz0q1oW0VSkewEAj3zzUDqoXAZyT1O481akz0GPxqufuknBb8qRKsQqWWRQHkGQRncaoyFhIRubI7k1ewRtI6joBWfIQX4zRYJMNzHqSfxpDycnk0lL2p6EDcClooqUgCilo6VQE1oQL2IkkYcHjrXqfwsJPhbUGPObw5P/AFryiNxHKH5454r2L4b2RtPA8c7NuW9uJJMD+EKQmP/AB3P415eZySpO/8AWp1YVXqI6DVLD+1dBvdOCIWnhZI/ZsfKfzrwGLCoYpAQ6tg54xX0XD8syuBtTd1714X4y0v+yPGOoWzArHI/nIT/AHW+bj8yPwrxsI7No7cV0kZ6MOm7n29KmRn/AIcFwMCqIIUkKTip47kxyB1JUjocV28pyRlqa+i3J/tJYZiEWdGhY9jkcfjX0D8DGkT4W2oeIbUuJtp3dfnPavmg30iyLOAS6Pvz7g19K/CC4iX4Z2rsCRLcTSLliAG3HIH45qoxvFsmpbQ9DkuBJCY1kRZcZcEg7R6mqmy2kaJYIlXzkYK56Hb/ABEVJawSGQ3UsKq0uFxkfdp9rJbQTzRgBjbR/KyjJKnk/rQ9NiGZ2mWdzA00NxqHnIf9W64zjvx/9ercrpDPNbSea0YQOzqQMA8D+VUo5LCIwmykcJKjE7j1Hrz0qJ4Z7nST5U8puJI/mcKDhAe1XK8tWCHXNpBPYQ7ZbgiM5LRPyh7A460+W7V08uO3adI0w8kTYO70xWfJaSadGjW12IYA2fM2/Nn39atNqbRLGi6ct4ZlHntEcbiaOfTULa3K8FtC8TTIwij3AMJeoHrWtEIrK24mSQNg5GME9Kp28lgqp5qXKRqcPFKAyrj6Cm3GLubCyRJaL86OybfxNErPUF5klqXvC20u6cjIO0ZHUn0NPls4yFl83LlQoaLk5+tV4pEeCJIZEhDd3YAue7Y9+1Sqwg1NgzhokO4qv044pWFe+pQS9MFzHYXEpeUS7vOK9+2f0q1fSiW+tLWVch2LvvAwSBkVRv7N74FUVVLyDe0nBAzwfWg3ccuowQTiPcqsigHkdqdm7JCe1yPWtOWyvIbpWki3ldsQ+YEdyfarl5PbQ6pbSeZuicbtkak9sDAFWjqFuZn0q4uPLul/1buvCcdM96Etlt0gnd4i0RwjRjcHHpVQ1Q7jU8tY4ZjHCsSkruckSlfT/wCtV9YdzI6aeJJdn33fC4HQn3qM20UgWONgGZw2/G4q30pZZ3tpLkRXKsPlU5GcHvxSfVITa3HCZ7adLmeyjtLY/K54Y+3T39qWaNdQklhVQu9siQfdKjn8DUMWoM1yzzSiXaoVVSPjPc5NT/bXtrR2SMlTnBdcHJ7Ucso6huTR20sN0mJIyhXCkcnPeq2nNGs8xRtsXPBX7x9RSeckytIzGBo4giuD8mT1Jx3qtp6XcjQ5jVVWMgs/HPcU0nZ3YXuXoBFNB5hwpmUCKOTGQQaSF7S1MN1LKGCyGBWH99upP5YrP1G8SMCCEK13IwUMBlYl/pVu/wBLeTRI7IFWIO+Rjxz2PvUtd+ovIW9ZrWe5YEBFCoqg4GD7etXbfzzaeYtzgHoGGcVSvpoldElUNPtXfhc5bHBrRtrbzLcG4G/jITGMUS0gri6jkimWymM0cbyOSxTGAfr+VNMVrI8W+2MUo5XC8g/UVZeBXiVCGIBzjd/WlkeOPLyMo28+47VjcogNqJIz5MjKGbLE9+aju3ksrMMMTENtUFfU8VXutcsfLBRhNIp3KorNv9VuTdWMlyjW9osMlxKSOOMYz6Y6/jVxjJvUTlZG3clY4nmuwoCDIGevHPFYl4H1gbSqW1lD8/7w7Vk9/wAK0bW2M8i3qSC8hkiVk804GT3HXt7VckZZo9t5Zk4BzgeYo+nf9KL2Y73Riwi0RmmtzvEh2MSeSBU7W9vIHV1BhByuDgjFXoJNNnRGjMaIOAjrt5+h71nXM0U032SwuEnf7z+UM7Rn1HFaJ3YXR8+3WWtZgMZMbDArAiJSLAYkHjI7V0BXJ2nnOc5rmoixBUoBtJzivEcbnrNakhz5mScjpigHKkYGO1IB8rHOCeRTU4HXoeM0r6i2JlYHgqWPbJppAUHp9TSJJ820DOR6UyRwi5yfyzV6bCY/cQRyKagTzCZJGVT6DPNMyC4JxjPHPApMhvmOCCcnJ70O19CfIkDBQ+AQR0x3qNyFdiHJB4wRQ5CqzFiABnGeDUUsirGDnqRjHOap2VrB5j2Lru2AEDBA6Vn3QOfvc46VeYHJyCCORVG7GAMfqa0trewSehSuMmFiBzir2CsxA/uqx9PwqhNzCy7QeM9atoQWQKQcxLnB4yKcl7pEW7k4IHIZQe3rSk9iQG6dKiPUkg4A7U8A8Zz0z+NTZaMv1Ir4brOQcnjqfzrDmz5hbIy3JxW5dSKkBLE8qc5/lVBdC1aaKKaPTrmSKUbkdIywI+o6V007yWhyVbcx6R4SX+xvh5NfbSJXWWcA9zjC/ngVneK5G074faZZF8TXLq0o/vADc3/jxWt7X4ks/D2l6ZEeGkggOTjKrgn69K474lXfma9BZIcpbQAY9Gbk/ptrSOiuE7pWOKr2zSNc06DRPCt5eWskt9psamCUM3yr0I4/L8K8Uwa9PSB5vCOmS2sZluIoo2SPONxByRz+NYzXMrXHR0lc3bjULHxH8Tbu9kgZQdNB2ysezCtJItJkw8NukinoyjdXDwTXsXiNdR1SGPTrSW3+ztI0gIHOfzrrbPxl4M0aIW8Go7Ix1EUTNk9zkClZm/Or2ZcmvNOis9RW0WFbmO3f/eDY7iuGj0PRUgjxpUcrMAWLzOMcdeDW3r/iTwZqNpdTaZfmLU5UKki1dfO4wATiq9zD5EcAGeUBBP0ou7BdMbHYWA0K7sre2S38wHYDIxUMRjJJJ9q4SfTtQtLsYgkZlbaHVSVbHoa7a/Uv4Yvdy/wt16YGK4mG9ura4jRJWEbEYTcSoB9q97LNaLaZx4l+8jWUyOgaX5WI5C9jVWe4W2kUN5nPTAzzXSeGNNtfE2uNpN758IeEyieBwCCD0II+tX5dBsNB1+60/DzXEO2SOeRvnCHkEdvWnUxKjLlWr7BGn7vNJ2RxUQe7DBFWMZ+9PII/508wadFkX+rKjEfdt4vNGD71P4qsHvPE9lBbAyS3qoiCQ8bi20c+nSpNa+HuqeF7JbvUrzTBCxwojmLM59ANorhq4mrzcrdvQ2hyWvGN/X+v1KBk8MxumbvULhV9YVUH+tQvqeix8RaT5vvI7D+RqgYrdyBvAz6moPJQ3IjMyqmcFzyBWThOXxSb+YfWHH4YpfI0/wC2NM6Dw/bEdszPn+dSf2rp7Kc+HrQfSZx/WqjWGnRgltTD46COM801YdMGN9zLgg/dXJ/lWXsodb/exrE1OrX3L/IvJqWjMw83Ro4x3KSMf60yT/hHpSWjuLuA+nlAgfrVQJpqoHKXbJnAfgA+tRyNYmVvLRhHxjeef0pxpNK8ZNfMcsQ2rSSfyNBdBlu/m06eG4XA4aRVf/vnNZs9pc2z7J4JY29HQj+dKbuOHy/ssRiljfcJw3zH/CtePxZeagiWetsb+26KZBl4/dcYyfrWqxGIpu7fNH7mJRw9TT4X+BkQW6ySlZWMagElsZxXrfwx87/hDZTJKWj+1MIlJ4UYXP65ryjULb7LLiNzJbv8yP2PsfcV658NiP8AhA04yftT/h0q8ZUhUw7lDZr9SKNOVOtyy3R1OBlSQ3Xr7V518W9OTGm6ugO5s28n4cr/AOzV6OiM5VM859a8k8c+NW8RQ/2VZ2zQWUEu8tLw7sBjp2rxcPGXOnE7sS1yNM4r5gBzjFO3gEDIxVcFgQMnFOzyc816jPNTLjXUao6CFF3AAnuPpXeeCte8UQ6LDa6Hq9pb2lqziSG5QEEsc56E/qK87jMOCZWfI6ADrXSeEr1YdQulRQN8W5ceo7frRC17JFX11Pqbw9rFpqXh+1ngkWNNp3naZFDjr+tTCa7+ytNZX9k5Y8r5BznoBjNeXfBHxKZ9d1nw5M2Y5VW6g56YwGH6g/nXtaIZU3Kkcco4LbMkemKqT62/r/hyZaSZzmnsjaiNFSQSxWytIG4CynPzKM+hNXktriG9kC2+IDE6Ls6AY4Ge1S61YR30cJjG28tnDRMTjB759jU+m3x1GN5GQoU/dSAnKlx1wO496UndXJv3Oes9l7p0+mSGV7iNPOQEYwR1APTvUoY2enJJJjczcY4YAjpmulhtIl2sYFQqOoOM565rL1DTmjRp7doniVtwhcYOe+1vXFOMknYDLuNIlmtre6s7uYTpnzCzEZX3FV7y6uIoofMZJ/3eUdh97Jwa1Z5WikhyPkQZy/G4ntUczG8Vdv2eNWYAE4baO+M03qNpMpwm0lzdy7IkSMI8e3OSD/DVa3EkVyXSIg4Z03D72e59a1niSOWIW8kDQICHOQMmsuaGQFMK8k6cx7TkNzyM1S31JtYfJdL5shFsZBgMQz4IPfBqlJqFn/wkemxJZRq8u7M/O5SP55q5qkJhhH79EI5K9y3v7VjanYz2zw3oRWETqyvu4VR9786rRob0NbWGsLzWraS1u7VLlf8AWq6ncVBrbhugI/Mt5Vd4Rhoo485965BtNWW/ku0lZBM3yOG+QcDgVp2sstre2813Ar20ed83OQPYDrRbTlWpPLZ3N61uVuJ5VmjeGZhuZiuAAPX0pCY5L4tEFe1IxvQnjkd6ym1ea+luYCFS3mjwsh4yO3vU00c8VnYW1rOYgql5MLuz+NSo23B+RryaVDfyvPJmNum0jH41nWscwuJLSeNz5C5PmHduJPBz37Vaulmiso7i6kSafeAGjBCk9sgelV9QuptL0a4mkjkupMea2zABHHBz0qYp9Aa6kQhTelvHEkLzfPLsXoB7UXOoyIklvBFvllcBJgDyh4JI7H+dVYPPhnmURehWSRs7ARz07VZt7uGyldIwS5Ay5XJJHoPStNb23E2i6YYbGwjIjRXGVDsMsDjqaWC6Z7JIQ6STxqck8gj1xWXbM8U0skXzyytkvIc4Hcc9KltVVHtpFVi4lIZlPBGaTXRhcn8wnUJGbCqhB5OMnHQCr8l9qS3MjiEfZ8KEBHOT71Dc7pZyZEh3qcAA/Nz3ojvx5ptWUqecHBOMdDRy31sJOxemurpbWIuqxyOAGRPnbJ9P8akNhG88UtyzSuBt2kDYfcjHNVXZ4XtvLimkdR87dR64q99r2q7um1Y+WGcnn2rFp290ad9ytewWtutsy28SpHMM7VACjB9Pwrm9R+16vqt1JFI0dqqeUNy/nj60l3rM97dpFDYTRwu2QAuCTnq3atS4kuhHFayLHCjHBRcEsO/Nawi42b3B2ZeW6/s62iiL/aH8tVjhTAbIHIpYZdYuojJ5VtbK33EkDM6898cVHHPaaXeyW0cBVQoYuGySfxpLHWtPkmKJdSGSR8BGU8n06Vm4u10hfMW30dGupn1GNLli++NiuVHrx0HNWprKytYTPHGtsIgWJgUKSPTgc1dV1Y4GQfQ1XWZbm6eJVJjhI3N2ZsH5ffHX64rPmkyrJHzKB843ev8AOudwy3M2V/5asB9M1v8ATbjrnJIrDu8x6tcBemcgj3FeZZvU9W2pE3y/KOcE8+9NUFRtHJz0NOZRuGBzximAsxDFMFeB3FLTRIa0Hq4VCMYJbqPakLnGT9KTDlc5249ajbozNlQvXPAoWuiF1uKGAfB649KSVvKt3YgBVGSQKQnIDqSQR1BpCzE5DZ9RVNKOgCCRSnc8cZoJAHLAeijrTGmwwVgSSM5x/Wm/KzJukKjOQQOtXCV7C6D2YEnOeap3jDpyfw7VY8wyO6sGQDvjrVS5KtGxUkmri7IlrQrSkGNs46YHGKEvY0CBshVXGFqKUgxZGenNUTWvLfcwnU5dEa66jCSFVW5PUirouJCowy9ehFc2vDjnHPWrjohtDL5jGUe/vScVHYj2r3Zc1CfbZFCAzs4Ib09sVWsdY1KwG20vZoV67Vb5fy6VXlVpMBSSFUE57dM1GvCHI7961he1iZt82p2R8S33iqa0t5FjhubdGKNE2DK3HQHvj3qzqegnxFqTXizW0QMYjLRy72LqMZcdienB4xXEQQtcEqijgFuvYdaijkeJw8bsjDoynBrTma9CW77mrc+GtYtELvZOyf3oyG/HA5rqYNe/su00ixnXbFJbglzwUbOMH2rmbLxVq1lgLcCVQMYlGf161ux+NNMvohHrWjJLxgOoDfzwR+FJxi9mVGXK7mh4jgOqaMkasAyyB1yeCcY5/A1xzWYW8CK8dvICVDIx2n656V1TQeFdct0tbbU5tP8AnyI3clcn2PX86p3vw91SLMlhPa38fG0K21yPoeP1ojSaXcp1E3c5fypLaUyPIY5UJIZMNn9a7zWdSa2skuZsbljARSfvHHpXPr4E8RsSG0+OIN3aVcD8iavx+B9X1G43alqdvGqL94EuR7YGKynD3kmOPMk9DV0ySbUfATfJ5lxPLIMgcKvv6CuJnYCcDIUocEZ6Y9K9T1vQR4B8O6NaR3r3g1C0luHwgUrwhIX2+b9K4DUbXSL6CWbTLloigUm3lXGffNezgk6NJt7bmNX3mkjU8J3j/wBravdQkhrfR55Yuf4gAQa6vxLP9utvC3iYdb+2FtcED5Q4GcfnurivAtrJH4huIN4McthOJiOgTb/iBXQ+GlufEHwou7CI/v8ASHa6tsDk8kkfU5YV57k/ac/9WNotSjyvsWDbQxPP4glfa2jW7yRAjh5G4Qfnim/EiZ7v4f8AhS8n5km2u5x1LICax9Vv7278A6XZFNk2ozSTTY43RxngEemcH8K0fHk5n+FvhzbAYo45VQZOekZH9KVdXlz/ACCn7tNx8jg7bRr/AFeX/QbVmQDJkYhU/wC+jgUmseGtX0JIn1G0MUcvCSKwZSfTIyK1dQ0q+i8P2Nxrd79jgZSLW0WMljgdSM8Zz1966HSmW9+DOq2srrMLWXfEwPKDcpxjt3/OpdV79BRpqV09zhbLRL6+tXuo41jtl6zzNsQn0BPU1bl8L3yW8Vwlzp8sMpIEiXShQR2JOMH2rrCumeL/AAVpGjabf21jeWPLwXJEYlcj5jnvk8/jXKa9oWveHbSOy1FCtk8hkjZGDRs+MZBHfFT7ZtvUfs4xV7XOw8d6LHZeHfDNmbqwtFitcy/MSZHIXLDAOec1yWkeHYL8aleyXbHS9PiDyzIm1pGPCqoPcn1/rXRfFpzHf6LY7NotrBdv0OB/7LRJF9g+CtkY1laHUb9jcGP1XOB6fwCs1U91O+5U4qVRq2xlv4c0278DnxJpjXBe0nWK8tp3B4OACpAB5LD9fStvxWumeE/EWn6hYaVCsT6fCyQq5H7xgSzZ5OcYH41yUmsXFj4fudGtrSSC0uZFeR5iS7kEEeg7DtW98W7RbLxXaQx/6o6fCyDOcAg/4UpXul3uCklFtLXQ5qW++3wXqbdsYma4iHddxAIr2XwZJYSeAtMawXCx71nX+Lzc5Yn1z29sV4TbStGzKPuyLtYe1e2fDmGOP4fWsgQBpbmVmPqQcD+QqpWVKUfmOlJynGTOojJDo4GDuB46ivEfiLp66Z4zu1iQJHOFnUdjuHJ/PNe1cYJbPbmvOvi5puV07V0GeDbyHPpyvH/fVceGny1DpxMb02zzEscg5o3nFJxg+tIGx2r02+55lx4Cs2D8oPc81paTcwWWoW8wbOGIYkYGDWXu4xn3qeONRh5HwMcBeam5cTrfCuqTeGfinptzG4VUu1iYtwDHJ8pz+DfpX1ffCXzzlP32cR+XkD6n1Ir44v7SfVbnTRZxtPd3S+X5aDLMw47e38q+x9M1eaTTLcXUO/UBCvnx253r5mPmAP1zWj0Wn9f1+pDeolmsVzIWkhYXEHWQHG7HTipZo/tttJLa7954KnAVmHQ/y5qN41vpY5pbQrtVhsEgy2O2BRFItq8bPDew+Z8zKqF0XHYkZxUyHuVdHvmvwyI86XMbkSxtJlUI4I5q7MyP+7hkO+LhY1O3n3Fcw11Jp3jW20+0kW6uL6GSa4RW/wBWqngn65xXR2ssdyokl3RzIcESpggCrt1EmkxZPNu084Mj+W4JQ5wD6frT7uC2kt5JFiUlQBhP4WzRbyrK0nktGpmb5WjHp1J96py3hieWJg0cJkJDH/lpnqfaly3eg0Qy6UtnKpJTayl3XsD3qvHpl3EEMYkKsM4DdF9q0s+XdQi32sqjBLHtjkVMlshaNHYqmGKtnByPQ+lU21qxW6HJX0b+Z50tuMSyiIBgd4X/ABqHUrLMmy2leKCUiMFQdobPeus1O1iuxAqbiWcMpKnOV547A1m6BM5uHsnmM/mMzgvyU44yPqKq6auwM7WNOJV/Li3Pbt80MYyVJA6Y+lWYiyxW8zGWKYjaqdD+RqWx1edHkkufLZ1fbLN5e0kDofTpV63tro30d1eym5iJZoRtx5fpn14NVrHRkppu5FLc295JPak4WAoDIE3AMcZBrVtjGltO8NqXELfKM4L4HNVY4zazzJDCkO5d+9sHzG7Z96faNKqgTBgwyG4PfnNRJXWg9ExkMomi+95bs2FWQep/WsbxAWaKSITkyOoi2ZyJOck49q6O4mt4LHzLrOEztPfJrmNPimmv7i8uFyyqEt946ZHUUQu7iexatTJNKvmRqnnAmR8HAIHGKWSc4eZpQhK9cD6YqGU3a2hgLkAjcsisT83Tr6VFPCZJo4pbiMRkBVXH3j3PHvVct22KxpQ3DbIraXyWZcbNvcEd/ekhgRZFQElICQAO9VPK+zRAqNshYAPjnH0qxLex2c2drMhTgEcj6CjYLWCOV559+7L7ckquM+lW4onDqDK8jAE7XUHmsaCXIBjMhicYLE8KQexrWZ3VrdIpxH8p3g4JNVJdCdwTUWgv4VnBVCCBt6kn1qmpmumBvJ5Iy8pHdcgdAK0Fs1Pl3JXzWXlV9/WnsZJQ89zbARoCwVuoPtU+6ndDsTSXCQReUmdoGACMtn39aqIHnkiln3R+WxKrjjPqahiikDeash80DJUjPHse1LDHOB5VxCFDZbEjZP4YqVHTRku5bmW3N28kkZcsBmQnoelUoo4LK+glWQGBGLElM/r65p7hWUbDOygchflAqrHeSGRbKI74WPzKRkgDk81cb7Cb6k+oNdzH/R7l1jZmaRk4IB7ZrQ0bU4SYLBLZ4sqxU4OMD19+apzXcEJaSG2mVVwA2eG/Cmxz3F4n2lZTblfkTgZx3NDSlCw76ngDPjqPwrF1LCanu6b0XbWpMxI5IJyTWLqRJvIm+YfugPrzXgK+x7VzEudSf7Qyh2AVu3SojqMu3Anlx+VUpZA0sjZ4LE4ojjlm4hilkI67VJrrVNJbHN7Qti/l2kGeY9wC1Qz3c0kRQzykN1UtxST2t3bANcWs8IbgGWMrn86qE7jyapRT1InUdrFpLyWGMRQyuFIwf/rVJBeSW64jnIBOduOlUl4GaD7E0+VdhKbWpqrqMp7xsMfxUovzkEorcdj0rKJA460ZGCeRj0pchXtTbS785sAEcc55xUVwV2sBn+lU7GQjzBv25HerE7rtO0g5FRs7GkZXVyrIAVPsKqc49qtOTtHNQAZU/X1rSOhjUV2MQkOpHUGtFbVru8EQcKSM+tW7HQDMgluJGjU4IVRkkUXCx2zS53LIAfLYHBp819EOFNpO5kHEVyyyZcKSPyras/DVxqPhuTVbeVcxz+UYXON3TlT+NYQ5Uknk9a9TsbMW3h/RNMDYMhE8gI5Ofmx+v6Vai9GRDW9zz6+s7zQj9ku4fLnliDjDg4Un2+mKyq2vFd6dQ8TXsmCFSTylBPQL8v8AQn8axjmiW9jNhkeleh+E5tOPhyKDVdMF1F5rFWEYYgZ/Md688AJz7V3/AIYdxoMBU4O58fnWFeTUbo3w6vKzL+reGvBF5aSz6deXFnchSEiG4oW9DuGf1rno9E1XT445NM1mGQ94klKlT1+6eK7D/j2jYxhSXO5twz1qFpnVRgIpzkEIKw+tTj7z3Oh4eDZzcPjDxBYhRfWbSRj5dxQqWP16Gtez8e6fMuJkNvKeu8ZX8xWxHqV4sZUTjaeoCCsxvD+kaiX+0WYR3z+8i+U57n0J+tXTzHpURDwrt7rNzxRrp8X6LYXKpb+TpFtNBut5NwYsqjn8F6e9eUXUG+2lkHWNU49Aa9O/4Ri10Xw8lpa31wbW/kE0vm4DKFHQY9e9cDMiLLqdusTASIPKDHk7Tn9cGvbpVXUw0nFaW/r/ADOaUPfSk7Mv+Er7TbSLVhqOpPZT3lmbOFvJLKA3ViR9B+ddh8MLqHSofJnmiNpcq8LzH7vDE5zXm+nxrewTAMIxbRb3L9+3FdZpDW9hoNvY3jxb3BcYcHcrHIO3rXJBwTfM9ymqjtKKHG+g1DxBeyWkCyWtqn2KzCdCik5YY45PNbPji3ll+FujQQ2krGK73SKi5IG1sk46DmqFtbWaoTZ7PLOQRFxj8ulVJtHUBvs11fQb8htty2D7GtZUbwUYvYj2urcupueNI4vEbaLqumJb3VlDbtFKsjqBG2B1BP8AnFUtNn0oeAfFOn2EQLBVYSA8SOSNwX1AA7Vz83hyyxGDD8wGC28/N9cd6Q6NZvEkckIbyxhcEjH5VDw8nHluN4mPNdIiv/BqYjksJAYmgQ7pX6yYyw9sVa1/xFCPh3p3hmWZLrUba5aWSVW3qi84UN3PNVx4f08EA25z7s2KdqNhbDQblAiIYxvTauORUyoNon6wrvlVrm94q1/SPHuhaZdQXdlp+q2amOdLxtuVwB8pwc8jP41Q0Hx3Z6b4eufCWotLdaLKjbLmGILLCzHJ2gnkZ5yec152KeFJ6Amso0lKOpp7eV7rc3NXv9LffFYPfXiyN8898w3gA5AXGce5qPxF4kk8RPbvNZwQm3hWBDGSTsUYAJJrHKMgBZSM+taVnpiDT/7VvxKtj5oiXy+sj9So9OO9W4pJEKUndLqZaHawNe9eCLWaz+HmlLOrI0zSyBGGCF3nBx79fxrw+8W1N3OLNXEGfkDHJAr3bwjqdxqvgTSrm8cvNE0kO8j7wDcfp/Ks6sP3TZph376NUfezyVHYms/xHpTa74Xv9PEXmTsu+DJ58xeRz71o8d8kinKSvJHQ+teYnZ3PSlqrM+ayjwytFICjqSrKRyD6UwnBIx1r6E1Pwro2tW13G+lWwvZo2KTquHD44OfrXz68bwzNG4KujFWB7EV6dKr7RWR5lWl7NjfrVi3tnmYBSu31LAYqIJuA55q7bRE8cEE/hWj01JitT034Cahb2HxAn06dA73dsyW8veNh8xA+oB/IV9G3V6LVRbCOaR8AIIiCxA459K+O9JupNE1/TdVi+9bTBzg9sgV9f2dtp97Ha3sMJdZ4RIs4YjOQDzz3rR2cVNkyikwLX9xsNrDb2rAEYlO5gPUAcVDe6leaXcojsl4JtqoqgIUOcEnrkcjip5LWJYLgbpGl2YCqeR9Pao7OGGRwphieZYw3J6EcfhzUq2/QRiQyW1p47uJrZBO8sTCVpAN8ZB5VcD7pIHWtyRbm7DOtjHE7DCNLJgH6gc1FPFepqLXBj85jGI0UAbVPU8/rShr1pEhiLKyNl+QcEg+tVbZpkxsrlJmu7G4ZjZxo2cEo+QM+lWFuILkRJcQukoOVIzwPesfVbvVLcCxubCabbGGlkg+feCcBsjpyKv2uk6hbOWupgkZXaNvzNkkDJ/CtLK17g2a8afazDKWTIbgdNy/T1qQW8dvM6rJMVbgKPmCZ9M9Aa5/VvDV08kMkcwnSHJEbDB+ua0he3NrZR5hEKDhjMMDPtUON1eLFfuWmjdVUyPISWxiPOBj2qG3W2mmd4Y5QqDBcL88hJ7HrimWurQyXMMG/HmZCqxA3n2p19PdW8klxGkS4iYq0hIwB2H1os72YIgtJhAklrMYpmJLMoOVHtzycUsE8VwwKOY5ZGyQx2jjjNZVhNI9pHJPGhllPJxjAp4AEvkbI2QMC5ccYzng9q05bCZt3SwQ2yxyMrFwW3AenfPpSpcCbyZbYq++MRsC2Ng65xWPcuG/0eMBY05jOc7vUVLakRzW2EEg2gM+cdT6etTy3Wu47kV+0er3cISVVhJwy/eHB6UxrAG58s5kiQl8B9uVHbFWbLStP0+88h45Scs/3iwLE9eKrSNFbyyyCWMMzYUbsHHcflVJ9Ii6ai293aiXyoLdxbhCqqfmB5znnpU9xZQsgaMMItu+PK/dyfmGay7e3unctbH5JgcFUOVA7ZrZhWa3giFxdHbtPloFGffNOWjBMyLbyZtRltnyBEd+GOSRjgip7qGe/2I2YoADlvU9qmTSLG4kFxbSSW08/ysS27eB1AH+FPjsjEiyXMUzXCZXYuSGXtx64qlKLdimvdvchtPswg8tVZI0HHq5/GprS4uNgdoomZQS6jtnp1qa4VJoFiktF25xkuQQO1OSxmRkffGoQ8pDnBGON2etEpLqZrYgt47lrlhLsMeCxQk5GemKtzS21wWZpZVzg7VOF4+tVB50lwk8TtF/A2R1qwtlGWM0szR5/gPP+c1LAhkugtyVjjlAY/wCsZcqBjHamXY1W4cS2iQMV4Q7sMR0PGK1Ip2KssCSbk2rnjaKZ8sg3xjO3jy+mTUcwMw5NLZmB1C8kWRRuC7tsbH04q9bz7P3SxrGGH38DAFaa6fa39lEs0boWBIUMflwe2agj0aS3lChVkU5/eBsH8RUOd27icXYZIVKsi+WUUAAg8H3psm9BloDHGV2gnGc1HDYT28sjy24KKcr+H6VORLfFXkdgobIQDH5j0o22Js+p80XDooDZIrA1i5KxpKnJQEe3ata8Zemckds1zWrSMyqM8EnIHevHp6tHry+Eg0/WZNMl8yK2tps/wzxbhVmbxhrUpYR3It4zx5cKBQP61iEZqV932VD5CqAxHmjOWPp1xXfZPc5HKTuSXWp396ipdXk86qcgSSFgD7ZqpRW1pfh2bVbI3EUoXDlMEe31oukJKU33MbNLnj0rqI/A1+3WaMc9uR+dVdZ8MNo0UZlu1eSTO2MLg/zqVOL0K9lNdDAyPxozTmj2jk4NNAyasjXYs2xIDHHHTJqR8AlsdRUasMKPTtSu7njHQdKz6nRH3UNLZ7VLp1uLjUIIcEq8gBB9O9QZOBx2xWt4Xi83W1ZhxEjOR+n9ab0TsLeSZ1UkZDkYwB0B9Kw9WtgzOzbVH95h0ro3QHjkHHes+98tSySqCvcHnNc0JSUjZnK29jb3er21pC8hWaVUPy4wCeSK9Ov7gW2pXd5tUxWFqVXHTOM/4Vy/hXTon8VLcK5aO0iMh3DGCcgD9as+JbqS18OXcm1Q9/dlSR2Xk/jwoH4133v6HO1yps8/kcySNI3LMSSfem4pKKh66mAvtXo/hjStSTwj/aEmnzizjdm80jA28fNjrjnrXm9d3pPi/ULvQ10m41cQIoMR3oCWixjbn/JrHERvA3w7Sl5nQkgRDHPHy4qFv4G4J781BaXUI0+KJJA4Qbd4YY4qVhuzg9x0rhs0tdz0Ha5Ko2x/jk1YtoyRsUg57E+vpUEednAIByDnvVmxlVLyPJUAHkEZrn5W5aF30G67r2nX9vFpNpK7XNnC5lYL8oOMEZ9q4fSrhYvEentcsHiDgMSexGP603Srgp4vvY40Li4eaMDpjJJz+lZ18hFyY2G1lOCD2r63LYL2LpHk1qnvqdtjVskit59dhkUKDavsDDqQ2R+ld9P4P07WfCuk7/3N6tpEVuI8ZHyjAPqK4vUR9stbPV7eJ2uEPkzqqk8KuNx9j6122hXrX/g+ymw8UkSGJl7jacD9BXkV+aGmzR6lJQm+V/L8zgNQ0TWvD90zys86k5E0JYjHvj+taGm3dxfQsRdmTb9/d8rD04HvxXT3N3OF2l2ZT2PIx71zepWkUEMt7ar9lnHO6A7dxyOKwpY9wfL1/A3q5deLb2/EtPZao0iRxQNJIxwig9an1n/imZIdPWOO71eWPzpGnXKQKenTqeta3gyW4n8RgytuFvCHG7n5iSCa5O/v7nU/Gur3EhywuPLA9FQ7R/KvZqSbqKn8zwYxjGDqGno13qPmyx6i8s1lLCwDPEFCPjg5GOKv/De1vNQ1547q3Mi/Y/MRJUGA27GR+H86oNe3TAw+fuTHMZAIxWp4F1C6h+IiQ+eQhsGyo6HniprQ5YtoVCac1fU8wktbqbULhYrffK0zKI1G5i2eQAOTio3guoZGinBt2H3lmBQj8DzXSJrFx4Rla5tFWPWrmVpHeRQ3lx54A9yck/hXe6vpVt4h+KXhW/liDw3lklzOMcHYpYE/jtFcntnH0Or2V723PO4/Auu3aOUNq1wkIlNsZwJtvb5TW7d2+np8I9GW9nYCPUJNxtlDsSQTt5xgjPJ9u9N0a+On/En/AISjVb23jtI7qUuPPDvtwyhQoyTxgfQVX1gRXHw2jaz/ANRLr8xhXGPlKcfpUyk5aMqMOVN21t/kcVEqF5dgJTDbdxwcV7f4CIPw104FsEXEoA9t2a8T8ohXKg4UAE171oMel2XgTRV067E9uC/mSkbS0hbJyO2CcfSunEU2sM2ZUf4qRod+hwPSngggDPNRiRSFAYHPcEVJxt6nOa8ZaI9MmjYidHGM5APvXz/4xtUtPGGrRR52i4Lc/wC1839a+gEBM2DgfWvC/HMJPi/V3PVZVyB7qMV14X42cmJV4o52LHynHStG125AJOazImKkYGfar8T8kjIzXW27WOSLszUkWJ4tpXdyOPWvpD4La8NX+H9taPJuvNNY28yt1AySn/jvH4V83WgARWLBn/p2r1n4Gai9v4q1LTyQEvLdZSpHLMnf8mq6V5QlD5/d/wAOXWWzPeViXzDIVG/G3PcikEEYBAHBGMegqnBeW811JpnzrNEgdge4z2/GtGs3dGFzPkSW0tZ7k4Z4wziNW+U4Hv3ptq8tvYQy3Ch5JPmmfbjAPr9OKdfXe9Da2hjkuJBt5OQgPc1mXGq3FjdRWtzGlygUJMU4YMeQRnrVxi5CbNj7U0IIliPPK+UjMMe5xxSXSTTWhBCiTPy7CTxQuo2a2vmm7jKKCSzMAeOuagGv6UriMXyuzcjaC3X6ClZt6IPUvKGSTJ2kMANwHJI9ap3DCWMwyMknmYVVK5U4PWoZvE2kxKcX0RYEcc8DPXpSwiHUGF1aNG0C8IFUrnPUmnFNayHoZ/8AYcUGoNeW0pMUBV/JIzyPSnXrx3lvdd/N+WPHUDjJP0rVjt2t59q/6tlwq9frmud1a0l0+F4d6mKVwqDncU6kZ7ZraEk3qxMfbtbpZiMtE0QACbTgue5qfEEUSRKVW5kbnIyVHas+K1t4tLi3JFGiD5EJJdRnPFWVubgWaSW8Ss0YIKyDJYdjntWko3dyfQhmQ289xctECEGVLLzz1I+tVLTVFvIbp7dGjuI8AAnCuT6e4rdsG1CTTGuJoRG6kvtbncuOQM1Xh0kTWUMltCq723vgbW9R1o5khMRBcTSRTGNg0yqC5BXbxz0p62FuxRJbqUvv+Qqobn34q9LFdIQzLuUAqApwSajtTHAI4pY38zkArztqb3WgbEQ05razEs087cjO48KCemBU4t4EnIiiCoRkAcg+9S3O544bZX80yfKWPHAFLFb3EgiiEm1IWAO3uBUc2l2x2M+/h+2uEgVhPAVaMxnb8hPIFaKaXJ5QzcMHBJ4J49s0gt5riaG4MzREH5YUGBtB71cDuPldyDnjFKUmlaIIqzQXZmQQkKqAbgVBDH1zUdxPcKZI3jj8gkKpHDCrjTgsYuWYHlsYAp0yp5e6RQwBwAOpzUJ90FjPgjlIkZkKg8Ehs8etMjt3EPmQThssSpb09KtmDMciiQ+Xnaqlv61B5MoZRMpkVG4RBgAVaYWGrNJEqhYFdsZYnoc+tMiVANxXaWOWzyFqbzVd1jCOEJxubqn1qRlaeImNQAeNyDrj1p3SFYu2gT7NGFYttGMkYNT1iTtPt8pJHieNQWOOv41K91exShQFMSqCSykt0rJ0763K5tC/dSRLEySsFDggZOM1mG2VHWMFvMTrt6VaS7jvrV5GTZ5TjBbnDf5NQxXJuGkKEuc/KoHvzzRFNImVmfKF9Jhz7+npVfQ/Ds3ii+njWQw21uMs4Gcn0FJqEnlhvlzxhcc5Ndz4e065tPAkTJrI03ZI8s8ohV1Iz6n8K8rmUdj14w5tziJ/hp4hSQiJIJY88OJMcepBqza/C/UWOL69t4B/dT5z+XFehN4auriMF/FupspAKmMKgP5VUfwRbST75te1KSYfx5G/860daVtAWGp31MG0+GOmwkNcz3Vxjqq4QH+v610VjoNjp1usNlBsRW3AEk5PfOe9N/4Qu2Ugf8JHrf18wAUyTwRYyHf/AG/q248BjgnNZyqSfU1jShEvmzG/BTC+wxivNvEqi88U3czDMMUarHzwAB/jmu6n0fUNNWKLT/Et1cBid8d2gYEAdAeorjdScDedvpnitKSdroym7aHE3AG5x2B4xVdetW7wbZpBnqc1UWupPQ4Z/ES9s4BoOOoOKaAvXgD60pK8880i7gMkcHiuh8GJnU7pwM7bc/qRXNjkYxzXWeCFHn3746Io/Mn/AAqal1F2CDvJHSlTjJ6+lZGoKQ4Pbpz1zW4wB5IGB1xWPqZVIGJyQASayg9bs3krD/DIWHRdYvsMHeQwLj2HH6msvxrO6fZNMGPLggWUn1Y8V09raeToOkWiHO9/OfjnHLY/PFcd4mnS51nUHUhwsCrn/gS9PzrrT00MZq6sczRT3feANqjA7Cmg47UjmEr1zSfAq2PhhzBBY6jrF6oVZJGBS3yOoyDyPpya8lPIJxXtSanDaPpVjKkyXN7ArJ5SgomAM9wamUW/Q2opXMHwfp+lppmoWt5bwTX9rdtE7cgqo/i/Eg/lVHUbVbbzIY5GhySyFW9en5Ve0iAWnjrWbSOMxw3MPnxhj1wR/UtVXxaWtbu2tw3lvccsVXPyis5RSldI6ISbikYulSzyancw3FzNIiKPvuSK9F8N26AQgoMbmAIGeAa87stPa3u2kW6DMxx8xxu+tdnbOlgsStLcSyJIX4mVVIODg1k60ItO+5cKUno2cjoUq2/jy/f5flefaG47msrUis900sW4tIxJLHrzXa6uND1HxNFcaXvi1IK32uCOPbEq7cbgT1Y5GfWuEuGZJEAboTg9ute/lbUotnnYiLi7G1pd5f6ZZz2bwBra6Gx5FzuT39xWp4Z1u606S8sb6GSSBsShx8xT/HtWbDIXgQse2OnSoodbfS7hWglfKHJiI+Rvr3rLE4B1XKcXqzrw+K5FGMtkdPLqmnXhVIpgMHkONp/WsTULqC5uIdnzWlv87HkFn9h3xVyHWbfW0DS6ZpMk69ppSjfmRzTjES/lyQ2FkAuFKSs+M9xxivB+rzo1ldarzPXnio1KLi3o+xoeF9VttP8AEUU7TBortRArAjCsMnmsvW9P/sTxxe5fNveA3ETnodxyRn1Bz+FTJ4esFtTEZzIrNuLZAyfWnyS6jZQ/Zn+xatZZyqXyksnsCK9qUfeVRHzqkuV03t0I43R5CquuSccc1c8Ev/xddS5/d/Zm5zgbcD+uapIst0pCRafpaEjP2VSzt+J6VZi01rKX7VpesvbXYj2BzErnGeRk9qKn7yLQoRVOSe5wmvTm917UJ1IKtcPsA/u54x+GK9afWYdC8S+BZbtvJhTTBBM8gwq5QdT25xXmuoaLq1ncm8SQTuDktbpg5PfAFP8A7K1fUoUuNXv3jtg2SbmfLj6Iec1w1ElFQbsdtFyldwV2y3r/AIQksdWuJjeWksEsheBbeQO7KxO0Y7cVTvdUtV8HWehwSSvPDdNcSNswmSMAA9ciifUrPT7d7XRIWQMNr3kmRK47jHQDNYRPNduGw05q9TRdO5FecIaQ3e5asRDI8yXHmEGNtgj/AL3UZ9q+g/hLa2sHwqt5p9OW+W4u5WKuQcEHAxnp0r56sHWO6Dv9wA5+mK+jvg3FeTfC+2heLylW8kaFpDgSL3I/HI/Cu2rHTXY5Yt3utzpDp/hWZw13o62zsM8g44+lNbwt4fuN4t9UuYG3DjdwPpkVuiyuMBZI4JBj+9k/ypPsUT/6y1O3/dP+FcsqVB62/I2+sYhbsw28BTbRJY6x5ncedHwfxFeVeJ/gz44u9X1K9gTTrpLp8hY5tpwOB97GDj3r3NbCH5TGZ42Q5BHercMU1vKvlzyupONr8gD+lYqlCL5o/wBfcKWInJWmj4c2lHKsMMOMdKsxcdWIOOMVv/EnQpPDvxD1eyc5R5zPG2MZV/nGPpux+Fc9E3IIGeORinNWbS/r+kTFp6mpbdAwAyeM10/gnV20bx7ouoyyNHAs/kysOcq424+lcjA+WAzxn8q1Sf3O6MCRkxgd89j+dRTajNX/AKRq7OJ9aSQLb6w2rNMiK6iJVAyXX/8AXVn/AE2+nIysNl6jmSQY6egGfxrnfDVvB4n+H2jXFvey8xKwlZdx3g4bIP8AtA10mjWl9Z2HlajeLd3G9mMqpsGCeBjtgVdRKKs3qtDntZi2NjBazyNaoEhxtwCTls88n8qsXdnb30BguYw8ZOcZIwfXIp1tEYIFjJyQTz+OalrC7vcZgDwhYBgTcXjY6BpQR/Kp7bwvpNshUW5f3dySPpWxRVe0n3FZGRL4Y0eVg/2NUkAwJEJDCqOoaBfraxxaZcoNjbiZGKsecjBHf3rpaKaqzXULI5eLVdQ0xdupK0pOPkwAwHfDdGqS41iPUh/okbsIwHIljxz6YPtW9c2sF5A0M8YdGBHPUfQ9jXJy2z6bI0fnEKkv792bDMh+6xP0/WtqbhN6qzE7ozry4udQuDPIvlKnymNep9Ota+jGa7hkYOsMh/1ZIyGYeoqpdyfapFingkGMbZW449c1Rv8AUYrCcPIGEflqqRRt1O71ra11ZE9bmneXupNPBpc0awuZVZpAfvKBzitnT5nulNuFAWJsF/UdcCua0+9l1bVr/Uri3ZPIj2xgAlQenFawsphaXC2a7J9wZVQ/LyBxUuKtZ6Bfsa87RJHLcSHdHEwAG7jOR/WqUKXLy3ilGU7y0YJ5w39Kx21iSBo4L+3EQSXJWRdy8d+PzrXu9QT7RbX9pLK8Lf61tnyqnbqOMmo9nKIXW5YGlS/YbVY5PLmhHB6j1pkUtxb2rzsTOHHBQY+pPvVuSZ5rZ1VWiTIHmA9B3PtUkEaxWoWLEjIo5H8WO/41nzv7Q0kQafcBk+aX5Qu4iQYYfWraKzA7mRtzbhjsKJoLeRGM6IQQNxb26c1CtoqjNtJtIz97kHNQ2m7jsxNjpueJ12u/PHApZVdyC0m4J8xG3Gajlu5bZCklq+wDAkjGR+VT284uIjMoHJ78ED3qtUri8hsbea+diYUfLt6Z96fNvLKAuATz6k+1RLbqi+Z55Uk8FTx9MU4x3By3nZ4zkqOPpS0uGo6ZF2mWYbgOijqKofZ3UloJmDSflV6TCYZ5B2ySKk3ojKAcKVyDimpNINygrXsa7SrSBCCJOuaJ+Q0pAebI65C4q+k6twqsT7Dih4Vch2T7hyFH8Rx3o5tdUFrlae3M0McaDymk5YY449qjttPks4Zyrq0jHKEDoO9TxxDzN0jM0rHOCOgqK4Fwu/YJSAdxOeMegoV9ri5Ve9j4+vpACgVwF34f1/CvT9ejVPA99CnCJZZ2j2Gc15Vq5BRiV5yDmvW9WUTeFdRRS2XsG6jH8NeM0k4/12Pai/daL2nSmTStPkThXt4yB6AqKydHmkfW9cglnL+XMpjJb7gI6Vc0e8hfT7a3V0MtvaRmRT1UFf5cGq1jYS2+u6tf7I/IvREYirZztHOahcps92aLF0ba5wc5OD/Kl3llY5AwKXd+72vhge3pTXRlBeNldWOCp+9mqu9USypqBJe22s24hxx1zivMtRYsO4YMcj1x3r0i/dgbRQuC0pzkf7JrzLVpSsbyDP8AEpC/U1tTvHTqY1Hc5e8k33Df5zVenOdzk02u1KyPMk7sKVTz0pKB1pgtx3XpXZeBUPl6i477F/nXGfSu38CD/Q704/jXn8KzmvdZrS+NHTsvy9BgisPULf7TeQ24UgTMFyv1roNpwVwcHv7VUtYQ2voxTKxRliR27VzrVpHZLTUl1K5+z3F5dL92ysyqLj+IjP8AhXnnhgh9djjfBWRWDBhnPGf6V1HiC8EWhTPjLXs7LnHOMHH8hXJeGzt8QWhJxy3/AKCa7muWN0cMn7xJHdW1vc6ikhwpkbywF9z+Xas27mWeYSBVB2gHA70k2PtE27JO44/OoalIhvoFeraDrNnqNjNrUww+iWCxYI6s3GR+RH415TXt/hXT4P8AhXun2d1bxSx3GZJFZfvgsWGfXHFTPY1ot30MP7Rb3vjDw7q9tINlyZIJMNwMA4B/76P5VW8QT215r880epW22H9ykfmDPHX9az/FunWUFnE1lbxK6XexreLqQQTkgfQVk6f4L1O8VZZwtpCwyDJy2P8AdH9cVUYuTuhufLodCk6WqSXKwwPJGpZfNXILYqh4Z0WOUJqmoXLlb1ZFiFupZlcNyX4wBwfrmupttKii2ZXeQoBaTkN+HatNLZYwQQoX+6owK6KeGa3InPW6MUaFDZ3E99DP50jRCMNIpyOR789BXn1+jQ3bxn7qOQDj3r1y9RIdKuGGFCAZ56c15HeyvIW38ncQPpmvRwkFBtIyqTctWaltPEbZFEyl8dAf6Vnamh+0Kw5BXFWG0u0lhD29wxOO5FVn0u8iA2sHA/ut0rovrchvuUimR90keuKuQ6rf2sYRbh2ix/q2PykUjfbFthb7JFCkltq53Z9ahzGQA8BXHVsc1yVpxbcZwujppJx1hKzLw1mBifN0yA56srt/LNXV1nTyCMzxj/ZjDfzNYPlIUYkkN2A6UqwxFVDOyyFsdsYrkdKinomvvN1UrPSVn62Oij1rTVcsZ7t+nHkKOPTg09/ENpHt8qw845583KA/lXLhVXcCAcLwc85qY3LG3AWJABkEnrmkqNOS6v5sn20ou3Kl8jffxLeOCLaOKyz/ABQlif1rCu5Z7qdpbmVpnGMs/Jp8d7bLKh+xowULgkHJPfPrmr9lpuq3YmW3sHVJOrzZjGPQZ61UJU6WsadvUqbdRWlO/kiikLSDaijpuJY4AHrVFxhyCR+Brr28OanezHzprWFXAV1hLSNgewGD+dX4Ph1btgtLqLAjOfKVB+tEMxineb+4znh9FyHHaTavd6jGkdv9oKgv5WcbsetfR/wv1m/8ReAzcX0NvFFbXBt7WKCPaoQKO2T3Jry5PBkenv5sEbRnBGXv0TIPrjmtrSvEfifwtoi6VozeHYrJJGcGa48x8k5OTmtZYylKOhn9WqW2Pd7eK3igD2aIsxGCXG2pgl8Mf6QuPUsD/SvCR8U/GsIMUz+HpVz0AbH86I/iv4vjPzLoEiZztMZB/PdXPdN6v7y5UpcqPfmmjjTa7GVx/eXjP5UnmN0KKoI7dq8Tg+MmvxN+90PS7oY5ENwFP61rWvxvjTH9peFL2L1a2lSUD9RU8q6amUqc7bHM/tHaGU1HR/EKA7ZoTaS+gZTuX8SGb/vmvEoskj+dfRPjfxv4L+IHgW/0xb57XUYV+02sFzEUcyqDhRng5BK9f4q+c9ksBCyK0Z64ZccU5RaSTVv6/wCDb5CjdF6AEtwcY6GtJOV+8QfUVlRSZBKkdq0rZlJ3P+FYydtTeL1PfP2fNYS48KX2jE/vrC434z/BJkjH4q3+TXr9fMnwe1kaR8TYbXcPI1aFoW9mVdyn8xj8a+m61xGrU+6/4Bz2s2gooorAAooooAKKKKACuU8R2t1caugjtriSEwLlokyC289TXV0VUJcruhNXOKvppgskb20nlK/yrKCpB9j6VTtNKn1i5t55LKQRjILSLgdevPXpXoNFdH1nSyRHJ5mHam5S+YPahVVvKOwYDjscf4USG4t0eUrI82eIooyQO3atyisva63sXYwIwJtMMd9Y3Uvm53AR/N16+orIniv7KForGxu5beRslHQ5C+n1rtqKuNdpt2JcEzE0mG7UbpEeMOxDA9Rxxwfyq/JCUmaVfMUEgbY+jfUVcorOVRydxqIzy42GCgIBzyO9Nib7yCNkCnjI4PXpUtFZlEamUyNuQBR93Bzmqv2PzmPmRLHk5LI3J9ulXqKak1sFii9tdo22GWNoscLIOn6U5bRjGocIrA/wHirYByTuP0parnYuVFdbONX3Dj2xR9lBHLn29qsUUuZhZFdrZyf9cwHpigWvCjzX49Mc1Yoo5mFkRpCEBG4nknNO2dcsSD24p1NMaEglFJHQ46UrgfEmr8o+DwAM46Zr2bEb6WBIPMVrZQV7P8vINeK6kfkkG3HHQmvYtNZZNEsgJQ+61TLA/e+Ud/WvNqRfKmj1ae7Mi0mFm91d2dtGqS2sK+W78phiCSPTn9K19OZ4U+zBV+zRwqyMB1OSCP5VGdMtJeryhjGsbHIztByP1qxBALeTcsszrjbtkbKjvnHrWaWl3ubyfQnbKoN27J+6R3pJCRtPHJxn0o3FeO+OCDUcnKELkntzTciblbU2Zksst0ucHb6bTXk2vT8vGucCVh6cZr1HV51hOmD5cNd7ef8AcY/0rx3V5zLfXBJ4ErAY+tb0Vd3OerKyMyjFPIAHOKbkV2nn2sJRS9OaesZdHZeiDJ/PFFwSGdDwa63wRfRRy3NjI6o82GjJOMkdR/n0rkqFZkYMrFWByCDgg1Mo8ysVCfK7nsbfJuB3Z6cCoN3kWl5c/wDLQxmNT3Hp/OsTw74mTUoFs7xwt6MBXP8Ay1H+P8627pN0dpbngPKJHUnHyr/9fFZU42lqdkpKULo5PxTIY7i1swSFgtWYjPcjFc7oknl61aN/00A/PitHWpzPqF9MXzyUBx1A4FZWnLINTtikbMyyK20D3rqeqscj0ndkNwMXMv8Avn+dRV0Vn4UvbyV5LgiBN3I4Zj+Ga6XT/DmmWIP7nz5s5EkuDj8OlONKTIe5w9lo+oagN1tauyf3zwv5nrXrVtqk1tpVjp1rar/osCI0rtjLAYOB/wDXqmGJUBuMVNGBGdwfGOcmuiNBdRxk47DIYI45Hn8tRK5w7gcn6mrgVdwUFRnk5p1laXd9vFlbvN5eN3OBz0rTj0eCzWSTWdQigVflaGI7nBPTpXQoKOiEUNyEbUy0h6BRnP0q8llL5RkukkgjA6shyRUsM73TY0OxkVQu0TOcFSOpHrmpQluDDLrOryT5BIt4z0PocVcewO3VlPWzoK+DNWSC6mv7prRirbCBGcdxXiL7/ITd0xxXtuqalCdA1S3trOG1tZYHRyRl8dzmvMIbuxGmQWl1a/PGGIkf7pyCRg+taUnyN31JnqjnlX5Gb04p6XU8f3ZW9eTmth9DguIdPktbsBrlW3KxBCFRk9O1ZMVlc3EfmQxGRd235eTnr0610KpF3M3Frcf/AGlc85cE+u2kGoSd0QnuSKr+VIER/Kfa5IU4OGI7CkwQehyOoIqbK4a7kxuyVx5UYOckgVHLMJcYRVAHYVGTSUtEFxc47D8q1NE0ufXdQjsoTHGGOWcr0rLPQ9K6nQbn7PofmQ585JW3beoyBg1hWquC0Lpx5nZmnBpdlouoOhjRnhORK3zOT7DoK2RrFtbx+d9hW6lHRrpyBn2FcwJBNcFU3byMsx6k/Wi0FxOlzO53pGwUZ6141Sm60rtnfBqCN5dY1a7IEV+LCPsLdAoH6VDFBJeMy3d/dXb5AyZGOf5VnwLNI2SQqnqvpXRaTbKgj2Nk7cniurD4ZNmdSu0jY0bwbZ3EqvHpqE4xumYEHn3zXZy+Ao20eGeKx0uNi2CDH0GcZHFQaE6wqH3D7mTmuzvWe38LWgkfy3eQcn33EV2zj7JRUerSOJVJTk2zzm88DEIyK2nBiOCEPH6VzV94LmgDFFtSc/8ALNyP6V6BqV4AxAcZ+8GHfiuU1C7laNhuIYnt/WsKyjbzN6bkcFeWDWspDGMD355qkA65ZNqnpuRsGtrUka4jkJbORx2rnY9JZrnfHI6uT6ZrlSlK6N3JRV2SSXVxt+aUyYOQHANRy3InyswVgezDIratdBN06xvu808ZAPP4VvaZ4Rju7u808kebbx+YJMcLxxmtqdByMJ1Ynn8Ohx6pdG2sCqagctFAek2BkhfQ1St3UjDgo6nDKeCpr2Lwj4NS1l0jxxqd1Haafp8cst0JFKmQgMFKj3rx2+1BdT13UNSjjEUd1dSTLEOiBmJwPpnH4VFemo6LccWmrrqXYbyTSNRs9Yttwls5klU5xnBHGa+0LG8i1Cwt7yBt0M8ayIfYjIr4qzHLZPEx2qeh/WvpX4Ia6NZ+G9pAzEz6e7Wz59Acr/46QPwqdZUn5P8AB6f5E1PiTPR6KKKwJCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooARiQpIBYgdB1NczrfjCXQ5AsnhXxFeKxwHsbVJwev918jp3A6iunoqotJ6q4HmGofHLQtKm8nUdA8SWkv9y4s0jb8mkFUW/aK8IgHGna1n3hi/wDjleu1g3PgjwpdtI0/hvSXeQku/wBjjDMfXcBnNbudB29xr53/AMhWZ5s/7R3h/JEOi6m/pkxj/wBmNVX/AGj7TGYvC14497gD/wBlNdXqXwN8C38RWLTp7FySTJbXL5/Jyyj8q56//Z20p0A0vxFqdqe/2gLMD+C7KVqLe9v6+Y0ZzftISAnb4NkI7Zv8f+0qX/ho6cLk+DJAP+wh/wDaqzLz9n/xRbzn+z9c025hHINyHjY/gFb+dczffC74h6erM+hC4jH8VvKjk/QBs/pV+yp2bTT+f/DMTZ2kn7Rl6SBF4QC5/v3uf/ZBVaT9ofXT/q/DNqv+9Mzf4V5ne6Xr+mwfaNR8P6rZx/357V0X82ArMGoxH7xZT7iq9nZX5dATHXpBR89W4FejeAGU+EIOBuWZxyegzXm18Ax4XDdc57V6H8PJA3hLBGSlww/rXiVNaasenTfv/I61mDZXAycAHFRkgMVbgZHU8ZpTgEgggY6elGR7FewFc+ux0MQOA27A571HliAMghT1NNcmNSWJZeo9hVczblbngcjBq7KwnYo6zza2zBs+XcAnH0I/rXkOoMftUyg/KJnx7816rrhYaWpPIM6AbeOp4rya+BF7Op6iRgfzrow8WpM48Ttcr0UUV1nEPiVXJUkAnoxbAH1q3DEqRXamSNj5QKlTkffFUgpYEgZAGTSUMqLs7gODRVi1sbq9fZbQPIe5A4H1PQVv2fg6ZyDezrECfuJyfz6D9aaTYjC022N5qdrbKxUyyqm4dRk9a9R1KTbqcm1htjhEajGeT15rJsdIsdP2mKJRLj/WE7mz9T0/CrgCL8u4hjzxzmtVR6spOysZUfhu2kk3XMjzEjG3G0Z9eK2olWJFUBsABRz6dKaX8sMzlcY4z3ogJuZoYYCHeZ9kfPBb0zW6hGIrtk2TksPToKCyIdoO5z1VRlq0l0AW9o0+s3iW/mMUhjgkyxI9Tjip7nWbPSrmMaBZwF1hCyXcgJYt3x6/yq4vohuFldjLbw9fXUFvMktr5L5LkyZKfUDpUif2BpxHmyTX9yG2yIqEKAPTtj3rHuPN1Cd7m5ZpJZP9Y6rsB+uKcgBCxq/sMDGKrXuS3HojZvPEVzdW6W9gDYQZyRGclvTntWcgLPlgXkPV2OSajCgnBXn271KoeOcFihT/AGe1Ve1rivcsRPLbv+4mliBHRTgUKQGJPDHkk96rrNHuKnJJ7GoZroxKegA6s1DlYnUl1e4hOmz2qOPNu0MManoSR2rzT7U9uGtLqISKjbWD8lcelXtV1SS/1MTQO0Sw4KbTkBh3rRnl0jxLCq3Mi2OrqQDJtOyUeprJYiCk1LY0SaWm5iwpZtP5lldSW8gzy4AGCMEdatafLqGjPm0a2l2vvwG5PFRal4S1jTSxe2MsQ6SRHcCPXishJZ7RzseSJvbINdKtNe5K68yW1f3lb0NiPVLqCS0WSweSK3uDOI2Gck9RnHTJzT/7Zt0tJ4pYp/NaMxhio5ySSTn06cVkjUbwNn7RIec8nNSjVpv40WQnqWJ5qXCa05V95V4SVnK3yJrW60+3iZ2jjkb7Ps8uSPOX3ckHtxTL+/s5Q8dtbRxxnZjCYbOPm5+tQvqO8c2kBPqQTioje5GDbW+PTZ/WplJ35nEPdStzL7ixfx2UKFYWDkhSpBzg980abc3mmp9ugVvJ37H4yrexqkbgYIEMY9667wPdRT2eqaZcwJLDKm5A3IDVlKo0tVcXKr6Mjg1PSL+XMu+zmJGNoyhNaVtYs02bWa3uIG/1iiXBI/xrhpLcgZUjOSMfQ06IyxxlhEWBPDrkHP1FFXDuLvF2RUKrmuXc9BTTpEf5QVwT8rjp+PetjT43Uj93kZ5I9a8wi1e+hBC3V3GOwDZH61Zj8UarH9zU3X03RgmlGc4a2FNReh71YYFrtBPK4Jx09q6/VNSj1XwPDeRROuyVVKMOQQdpr5jh8feIbcrsvomA6b0rRHxV8VvafYze2Ytydxj8ogE/hV1aznytx2ZnGCT0Z6bezkrx19KyZ1ZtxOelcF/wsLWHJ3/2cxPco9L/AMLA1M8mazjPby4C386wc5Sd2mdCsup1klo8x2rBMxPI2oST+VaOneGLuRs/ZGjHQGcbcV55P8QvEDbxDq8seRgeTAqf/XrFvvEWq6iAt7qmoXI/uy3BI/Krg6iWkCZcj3ke4o2geHSZr/WNPW4ReSZgxTPYRjk1hXvxb8P6PZXNp4d0ua/uLgHzry7IjVzjqAOSPbivF++QgXHpzWhHpFw1q1w6HIKhYs4d888L1PFb/vGvfdkZe4tYo6aTWtT8YWl7Jqt2zQ2sGIYUysEAwcYQcfieaf4Z8B2er/DnWvFE2seRcWG/y7ZcYYquQGz654xUsWn3Gl+HtTgkVI5prEStF/EqEEjNcAt3cpZvaLczC2dg7QhyEZh3K9CajEuMWra6MUW+pZjudyrnn1r1/wDZz1drfxPq+kHJjurdZh7NG2P5OfyrxMHA9vSve/2dfDFwLnUPE9wjpEY/stvkEByTlyPYbQPxPpXPTXuyvtZ/8D8bFTd7H0DRRRXMAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVm6h4d0TVpBJqWj6feyDo1zapIR+LA1pUUJ22A+F7xiWbKn6+td98OXJ8NTr2W6OcfQV59enDZ5JxgV3Xw0mB0q+iJxtkDY+v8A+quOa/dHoUn7/wAjtW5+bnBPr/SmscMTjjPQdqCyKpIOeBz2prHgkHtySOtcq6nSKkrRD5eM+nWoZPLmXJGxl5yB97600tlQc4GOw6VHkoOpzTje24mjM1yMppEpLKyK6MSpzj5hXk+ojGpXXX/Wt/OvVdZkA0q4bsAMkd+a84udMvdQ1O4eGBipkJ3t8ox9T1rtoLVs48TsjIpyI8jhI1Z3Y4CqMk11Nt4SjXm5ud5xkrGMAH69x+VbtpFDp0ey0iEa4+Ygcn6mutQbOSxyll4V1G4O64jNrDjO+Tr/AN89a3bbwxpltguHuHGDmU4X8AP65rSaSSbkyMcnnNNAOAxPJ4FaqEUOxNhUiVERAgAAUDaAPpShiVYbuDwQeBUJYKTuPOPSnK6EqXVmQEb1U4JFXsws7A8qBB83TrjmtC00e/vF85Iore1jcJLNM2woPXB6ilt9dFvapHDpFj9ojXZHcMCGCejAdTUFzqmo6ipW9ut8e3Z5YUBcZz0rTRXSGlHqahtfD+nKs1zdPqV0khBiB4cewHH40h8S37SKLaysrG3RiUhSMMGHqQRwfpWH5caxlVUIWP8ADxUpcAZycjt60rJvXUXN2F8mPLMQpZiW5OQM+lTAcZ6LUfyr6fhTbi4t7OA3FxJ5cS9yOp9KpvW5JaD7QMsQO4p424znHPfiuYbxhaNIwhgZj0G7ABpf+Ehu9pdbSB1z/C9R7WER8jlsdOJO5O7nPHFKZVUHdksOBjnBrnovEtsRi4ilhPHRcirUerWc4Kx3K5b+HuT7VSqwetw5XbYuTzocmQZbsQOlc3q+oNzDHKQTy3rip9RvinyqeCOcHkVz0jF2Lnk+p61lUqFRj1Y0qRkIMD2pWEUqgOgJ6Cm/MBheh96jkODxkVjFFM1dO1bWNHx/Z2pMFH/LKTlfyNab+MhLGE1Xw/bT8/NLF8pPFcqkhXPFSCd9vX8OtKVPqgTZ0T3/AIIunBazu7UEc/LnH0waglsvCcsbfZtSkVm6eYhG2sQuj5LKpH0zUUkMOSdnbineotpMbt2RpHSdLZgBq8ajHVsVC2l2KjP9qwn6VnGCPbkA59KYIoweSabq1O5Kir7Gk9hpSo5Gq5I+7+7PNbvgq2UX1w9tceaqriTjaMHpXHOqAfKTn0rsPh5bvNPqBj6oqd+3zVDlLqwa10RzjEEt2yzfzrX0O5gt7ZjP5bqCf3bSBT1rGk+/Jnrubn8aS2tJb6Vo4du5VLHcccV62IpqrT5ZMzw1aVGo5ROpuo9LuY/N8poQQcEndn261Vj03S2tlfCeaAMp/eJNc5Jb3FoVd0aMt909M1MNUvTGYzcNtYYPyjP54zXm/UZXXJI9OOY02vfh+v5lmXRpP7L/ALTjINv5jKw7rg4B+lVEhiIySSMdj0qyt5PDYQwh2ADMRHyuQfX1rRitLPSJ5GvpEnke3EkKRDzAHz0P/wBf1rrhVlBuM1ft8jy6sFo1LV9DNGnf6K1yYnWJf4n4B+nrV2z8PefpMmsXEhh09G2blUsxbOOn407XtZXUxDFAzNaQrvGV25cjn8q2/DniZPD0sCw6rJPp+0vJZfZ8sXI5CnHr70Sq1PZ88V1/AmEI81mzAXQLm6sr2/sXWXTrY48+T93vOB8oB781PbeC9VuksJUa28q8uPs6sJQSjd8j2wa1zq9tf6DY2Mmk3zrFqUl3NCkJKMjFiFz+IH51ft9b1WM26aVoEFvBb3Dzw+dKFALAj7vGODXNLFVtkjqjShb3iz4Q8N6XFb6raXd4lzHdTrY+Z5ewrIuSyqT9RyKWygs/DljFPrdvayXYvJUkkkl/eLCF2qEI5P096wo9E1q4tfst1q0FvbLcm7KxAswkPG7IAP61rad4Os57n7VK8+ozs2He7+Vfr6mue7cnKUt/6/4BSaiuVIt6f5Hiu71i/cyafp39mi28ycZ24Ujd7gDmvK7+2htL2SCC7ju4lxtmiBCtx6EA16zcXCf8Irq6oVEcdtLFgHocYAxXkUcQcDOck11TmpRjFI5mnKbk92evfD/4OaZ4i8i91DxLYTQnDNaWEwaU8dGJ+778GvpOxsbXTLGGysoEgtoECRxIMBQO1fHfg2zuLfVYryFnjZGGxx0INfV/hi+nu9OjFwcuF5JrWvBukpLbt/W/zM07SszdoopNwz/9auAu4tFFFAwoooxmgBOe1LnnFJjHTgUtABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABSMwVSxOAOtDMEUsegrxz4ofFm20d5dF0d2n1PGGKEFIjx973x2rSnDmeuwmz50ul2tn8znqa7P4ZuWj1VD91VRv1P+FcReHYSnduceldj8M3xNqiZABjQk/ia4qmlNv+tzthO9VI77LK2RgjHPGaZkhMtnPT3qpdalZWnEkm9uuIxu/lWXcazdzZW3jSAE5V2bJ/Gs4UJyWiOidWMTdkcJGXZ9qKOScDisq41q0EbG2DzSKcbCCo+uaxp1NxL5k8huGznluMikYjPXGOoHFdVPCR3mznliG9iee7nueZWEaAA+Up4qDeuR+73jqc0xjlgQrU3O045yK6YwUVZIwcnLceJGJHy8dOtKeU2gZBFRrnlcA8k56fhU6IUQqoBz1qyWCMQqhQMBSCCP1py4ChtvIzjjNMOd23nA44NCswUZBPbCmn0uJi5YZLcD1FOVweTuwehxSNycZG0juaUDauAFximGhIqkcjqevNGwhvmyPakQHgAZGPWlC/KOScdzTTsIcWy3I/AUoIZmGMf0oUHB69fSlCnjgj3x1qlbqFmLltgIHTpk1yvjO5YTW9ngBQvmsB3J4/pXWGJ2G1AxIGORXHeNYHj1S3cowR4AFyMcgnP9Kio1yuwNWOaq1Zm8LsbUSMVUswUZwPU1VqxaXk1m7NCQCy7WBGQRXLG19QRaXV3cBZo1YYxkD9asLeQTEY+U4xzxWOgXcN5O3POOtTC3En+pcMf7p4P/ANei3kUpyNv966biNygc0zYmSDkH2NYqyT2smQWUjjmrCaiSf3ifitKzRXOuxeMJCkA5AOOTVd0kXaOAcenU1JFcRyHCMCT26GrCzMDuyAfpVxbQ9GiicZwQOR6U3btA6e9aI2NwUXJPXHNSwxW4VgVLH1YA4qlISVzKHOAPxqMn5hkEY9a6UW1nPFGqeXC6n5nC8tUH2e1t3YPfowB6uBzRdbDaSOeyQF9+vNMY85444rrIrH7Rb/aIbM3kXIG1OuPSsK40fUt7MNLuUGScCMnFK+omjM+taWga5caBqQu4RvBUq8ZOA4qMWUicz2dyg6Z8s9aki0xLoZglPGc7x0NNozt1RBLJvZ3UYDMWx6ZOas6SkrXx8lULBCdrnANNbS723OTF5yf7BziltXS3uBIgIbGGjl+X8M13Rr80bdTPk1NC5tpZDtv7SfceEaE7wB6Yp+m3WiWlt5c8Mgugx3SSx7sewx/hTrO8twskl1NLG/JjSHL59qzLbTb+9lZ44TuzuLSfLnn3pRXOnGWiKbtsWtVvLXUdQjkLuLdQqF9vzY5ycV2Gj+Bvsc9zLcSwywtbEQlc7iTyCa5uDQbvUr+Vr4LaxAL8sQ4PHQc11ejajfWvhC8s7pJBe26OloTyZOPl/KubExapqMOhrh5JN83U5jQNMsW0trq7tmu5lchY2YqgAPt17101mYfIup4ra2sYrdA7G1i+ZvasnTtLu7axhhMWGAy3Pc9a0IUvbYN5aN852sAOCB65pVVORippO3Q0ltpbuCJ4r6Ql137XHIGcdKdHpsUewzyNknGDjHrzmsO41VLUI1xd+V2A6kc+n1qmPF9hG3JmuTkk7uM/ia5pQmbqUba7nVPHBDJegZW3khUKUXJyG5qxd6tGkMLwzBCmSxIwFGK4O68bXcoKRLDDCwIwTvasSS/vdSmAUyTNkDL9D+A4qY0XJ3YOTtY7HUtTMukXenaaFP2lszSAckd8Vl6Z4aJaM5yDjGRjn0zW74Z0NbW3keVzLPIRvLD7v0rr9P05UmDFNsYPAPOfevWpUL7nNKpbYi8NaCsMyny2w2CR1APtXs/h9RFaKvcgDp0rkNIs/KIYLg49Mce1drpo2RgYwRyavF2VPkRlC/NdmrRUasNvHOPWnZGRn8K8qxvcdRSAepzS0igooooAKKKKACiiigAooooAKKBRQAUUUUAFFFFABRRRQAUUUUAFFFFABTJZY4IzJIwVR3NJNNHbxNJK4RFGSTXiPxR+KsdjGdN0grNfSDPmHkRD6euK0p0+bV7Et9ET/FD4prpsT6dppVr6TKx4OTGP7xHbivA41kBeaV2kmc7ndmySfrTR5skrXFxI0s8hy8jnJJpztkZxgfWt3K+iWhUY2NCDwq8j+bfT7d3JjhG4/n2rctbK006KRLVDGko2yZOS351sXGjWksnmWtx9j2j/AFEKAID6Emsq8hvLF83cSNDt+WSDMg/HA4rip1qbVtj2sTk2Jw+trruhVMS42IqjqKduzyejDIzVaExyBSpG4c4qUszNk8HHbtW6Vzy3F3sOALBc856YqMAk4HHXIJpyZPy4HA61OoGWEaqO/wCH1rReROxV8sngMR7+hpzI3LHDMvPNS5wccAelOiTzDuwMev0pXuwvcQQBlWQ/Lu6A04RKSR1yOo4p7sCyg/dHFAwEwpBzzyKewtOoghQkA5A7ml8tSVLLnHOM04ncMHG30Hegckkge1FgEManGAPxpfVQFGfapFVuoxj0FK6ZGR19aalYb1AIu05kAOOuKUqFGVl3AdgKYr4YLnAHtU2RnO/Ofei+gWuOiQyHeJXHrjAqdYcEATyAFeRkVTI8vBY7k9M1ZjZSFZR1HHFDdhqyEjLeaUllcckht+PzrH8Z6Yl3oyzwh2uLVizZJOUPX+hrYliLZZeSORwBmnRzBoSXAO5drAtnI/8Ar1L1Q7XuePdDSV1+r+D2MzzaWFeNjn7OWwy/QnjFcvPaTW8hSWN43BwVdcVk0+hlZoizxigAAikKlTgikpcwizHIyjBYOo5Kt0oAtZjjJgI+rA1AucHkDAptDY7kzWzgZUq46/Kc0izTQnG5hjsajVipypINT/ai2BMiygevX86QaEyX/GJFP4VbivUYgK/XseKziLeQnBaI9u4prWzjlSrj/ZYGizKUmbqTYOfM4PUGrICyx4ZFZcZ+YZrmFkli45HsRVuLVZYyDtXgdOearQamdHbXF7awiK1u5IEU5CqBgd+hq9b+IdVgBV7tZ3X+8oBH4Cubg1zcw3w/N2C85q1pkkKRS/aXWK4kcvh+DTsuo1N7o3J9Zubj5ZmjRe/aqMVxaQApHJCeTuOeTnvUTW8yXDTCCK6DABWZshfwqzaadZLcRz3tszNvDMqdCB2OTjFWlDqgu2tyVSjHPQf7NXGsYpY1klt1kU9C65olexS6uGgUqJHG2EDOOOgArI1y91PS9StPPjktrIuJFjLcyAYySAf0rb3VqjNs6CGOGPAWKKMeygVZB3LjJxntXM3njS1jYpZ2hkA6M5wKyf8AhMNS84PtgC90VMA/rUupGJK1O8KOVICtn0NKsbEnP5V5sfEGpNFLGblz5hzncQV57VC+sX8iwq1y58rlT3P19aXt4hY9XjRgSOvbirKCRf4Tx7V5RF4k1CK/N2GRmK7djA7APpmp7XxbqlrYS26TM0kj7vNdiSo9AOlWsTEGj1gFTxJHG+R0dAaim0DQ9QH+k6XAWbq0Y8sj8q4GLx7cIlnHt3bSv2l5QDu6ZwBit6x+IdlJf3SzQpHaohaKQ5VnI7YGev8ASto1oSdrktMvS/DDQLnBgu7y1J7HDgfpRbfDK7snza6lb3C7wyqwKsantvH2jvpcN9c+ZD5knlmJWVmUjvgc4/Cuhj1/SRqC2L3ixXTAMscq4yMZz+VXD2Vron30SWOj3tsGEtqSGP3l5xW1Z2ib+Fb3DU2x1CK5jLWl9bzLvwzRSggHuK01muI1xtySfvYzXUnFPQzaZpWUKoRnJwNoBrftw+FDD93jgjrXLw6jOhG5IW/3hjir1v4ngQp5qrgjlY3BIA9q5q1Oc9kOJ1CAjlWGPTHWpk4Xtn1rnrbxZo1ydpvPLfOMSAjH41sx3UUmdkiNgcFTnNefUpzj8SsWi1uBAx0PenVGDjoPxxinZz6jFY2LuOopPxopDuLRRSZBxigYtFFFABRRRmgAooooAKKKKACiiigAooooAKKKTIoAWoLm7htYTLK4AHQetFzcxWsDzzyJHGgyzMcAV4J8Tviy3nPpeiFGmxtMxGfLHX862p0+bWWxF29if4p/FCWDzdL0x1F3INnGCY17k+hrxBI3aTz5pHlmfl3Ykk/iaFVmLTyyGadzlndiST9TQ7HBODketaSd9loXFWFkfABwfwqMthTjJxzzSMST1OfSmgtkb+nWp21HY9TM2SWMeAR8w3Hn0qRb2dXO2YbV4OD0+vY1W88OTheMcCjiUoAgQEEsq9vrXgyvKVuh+xuC6oWfTNJu2Mm1bW5Yk+dABk/UGsu40vUrVTLCsd1Djlkky+PdQK1obdZQJdy8A4zzk+9P82SIEKzBl6kN+NbQq1IPc8rFZPhcQ9tTDhkRlGEIY9dykfoamLbRgLgkckd61JFs9TLS31ssjqvEhOGUe3NUH0a4Cq1hOZlI/wBXcMqEfkK7KeLjKzasfL4vh3EUtafvIg27sHHHHFTADngBe2KqmaSCQR3Fu0bLw3ynBPscVMku5BgY+tdSd1c8CrTnTdpqw8LjLMDnng07OFHA6dhmoWucyZKbh6dKEnJU5QdeCD+lXczSJxgH0NPAAXgDrmqy3BJxsCtjoTmnm4yR8gA9c0vQE9CfGRwBx3pUbDDaenrVc3b4OAnTjPWkacsFyFBHOaFfYfoTyAPwQcin287IdrYUnjiqnnkA4YnufrTTIjbQTzjJI9aPJArmsz7w2cDNUml8mXaSMdiehqvHdEfIScdck/1pZXDAKT780XstBNXJ2nYKQGJbsKy5ZZLeTaDhWND3wTKfdI49c1SvZX2qXZWIGQQRU+0KUGTSXjx8C4IYnJyetZNxfyNMS7eYoJPzHNRNIZemdw9TVO5R1PODxnApOQ+45obeUEIfJ7+oP4VUmt9jdNwPQp/hT9xYA46D0pjSkYxxUK5FkyLym+YAjPoeDUZBU4IINWsmTJbB461HjJxu7Y5p2uS4kFKBnipGVR2K49OaYFOeOaVhWEPWgEg5BwackUkn3I2b6DNWxpN35e94wi4zlmFCTbEVvtMu0KzbwOzDNOMkTtl4tv8AuHFX4NGDuoeU4yM4FaKaTYxkHy2cj+83H5VSix6mNYRI9wJADhOefWrc8p3Hc2c+1Xnt9vyxgIOm0cCq0trMxwUBAHWmolIqG5KfLs4PUZOKtRXrvyYomGMYbOP51Etkdx3o5OMn5eBVyKwibIxO2egC8A1DutUbR82Tf2pfCMrBKkC+kSAH86y9VDyQpM8s0rbsFpXLH9a6S202PaD9mLDHWRu9aMlhBdWv2aSJEiPUIMfjVRhNsmco2aPNKK6678ETnc9hcJIP7knyt/gax5/DWr25QPYysXHHljfj646U3RknZanPcyaKsyWF5FO8EltMssfLKUOQPWoNjFd2049cVHJLsO42ineW4AOxsHocdasxaXfTXiWiWkpuH+7GVIJ/Omqc30FdFSiugtPBWv3k8kKadKjRgkmX5AfYE8GtWz+GWuXVo8rm3t5VOFhlf5m/IEVaoTfQXMjiqliuJ4JlmhmkjlXo6MQw7da9KtfhIrLbPc6wi5x58aR5ZT3CnOD9cVv2Pwx8NW93JLK93dwshVIpGC7Se+RjpW8cJN7sXOjxuK/uora4t0mIjuCplBAJYg5HPXvW9Z+NvEcEmmx213MPsnypHGzfvsno4z83pXr+n+AvDllp7Wn9lJd7juaa4OXP0IAx+FdDHollF9jaPSrLdartgbyAWj+hIrohh5RS95k89zxXUviR42u7m8CytawkEPbx2y4iXp1I3D65rpPhT4s07w1bXV3eWXnTXUh3lACwAPA+Y9OTXqq3LW7u08sEQkQ7xIANw964y7k+HOi723WS7mLsqSbznvgc/lWeJotq8J2/r5Hbl+IpUqj9vDmi1bQ6M/FvQwjAabJzzhoYyP8A0IVY074veH96rd2zxkDAaKFML/4+T+Veb3vxG8DWUpFpoAvjjhmgRV/UZ/SuMvPHFj588ul+FtMtWmGGaVBJgewwAK8+VOaf8S/y/wCCelPF5c1ZUH/4Fr+TPqWHxv4faB7ltds5opHAiiRSJOTgDbnJOfYV0OcHGcEmvk7wvcG41LSxLyWuowRjjG8V9alQwwailNyTk9r2+63+Znm+Ao4VU3RbfMr62/QaD1INKTtGaNuM4PamgSYIIU/jVnjWYKRKnKkKexFOVQqAKMAdBTTuXIK/LjqKbuLnG35cdzinYL23JCwBA7mnVEqlW4OfUE9KcM4yST7UrBcdRxTQSOwpewGKB3FFLSdKM80h3FopMjpS0BcKKTPSjPNAXFpDxSHGOpFI2cYz3p2E2KTg1WurpbWF5pW2IgySTxUU85jikd9qBBlnzwPxr56+KHxR/taWTQ9DkzBnbcXQ5Dd/lxW1OknrLYnVl34m/FUXUr6JoW1pMYubqQAhfZB6+p/yPHyArFmcySMctI5yT9TTQqom1M9cknqaYXyRkflWjk3p0RpGKQ8kdAPyqJicfN69ajLYPTr3oJVh7VHMVYXOWJ5PPejcFAzyPWmM/BOa7jwJ4IfXZU1TUkK6XG3yoes5H9KUpJasOVt2RvR+YkRG0BgOmR602TKhnH3t35/jUi5IRSxAYH5nWlkiOO7tnOQ2Bx1rwGz9ivrqV8l2OcMoOCqnipDN5SnLknpgDoKTL+Xk7VK/3jjJNRufMYkArnB4H9armdrl2uTLLmIJFgKM/KTzTw5UAKcuQDgdaYfMnZ9uB2ZyQM0PticoseSRwRyvT1q00tOtyLLYV7lJh5N1brPHnJEpLZ/Wqd1pFvI+bCVrVh0hCL5ZPpntVkIMKET5T1J6ikQEzMQML97d9KvmktY6HPiMFh8QrVI3MW5hv7AD7XCuwn5XgO8Ae+BxTI5Qy7weCK6GO7njSP8AeYRg2Vx8v0qrc6ZptzukeFLSbg+bbqD19Qa6IYxpWmj5nF8M296g/kZqgqdxXOPUdaQvnrwPQ06503U7ePzFaO6hB+8rjzMf7oFUEuFZ9gLBxyVZSOfx61205xqK8WfM4jA18PK1SNi8CE4JViWxwaaXAPfpUC8jcCcA9qUsTnBBx0q7nJYm8w8A8ikMgAUHAzUBkI5OQf5VCGOzkn8eaW2wWZaZssMEBfemfbVjjEbnPUg9xVKRiF+8CeaquxJLH0qJS0KWjJJz5hZlZAeercCiWSMABpkc4AJQ8Hiqb7MHjPfFQFUI3dyfuistdzRSJWdBIWRl685psskDfKHBPqOagNtJJyEPPvT109s/e2j25p7EDQ9uiSIX3FsYOMbaqyNG4G0HNaK6dF0ZizGrUdogxtjA9DimmxNNmNFFLJhY45MkemKnj02Ytuf5QOo61uw28xU7QT264qZLGYgggqD/ALVO9kHIYkemR5+dmYnr2FXIrCFTkRqCOnFaf2aOAgMykkZqdDbqx83aFPAPWj2kXqg9mZotpGJChlA6mp0s224Y7lzkE1fNxBGueCR265qrcX6kKFVRxzgYqfa9kX7Ictmqjr9ajeNI8k54689aibUFAPqe2cYrPnvHbI985NS6smPkSWpckuEUHpUI1GP5gQu085x3rLeVupJPrzVff23/AEq1JmbUdjoodTgyue/tV6G+szw0mzPXPrXIltq5OSfanrKxGCDnuCa0jJolpHdwSQSMAkqEYzgHNXEUnGOlec+ZsbO4jHocVYj1C5jYPHcuCOmTmrVVonkXc9FyFGM8+1SLLtOPmx7VwsPie/icFzFJ16rirkXi+4UjfHGSeeOAKv28epPsmdmk7HcV2hiOSRnNOijiEBhFvbmEnmPyxgn6VysfjBN3zW7Y/iYY5qzH4xhDKPK5bp3q44iAeyk9kdasYKJG9vF5akFV2DCY9KuKzsRnA44OMVxo8boHJMII74I4/KmP47GfuEZHGUzT+t00HsJneosrEFs4UZwacoXAZ5VQdTuODXms3jW8kVgsmCDjpgYrKuPEs05BcnI77ic/rU/XV0Q/q76s9bk1vSLPPm3sRKgH5Tk1m3PxA0iBW+zxvIByHbABryGbV5snYxUE9Qc5qlLfSS8u5b0yOlZyxlSWysV7KlHc9QvfirdKpS2tI0UcKWwxH5GuavviX4kul8pb4RrkHMSbT+ea41p3Ykk0wkk1DrTetwbgtkaF5rGo3zE3OoXEueoeViP1NUCcnPJ+tN/GjtWd31JcrjgrHopP0FWoNOuLkHYoXH987f51dtgoQADArSi+ueK5J4hx2R7mEyqFSznI3/DMAg8QaREG3n7TFnHTO8cV9YsSM4618oeGW2eJdKb0u4v/AEMV9UyMWkIUjPQAmtMJeVLXu/yRrxJFRdKK2sPyxJXdjjIwaerED5iOKqNJtJyD6ArTvO5IJ4xk8V08rPmLloseOmO9G9SSOeO+Kg3qyYw21hnpTg7EBVU59xilyj5iUKg5AGTRgDmmhSGz3PvQkezIDsfrSD5CshZcZpcEHPWl5oJx1pBZCZxx0oPHcYpc0dRQAnakBA6npRwRxSFRknnOOlMXoHmKRnORSb8n7p/Gm5IXhAT6Co5HA+8Dj0HNNRFzEpYbuePxqldXCwxPNLKIkjUszvwFHrmqN/q9rZwS3E8yRW0SlpJpDhVA65Jr5v8AiL8S7jxdcS6bpJlg0ZW5ZmO6bHcj09q2UOVXkJLmL3xM+Kdz4ink0TQbh4tJjOJZ04a4Prkfw+3evMhiNQqjp196AFiQhD/9emMSpJz3qZSbZulYl80EAYINRvkPnLZApoOeoOT6mkOR1JHfrQwFPHcnNIWPIxQRgHAJHsaTdjGaG2PY67wL4ObxPdyXt22zS7RwJAD80jddo9vU+/5epT6m8OpRafZWojt4EBO1flb0RMV5t8O9QuXXU9ChuRCLlRKufbhse+MflXe6NFNPd232O4xa2jFZXYcnHZfX3NclST5rN6HTR5VG5j7hFuBLeXnK8k4/D60K4NwCwyq5xjjjFU5JHKAv7AGpBOCwj29Tk4bivNbT1Z+s+z0GMXcsh2kqeSDk1MFIckKQAAuFPB96dHLtOMqCAQBkcUgkBLFVyzY3lupoWmw22+gg6kqAAepxmohIdgjCs65wCfWrAhlZBlht67R6VFInG5RgZ9/l/wAKmyCLTI9pV1xs2np83WnuFMjKCoVuox09hSgoP9Yq7UwB0GfemPDGjDaW+bOBjpWik9rlXu9R/mIqqHHIHGBxTHZcq4DbSMZ9fTilMjBtyrx796QvuTaDyem32qXa4JEkdy0DDZI2OmVOKiu1s75j9ts1kfgCTadw/HNISqx9HZQcZzimHBGfMbHfJ70RfvJ7EzoU6itNXKM2gSo5OnXSzIckQzuqED2Pest5WibZcxvE4OPukj88YrpICzzbQVBI5ZuMD61V1DxPYRA25hbUSPlaOQEJj1BGa7KdeovM+XzTJcFSjz83IYwYdeCM9+aRmOCz7Qp5+lU5J2lld44IreNjlYo8kJz0pskbSMAAzD9BXU6t7Nnxs6aTdncHuIz0bJPb0qEyByoCAD3FWlsJVO47SvqDyKsiw2ISxA4796iUl0YlAzPKL9M/lTxBswCMZ9qulolUKc8datpcW45jZD6kGo57DUHsZ6WrkAg9u1WEtASpI4PcmnXd+rQqi/Kvf3qgbvjAJz/KhTb2L5dDWFlEijK49STRL5MRCptIA5rIF/IMhmJBOTzmqz3xMxbcVxwMChuUuoWtobK36xPuXGcYw3Q0v9qBkypCEdRjrXPm54+Yk4qI3betFtLBdbm1c3qud54PTGc1We7O07R19ayTOCSc015uvNNRWwnNWNRr4ngHioXvCecnHcYrML+lIXz3q0ktjJzLrXXTnj3pjXIPRj9KpknPWkzTsQ6jLLTljkk00OTyQOKr0ueKtPUjm7luNt7bVAyadIuAMgA5qmGIOc804ys33mJp3HcsY3cEUpG1uOmOlQxzeW4JAYelK8245HHtRfQNBXLNtweAemaUMRnOc0xWDsQxAyetI7AE4I/Ck9R+YpkYPUglOOM4qDYWBYMvHvzSBsDAJ+lLqNSsWPN2MCH7c0PcnHBquVAAO4Um7HuKTQc76knnsRyajJYnJzSHmjJxjPFBDlfcPvMATj3NFJRTJFzkdKM0lFFwFpKKcmz5t2enGPWgCxDPcKQwyyjqD0q2dWkXpEgwOzGs9JMRleTmrmnaFquryCPTtOurpicfuoi2PrjpQsP7R6RudUMbVpL3ZHZ+FpfM17SWJHN3Fn/vsV9WXEbs5KShTk14H4V+FfiW01nT5dTiitLWCRJ2feGLEENtAB68Y/xr3aW5ikkLIM57jtVUKMqUXF93+h2ZxjKeJVPld2lqWQirkbiz543UkceQTKynnoTVRZlRyVBJbjpSmaSZedqnuBW3Izw7ouHzWAXohHXNOEzsQI1yOhOelUDNJlxu28YLg04PgKjOxB79yaXswuaKOCPvCkaTYOhP0qijHZy2GP8AD2FOeTBPzDjocVPs9Q5i156knAPWjzsgErx0POarGYq7HoegIFOV128sQD3PSjkDmLBYkjBx61GJXLnk47CmeYoA5PB6CjehznA9KFEV2SZ7ZIJ4HH6ULtAI/h6gCoQ+05Bx3qOSYegPPYU1FsVyaV9ozvI9vSsjV9Xs9MsZ76+ufJtIl3MS2N1Q6rqlrYW0ss06RRxgtLI/3VX6180fEHx7P4yv/s1oGi0i3OIlOQ0n+0349K25FBXZUY3H+P8A4jX/AI3uvs0ZNro8Tfu4V+Uye7evNcYWG3C4XB7Cm7iMKMYHAzTS3U7M+9ZN3ep0JWHhiRkH9KaxOc5GT2pm5hQSxGQBnHpSFuO3NknsKTdgcA9KYSBS5yM9velewxynA6fnSAfSmZHXIpcjIppoRf0PUzo+u2Wo7ciGUF1A6qeGH5E19FQxW1rBEloixwbMoqdOec18zHByM17t4C1VtX8F2hZwZbMm3fPouNv6EVzV43tLqbUJa2ZzMs2qWY3XMJdP7w5H6UialayBS6lGAxjbxVm01SInEdw6FieWPCj86km8i5LG5tbZwed4O1j+Rrx3ezi9j9WTn01K/mJJGJFKEk8oSP8AGhQwLbgqZI6Co30y0LE2N28bjp5hGPzFRvBqtmM486Nv4ozuH+IojKyRoq1tJKxZaWVVwMgfwkDmnea0blQ+4k4JxjmqS6uhXE0TIwOPlyMVOk9vMixpLgk/xgDA+uaXNbQuNSEiy8a8bgCRz06VGqkYyjtknJ7CmMrxqCp3L/eDZX8MU3fIrdWJPv1rSzt73U0S00ZIzEJGC3OTjODj/CgIyJ8rr8ww2OahLEjBC+uRTmc7TggFT270PSNkVysN53f6zI3feIp3kmVwFZpewx2FMBGSGxsHJFSQyi2jmugAywKWKZPJHShWXuvoTOShFy7GD4k1NoB/Z1rIFC486RW+9nHH4VzLS7BgHauegHFEsrSSySkZ3tkmqjyZycCvTpwUYWPy7McbPE4hzk9OhdS6YZ5IH1q9b6jsxvCMB3rAEnoMU8S+/FKULnHGSsdS2pqy/LtAxgkHNUrnUZJI2XccdeaxlmK9+vWmtLljWap6l86SNE3g2dT9MVB9oAbeDhu1UvMYnimliTWnJoR7Sxda6zjNReecHB5qtkk9KMHOKfKiXUZOZiOM/lTDIx6ZqMg0vIHBp2FdiFj60m7mlJ/hI59aYfSqRnJ2FJFNJooAJOAM07EN3CiiigQUUUUAFFFFABRRRQAUZoooAKWkooACaPpRRTAKKKKQBRRRQAUUUop2ASpY7eWX7qHHrTVbaelTxzkEHJ+laxgnuJtl220KSZwstxFEvfqT+VdDpvhjQ1ZXvLi4uB3VCEB/r+tc7FeM3Gcd81oQXb4HOfrXQoQXQl3Z6Pop8Kabg2+jWbSA7t1wvmkEehbNd7pfjBtvzLCkIGFEKAV4hb37AgscZ4yBWvaXsjEBXO7rlWxXSqsXo0Z8h71aaiNQ2LAw2rz16itDcitjBB6n0rzfwnJIbhf3nbpnj616FlY1BALHGMkdaJxWjQiyCYwTycmlBBfO5kA569frUCkOV3KwB5Ht9alyS4AGMnI4rFoRKWycAhienpRvRGBJyaiRsHOVPb05pUAVySpJB/CpsMnQ7iHIAHanZy564I71FuJPzrhcU5W2knqPc1NhCkjduBYgfjzTlbHHDe5qNdyZHl5X/Z9KUMhOCMZ/zihoZMZF3kHqR6U1nAbkYJPSmYTIIJOeBTXKl8g8EcZpJCbHgnzML2z271lX+ofZ4pdsiq8aktI/3UHqaNR1aC2t5pHkSOCNMvI7bVXHvXzr48+IkviN20zS2kh0xTmRyfmnP+HtWqSgry+4cYuQnxC8bjXbhtM065mmsVbM8ucLMw6FfauE3FegwoGMAUYVSVFMBZR97n61jObk7s6EktEISTj/AApCcnpj+tGSTmk5NZlC9gSePSkJGRg9aTr1NN3EgUmIU5B560DLHAyeOgpG65qSCTyWLbQzYwM9vepS1Ah6U4H6ZpGOeScmkHWlsxDhjn16V6B8KNVFtr1zpUj4jvo8pn++vPT6Z/KvPxyc55q3pmoSaTqtpqEPMkEokxnrg8j8en40pRurFRfK0zrDGeuTkEA5qVbyeB1AlbKggZqMPuD5YnB445pGAdlyzH/eNeVyx6H6JGpJdTQj1Qht8sRZvXPH5VdttTjCAR3DBuBh+MfrXPsCAcE4zmmsQMYGD1PtWcqSTuup1QxckrPVHVvMtyNs0EdycHYW5/UGqsmkWNwUaCV7Zm/hxuX375FYSTyLxHI655wD3q7Hq86rtlG5TznnP6VLhNbamvtqU91Ysmx1W1TzIJFmiXqI5M/hjrUSapLbyslxA3IwyPkf/qp0N/G2JMsrkkHb/wDrrUa4MkYWcQypjhGIJNSvPc2s18Ermel5azfxGNsdAvH86k2mUeZGRIerDPINNms9MnVmCy2z4z8oyPyNQPo93Dh7S5SUY/v7W/Km1pZMv29Wn8SJtzJk4xnjn9adK5OmXyHO8w9h2yKzjfXkB23CORjGHBqzZarbeZidWMbcMOuaXvLUVTEU6kHB6NnBuu0HjjNVnbrWxq9p9kupBG++MnKsP/rViueeK9mElKKaPzDF0pUajhI3L7w3Ja6NDqUV1FLE+MqGGVJ7VgZNSNczNbi3Mh8lW3BOwPrUeOM0RTW5z1Zxk7wVh27A6CkzzSD6UvNMi7YvU0o65oCOx4VmPsKtRafdSgMECj1dsUm0aQhKT0RXzzSbuetX105P+Ws5Df7IBFSLa2sYOEMh/wBvj+VZucUdSwlV76Gbgt0B/AUhDbeVNbCyCIfuUWP/AHageFZB0xSVRGksE7aPUzMMDz8tHyDOcsfarEllIPuZZfeqzRun3lI+orZST2OCpSnD4kKzKfupj8c00sSc9PpSUVVzEKKMUuKQWEopcc80pAHrRcdmNopccUlArBRRiigAooooAKKKKAHrJtbdsU8YwRxUi3AUk+REcjHK9Kgop3YErT7owvlRj/aC81GWJAHpSUU+Z2sAUUU4LmpCw2ipNoxgZJPtQB6j86ZSiIEJFSomMnrSIu4kA1KquoOOatNDUSRCE4IqzDISMYIHbmq6YyC3THSpUQscA8U1O7CxehkYtx8vPSui0uECUbucgEgc1jWcG/DbAcdc11ulws7BVwGxlSRjI9K6qaInY7rw3FgpsXBXj6jFehQuWhTeCTjriuE0MfImGAbjiuztpWESmRSpPvkD612VFeKscty4WAUHB6YPPOaYQNuCT/wI80I4wc7cHrz3qORwsir1IGStYJahcsIoiA/iz15zg1IjuxyTgE9M81WTlBnOc5OKfvMYJ64GcntSaAmSQAjgknoDTtwOPmAyepFRK+Bk4z6ikX5gTnGeeehqbAPVhzyeB1zT8lWIIzxkHNM4YED8NtRtIQ5+ck9sjvRa4E+5RgccZJNY2s65Bp8TgzRAqpZ3dsCNe5NQazrcdlZz3EtxHbwwZ82Z+MV87+M/HMniKWSysTJFpu7czOPnnPq3t6CqfLTXNLfsVGLkyTx/45m8U6kbW1nkXSIDhUB2+af7xH16VxpIxheB7U0kHIXoOlNBPI49q5ZTcndnSlZAeBnPf1oyTng00nnmlJ4ODUAJ164z9aM45OcUev6YpoJHrih3sAZ4NIelL1OeaaakQUZyetFJU3sA4miNGlkWNBlmIAHvTe1KCVIIOCO9DdwJXR4JXhbAYHB57io/ypWO7nOfWkHtVNjO5ICOByeMk49+lGGUs23AJ456CguoY4XaPRhzS4HUNndzXkNO9z7+7tqNwMs2RgetRsWdgc9B+npT8YBPy4K9D60xl5BzkkcDFPV9dxoccqowq8DGeuaHDORwvTqtIo4I3cA/TmmADavIyRzxQ9LjQEBQCep5p8cskZ3q+0nptPIqPHGe3TpSsADgPn2xU2Rak11L0OqyhQjIrqvTNWY7+GVgTlGz26Y/OsY4AAAOaBk5C8nFR7Nbo6IYucOp0gvmbMYPmxtghJOQfwzVaaCyncCW2WFzyWh7fgeKx0leMnaxU47VOL5227wDjjnv9an2TvubfWKU/jiSXOiq8X7m4WRSfuy4WufvdAkiOWRkz0wOPzroPtcbkAjapAB6mh794lKIzMCcjOQPyq4VJwOHF4HDV1dnHNpU+cKU/FsVPB4fupmC+ZboD3aUVsXU3nNuMSKx5JUYzVQ5ySvFdPtp23PBnleGi+v3jDo1hCCHu5pHHGFQAZ+tKUtEwEs4+O7ZJP604Mw6jNA2t1BH4VLnJ7s0jhaMfgihnnyKmyP5F9F4qMlm6kmrSwqTwasR2gY8YzUOokdEMHOeiM0Rn0qQQMecVsJZIKnECAdP0rN4jsd9LKJP4mYyWbHqKnSwJ6itURj0pwXisnXZ3U8qprcoLYL3qT7BbsP3sSuPereKMVn7SXc61gqKVuVMxLrw3DIAbaRg5/hYBR+dYt1plzaNtePPunIrtwPSnbiUKHJQ9VJ4P1renjJx0ep5eL4cwtb3qfuv8DzvbtNLjiuzudDsrssVTyX7CNcj9TWLeeHbu1yy7JY/VWyf0rup4qE12PmMXkOKw2tuZd0YvWnbOeBmpfJIO0qyn3GKUwMuK6baHjuDW5D5ZHJwPY0m3cf8Km8o4OQSfpSlGzzgD2odxcqICuBSFMDJqX5Q2Tk8807y1JJY4FCE4og2jNNK89amILYCjOKRkK8Hg/Si4nAhxRipDnPQZo2jJ6dKZPKR44pQufSnY56flSlcnrQHKMApcDGO9P2jOPWl2ADrzRsNRGBec04dSMCnqvAwOfalWNiM7SM9eKaQ9hFx124pccip0tmYfMv6VYj05yQOOaag+gORTRWJwig81aQ4GAgLehq/DpRGDz6VoQaSqHeVBI9R1rRUWTzpGGlm0h69ua0rbT22D24yT1rah08Db8oIHbFX7e0RDkqBnjgdK3hRRDmUrLTjhQQeePTNdTptrs8sBAQB+lVoIARlUyBxk9q2bOPYi8HI7GuunCxjKVzodPhWPy3I2nrkdB9a6JWlmVFjdREep71z9mjRygyODHjgV0Fo4WPaI84OBgY4reS925k9y1GwRRl1Y9AQOtPICM0uzezDPNQSNCiZLojdtx6GnglypDBvesWuoyQzZA2Icddx70GbavO7PXAGaqvIBKYlyGP3lHO2pV+QocdFwR1o5UIsqxIBPQA4p3XJDcdsio0fpg9umOKc+dueNvBwaza1ARpihDFue5FZOq6xaaTp819qNwYoYRkt0J9h71FrviHTtB06W71KYRRKMbQ3zMewA7187eNPHV74wvAGBt9PjP7uBT1929TSnNU15mkYOT1JPGnju88X3HkqWt9LjOY4ejOfV8Hk1yZK8HocU1m3YwDgUhII59K4XJyk5M6UklZClsnrTc9Pp603NGcEVN7CuOzwOOtAJ69qac0A57076+YDhwOtNo9+KfHG0m4IpJAycUeSEMB55ptFFZ3AKKKKQBRRWvoOhS61PIQwjt4AGmfPIHoPUnFA0m9EZRVgisR8rZxSVr+IbS3sr5ILZGjTYDtY8/X8ax6a8wkrOx3RUY4YttPGRQysuAMgMMKT2pCrFn/3fWlUsFw24+g9K8y2umx98NKktnzM8fpStICxIBJPAHQCmj5cHJPUYxQpzuypO0cYFOSd3qMONhPIPsOKZ8pOcjoaX0bkcYpFwU9wcgAdaLoYfMVGF4BzSjDFuSM0hVmU8Hrx9KaWGTlR1qXG24AAMkLmgcnk49c0Fhk8cZ4GaQdB+J5q0lsO4dOQKDwAD60Acc8CgowGCo5ofZBcaTwBmgPgYzkUuMj7vSmnpnHFRbsFxx2N1UDjr60GOPsSB9KQAk4AHHpRkkHGcUmuqHdPdEyWw3YwMgAn8am+xQt95AaqAkHNSCeRRgMcelZyhJPc6aU6SVpRJG05Cco5Wmm2uIeQQR9amS8HAZQPU1MkyP3waycprc6o0sNPWDsymtxIpwwP5VOl0h68VZKrJ1Ab61G1lC/T5P8AdFTzRe5sqNeHwO49XR+h/OnYqobGZVLRsGA9SAfypvm3EJwwb8qOTsyvrEo6VI2L2KTbz0qsl6AMMKsRzxt3xxUuDT1N4Vqc9mOxk+lLtxj0pwHy7ty49M80vU0lbqbpCBcfWlR2jbKkg+vSl6AHFP2FwMdug7mtYxTWgNWIbi0s74H7Xao7Y/1ij5h/Q1lTeGmA32EvmjukhVCP8a2lUAcDmpMFQCTls559K6Kc6kEuVnm4vKcLifjjr3RxkkJhbbMkkbg8jacfnimfZtwypznjiu8ldbyBY7mITx5yd/8AD9Dms+fw1avn+z7poHYZETKu0n616FLEqTtNHyWN4aq07you67HItZYGdvOahks3OcA471vXFle2Tlby0ZV2/ejBcfmBTERZVyORXUowmuaLufO1aVWi+WorHPmB0PA470zypP4gT9a6Q2ynA2A9xxTDZbuSu3NEqTaujHnObKktjbj1NBix2NdEbJc4VAPelGmoQGIyc0exYc/c5zyDuHFS/ZnZdwjYgdxXQjTkwPl4zxUq2YXhYyAe+ap0ric0c4LKUHcVIBqwmnMWxxmuiFmipk4LYqRIBtwFFWqSI5mYkel568A1bj0xPl+Untx3rXjgw3QZx6VYSA9h1rVU7WRPMzNj05RwRjHWrMVqirjYD+HNaKWhzwOcetWBbBFAIBOMVfszNyM6KDH8PHYVOtuTzjjqRitFLQHBC5HTJq4lsQBjgn1XrWnIS5GbFbfLkdhx61fgsyQDtPUE5NW0t/ulk7c+tWo4jtBAPPGAK0UCW+5FBb4YbT8zcAY4rUtoFyolwT7e1MjjClflJOcVfSMk5x0OenQVrFCZYgLJHhV3EHArZt+Exls46n1rOQ4jyTn0wOauRHcqnJHHSra0ITHTWs9xGQdgBYHkelTySESKsY56MV/hquJHlkZI5PkAwff6e9WYljiUbQzcDPPWs3puNMlhR49uGBOMFsdanZgwA549KhBCquSAe+KC+MlwRWTV3caJSQu6RhkY6+lc94h8V2Wg6fLcXkvlxp8oHdz2AHes/wAV+K9O8P2El1PeRSkDakEbjcxPt7V89+IvEeoeJtRN1eynb/yziB+VB7D+tZ1Kkaem7NIQ5tWWPFXiu/8AFmpNcXTlbdCRDCOAo/xrBJw2M8Y7Umee9JxkZzXA5Nu7OiyWiDIwef0pO1B4NJUCF4x1pTyM+lNpe1CYw6jrRnFJ70AD3o6gLwT6VqNOE01YjsXapUED5nJ9ayafJIZGyegGAPSlzCGUUUUgCiinRxvNKscSM7scKqjJJpASWtrLeXKQQLukc4A/rXRtrw0G2bTNLWGRMhpp3BJdsYI+lRXRTw9pxsYGH9pTgfaJR/yzXrtU9veucP60466lNcpJcXEt1O80zFnc5JNJFDJNuEaFsDJx2FMrR0q6W3E4yA7qFGR155ptiSuf/9k=", 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", + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "### Loading data ###\n", "b3d.reload(b3d.io.data_loader)\n", @@ -68,7 +95,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -78,6 +105,7 @@ "import b3d.chisight.gen3d.transition_kernels as transition_kernels\n", "b3d.reload(b3d.chisight.gen3d.transition_kernels)\n", "import b3d.chisight.gen3d.image_kernel as image_kernel\n", + "import b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels as pixel_rgbd_kernels\n", "b3d.reload(b3d.chisight.gen3d.image_kernel)\n", "import b3d.io.data_loader\n", "import jax\n", @@ -91,34 +119,25 @@ "from b3d.chisight.gen3d.model import dynamic_object_generative_model\n", "from genjax import ChoiceMapBuilder as C\n", "from genjax import Pytree\n", - "from b3d.chisight.gen3d.projection import PixelsPointsAssociation\n", "\n", - "p_resample_color = 0.005\n", - "hyperparams = {\n", - " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.2),\n", - " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(scale=0.05),\n", - " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.001, 0.999])\n", - " ),\n", - " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.001, 0.999])\n", - " ),\n", - " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05,\n", - " support=jnp.array([0.0025, 0.005, 0.01, 0.02]),\n", - " ),\n", - " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.05, support=jnp.array([0.01])\n", - " ),\n", - " \"image_kernel\": image_kernel.NoOcclusionPerVertexImageKernel(image_kernel.OldOcclusionPixelRGBDDistribution()),\n", - "}" + "import b3d.chisight.gen3d.settings \n", + "hyperparams = b3d.chisight.gen3d.settings.hyperparams\n", + "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "489336.38\n" + ] + } + ], "source": [ "\n", "T = 0\n", @@ -191,7 +210,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -210,9 +229,149 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 0%| | 0/45 [00:00 3\u001b[0m trace \u001b[38;5;241m=\u001b[39m \u001b[43minference_old\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minference_step\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m 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\u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference_old.py:188\u001b[0m, in \u001b[0;36minference_step\u001b[0;34m(trace, key, inference_hyperparams)\u001b[0m\n\u001b[1;32m 179\u001b[0m poses \u001b[38;5;241m=\u001b[39m Pose\u001b[38;5;241m.\u001b[39mconcatenate_poses(\n\u001b[1;32m 180\u001b[0m [\n\u001b[1;32m 181\u001b[0m Pose\u001b[38;5;241m.\u001b[39msample_gaussian_vmf_pose_vmap(keys[:\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m], current_pose, var, conc),\n\u001b[1;32m 182\u001b[0m current_pose[\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m],\n\u001b[1;32m 183\u001b[0m ]\n\u001b[1;32m 184\u001b[0m )\n\u001b[1;32m 185\u001b[0m pose_scores \u001b[38;5;241m=\u001b[39m Pose\u001b[38;5;241m.\u001b[39mlogpdf_gaussian_vmf_pose_vmap(\n\u001b[1;32m 186\u001b[0m poses, trace\u001b[38;5;241m.\u001b[39mget_choices()[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpose\u001b[39m\u001b[38;5;124m\"\u001b[39m], var, conc\n\u001b[1;32m 187\u001b[0m )\n\u001b[0;32m--> 188\u001b[0m scores \u001b[38;5;241m=\u001b[39m \u001b[43mupdate_all_get_score_vmap\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mposes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 189\u001b[0m scores_pose_q_correction \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 190\u001b[0m scores \u001b[38;5;241m-\u001b[39m pose_scores\n\u001b[1;32m 191\u001b[0m ) \u001b[38;5;66;03m# After this, scores are fair estimates of P(data | previous state)\u001b[39;00m\n\u001b[1;32m 192\u001b[0m \u001b[38;5;66;03m# and can be used to resample the choice sets.\u001b[39;00m\n", + " \u001b[0;31m[... skipping hidden 10 frame]\u001b[0m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/jax/_src/interpreters/pxla.py:1185\u001b[0m, in \u001b[0;36mExecuteReplicated.__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 1183\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handle_token_bufs(result_token_bufs, sharded_runtime_token)\n\u001b[1;32m 1184\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1185\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mxla_executable\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute_sharded\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_bufs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1186\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dispatch\u001b[38;5;241m.\u001b[39mneeds_check_special():\n\u001b[1;32m 1187\u001b[0m out_arrays \u001b[38;5;241m=\u001b[39m results\u001b[38;5;241m.\u001b[39mdisassemble_into_single_device_arrays()\n", + "\u001b[0;31mXlaRuntimeError\u001b[0m: RESOURCE_EXHAUSTED: Out of memory while trying to allocate 39935984384 bytes.\nBufferAssignment OOM Debugging.\nBufferAssignment stats:\n parameter allocation: 5.89MiB\n constant allocation: 97B\n maybe_live_out allocation: 39.1KiB\n preallocated temp allocation: 37.19GiB\n preallocated temp fragmentation: 1.2KiB (0.00%)\n total allocation: 37.20GiB\nPeak buffers:\n\tBuffer 1:\n\t\tSize: 6.35GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/inference_old.py\" source_line=60\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,3]\n\t\t==========================\n\n\tBuffer 2:\n\t\tSize: 2.82GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/reduce_or[axes=(1, 2)]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=29\n\t\tXLA Label: fusion\n\t\tShape: f32[4,10000,18927]\n\t\t==========================\n\n\tBuffer 3:\n\t\tSize: 2.82GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/concatenate[dimension=2]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/image_kernel.py\" source_line=181\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,4]\n\t\t==========================\n\n\tBuffer 4:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/and\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=104\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3]\n\t\t==========================\n\n\tBuffer 5:\n\t\tSize: 2.12GiB\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 6:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/log_prob/sub\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=93\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 7:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=130\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 8:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=130\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 9:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/cdf/sign\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=95\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3]\n\t\t==========================\n\n\tBuffer 10:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/cdf/sign\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=95\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 11:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/cdf/sign\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=95\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 12:\n\t\tSize: 1.59GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(vmap(jit(_where))))/broadcast_in_dim[shape=(10000, 18927, 3, 3) broadcast_dimensions=(0, 1, 3)]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/pose/core.py\" source_line=119\n\t\tXLA Label: fusion\n\t\tShape: pred[10000,18927,3,3]\n\t\t==========================\n\n\tBuffer 13:\n\t\tSize: 722.01MiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/reduce[computation=_ArgMinMaxReducer(gt) dimensions=(2,)]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/inference_old.py\" source_line=47\n\t\tXLA Label: fusion\n\t\tShape: s32[10000,18927]\n\t\t==========================\n\n\tBuffer 14:\n\t\tSize: 722.01MiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=170\n\t\tXLA Label: fusion\n\t\tShape: f32[1,10000,18927]\n\t\t==========================\n\n\tBuffer 15:\n\t\tSize: 722.01MiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=170\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927]\n\t\t==========================\n\n" + ] + } + ], "source": [ "for T in tqdm(range(len(all_data))):\n", " trace = inference.advance_time(key, trace, all_data[T][\"rgbd\"])\n", @@ -227,12 +386,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 96, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.6352941 0.52941173 0.26274508 0.852396 ] [0.6352941 0.52941173 0.26274508 0. ]\n" + ] + } + ], "source": [ - "vertex_index = 2426\n", - "trace.get_retval()[\"new_state\"][\"visibility_prob\"][vertex_index]" + "T = 35\n", + "vertex_index = 4708\n", + "trace.get_retval()[\"new_state\"][\"visibility_prob\"][vertex_index]\n", + "\n", + "latent_rgbd_per_point, observed_rgbd_per_point = b3d.chisight.gen3d.image_kernel.get_latent_and_observed_correspondences(\n", + " trace.get_retval()[\"new_state\"], trace.get_args()[0], trace.get_choices()[\"rgbd\"]\n", + ")\n", + "print(latent_rgbd_per_point[vertex_index], observed_rgbd_per_point[vertex_index])" ] }, { diff --git a/notebooks/bayes3d_paper/run_ycbv_evaluation.py b/notebooks/bayes3d_paper/run_ycbv_evaluation.py old mode 100644 new mode 100755 index 09dd9110..4e25d6fd --- a/notebooks/bayes3d_paper/run_ycbv_evaluation.py +++ b/notebooks/bayes3d_paper/run_ycbv_evaluation.py @@ -1,8 +1,9 @@ #!/usr/bin/env python + import os -import b3d import b3d.chisight.gen3d.image_kernel as image_kernel +import b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels as pixel_rgbd_kernels import b3d.chisight.gen3d.transition_kernels as transition_kernels import fire import genjax @@ -20,10 +21,13 @@ def run_tracking(scene=None, object=None, debug=False): + import b3d + FRAME_RATE = 50 - ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") - b3d.rr_init("run_ycbv_evaluation") + b3d.utils.rr_init("run_ycbv_evaluation") + + ycb_dir = os.path.join(b3d.utils.get_assets_path(), "bop/ycbv") if scene is None: scenes = range(48, 60) @@ -33,25 +37,29 @@ def run_tracking(scene=None, object=None, debug=False): scenes = scene hyperparams = { - "pose_kernel": transition_kernels.UniformPoseDriftKernel(max_shift=0.1), + "pose_kernel": transition_kernels.GaussianVMFPoseDriftKernel( + variance=0.02, concentration=1000.0 + ), "color_kernel": transition_kernels.LaplaceNotTruncatedColorDriftKernel( - scale=0.15 + scale=0.02 ), "visibility_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.05, possible_values=jnp.array([0.01, 0.99]) + resample_probability=0.05, support=jnp.array([1e-5, 1.0 - 1e-5]) ), "depth_nonreturn_prob_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.05, possible_values=jnp.array([0.01, 0.99]) + resample_probability=0.05, support=jnp.array([1e-5, 1.0 - 1e-5]) ), "depth_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.05, possible_values=jnp.array([0.0025, 0.01, 0.02]) + resample_probability=0.05, + support=jnp.array([0.01, 0.005, 0.01, 0.02]), ), "color_scale_kernel": transition_kernels.DiscreteFlipKernel( - resample_probability=0.05, possible_values=jnp.array([0.05, 0.1, 0.15]) + resample_probability=0.05, support=jnp.array([0.001]) + ), + "image_kernel": image_kernel.NoOcclusionPerVertexImageKernel( + pixel_rgbd_kernels.OldOcclusionPixelRGBDDistribution() ), - "image_likelihood": image_kernel.SimpleNoRenderImageLikelihood(), } - info_from_trace = hyperparams["image_likelihood"].info_from_trace for scene_id in scenes: print(f"Scene {scene_id}") @@ -119,25 +127,30 @@ def run_tracking(scene=None, object=None, debug=False): model_vertices = model_vertices[subset] model_colors = model_colors[subset] + hyperparams["intrinsics"] = { + "fx": fx, + "fy": fy, + "cx": cx, + "cy": cy, + "image_height": Pytree.const(image_height), + "image_width": Pytree.const(image_width), + "near": 0.01, + "far": 3.0, + } + hyperparams["vertices"] = model_vertices + num_vertices = model_vertices.shape[0] previous_state = { "pose": template_pose, "colors": model_colors, "visibility_prob": jnp.ones(num_vertices) - * hyperparams["visibility_prob_kernel"].possible_values[-1], + * hyperparams["visibility_prob_kernel"].support[-1], "depth_nonreturn_prob": jnp.ones(num_vertices) - * hyperparams["depth_nonreturn_prob_kernel"].possible_values[0], - "depth_scale": hyperparams["depth_scale_kernel"].possible_values[0], - "color_scale": hyperparams["color_scale_kernel"].possible_values[0], + * hyperparams["depth_nonreturn_prob_kernel"].support[0], + "depth_scale": hyperparams["depth_scale_kernel"].support[0], + "color_scale": hyperparams["color_scale_kernel"].support[0], } - hyperparams["vertices"] = model_vertices - hyperparams["fx"] = fx - hyperparams["fy"] = fy - hyperparams["cx"] = cx - hyperparams["cy"] = cy - hyperparams["image_height"] = Pytree.const(image_height) - hyperparams["image_width"] = Pytree.const(image_width) choicemap = ( genjax.ChoiceMap.d( { @@ -160,12 +173,19 @@ def run_tracking(scene=None, object=None, debug=False): key, choicemap, (hyperparams, previous_state) )[0] - from b3d.chisight.gen3d.inference import inference_step + import b3d.chisight.gen3d.inference as inference + import b3d.chisight.gen3d.inference_old as inference_old + import b3d.chisight.gen3d.settings + + inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams ### Run inference ### for T in tqdm(range(len(all_data))): key = b3d.split_key(key) - trace = inference_step(trace, key, all_data[T]["rgbd"]) + trace = inference.advance_time(key, trace, all_data[T]["rgbd"]) + trace = inference_old.inference_step(trace, key, inference_hyperparams)[ + 0 + ] tracking_results[T] = trace if debug: @@ -190,14 +210,15 @@ def run_tracking(scene=None, object=None, debug=False): ) trace = tracking_results[len(all_data) - 1] - info = info_from_trace(trace) - rendered_rgbd = info["latent_rgbd"] + latent_rgb = b3d.chisight.gen3d.image_kernel.get_latent_rgb_image( + trace.get_retval()["new_state"], trace.get_args()[0] + ) a = b3d.viz_rgb( trace.get_choices()["rgbd"][..., :3], ) b = b3d.viz_rgb( - rendered_rgbd[..., :3], + latent_rgb[..., :3], ) b3d.multi_panel([a, b, b3d.overlay_image(a, b)]).save( f"photo_SCENE_{scene_id}_OBJECT_INDEX_{OBJECT_INDEX}_POSES.png" diff --git a/notebooks/gen3d/interactive_visualization.ipynb b/notebooks/gen3d/interactive_visualization.ipynb index 84ec2c7e..d26f5c5a 100644 --- a/notebooks/gen3d/interactive_visualization.ipynb +++ b/notebooks/gen3d/interactive_visualization.ipynb @@ -14,7 +14,8 @@ "import b3d\n", "import jax.numpy as jnp\n", "import pytest\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "from genjax import Pytree" ] }, { @@ -23,56 +24,45 @@ "metadata": {}, "outputs": [], "source": [ - "near, far, image_height, image_width = 0.001, 1.0, 480, 640\n", - "img_model = image_kernel.NoOcclusionPerVertexImageKernel(\n", - " near, far, image_height, image_width\n", - ")\n", - "\n", - "inference_hyperparams = inference.InferenceHyperparams(\n", - " n_poses=1500,\n", - " do_stochastic_color_proposals=True,\n", - " pose_proposal_std=0.04,\n", - " pose_proposal_conc=1000.,\n", - " prev_color_proposal_laplace_scale=0.001,\n", - " obs_color_proposal_laplace_scale=0.001,\n", - ")\n", - "\n", - "hyperparams = {\n", - " \"pose_kernel\": transition_kernels.UniformPoseDriftKernel(max_shift=0.1),\n", - " \"color_kernel\": transition_kernels.LaplaceNotTruncatedColorDriftKernel(\n", - " scale= 0.05\n", - " ),\n", - " \"visibility_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.1, support=jnp.array([0.01, 0.99])\n", - " ),\n", - " \"depth_nonreturn_prob_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.1, support=jnp.array([0.01, 0.99])\n", - " ),\n", - " \"depth_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.1,\n", - " support=jnp.array([0.0025, 0.01, 0.02, 0.1, 0.4, 1.0]),\n", - " ),\n", - " \"color_scale_kernel\": transition_kernels.DiscreteFlipKernel(\n", - " resample_probability=0.1, support=jnp.array([0.002, 0.01, 0.025, 0.05, 0.1, 0.15, 0.3, 0.8])\n", - " ),\n", - " \"image_kernel\": img_model,\n", - "}" + "import b3d.chisight.gen3d.settings \n", + "b3d.reload(b3d.chisight.gen3d.settings)\n", + "import b3d.chisight.gen3d.settings \n", + "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams\n", + "hyperparams = b3d.chisight.gen3d.settings.hyperparams" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, + "outputs": [], + "source": [ + "hyperparams[\"intrinsics\"] = {\n", + " \"fx\": 100.0,\n", + " \"fy\": 100.0,\n", + " \"cx\": 50.0,\n", + " \"cy\": 50.0,\n", + " \"near\": 0.01,\n", + " \"far\": 3.0,\n", + " \"image_width\": Pytree.const(100),\n", + " \"image_height\": Pytree.const(100),\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e43892100b2c48e9898f4c3e89e22554", + "model_id": "1212c5d7004143ccbc04e120fe8f44f4", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "interactive(children=(ToggleButtons(description='Prev Vis Prob:', options=('0.01', '0.99'), value='0.01'), Tog…" + "interactive(children=(FloatSlider(value=0.10000000149011612, continuous_update=False, description='Observed R:…" ] }, "metadata": {}, @@ -81,12 +71,24 @@ ], "source": [ "from b3d.chisight.gen3d.visualization import create_interactive_visualization\n", + "from b3d.chisight.gen3d.inference_old import attribute_proposal\n", + "b3d.reload(b3d.chisight.gen3d.inference_old)\n", "b3d.reload(b3d.chisight.gen3d.visualization)\n", - "observed_rgbd_for_point = jnp.array([0.1, 0.2, 0.3, 0.4])\n", + "\n", + "observed_rgbd_for_point = jnp.array([0.1, 0.2, 0.3, 0.0])\n", + "latent_rgbd_for_point = jnp.array([0.1, 0.2, 0.3, 1.0])\n", + "previous_color = jnp.array([0.1, 0.2, 0.3])\n", + "previous_visibility_prob = hyperparams[\"visibility_prob_kernel\"].support[-1]\n", + "previous_dnrp = hyperparams[\"depth_nonreturn_prob_kernel\"].support[0]\n", "create_interactive_visualization(\n", " observed_rgbd_for_point,\n", + " latent_rgbd_for_point,\n", " hyperparams,\n", " inference_hyperparams,\n", + " previous_color,\n", + " previous_visibility_prob,\n", + " previous_dnrp,\n", + " attribute_proposal\n", ")" ] }, diff --git a/src/b3d/chisight/gen3d/image_kernel.py b/src/b3d/chisight/gen3d/image_kernel.py index 0043f3cc..279e97bf 100644 --- a/src/b3d/chisight/gen3d/image_kernel.py +++ b/src/b3d/chisight/gen3d/image_kernel.py @@ -1,26 +1,175 @@ from abc import abstractmethod +from functools import cached_property from typing import Mapping import genjax import jax import jax.numpy as jnp from genjax import Pytree -from genjax.typing import FloatArray, PRNGKey +from genjax.typing import FloatArray, IntArray, PRNGKey -from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( - RenormalizedLaplacePixelColorDistribution, - UniformPixelColorDistribution, -) -from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( - RenormalizedLaplacePixelDepthDistribution, - UniformPixelDepthDistribution, -) +import b3d.utils from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import ( - FullPixelRGBDDistribution, PixelRGBDDistribution, is_unexplained, ) -from b3d.chisight.gen3d.projection import PixelsPointsAssociation + +# using this in combination with mode="drop" in the .at[] +# methods can help filter out vertices that are not visible in the image +INVALID_IDX = jnp.iinfo(jnp.int32).min # -2147483648 + + +@Pytree.dataclass +class PixelsPointsAssociation(Pytree): + """A utility class to associate 3D points with their projected 2D pixel.""" + + projected_pixel_coordinates: IntArray # (num_vertices, 2) + image_height: int + image_width: int + + @classmethod + def from_hyperparams_and_pose(cls, hyperparams, pose_CO): + """`pose_CO` is the same thing as `pose` in the model.""" + vertices_O = hyperparams["vertices"] + vertices_C = pose_CO.apply(vertices_O) + return cls.from_points_and_intrinsics( + vertices_C, + hyperparams["intrinsics"], + ) + + @classmethod + def from_points_and_intrinsics( + cls, points: FloatArray, intrinsics: dict + ) -> "PixelsPointsAssociation": + """Create a PixelsPointsAssociation object from a set of 3D points and + the camera intrinsics. + + Args: + points (FloatArray): The points/vertices in 3D space (num_vertices, 3). + intrinsics (dict): Camera intrinsics. + image_height (int): Height of the image. + image_width (int): Width of the image. + """ + projected_coords = jnp.rint( + b3d.utils.xyz_to_pixel_coordinates( + points, + intrinsics["fx"], + intrinsics["fy"], + intrinsics["cx"], + intrinsics["cy"], + ) + - 0.5 + ) + + image_height, image_width = ( + intrinsics["image_height"].unwrap(), + intrinsics["image_width"].unwrap(), + ) + + # handle NaN before converting to int (otherwise NaN will be converted + # to 0) + projected_coords = jnp.nan_to_num(projected_coords, nan=INVALID_IDX) + + # handle the case where the projected coordinates are outside the image + projected_coords = jnp.where( + projected_coords > 0, projected_coords, INVALID_IDX + ) + projected_coords = jnp.where( + projected_coords < jnp.array([image_height, image_width]), + projected_coords, + INVALID_IDX, + ) + + return cls(projected_coords.astype(jnp.int32), image_height, image_width) + + def __len__(self) -> int: + return self.projected_pixel_coordinates.shape[0] + + def shape(self) -> tuple[int, int]: + return self.projected_pixel_coordinates.shape + + @property + def x(self) -> IntArray: + return self.projected_pixel_coordinates[:, 0] + + @property + def y(self) -> IntArray: + return self.projected_pixel_coordinates[:, 1] + + def get_pixel_attributes(self, point_attributes: FloatArray) -> FloatArray: + """Given a (num_vertices, attribute_length) array of point attributes, + return a (image_height, image_width, attribute_length) array of attributes. + Pixels that don't hit a vertex will have a value filled with -1. + """ + return point_attributes.at[self.pixel_to_point_idx].get( + mode="drop", fill_value=-1 + ) + + def get_point_rgbds(self, rgbd_image: FloatArray) -> FloatArray: + """ + Get a (num_vertices, 4) array of RGBD values for each vertex + by indexing into the given image. + Vertices that don't hit a pixel will have a value of (-1, -1, -1, -1). + """ + return rgbd_image.at[self.x, self.y].get(mode="drop", fill_value=-1.0) + + def get_point_depths(self, rgbd_image: FloatArray) -> FloatArray: + """ + Get a (num_vertices,) array of depth values for each vertex + by indexing into the given image, or -1 if the vertex doesn't hit a pixel. + """ + return self.get_point_rgbds(rgbd_image)[..., 3] + + def get_point_rgbs(self, rgbd: FloatArray) -> FloatArray: + """ + Get a (num_vertices, 3) array of RGB values for each vertex + by indexing into the given image, or [-1, -1, -1] if the vertex doesn't hit a pixel. + """ + return self.get_point_rgbds(rgbd)[..., :3] + + @cached_property + def num_point_per_pixel(self) -> IntArray: + """Return a 2D array of shape (image_height, image_width) where each + element is the number of points that project to that pixel. + """ + counts = jnp.zeros((self.image_height, self.image_width), dtype=jnp.int32) + counts = counts.at[self.x, self.y].add(1, mode="drop") + return counts + + @cached_property + def pixel_to_point_idx(self) -> IntArray: + """Return a 2D array of shape (image_height, image_width) where each + element is the index of the point that projects to that pixel (if any). + If none of the points project to that pixel, the value is set to INVALID_IDX. + + Warning: this implementaion does not handle race condition. That is, if + multiple points project to the same pixel, this method will randomly + return one of them (the non-determinism is subject to GPU parallelism). + """ + registered_pixel_idx = jnp.full( + (self.image_height, self.image_width), INVALID_IDX, dtype=jnp.int32 + ) + registered_pixel_idx = registered_pixel_idx.at[self.x, self.y].set( + jnp.arange(len(self)) + ) + return registered_pixel_idx + + def get_pixel_idx(self, point_idx: int) -> IntArray: + return self.projected_pixel_coordinates[point_idx] + + def get_pixels_with_multiple_points(self) -> tuple[IntArray, IntArray]: + """Return a tuple of (x_coords, y_coords) of pixels that have more than + one vertices associated with them. Note that this method is not JIT-compatible + because the return values are not of fixed shape. + """ + return jnp.nonzero(self.num_point_per_pixel > 1) + + def get_one_latent_point_idx(self, pixel_x: int, pixel_y: int) -> int: + """Return the index of one of the points that project to the given pixel. + If there are multiple points, this method will return one of them randomly + (the non-determinism is subject to GPU parallelism). + """ + return self.pixel_to_point_idx[pixel_x, pixel_y] def get_latent_and_observed_correspondences(state, hyperparams, observed_rgbd): @@ -35,6 +184,15 @@ def get_latent_and_observed_correspondences(state, hyperparams, observed_rgbd): return latent_rgbd_per_point, observed_rgbd_per_point +def get_latent_rgb_image(state, hyperparams): + transformed_points = state["pose"].apply(hyperparams["vertices"]) + ppa = PixelsPointsAssociation.from_points_and_intrinsics( + transformed_points, hyperparams["intrinsics"] + ) + latent_rgb_image = jnp.clip(ppa.get_pixel_attributes(state["colors"]), 0.0, 1.0) + return latent_rgb_image + + @Pytree.dataclass class ImageKernel(genjax.ExactDensity): """An abstract class that defines the common interface for image kernels, @@ -44,14 +202,6 @@ class ImageKernel(genjax.ExactDensity): The support of the distribution is [0, 1]^3 x [near, far]. """ - def get_pixels_points_association( - self, transformed_points, hyperparams: Mapping - ) -> PixelsPointsAssociation: - return PixelsPointsAssociation.from_points_and_intrinsics( - transformed_points, - hyperparams["intrinsics"], - ) - @abstractmethod def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: raise NotImplementedError @@ -68,12 +218,7 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: @Pytree.dataclass class NoOcclusionPerVertexImageKernel(ImageKernel): - rgbd_vertex_kernel: PixelRGBDDistribution = FullPixelRGBDDistribution( - RenormalizedLaplacePixelColorDistribution(), - UniformPixelColorDistribution(), - RenormalizedLaplacePixelDepthDistribution(), - UniformPixelDepthDistribution(), - ) + rgbd_vertex_kernel: PixelRGBDDistribution def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: """Generate latent RGBD image by projecting the vertices directly to the image @@ -81,8 +226,9 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr """ transformed_points = state["pose"].apply(hyperparams["vertices"]) - points_to_pixels = self.get_pixels_points_association( - transformed_points, hyperparams + points_to_pixels = PixelsPointsAssociation.from_points_and_intrinsics( + transformed_points, + hyperparams["intrinsics"], ) vertex_kernel = self.get_rgbd_vertex_kernel() @@ -126,9 +272,15 @@ def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArr def logpdf( self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping ) -> FloatArray: - latent_rgbd_per_point, observed_rgbd_per_point = ( - get_latent_and_observed_correspondences(state, hyperparams, observed_rgbd) + transformed_points = state["pose"].apply(hyperparams["vertices"]) + ppa = PixelsPointsAssociation.from_points_and_intrinsics( + transformed_points, hyperparams["intrinsics"] + ) + observed_rgbd_per_point = ppa.get_point_rgbds(observed_rgbd) + latent_rgbd_per_point = jnp.concatenate( + (state["colors"], transformed_points[..., 2, None]), axis=-1 ) + vertex_kernel = self.get_rgbd_vertex_kernel() scores = jax.vmap(vertex_kernel.logpdf, in_axes=(0, 0, None, None, 0, 0, None))( observed_rgbd_per_point, @@ -144,6 +296,9 @@ def logpdf( scores = jnp.where(is_unexplained(observed_rgbd_per_point), 0.0, scores) score_for_pixels_with_points = scores.sum() + # a = jnp.unique(ppa.projected_pixel_coordinates, axis=0, size=30000, fill_value=-1) + # num_pixels = ( a.sum(-1) >= 0).sum() + # TODO: add scores for pixels that don't get a point return score_for_pixels_with_points @@ -153,149 +308,3 @@ def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: # they don't expect observed_rgbd to be invalid, so we need to handle # that manually. return self.rgbd_vertex_kernel - - -# @Pytree.dataclass -# class OldNoOcclusionPerVertexImageKernel(ImageKernel): -# @jax.jit -# def sample(self, key: PRNGKey, state: Mapping, hyperparams: Mapping) -> FloatArray: -# return jnp.zeros( -# ( -# hyperparams["intrinsics"]["image_height"].unwrap(), -# hyperparams["intrinsics"]["image_width"].unwrap(), -# 4, -# ) -# ) - -# @jax.jit -# def logpdf( -# self, observed_rgbd: FloatArray, state: Mapping, hyperparams: Mapping -# ) -> FloatArray: -# return self.info_func(observed_rgbd, state, hyperparams)["scores"].sum() - -# def info_from_trace(self, trace): -# return self.info_func( -# trace.get_choices()["rgbd"], -# trace.get_retval()["new_state"], -# trace.get_args()[0], -# ) - -# def info_func(self, observed_rgbd, state, hyperparams): -# transformed_points = state["pose"].apply(hyperparams["vertices"]) -# projected_pixel_coordinates = jnp.rint( -# b3d.xyz_to_pixel_coordinates( -# transformed_points, -# hyperparams["intrinsics"]["fx"], -# hyperparams["intrinsics"]["fy"], -# hyperparams["intrinsics"]["cx"], -# hyperparams["intrinsics"]["cy"], -# ) -# ).astype(jnp.int32) - -# observed_rgbd_masked = observed_rgbd[ -# projected_pixel_coordinates[..., 0], projected_pixel_coordinates[..., 1] -# ] - -# color_visible_branch_score = jax.scipy.stats.laplace.logpdf( -# observed_rgbd_masked[..., :3], state["colors"], state["color_scale"] -# ).sum(axis=-1) -# color_not_visible_score = jnp.log(1 / 1.0**3) -# color_score = jnp.logaddexp( -# color_visible_branch_score + jnp.log(state["visibility_prob"]), -# color_not_visible_score + jnp.log(1 - state["visibility_prob"]), -# ) - -# depth_visible_branch_score = jax.scipy.stats.laplace.logpdf( -# observed_rgbd_masked[..., 3], -# transformed_points[..., 2], -# state["depth_scale"], -# ) -# depth_not_visible_score = jnp.log(1 / 1.0) -# _depth_score = jnp.logaddexp( -# depth_visible_branch_score + jnp.log(state["visibility_prob"]), -# depth_not_visible_score + jnp.log(1 - state["visibility_prob"]), -# ) -# is_depth_non_return = observed_rgbd_masked[..., 3] < 0.0001 - -# non_return_probability = 0.05 -# depth_score = jnp.where( -# is_depth_non_return, jnp.log(non_return_probability), _depth_score -# ) - -# lmbda = 0.5 -# scores = lmbda * color_score + (1.0 - lmbda) * depth_score -# return { -# "scores": scores, -# "observed_rgbd_masked": observed_rgbd_masked, -# } - -# def get_rgbd_vertex_kernel(self) -> PixelRGBDDistribution: -# # Note: The distributions were originally defined for per-pixel computation, -# # but they should work for per-vertex computation as well, except that -# # they don't expect observed_rgbd to be invalid, so we need to handle -# # that manually. -# raise NotImplementedError - - -@Pytree.dataclass -class OldOcclusionPixelRGBDDistribution(PixelRGBDDistribution): - """ - Distribution args: - - latent_rgbd: 4-array: RGBD value. (a value of [-1, -1, -1, -1] indicates no point hits here.) - - color_scale: float - - depth_scale: float - - visibility_prob: float - - depth_nonreturn_prob: float - - The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). - - Note that this distribution expects the observed_rgbd to be valid. If an invalid - pixel is observed, the logpdf will return -inf. - """ - - def sample( - self, - key: PRNGKey, - latent_rgbd: FloatArray, - color_scale: float, - depth_scale: float, - visibility_prob: float, - depth_nonreturn_prob: float, - intrinsics: dict, - ) -> FloatArray: - return jnp.ones((4,)) * 0.5 - - def logpdf( - self, - observed_rgbd: FloatArray, - latent_rgbd: FloatArray, - color_scale: float, - depth_scale: float, - visibility_prob: float, - depth_nonreturn_prob: float, - intrinsics: dict, - ) -> float: - color_visible_branch_score = jax.scipy.stats.laplace.logpdf( - observed_rgbd[:3], latent_rgbd[:3], color_scale - ).sum(axis=-1) - color_not_visible_score = jnp.log(1 / 1.0**3) - color_score = jnp.logaddexp( - color_visible_branch_score + jnp.log(visibility_prob), - color_not_visible_score + jnp.log(1 - visibility_prob), - ) - - depth_visible_branch_score = jax.scipy.stats.laplace.logpdf( - observed_rgbd[3], latent_rgbd[3], depth_scale - ) - depth_not_visible_score = jnp.log(1 / 1.0) - _depth_score = jnp.logaddexp( - depth_visible_branch_score + jnp.log(visibility_prob), - depth_not_visible_score + jnp.log(1 - visibility_prob), - ) - is_depth_non_return = observed_rgbd[3] < 0.0001 - - depth_score = jnp.where( - is_depth_non_return, jnp.log(depth_nonreturn_prob), _depth_score - ) - - return color_score + depth_score diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py index fa75e555..e2cf99eb 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference_moves.py @@ -9,6 +9,7 @@ from b3d import Pose from b3d.modeling_utils import renormalized_color_laplace +from .image_kernel import PixelsPointsAssociation from .model import ( get_hypers, get_n_vertices, @@ -16,7 +17,6 @@ get_observed_rgbd, get_prev_state, ) -from .projection import PixelsPointsAssociation def normalize_log_scores(scores): @@ -118,7 +118,7 @@ def propose_all_pointlevel_attributes(key, trace, inference_hyperparams): get_hypers(trace), get_new_state(trace)["pose"] ).get_point_rgbds(get_observed_rgbd(trace)) - colors, visibility_probs, depth_nonreturn_probs, log_qs, metadata = jax.vmap( + sample, metadata = jax.vmap( propose_a_points_attributes, in_axes=(0, 0, 0, None, None, None, None) )( split(key, get_n_vertices(trace)), @@ -130,7 +130,13 @@ def propose_all_pointlevel_attributes(key, trace, inference_hyperparams): inference_hyperparams, ) - return colors, visibility_probs, depth_nonreturn_probs, log_qs.sum(), metadata + return ( + sample["colors"], + sample["visibility_prob"], + sample["depth_nonreturn_prob"], + metadata["log_q_score"].sum(), + metadata, + ) def propose_a_points_attributes( @@ -154,17 +160,20 @@ def propose_a_points_attributes( return _propose_a_points_attributes( key, observed_rgbd_for_point=observed_rgbd_for_point, - latent_depth=new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2], + latent_rgbd_for_point=jnp.array( + [ + 0.0, + 0.0, + 0.0, + new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2], + ] + ), previous_color=prev_state["colors"][vertex_index], previous_visibility_prob=prev_state["visibility_prob"][vertex_index], previous_dnrp=prev_state["depth_nonreturn_prob"][vertex_index], - dnrp_transition_kernel=hyperparams["depth_nonreturn_prob_kernel"], - visibility_transition_kernel=hyperparams["visibility_prob_kernel"], - color_kernel=hyperparams["color_kernel"], - obs_rgbd_kernel=hyperparams["image_kernel"].get_rgbd_vertex_kernel(), color_scale=new_state["color_scale"], depth_scale=new_state["depth_scale"], - intrinsics=hyperparams["intrinsics"], + hyperparams=hyperparams, inference_hyperparams=inference_hyperparams, ) @@ -172,20 +181,22 @@ def propose_a_points_attributes( def _propose_a_points_attributes( key, observed_rgbd_for_point, - latent_depth, + latent_rgbd_for_point, previous_color, previous_visibility_prob, previous_dnrp, - dnrp_transition_kernel, - visibility_transition_kernel, - color_kernel, - obs_rgbd_kernel, color_scale, depth_scale, - intrinsics, + hyperparams, inference_hyperparams, ): k1, k2 = split(key, 2) + dnrp_transition_kernel = hyperparams["depth_nonreturn_prob_kernel"] + visibility_transition_kernel = hyperparams["visibility_prob_kernel"] + color_kernel = hyperparams["color_kernel"] + obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() + latent_depth = latent_rgbd_for_point[3] + intrinsics = hyperparams["intrinsics"] def score_attribute_assignment(color, visprob, dnrprob): visprob_transition_score = visibility_transition_kernel.logpdf( @@ -247,11 +258,13 @@ def score_attribute_assignment(color, visprob, dnrprob): log_q_score = log_normalized_scores[index] + log_qs_rgb[index] return ( - rgb, - visibility_prob, - dnr_prob, - log_q_score, { + "colors": rgb, + "visibility_prob": visibility_prob, + "depth_nonreturn_prob": dnr_prob, + }, + { + "log_q_score": log_q_score, "log_qs_rgb": log_qs_rgb, "log_normalized_scores": log_normalized_scores, "index": index, diff --git a/src/b3d/chisight/gen3d/inference_old.py b/src/b3d/chisight/gen3d/inference_old.py index 013a7508..c45f9dc9 100644 --- a/src/b3d/chisight/gen3d/inference_old.py +++ b/src/b3d/chisight/gen3d/inference_old.py @@ -14,7 +14,7 @@ @jax.jit -def attribute_proposal_only_color_and_visibility( +def attribute_proposal( key, observed_rgbd_for_point, latent_rgbd_for_point, @@ -130,7 +130,7 @@ def update_vertex_attributes(key, trace, inference_hyperparams): keys = jax.random.split(key, len(observed_rgbd_per_point)) sample = jax.vmap( - attribute_proposal_only_color_and_visibility, + attribute_proposal, in_axes=(0, 0, 0, 0, 0, 0, None, None, None, None), )( keys, @@ -172,7 +172,7 @@ def update_all_get_score(key, trace, pose, inference_hyperparams): def inference_step(trace, key, inference_hyperparams): number = 10000 current_pose = trace.get_choices()["pose"] - var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] + var_conc = [(0.04, 1000.0), (0.01, 2000.0), (0.005, 3000.0)] for var, conc in var_conc: key = jax.random.split(key, 2)[-1] keys = jax.random.split(key, number) diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index 36541238..cb77b925 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -6,7 +6,7 @@ from genjax import ChoiceMapBuilder as C import b3d -from b3d.chisight.gen3d.projection import PixelsPointsAssociation +from b3d.chisight.gen3d.image_kernel import PixelsPointsAssociation # TODOs # 1. Tests of drift kernels diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py index 934aca67..e0992897 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py @@ -165,3 +165,134 @@ def logpdf( outlier_color_log_prob + outlier_depth_log_prob, total_log_prob, ) + + +# @Pytree.dataclass +# class OldOcclusionPixelRGBDDistribution(PixelRGBDDistribution): +# """ +# Distribution args: +# - latent_rgbd: 4-array: RGBD value. (a value of [-1, -1, -1, -1] indicates no point hits here.) +# - color_scale: float +# - depth_scale: float +# - visibility_prob: float +# - depth_nonreturn_prob: float + +# The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). + +# Note that this distribution expects the observed_rgbd to be valid. If an invalid +# pixel is observed, the logpdf will return -inf. +# """ + +# def sample( +# self, +# key: PRNGKey, +# latent_rgbd: FloatArray, +# color_scale: float, +# depth_scale: float, +# visibility_prob: float, +# depth_nonreturn_prob: float, +# intrinsics: dict, +# ) -> FloatArray: +# return jnp.ones((4,)) * 0.5 + +# def logpdf( +# self, +# observed_rgbd: FloatArray, +# latent_rgbd: FloatArray, +# color_scale: float, +# depth_scale: float, +# visibility_prob: float, +# depth_nonreturn_prob: float, +# intrinsics: dict, +# ) -> float: +# total_visible_log_prob = 0.0 + +# total_visible_log_prob += renormalized_laplace.logpdf( +# observed_rgbd[:3], latent_rgbd[:3], color_scale, 0.0, 1.0 +# ).sum(axis=-1) + +# color_not_visible_score = jnp.log(1 / 1.0**3) +# color_score = jnp.logaddexp( +# color_visible_branch_score + jnp.log(visibility_prob), +# color_not_visible_score + jnp.log(1 - visibility_prob), +# ) + +# depth_visible_branch_score = renormalized_laplace.logpdf( +# observed_rgbd[3], +# latent_rgbd[3], +# depth_scale, +# intrinsics["near"], +# intrinsics["far"], +# ) +# depth_not_visible_score = jnp.log(1 / (intrinsics["far"] - intrinsics["near"])) +# _depth_score = jnp.logaddexp( +# depth_visible_branch_score + jnp.log(visibility_prob), +# depth_not_visible_score + jnp.log(1 - visibility_prob), +# ) +# is_depth_non_return = observed_rgbd[3] < 0.0001 + +# depth_score = jnp.where( +# is_depth_non_return, +# jnp.log(depth_nonreturn_prob), +# jnp.log(1.0 - depth_nonreturn_prob) + _depth_score, +# ) + +# total_log_prob = 0.0 + +# is_depth_non_return = observed_rgbd[3] == 0.0 + +# # Is visible +# total_visible_log_prob = 0.0 +# # color term +# total_visible_log_prob += self.inlier_color_distribution.logpdf( +# observed_rgbd[:3], latent_rgbd[:3], color_scale +# ) +# # depth term +# total_visible_log_prob += jnp.where( +# is_depth_non_return, +# jnp.log(depth_nonreturn_prob), +# jnp.log(1 - depth_nonreturn_prob) +# + self.inlier_depth_distribution.logpdf( +# observed_rgbd[3], +# latent_rgbd[3], +# depth_scale, +# intrinsics["near"], +# intrinsics["far"], +# ), +# ) + +# # Is not visible +# total_not_visible_log_prob = 0.0 +# # color term +# outlier_color_log_prob = self.outlier_color_distribution.logpdf( +# observed_rgbd[:3], +# latent_rgbd[:3], +# color_scale, +# ) +# outlier_depth_log_prob = self.outlier_depth_distribution.logpdf( +# observed_rgbd[3], +# latent_rgbd[3], +# depth_scale, +# intrinsics["near"], +# intrinsics["far"], +# ) + +# total_not_visible_log_prob += outlier_color_log_prob +# # depth term +# total_not_visible_log_prob += jnp.where( +# is_depth_non_return, +# jnp.log(depth_nonreturn_prob), +# jnp.log(1 - depth_nonreturn_prob) + outlier_depth_log_prob, +# ) + +# total_log_prob += jnp.logaddexp( +# jnp.log(visibility_prob) + total_visible_log_prob, +# jnp.log(1 - visibility_prob) + total_not_visible_log_prob, +# ) +# return jnp.where( +# jnp.any(is_unexplained(latent_rgbd)), +# outlier_color_log_prob + outlier_depth_log_prob, +# total_log_prob, +# ) + +# return color_score + depth_score diff --git a/src/b3d/chisight/gen3d/settings.py b/src/b3d/chisight/gen3d/settings.py index 0b4c74c7..ae90104c 100644 --- a/src/b3d/chisight/gen3d/settings.py +++ b/src/b3d/chisight/gen3d/settings.py @@ -3,6 +3,17 @@ import b3d.chisight.gen3d.image_kernel as image_kernel import b3d.chisight.gen3d.inference as inference import b3d.chisight.gen3d.transition_kernels as transition_kernels +from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( + RenormalizedLaplacePixelColorDistribution, + UniformPixelColorDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import ( + RenormalizedLaplacePixelDepthDistribution, + UniformPixelDepthDistribution, +) +from b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels import ( + FullPixelRGBDDistribution, +) p_resample_color = 0.005 hyperparams = { @@ -29,7 +40,14 @@ "color_scale_kernel": transition_kernels.DiscreteFlipKernel( resample_probability=0.1, support=jnp.array([0.05, 0.1, 0.15]) ), - "image_kernel": image_kernel.NoOcclusionPerVertexImageKernel(), + "image_kernel": image_kernel.NoOcclusionPerVertexImageKernel( + FullPixelRGBDDistribution( + RenormalizedLaplacePixelColorDistribution(), + UniformPixelColorDistribution(), + RenormalizedLaplacePixelDepthDistribution(), + UniformPixelDepthDistribution(), + ) + ), } inference_hyperparams = inference.InferenceHyperparams( diff --git a/src/b3d/chisight/gen3d/transition_kernels.py b/src/b3d/chisight/gen3d/transition_kernels.py index 48571e18..ae5c0ede 100644 --- a/src/b3d/chisight/gen3d/transition_kernels.py +++ b/src/b3d/chisight/gen3d/transition_kernels.py @@ -357,6 +357,26 @@ def logpdf(self, new_pose, prev_pose) -> ArrayLike: return position_score + jnp.pi**2 +@Pytree.dataclass +class GaussianVMFPoseDriftKernel(DriftKernel): + """A specialized uniform drift kernel with fixed min_val and max_val, with + additional logics to handle the color channels jointly. + + Support: [max(0.0, prev_value - max_shift), min(1.0, prev_value + max_shift)] + """ + + variance: float = Pytree.static() + concentration: float = Pytree.static() + + def sample(self, key: PRNGKey, prev_pose): + return prev_pose + + def logpdf(self, new_pose, prev_pose) -> ArrayLike: + return Pose.logpdf_gaussian_vmf_pose( + new_pose, prev_pose, self.variance, self.concentration + ) + + # Discrete Kernels # TODO: add back in the base class for discretekernel. diff --git a/src/b3d/chisight/gen3d/visualization.py b/src/b3d/chisight/gen3d/visualization.py index 26600126..dd93bca2 100644 --- a/src/b3d/chisight/gen3d/visualization.py +++ b/src/b3d/chisight/gen3d/visualization.py @@ -84,12 +84,19 @@ def create_interactive_visualization( depth_scale_kernel = hyperparams["depth_scale_kernel"] def f( + observed_r, + observed_g, + observed_b, + observed_d, color_scale, depth_scale, ): + _observed_rgbd_for_point = jnp.array( + [observed_r, observed_g, observed_b, observed_d] + ) samples = jax.vmap(attribute_proposal_function, in_axes=(0, *(None,) * 9))( jax.random.split(key, 100), - observed_rgbd_for_point, + _observed_rgbd_for_point, latent_rgbd_for_point, previous_color, previous_visibility_prob, @@ -101,7 +108,7 @@ def f( ) plot_samples( samples, - observed_rgbd_for_point, + _observed_rgbd_for_point, latent_rgbd_for_point, previous_color, previous_visibility_prob, @@ -135,4 +142,52 @@ def f( readout=True, readout_format=".4f", ), + observed_r=widgets.FloatSlider( + value=observed_rgbd_for_point[0], + min=0.0, + max=1.0, + step=0.01, + description="Observed R:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), + observed_g=widgets.FloatSlider( + value=observed_rgbd_for_point[1], + min=0.0, + max=1.0, + step=0.01, + description="Observed G:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), + observed_b=widgets.FloatSlider( + value=observed_rgbd_for_point[2], + min=0.0, + max=1.0, + step=0.01, + description="Observed B:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), + observed_d=widgets.FloatSlider( + value=observed_rgbd_for_point[3], + min=-1.0, + max=hyperparams["intrinsics"]["far"], + step=0.01, + description="Observed Depth:", + disabled=False, + continuous_update=False, + orientation="horizontal", + readout=True, + readout_format=".2f", + ), ) diff --git a/tests/gen3d/inference/test_full_inference_alg.py b/tests/gen3d/inference/test_full_inference_alg.py index 01188253..67ee3360 100644 --- a/tests/gen3d/inference/test_full_inference_alg.py +++ b/tests/gen3d/inference/test_full_inference_alg.py @@ -165,7 +165,7 @@ def gt_pose(T): ) assert ( jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) - < 0.004 + < 0.007 ) ### Real inference run ### diff --git a/tests/gen3d/inference/test_point_attribute_inferences.py b/tests/gen3d/inference/test_point_attribute_inferences.py index 877dde7c..6dfc0343 100644 --- a/tests/gen3d/inference/test_point_attribute_inferences.py +++ b/tests/gen3d/inference/test_point_attribute_inferences.py @@ -30,33 +30,27 @@ def test_visibility_prob_inference(hyperparams_and_inference_hyperparams): depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - color_kernel = hyperparams["color_kernel"] - obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() previous_color = jnp.array([0.1, 0.2, 0.3]) + latent_rgbd_for_point = jnp.concatenate([previous_color, jnp.array([1.0])]) previous_dnrp = depth_nonreturn_prob_kernel.support[0] - latent_depth = 1.0 def get_visibility_prob_sample( key, observed_rgbd_for_point, previous_visibility_prob ): - _, visibility_prob, _, _, _ = inference_moves._propose_a_points_attributes( + sample, _ = inference_moves._propose_a_points_attributes( key, observed_rgbd_for_point, - latent_depth, + latent_rgbd_for_point, previous_color, previous_visibility_prob, previous_dnrp, - depth_nonreturn_prob_kernel, - visibility_prob_kernel, - color_kernel, - obs_rgbd_kernel, color_scale, depth_scale, - hyperparams["intrinsics"], + hyperparams, inference_hyperparams, ) - return visibility_prob + return sample["visibility_prob"] get_visibility_prob_samples = jax.vmap( get_visibility_prob_sample, in_axes=(0, None, None) @@ -66,7 +60,7 @@ def get_visibility_prob_sample( # Verify that when the color matches exactly but the depth change drasticaly, the visibility prob switches to low. previous_visibility_prob = visibility_prob_kernel.support[-1] - observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.3, 4.0]) + observed_rgbd_for_this_vertex = jnp.array([0.1, 0.2, 0.35, 4.0]) visibility_prob_samples = get_visibility_prob_samples( keys, observed_rgbd_for_this_vertex, previous_visibility_prob ) @@ -105,31 +99,25 @@ def test_depth_nonreturn_prob_inference(hyperparams_and_inference_hyperparams): depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - color_kernel = hyperparams["color_kernel"] - obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() previous_color = jnp.array([0.1, 0.2, 0.3]) previous_visibility_prob = visibility_prob_kernel.support[-1] - latent_depth = 1.0 + latent_rgbd_for_point = jnp.concatenate([previous_color, jnp.array([1.0])]) def get_dnr_prob_sample(key, observed_rgbd_for_point, previous_dnrp): - _, _, dnr_prob, _, _ = inference_moves._propose_a_points_attributes( + sample, _ = inference_moves._propose_a_points_attributes( key, observed_rgbd_for_point, - latent_depth, + latent_rgbd_for_point, previous_color, previous_visibility_prob, previous_dnrp, - depth_nonreturn_prob_kernel, - visibility_prob_kernel, - color_kernel, - obs_rgbd_kernel, color_scale, depth_scale, - hyperparams["intrinsics"], + hyperparams, inference_hyperparams, ) - return dnr_prob + return sample["depth_nonreturn_prob"] get_dnr_prob_samples = jax.vmap(get_dnr_prob_sample, in_axes=(0, None, None)) @@ -176,31 +164,28 @@ def test_color_prob_inference(hyperparams_and_inference_hyperparams): depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - color_kernel = hyperparams["color_kernel"] - obs_rgbd_kernel = hyperparams["image_kernel"].get_rgbd_vertex_kernel() previous_visibility_prob = visibility_prob_kernel.support[-1] previous_dnrp = depth_nonreturn_prob_kernel.support[0] latent_depth = 1.0 + latent_rgbd_for_point = jnp.concatenate( + [jnp.array([0.1, 0.2, 0.3]), jnp.array([latent_depth])] + ) def get_color_sample(key, observed_rgbd_for_point, previous_color): - rgb, _, _, _, _ = inference_moves._propose_a_points_attributes( + sample, _ = inference_moves._propose_a_points_attributes( key, observed_rgbd_for_point, - latent_depth, + latent_rgbd_for_point, previous_color, previous_visibility_prob, previous_dnrp, - depth_nonreturn_prob_kernel, - visibility_prob_kernel, - color_kernel, - obs_rgbd_kernel, color_scale, depth_scale, - hyperparams["intrinsics"], + hyperparams, inference_hyperparams, ) - return rgb + return sample["colors"] get_color_samples = jax.vmap(get_color_sample, in_axes=(0, None, None)) diff --git a/tests/gen3d/test_model.py b/tests/gen3d/test_model.py index 1b6bcaef..5bc59d93 100644 --- a/tests/gen3d/test_model.py +++ b/tests/gen3d/test_model.py @@ -92,7 +92,7 @@ def test_model(): fig.suptitle( f""" -pose_kernel max_shift: {hyperparams['pose_kernel'].max_shift}, +pose_kernel max_shift: FILL IN, color_kernel scale: FILL IN, visibility_prob_kernel resample_probability: {hyperparams['visibility_prob_kernel'].resample_probability}, depth_nonreturn_prob_kernel resample_probability: {hyperparams['depth_nonreturn_prob_kernel'].resample_probability}, From 1a57b0979fa803f50c7b1d4c0ddc7348d19f62e2 Mon Sep 17 00:00:00 2001 From: Xiaoyan Wang Date: Mon, 16 Sep 2024 19:10:34 -0400 Subject: [PATCH 29/37] Metric compute (1/2): Loader for precomputed YCBV pose tracking result (#180) This PR introduces some utility snippets to load the precomputed YCBV results from FoundationPose so that we can make some comparisons. To fetch the precomputed results, use the `b3d_pull` command. e.g. ```bash python -m b3d.bucket_utils.b3d_pull ``` This should fetch and place the precomputed results under `assets/shared_data_bucket/foundation_pose_tracking_results`. Some examples on how to use this loader can be found in the test file in this PR. It can also be used to make sure that the results are fetched correctly: ```bash pytest tests/gen3d/test_metrics.py ``` I'm going to put together another PR to compute the actual metrics in a bit... --- src/b3d/chisight/gen3d/metrics.py | 49 +++++++++++++++++++++++++++++++ tests/gen3d/test_metrics.py | 24 +++++++++++++++ 2 files changed, 73 insertions(+) create mode 100644 src/b3d/chisight/gen3d/metrics.py create mode 100644 tests/gen3d/test_metrics.py diff --git a/src/b3d/chisight/gen3d/metrics.py b/src/b3d/chisight/gen3d/metrics.py new file mode 100644 index 00000000..ca30e5dc --- /dev/null +++ b/src/b3d/chisight/gen3d/metrics.py @@ -0,0 +1,49 @@ +from pathlib import Path + +import jax.numpy as jnp +from genjax import Pytree +from genjax.typing import FloatArray + +from b3d.utils import get_assets_path + +FP_RESULTS_ROOT_DIR = ( + get_assets_path() / "shared_data_bucket/foundation_pose_tracking_results" +) +DEFAULT_FP_YCBV_RESULT_DIR = ( + FP_RESULTS_ROOT_DIR / "ycbv/2024-07-11-every-50-frames-gt-init" +) + + +@Pytree.dataclass +class YCBVTrackingResultLoader(Pytree): + """A utility class that loads precomputed YCBV tracking results from the + specified directory as commanded. Note that this dataclass itself does not + keep a copy of the result + """ + + result_dir: Path + + def load(self, test_scene_id: IndentationError, object_id: int) -> FloatArray: + """Given the test scene and object id, load the corresponding tracking + result from the specified directory. The returning JAX array will have + shape (num_frames, 4, 4), where the estimated pose in each frame is + stored as a 4x4 transformation matrix. + """ + filename = self.result_dir / str(test_scene_id) / f"object_{object_id}.npy" + return jnp.load(filename) + + def get_scene_ids(self) -> list[int]: + return sorted( + [int(test_scene.name) for test_scene in self.result_dir.iterdir()] + ) + + def get_object_ids(self, test_scene_id: int) -> list[int]: + scene_dir = self.result_dir / str(test_scene_id) + prefix_length = len("object_") + return sorted( + [int(object_id.stem[prefix_length:]) for object_id in scene_dir.iterdir()] + ) + + +# a default loader for the most recently computed foundation pose tracking results +foundation_pose_ycbv_result = YCBVTrackingResultLoader(DEFAULT_FP_YCBV_RESULT_DIR) diff --git a/tests/gen3d/test_metrics.py b/tests/gen3d/test_metrics.py new file mode 100644 index 00000000..3419de15 --- /dev/null +++ b/tests/gen3d/test_metrics.py @@ -0,0 +1,24 @@ +import pytest +from b3d.chisight.gen3d.metrics import ( + FP_RESULTS_ROOT_DIR, + foundation_pose_ycbv_result, +) + +TEST_FP_YCBV_RESULT_DIR = ( + FP_RESULTS_ROOT_DIR / "ycbv/2024-07-11-every-50-frames-gt-init" +) + + +@pytest.mark.skipif( + not TEST_FP_YCBV_RESULT_DIR.exists(), + reason="No foundation pose tracking results found.", +) +def test_loading_precomputed_ycbv_results(): + precomputed_poses = foundation_pose_ycbv_result.load(test_scene_id=48, object_id=1) + assert precomputed_poses.shape == (45, 4, 4) + + test_scenes = foundation_pose_ycbv_result.get_scene_ids() + assert len(test_scenes) == 12 + + obj_ids_scene_48 = foundation_pose_ycbv_result.get_object_ids(test_scene_id=48) + assert len(obj_ids_scene_48) == 5 From 7cc26dc6577902bba77af9cbc9cca7381a2fc342 Mon Sep 17 00:00:00 2001 From: nishadgothoskar Date: Mon, 16 Sep 2024 20:35:35 -0400 Subject: [PATCH 30/37] YCBV Run Script (#182) --- .../old_inference_algorithm.ipynb | 247 ++++------- .../run_ycbv_evaluation.py | 70 +--- src/b3d/chisight/gen3d/image_kernel.py | 2 + src/b3d/chisight/gen3d/inference_old.py | 390 +++++++++--------- .../gen3d/pixel_kernels/pixel_rgbd_kernels.py | 201 ++++----- src/b3d/chisight/gen3d/visualization.py | 28 ++ src/b3d/utils.py | 13 + 7 files changed, 407 insertions(+), 544 deletions(-) rename {notebooks/bayes3d_paper => scripts}/run_ycbv_evaluation.py (73%) diff --git a/notebooks/bayes3d_paper/old_inference_algorithm.ipynb b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb index 78eb3652..a4e03035 100644 --- a/notebooks/bayes3d_paper/old_inference_algorithm.ipynb +++ b/notebooks/bayes3d_paper/old_inference_algorithm.ipynb @@ -27,8 +27,7 @@ "import numpy as np\n", "from genjax import SelectionBuilder as S\n", "from genjax import ChoiceMapBuilder as C\n", - "\n", - "b3d.rr_init(\"dynamics2\")" + "\n" ] }, { @@ -40,20 +39,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "Scene 48\n" + "Scene 49\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 45/45 [00:05<00:00, 8.95it/s]\n" + "100%|██████████| 49/49 [00:03<00:00, 12.37it/s]\n" ] }, { "data": { - "image/jpeg": 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", 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", 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", 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", "text/plain": [ "" ] @@ -66,7 +65,7 @@ "source": [ "### Loading data ###\n", "b3d.reload(b3d.io.data_loader)\n", - "scene_id = 48\n", + "scene_id = 49\n", "FRAME_RATE = 50\n", "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", "print(f\"Scene {scene_id}\")\n", @@ -97,7 +96,15 @@ "cell_type": "code", "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "253820.56\n" + ] + } + ], "source": [ "import b3d\n", "import b3d.chisight.gen3d.model\n", @@ -107,6 +114,7 @@ "import b3d.chisight.gen3d.image_kernel as image_kernel\n", "import b3d.chisight.gen3d.pixel_kernels.pixel_rgbd_kernels as pixel_rgbd_kernels\n", "b3d.reload(b3d.chisight.gen3d.image_kernel)\n", + "b3d.reload(b3d.chisight.gen3d.model)\n", "import b3d.io.data_loader\n", "import jax\n", "import jax.numpy as jnp\n", @@ -120,29 +128,11 @@ "from genjax import ChoiceMapBuilder as C\n", "from genjax import Pytree\n", "\n", - "import b3d.chisight.gen3d.settings \n", - "hyperparams = b3d.chisight.gen3d.settings.hyperparams\n", - "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "489336.38\n" - ] - } - ], - "source": [ "\n", + "b3d.rr_init(\"dynamics2\")\n", "T = 0\n", "b3d.rr_set_time(T)\n", - "OBJECT_INDEX = 0\n", + "OBJECT_INDEX = 3\n", "\n", "template_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]\n", "rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[OBJECT_INDEX].transform(template_pose))\n", @@ -161,13 +151,19 @@ "# model_vertices = mesh.vertices\n", "# model_colors = mesh.vertex_attributes\n", "\n", - "hyperparams[\"intrinsics\"] = {\n", + "intrinsics = {\n", " \"fx\": fx, \"fy\": fy, \"cx\": cx, \"cy\": cy,\n", " \"image_height\": Pytree.const(image_height),\n", " \"image_width\": Pytree.const(image_width),\n", " \"near\": 0.01,\n", " \"far\": 3.0,\n", "}\n", + "\n", + "import b3d.chisight.gen3d.settings \n", + "b3d.reload(b3d.chisight.gen3d.settings)\n", + "hyperparams = b3d.chisight.gen3d.settings.hyperparams\n", + "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams\n", + "hyperparams[\"intrinsics\"] = intrinsics\n", "hyperparams[\"vertices\"] = model_vertices\n", "\n", "\n", @@ -210,15 +206,45 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "traces = [\n", + " trace.update(\n", + " key,\n", + " C.d({\n", + " \"rgbd\": all_data[T][\"rgbd\"],\n", + " \"pose\": all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX],\n", + " })\n", + " )[0]\n", + " for T in range(len(all_data ))\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d.chisight.gen3d.visualization as viz\n", + "viz.make_video_from_traces(\n", + " traces,\n", + " \"output_video_test.mp4\", \n", + " scale=0.25\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import b3d.chisight.gen3d.inference as inference\n", - "import b3d.chisight.gen3d.inference_old as inference_old\n", "import b3d.chisight.gen3d.settings \n", "b3d.reload(b3d.chisight.gen3d.inference)\n", - "b3d.reload(b3d.chisight.gen3d.inference_old)\n", "inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams\n", "import b3d.chisight.gen3d.visualization as viz\n", "b3d.reload(b3d.chisight.gen3d.visualization)\n", @@ -229,155 +255,34 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/45 [00:00 3\u001b[0m trace \u001b[38;5;241m=\u001b[39m \u001b[43minference_old\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minference_step\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 4\u001b[0m results[T] \u001b[38;5;241m=\u001b[39m trace\n\u001b[1;32m 6\u001b[0m b3d\u001b[38;5;241m.\u001b[39mchisight\u001b[38;5;241m.\u001b[39mgen3d\u001b[38;5;241m.\u001b[39mmodel\u001b[38;5;241m.\u001b[39mviz_trace(trace, T,\n\u001b[1;32m 7\u001b[0m ground_truth_vertices\u001b[38;5;241m=\u001b[39mmeshes[OBJECT_INDEX]\u001b[38;5;241m.\u001b[39mvertices,\n\u001b[1;32m 8\u001b[0m ground_truth_pose\u001b[38;5;241m=\u001b[39mall_data[T][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcamera_pose\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39minv() \u001b[38;5;241m@\u001b[39m all_data[T][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mobject_poses\u001b[39m\u001b[38;5;124m\"\u001b[39m][OBJECT_INDEX] \n\u001b[1;32m 9\u001b[0m )\n", - "File \u001b[0;32m~/b3d/src/b3d/chisight/gen3d/inference_old.py:188\u001b[0m, in \u001b[0;36minference_step\u001b[0;34m(trace, key, inference_hyperparams)\u001b[0m\n\u001b[1;32m 179\u001b[0m poses \u001b[38;5;241m=\u001b[39m Pose\u001b[38;5;241m.\u001b[39mconcatenate_poses(\n\u001b[1;32m 180\u001b[0m [\n\u001b[1;32m 181\u001b[0m Pose\u001b[38;5;241m.\u001b[39msample_gaussian_vmf_pose_vmap(keys[:\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m], current_pose, var, conc),\n\u001b[1;32m 182\u001b[0m current_pose[\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m],\n\u001b[1;32m 183\u001b[0m ]\n\u001b[1;32m 184\u001b[0m )\n\u001b[1;32m 185\u001b[0m pose_scores \u001b[38;5;241m=\u001b[39m Pose\u001b[38;5;241m.\u001b[39mlogpdf_gaussian_vmf_pose_vmap(\n\u001b[1;32m 186\u001b[0m poses, trace\u001b[38;5;241m.\u001b[39mget_choices()[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpose\u001b[39m\u001b[38;5;124m\"\u001b[39m], var, conc\n\u001b[1;32m 187\u001b[0m )\n\u001b[0;32m--> 188\u001b[0m scores \u001b[38;5;241m=\u001b[39m \u001b[43mupdate_all_get_score_vmap\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkeys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrace\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mposes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minference_hyperparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 189\u001b[0m scores_pose_q_correction \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 190\u001b[0m scores \u001b[38;5;241m-\u001b[39m pose_scores\n\u001b[1;32m 191\u001b[0m ) \u001b[38;5;66;03m# After this, scores are fair estimates of P(data | previous state)\u001b[39;00m\n\u001b[1;32m 192\u001b[0m \u001b[38;5;66;03m# and can be used to resample the choice sets.\u001b[39;00m\n", - " \u001b[0;31m[... skipping hidden 10 frame]\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/jax/_src/interpreters/pxla.py:1185\u001b[0m, in \u001b[0;36mExecuteReplicated.__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 1183\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_handle_token_bufs(result_token_bufs, sharded_runtime_token)\n\u001b[1;32m 1184\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1185\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mxla_executable\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute_sharded\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_bufs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1186\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dispatch\u001b[38;5;241m.\u001b[39mneeds_check_special():\n\u001b[1;32m 1187\u001b[0m out_arrays \u001b[38;5;241m=\u001b[39m results\u001b[38;5;241m.\u001b[39mdisassemble_into_single_device_arrays()\n", - "\u001b[0;31mXlaRuntimeError\u001b[0m: RESOURCE_EXHAUSTED: Out of memory while trying to allocate 39935984384 bytes.\nBufferAssignment OOM Debugging.\nBufferAssignment stats:\n parameter allocation: 5.89MiB\n constant allocation: 97B\n maybe_live_out allocation: 39.1KiB\n preallocated temp allocation: 37.19GiB\n preallocated temp fragmentation: 1.2KiB (0.00%)\n total allocation: 37.20GiB\nPeak buffers:\n\tBuffer 1:\n\t\tSize: 6.35GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/inference_old.py\" source_line=60\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,3]\n\t\t==========================\n\n\tBuffer 2:\n\t\tSize: 2.82GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/reduce_or[axes=(1, 2)]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=29\n\t\tXLA Label: fusion\n\t\tShape: f32[4,10000,18927]\n\t\t==========================\n\n\tBuffer 3:\n\t\tSize: 2.82GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/concatenate[dimension=2]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/image_kernel.py\" source_line=181\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,4]\n\t\t==========================\n\n\tBuffer 4:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/and\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=104\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3]\n\t\t==========================\n\n\tBuffer 5:\n\t\tSize: 2.12GiB\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 6:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/log_prob/sub\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=93\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 7:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=130\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 8:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=130\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 9:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/cdf/sign\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=95\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3]\n\t\t==========================\n\n\tBuffer 10:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/cdf/sign\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=95\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 11:\n\t\tSize: 2.12GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(Laplace))/cdf/sign\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/modeling_utils.py\" source_line=95\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927,3,1]\n\t\t==========================\n\n\tBuffer 12:\n\t\tSize: 1.59GiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/vmap(vmap(vmap(jit(_where))))/broadcast_in_dim[shape=(10000, 18927, 3, 3) broadcast_dimensions=(0, 1, 3)]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/pose/core.py\" source_line=119\n\t\tXLA Label: fusion\n\t\tShape: pred[10000,18927,3,3]\n\t\t==========================\n\n\tBuffer 13:\n\t\tSize: 722.01MiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/reduce[computation=_ArgMinMaxReducer(gt) dimensions=(2,)]\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/inference_old.py\" source_line=47\n\t\tXLA Label: fusion\n\t\tShape: s32[10000,18927]\n\t\t==========================\n\n\tBuffer 14:\n\t\tSize: 722.01MiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=170\n\t\tXLA Label: fusion\n\t\tShape: f32[1,10000,18927]\n\t\t==========================\n\n\tBuffer 15:\n\t\tSize: 722.01MiB\n\t\tOperator: op_name=\"jit(update_all_get_score)/jit(main)/vmap(jit(update_vertex_attributes))/vmap(jit(attribute_proposal))/add\" source_file=\"/home/nishadgothoskar/b3d/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py\" source_line=170\n\t\tXLA Label: fusion\n\t\tShape: f32[10000,18927]\n\t\t==========================\n\n" + " 0%| | 0/45 [00:00 int: return self.pixel_to_point_idx[pixel_x, pixel_y] +@jax.jit def get_latent_and_observed_correspondences(state, hyperparams, observed_rgbd): transformed_points = state["pose"].apply(hyperparams["vertices"]) points_to_pixels = PixelsPointsAssociation.from_points_and_intrinsics( @@ -184,6 +185,7 @@ def get_latent_and_observed_correspondences(state, hyperparams, observed_rgbd): return latent_rgbd_per_point, observed_rgbd_per_point +@jax.jit def get_latent_rgb_image(state, hyperparams): transformed_points = state["pose"].apply(hyperparams["vertices"]) ppa = PixelsPointsAssociation.from_points_and_intrinsics( diff --git a/src/b3d/chisight/gen3d/inference_old.py b/src/b3d/chisight/gen3d/inference_old.py index c45f9dc9..712bf9d5 100644 --- a/src/b3d/chisight/gen3d/inference_old.py +++ b/src/b3d/chisight/gen3d/inference_old.py @@ -1,195 +1,195 @@ -import jax -import jax.numpy as jnp -import jax.random -from genjax import ChoiceMapBuilder as C - -import b3d -from b3d import Pose - -from .model import ( - make_colors_choicemap, - make_depth_nonreturn_prob_choicemap, - make_visibility_prob_choicemap, -) - - -@jax.jit -def attribute_proposal( - key, - observed_rgbd_for_point, - latent_rgbd_for_point, - previous_color, - previous_visibility_prob, - previous_dnrp, - color_scale, - depth_scale, - hyperparams, - inference_hyperparams, -): - image_kernel = hyperparams["image_kernel"] - vertex_rgbd_kernel = image_kernel.get_rgbd_vertex_kernel() - - # color_outlier_probability_sweep is (k,) shape array - depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] - dnrp_values = depth_nonreturn_prob_kernel.support - - def likelihood_scorer(dnrp): - return vertex_rgbd_kernel.logpdf( - observed_rgbd_for_point, - latent_rgbd_for_point, - color_scale, - depth_scale, - previous_visibility_prob, - dnrp, - hyperparams["intrinsics"], - ) - - dnrp = dnrp_values[jnp.argmax(jax.vmap(likelihood_scorer)(dnrp_values))] - - # color_outlier_probability_sweep is (k,) shape array - visibility_values = hyperparams["visibility_prob_kernel"].support - visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - - visbility_transition_scores = jax.vmap( - visibility_prob_kernel.logpdf, in_axes=(0, None) - )(visibility_values, previous_visibility_prob) - - color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) - observed_color = observed_rgbd_for_point[:3] - color_sweep = ( - color_interpolations_per_proposal[..., None] * observed_color - + (1.0 - color_interpolations_per_proposal[..., None]) * previous_color - ) - - color_kernel = hyperparams["color_kernel"] - color_transition_scores = jax.vmap(color_kernel.logpdf, in_axes=(0, None))( - color_sweep, previous_color - ) - - def likelihood_scorer(color, visibility_prob): - latent_rgbd_adjusted = latent_rgbd_for_point.at[:3].set(color) - return vertex_rgbd_kernel.logpdf( - observed_rgbd_for_point, - latent_rgbd_adjusted, - color_scale, - depth_scale, - visibility_prob, - dnrp, - hyperparams["intrinsics"], - ) - - vmap_version = jax.vmap( - jax.vmap( - likelihood_scorer, - in_axes=(None, 0), - ), - in_axes=(0, None), - ) - - likelihood_scores_per_sweep_point_and_vertex = vmap_version( - color_sweep, visibility_values - ) - - scores_color_and_visibility = ( - likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points) - + color_transition_scores[:, None, ...] - + visbility_transition_scores[None, ...] - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - idx_color, idx_visibility = jnp.unravel_index( - jnp.argmax(scores_color_and_visibility.reshape(-1)), - scores_color_and_visibility.shape, - ) - return { - "colors": color_sweep[idx_color], - "visibility_prob": visibility_values[idx_visibility], - "depth_nonreturn_prob": dnrp, - # "scores": scores_color_and_visibility, - } - - -@jax.jit -def update_vertex_attributes(key, trace, inference_hyperparams): - hyperparams, previous_state = trace.get_args() - - latent_rgbd_per_point, observed_rgbd_per_point = ( - b3d.chisight.gen3d.image_kernel.get_latent_and_observed_correspondences( - trace.get_retval()["new_state"], - trace.get_args()[0], - trace.get_choices()["rgbd"], - ) - ) - - previous_state = trace.get_args()[1] - previous_color = previous_state["colors"] - previous_visibility_prob = previous_state["visibility_prob"] - previous_dnrp = previous_state["depth_nonreturn_prob"] - color_scale = previous_state["color_scale"] - depth_scale = previous_state["depth_scale"] - - keys = jax.random.split(key, len(observed_rgbd_per_point)) - - sample = jax.vmap( - attribute_proposal, - in_axes=(0, 0, 0, 0, 0, 0, None, None, None, None), - )( - keys, - observed_rgbd_per_point, - latent_rgbd_per_point, - previous_color, - previous_visibility_prob, - previous_dnrp, - color_scale, - depth_scale, - hyperparams, - inference_hyperparams, - ) - trace = trace.update( - key, - make_colors_choicemap(sample["colors"]) - ^ make_visibility_prob_choicemap(sample["visibility_prob"]) - ^ make_depth_nonreturn_prob_choicemap(sample["depth_nonreturn_prob"]), - )[0] - return trace, {} - - -def update_all(key, trace, pose, inference_hyperparams): - trace = trace.update(key, C["pose"].set(pose))[0] - trace, _ = update_vertex_attributes(key, trace, inference_hyperparams) - return trace - - -def update_all_get_score(key, trace, pose, inference_hyperparams): - trace = update_all(key, trace, pose, inference_hyperparams) - return trace.get_score() - - -update_all_get_score_vmap = jax.jit( - jax.vmap(update_all_get_score, in_axes=(0, None, 0, None)) -) - - -def inference_step(trace, key, inference_hyperparams): - number = 10000 - current_pose = trace.get_choices()["pose"] - var_conc = [(0.04, 1000.0), (0.01, 2000.0), (0.005, 3000.0)] - for var, conc in var_conc: - key = jax.random.split(key, 2)[-1] - keys = jax.random.split(key, number) - poses = Pose.concatenate_poses( - [ - Pose.sample_gaussian_vmf_pose_vmap(keys[:-1], current_pose, var, conc), - current_pose[None, ...], - ] - ) - pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( - poses, trace.get_choices()["pose"], var, conc - ) - scores = update_all_get_score_vmap(keys, trace, poses, inference_hyperparams) - scores_pose_q_correction = ( - scores - pose_scores - ) # After this, scores are fair estimates of P(data | previous state) - # and can be used to resample the choice sets. - current_pose = poses[jnp.argmax(scores)] - trace = update_all(key, trace, current_pose, inference_hyperparams) - return trace, scores, scores_pose_q_correction +# import jax +# import jax.numpy as jnp +# import jax.random +# from genjax import ChoiceMapBuilder as C + +# import b3d +# from b3d import Pose + +# from .model import ( +# make_colors_choicemap, +# make_depth_nonreturn_prob_choicemap, +# make_visibility_prob_choicemap, +# ) + + +# @jax.jit +# def attribute_proposal( +# key, +# observed_rgbd_for_point, +# latent_rgbd_for_point, +# previous_color, +# previous_visibility_prob, +# previous_dnrp, +# color_scale, +# depth_scale, +# hyperparams, +# inference_hyperparams, +# ): +# image_kernel = hyperparams["image_kernel"] +# vertex_rgbd_kernel = image_kernel.get_rgbd_vertex_kernel() + +# # color_outlier_probability_sweep is (k,) shape array +# depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] +# dnrp_values = depth_nonreturn_prob_kernel.support + +# def likelihood_scorer(dnrp): +# return vertex_rgbd_kernel.logpdf( +# observed_rgbd_for_point, +# latent_rgbd_for_point, +# color_scale, +# depth_scale, +# previous_visibility_prob, +# dnrp, +# hyperparams["intrinsics"], +# ) + +# dnrp = dnrp_values[jnp.argmax(jax.vmap(likelihood_scorer)(dnrp_values))] + +# # color_outlier_probability_sweep is (k,) shape array +# visibility_values = hyperparams["visibility_prob_kernel"].support +# visibility_prob_kernel = hyperparams["visibility_prob_kernel"] + +# visbility_transition_scores = jax.vmap( +# visibility_prob_kernel.logpdf, in_axes=(0, None) +# )(visibility_values, previous_visibility_prob) + +# color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) +# observed_color = observed_rgbd_for_point[:3] +# color_sweep = ( +# color_interpolations_per_proposal[..., None] * observed_color +# + (1.0 - color_interpolations_per_proposal[..., None]) * previous_color +# ) + +# color_kernel = hyperparams["color_kernel"] +# color_transition_scores = jax.vmap(color_kernel.logpdf, in_axes=(0, None))( +# color_sweep, previous_color +# ) + +# def likelihood_scorer(color, visibility_prob): +# latent_rgbd_adjusted = latent_rgbd_for_point.at[:3].set(color) +# return vertex_rgbd_kernel.logpdf( +# observed_rgbd_for_point, +# latent_rgbd_adjusted, +# color_scale, +# depth_scale, +# visibility_prob, +# dnrp, +# hyperparams["intrinsics"], +# ) + +# vmap_version = jax.vmap( +# jax.vmap( +# likelihood_scorer, +# in_axes=(None, 0), +# ), +# in_axes=(0, None), +# ) + +# likelihood_scores_per_sweep_point_and_vertex = vmap_version( +# color_sweep, visibility_values +# ) + +# scores_color_and_visibility = ( +# likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points) +# + color_transition_scores[:, None, ...] +# + visbility_transition_scores[None, ...] +# ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) + +# idx_color, idx_visibility = jnp.unravel_index( +# jnp.argmax(scores_color_and_visibility.reshape(-1)), +# scores_color_and_visibility.shape, +# ) +# return { +# "colors": color_sweep[idx_color], +# "visibility_prob": visibility_values[idx_visibility], +# "depth_nonreturn_prob": dnrp, +# # "scores": scores_color_and_visibility, +# } + + +# @jax.jit +# def update_vertex_attributes(key, trace, inference_hyperparams): +# hyperparams, previous_state = trace.get_args() + +# latent_rgbd_per_point, observed_rgbd_per_point = ( +# b3d.chisight.gen3d.image_kernel.get_latent_and_observed_correspondences( +# trace.get_retval()["new_state"], +# trace.get_args()[0], +# trace.get_choices()["rgbd"], +# ) +# ) + +# previous_state = trace.get_args()[1] +# previous_color = previous_state["colors"] +# previous_visibility_prob = previous_state["visibility_prob"] +# previous_dnrp = previous_state["depth_nonreturn_prob"] +# color_scale = previous_state["color_scale"] +# depth_scale = previous_state["depth_scale"] + +# keys = jax.random.split(key, len(observed_rgbd_per_point)) + +# sample = jax.vmap( +# attribute_proposal, +# in_axes=(0, 0, 0, 0, 0, 0, None, None, None, None), +# )( +# keys, +# observed_rgbd_per_point, +# latent_rgbd_per_point, +# previous_color, +# previous_visibility_prob, +# previous_dnrp, +# color_scale, +# depth_scale, +# hyperparams, +# inference_hyperparams, +# ) +# trace = trace.update( +# key, +# make_colors_choicemap(sample["colors"]) +# ^ make_visibility_prob_choicemap(sample["visibility_prob"]) +# ^ make_depth_nonreturn_prob_choicemap(sample["depth_nonreturn_prob"]), +# )[0] +# return trace, {} + + +# def update_all(key, trace, pose, inference_hyperparams): +# trace = trace.update(key, C["pose"].set(pose))[0] +# trace, _ = update_vertex_attributes(key, trace, inference_hyperparams) +# return trace + + +# def update_all_get_score(key, trace, pose, inference_hyperparams): +# trace = update_all(key, trace, pose, inference_hyperparams) +# return trace.get_score() + + +# update_all_get_score_vmap = jax.jit( +# jax.vmap(update_all_get_score, in_axes=(0, None, 0, None)) +# ) + + +# def inference_step(trace, key, inference_hyperparams): +# number = 10000 +# current_pose = trace.get_choices()["pose"] +# var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.01, 2000.0), (0.005, 2000.0)] +# for var, conc in var_conc: +# key = jax.random.split(key, 2)[-1] +# keys = jax.random.split(key, number) +# poses = Pose.concatenate_poses( +# [ +# Pose.sample_gaussian_vmf_pose_vmap(keys[:-1], current_pose, var, conc), +# current_pose[None, ...], +# ] +# ) +# pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( +# poses, trace.get_choices()["pose"], var, conc +# ) +# scores = update_all_get_score_vmap(keys, trace, poses, inference_hyperparams) +# scores_pose_q_correction = ( +# scores - pose_scores +# ) # After this, scores are fair estimates of P(data | previous state) +# # and can be used to resample the choice sets. +# current_pose = poses[jnp.argmax(scores)] +# trace = update_all(key, trace, current_pose, inference_hyperparams) +# return trace, scores, scores_pose_q_correction diff --git a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py index e0992897..a1d75b64 100644 --- a/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py +++ b/src/b3d/chisight/gen3d/pixel_kernels/pixel_rgbd_kernels.py @@ -1,6 +1,7 @@ from abc import abstractmethod import genjax +import jax import jax.numpy as jnp from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import PixelColorDistribution from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import PixelDepthDistribution @@ -167,132 +168,74 @@ def logpdf( ) -# @Pytree.dataclass -# class OldOcclusionPixelRGBDDistribution(PixelRGBDDistribution): -# """ -# Distribution args: -# - latent_rgbd: 4-array: RGBD value. (a value of [-1, -1, -1, -1] indicates no point hits here.) -# - color_scale: float -# - depth_scale: float -# - visibility_prob: float -# - depth_nonreturn_prob: float - -# The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). - -# Note that this distribution expects the observed_rgbd to be valid. If an invalid -# pixel is observed, the logpdf will return -inf. -# """ - -# def sample( -# self, -# key: PRNGKey, -# latent_rgbd: FloatArray, -# color_scale: float, -# depth_scale: float, -# visibility_prob: float, -# depth_nonreturn_prob: float, -# intrinsics: dict, -# ) -> FloatArray: -# return jnp.ones((4,)) * 0.5 - -# def logpdf( -# self, -# observed_rgbd: FloatArray, -# latent_rgbd: FloatArray, -# color_scale: float, -# depth_scale: float, -# visibility_prob: float, -# depth_nonreturn_prob: float, -# intrinsics: dict, -# ) -> float: -# total_visible_log_prob = 0.0 - -# total_visible_log_prob += renormalized_laplace.logpdf( -# observed_rgbd[:3], latent_rgbd[:3], color_scale, 0.0, 1.0 -# ).sum(axis=-1) - -# color_not_visible_score = jnp.log(1 / 1.0**3) -# color_score = jnp.logaddexp( -# color_visible_branch_score + jnp.log(visibility_prob), -# color_not_visible_score + jnp.log(1 - visibility_prob), -# ) - -# depth_visible_branch_score = renormalized_laplace.logpdf( -# observed_rgbd[3], -# latent_rgbd[3], -# depth_scale, -# intrinsics["near"], -# intrinsics["far"], -# ) -# depth_not_visible_score = jnp.log(1 / (intrinsics["far"] - intrinsics["near"])) -# _depth_score = jnp.logaddexp( -# depth_visible_branch_score + jnp.log(visibility_prob), -# depth_not_visible_score + jnp.log(1 - visibility_prob), -# ) -# is_depth_non_return = observed_rgbd[3] < 0.0001 - -# depth_score = jnp.where( -# is_depth_non_return, -# jnp.log(depth_nonreturn_prob), -# jnp.log(1.0 - depth_nonreturn_prob) + _depth_score, -# ) - -# total_log_prob = 0.0 - -# is_depth_non_return = observed_rgbd[3] == 0.0 - -# # Is visible -# total_visible_log_prob = 0.0 -# # color term -# total_visible_log_prob += self.inlier_color_distribution.logpdf( -# observed_rgbd[:3], latent_rgbd[:3], color_scale -# ) -# # depth term -# total_visible_log_prob += jnp.where( -# is_depth_non_return, -# jnp.log(depth_nonreturn_prob), -# jnp.log(1 - depth_nonreturn_prob) -# + self.inlier_depth_distribution.logpdf( -# observed_rgbd[3], -# latent_rgbd[3], -# depth_scale, -# intrinsics["near"], -# intrinsics["far"], -# ), -# ) - -# # Is not visible -# total_not_visible_log_prob = 0.0 -# # color term -# outlier_color_log_prob = self.outlier_color_distribution.logpdf( -# observed_rgbd[:3], -# latent_rgbd[:3], -# color_scale, -# ) -# outlier_depth_log_prob = self.outlier_depth_distribution.logpdf( -# observed_rgbd[3], -# latent_rgbd[3], -# depth_scale, -# intrinsics["near"], -# intrinsics["far"], -# ) - -# total_not_visible_log_prob += outlier_color_log_prob -# # depth term -# total_not_visible_log_prob += jnp.where( -# is_depth_non_return, -# jnp.log(depth_nonreturn_prob), -# jnp.log(1 - depth_nonreturn_prob) + outlier_depth_log_prob, -# ) - -# total_log_prob += jnp.logaddexp( -# jnp.log(visibility_prob) + total_visible_log_prob, -# jnp.log(1 - visibility_prob) + total_not_visible_log_prob, -# ) -# return jnp.where( -# jnp.any(is_unexplained(latent_rgbd)), -# outlier_color_log_prob + outlier_depth_log_prob, -# total_log_prob, -# ) - -# return color_score + depth_score +@Pytree.dataclass +class OldOcclusionPixelRGBDDistribution(PixelRGBDDistribution): + """ + Distribution args: + - latent_rgbd: 4-array: RGBD value. (a value of [-1, -1, -1, -1] indicates no point hits here.) + - color_scale: float + - depth_scale: float + - visibility_prob: float + - depth_nonreturn_prob: float + + The support of the distribution is [0, 1]^3 x ([near, far] + {DEPTH_NONRETURN_VALUE}). + + Note that this distribution expects the observed_rgbd to be valid. If an invalid + pixel is observed, the logpdf will return -inf. + """ + + def sample( + self, + key: PRNGKey, + latent_rgbd: FloatArray, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, + intrinsics: dict, + ) -> FloatArray: + return jnp.ones((4,)) * 0.5 + + def logpdf( + self, + observed_rgbd: FloatArray, + latent_rgbd: FloatArray, + color_scale: float, + depth_scale: float, + visibility_prob: float, + depth_nonreturn_prob: float, + intrinsics: dict, + ) -> float: + is_depth_non_return = observed_rgbd[3] < 0.0001 + + visible_branch_log_score = 0.0 + color_visible_branch_score = jax.scipy.stats.laplace.logpdf( + observed_rgbd[:3], latent_rgbd[:3], color_scale + ).sum(axis=-1) + depth_visible_branch_score = jnp.where( + is_depth_non_return, + jnp.log(depth_nonreturn_prob), + jnp.log(1.0 - depth_nonreturn_prob) + + jax.scipy.stats.laplace.logpdf( + observed_rgbd[3], latent_rgbd[3], depth_scale + ), + ) + visible_branch_log_score = ( + color_visible_branch_score + depth_visible_branch_score + ) + + color_not_visible_branch_score = jnp.log(1 / 1.0**3) + depth_not_visible_branch_score = jnp.where( + is_depth_non_return, + jnp.log(depth_nonreturn_prob), + jnp.log(1.0 - depth_nonreturn_prob) + + jnp.log(1 / (intrinsics["far"] - intrinsics["near"])), + ) + not_visible_branch_log_score = ( + color_not_visible_branch_score + depth_not_visible_branch_score + ) + + return jnp.logaddexp( + jnp.log(visibility_prob) + visible_branch_log_score, + jnp.log(1 - visibility_prob) + not_visible_branch_log_score, + ) diff --git a/src/b3d/chisight/gen3d/visualization.py b/src/b3d/chisight/gen3d/visualization.py index dd93bca2..821d98db 100644 --- a/src/b3d/chisight/gen3d/visualization.py +++ b/src/b3d/chisight/gen3d/visualization.py @@ -5,6 +5,8 @@ from ipywidgets import interact from matplotlib.gridspec import GridSpec +import b3d + def plot_samples( samples, @@ -191,3 +193,29 @@ def f( readout_format=".2f", ), ) + + +# Make video + + +def make_video_from_traces(traces, output_filename, scale=0.2, fps=5.0): + images = [] + for trace in traces: + latent_rgb = b3d.chisight.gen3d.image_kernel.get_latent_rgb_image( + trace.get_retval()["new_state"], trace.get_args()[0] + ) + + a = b3d.scale_image( + b3d.viz_rgb( + trace.get_choices()["rgbd"][..., :3], + ), + scale, + ) + b = b3d.scale_image( + b3d.viz_rgb( + latent_rgb[..., :3], + ), + scale, + ) + images.append(b3d.multi_panel([a, b, b3d.overlay_image(a, b)])) + b3d.utils.make_video_from_pil_images(images, output_filename, fps=fps) diff --git a/src/b3d/utils.py b/src/b3d/utils.py index 3585df9a..2c5f3701 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -911,3 +911,16 @@ def make_grid_points(min_vec, max_vec, num_vec): ) deltas = deltas.reshape((-1, len(min_vec)), order="F") return deltas + + +def scale_image(img, factor): + """Scale an image. + + Args: + img (PIL.Image): Image to scale. + factor (float): Scale factor. + Returns: + PIL.Image: Scaled image. + """ + w, h = img.size + return img.resize((int(w * factor), int(h * factor))) From 0030b651b0df4bb3e5a5309425a7f25764461497 Mon Sep 17 00:00:00 2001 From: Xiaoyan Wang Date: Mon, 16 Sep 2024 20:54:53 -0400 Subject: [PATCH 31/37] Metric compute (2/2): Script to get ADD, ADD-S errors, as well as AUC aggregation (#181) As the title suggests, this PR adds the metrics that are commonly used in 6DoF pose tracking into our repo. Note that currently the metrics are computed using numpy/scipy/sklearn, so they are not compatible with other JAX transformations (e.g. vmap or jit). This is because many of the methods do not have a ready-to-use JAX equivalent, and implementing one ourselves might not be worthwhile given that we likely only need to compute those scores at the very end of the inference. I'm also including an example of using these scoring function in the [test file here](https://github.com/probcomp/b3d/blob/74c2a50205ec6a90855d3271b22edf571373df75/tests/gen3d/test_metrics.py#L54-L81). They can also be triggered by ```bash pytest tests/gen3d/test_metrics.py ``` Check out the earlier PR https://github.com/probcomp/b3d/pull/180 for the instruction of obtaining the precomputed FoundationPose tracking results. --- src/b3d/chisight/gen3d/metrics.py | 88 +++++++++++++++++++++++++++++-- tests/gen3d/test_metrics.py | 59 +++++++++++++++++++++ 2 files changed, 143 insertions(+), 4 deletions(-) diff --git a/src/b3d/chisight/gen3d/metrics.py b/src/b3d/chisight/gen3d/metrics.py index ca30e5dc..5ecade7e 100644 --- a/src/b3d/chisight/gen3d/metrics.py +++ b/src/b3d/chisight/gen3d/metrics.py @@ -1,8 +1,9 @@ from pathlib import Path +from typing import Sequence -import jax.numpy as jnp +import numpy as np from genjax import Pytree -from genjax.typing import FloatArray +from scipy import spatial from b3d.utils import get_assets_path @@ -23,14 +24,14 @@ class YCBVTrackingResultLoader(Pytree): result_dir: Path - def load(self, test_scene_id: IndentationError, object_id: int) -> FloatArray: + def load(self, test_scene_id: IndentationError, object_id: int) -> np.ndarray: """Given the test scene and object id, load the corresponding tracking result from the specified directory. The returning JAX array will have shape (num_frames, 4, 4), where the estimated pose in each frame is stored as a 4x4 transformation matrix. """ filename = self.result_dir / str(test_scene_id) / f"object_{object_id}.npy" - return jnp.load(filename) + return np.load(filename) def get_scene_ids(self) -> list[int]: return sorted( @@ -47,3 +48,82 @@ def get_object_ids(self, test_scene_id: int) -> list[int]: # a default loader for the most recently computed foundation pose tracking results foundation_pose_ycbv_result = YCBVTrackingResultLoader(DEFAULT_FP_YCBV_RESULT_DIR) + + +def apply_transform(pose: np.ndarray, vertices: np.ndarray) -> np.ndarray: + return (pose[:3, :3] @ vertices.T + pose[:3, 3][:, None]).T + + +def add_err(pred_pose: np.ndarray, gt_pose: np.ndarray, vertices: np.ndarray) -> float: + """Compute the Average Distance (ADD) error between the predicted pose and the + ground truth pose, given the vertices of the object. + + References: + - https://github.com/thodan/bop_toolkit/blob/59c5f486fe3a7886329d9fc908935e40d3bc0248/bop_toolkit_lib/pose_error.py#L210-L224 + - https://github.com/NVlabs/FoundationPose/blob/cd3ca4bc080529c53d5e5235212ca476d82bccf7/Utils.py#L232-L240 + - https://github.com/chensong1995/HybridPose/blob/106c86cddaa52765eb82f17bd00fdc72b98a02ca/lib/utils.py#L36-L49 + + Args: + pred_pose (np.ndarray): A 4x4 transformation matrix representing the predicted pose. + gt_pose (np.ndarray): A 4x4 transformation matrix representing the ground truth pose. + vertices (np.ndarray): The vertices of shape (num_vertices, 3) in the object frame, + representing the 3D model of the object. Note that we should be using the vertices + from the ground truth mesh file instead of the reconstructed point cloud. + """ + pred_locs = apply_transform(pred_pose, vertices) + gt_locs = apply_transform(gt_pose, vertices) + return np.linalg.norm(pred_locs - gt_locs, axis=-1).mean() + + +def adds_err(pred_pose: np.ndarray, gt_pose: np.ndarray, vertices: np.ndarray) -> float: + """Compute the Average Closest Point Distance (ADD-S) error between the predicted pose and the + ground truth pose, given the vertices of the object. ADD-S is an ambiguity-invariant pose + error metric which takes care of both symmetric and non-symmetric objects + + References: + - https://github.com/thodan/bop_toolkit/blob/59c5f486fe3a7886329d9fc908935e40d3bc0248/bop_toolkit_lib/pose_error.py#L227-L247 + - https://github.com/NVlabs/FoundationPose/blob/cd3ca4bc080529c53d5e5235212ca476d82bccf7/Utils.py#L242-L253 + - https://github.com/chensong1995/HybridPose/blob/106c86cddaa52765eb82f17bd00fdc72b98a02ca/lib/utils.py#L51-L68 + + Args: + pred_pose (np.ndarray): A 4x4 transformation matrix representing the predicted pose. + gt_pose (np.ndarray): A 4x4 transformation matrix representing the ground truth pose. + vertices (np.ndarray): The vertices of shape (num_vertices, 3) in the object frame, + representing the 3D model of the object. Note that we should be using the vertices + from the ground truth mesh file instead of the reconstructed point cloud. + """ + pred_locs = apply_transform(pred_pose, vertices) + gt_locs = apply_transform(gt_pose, vertices) + + # Calculate distances to the nearest neighbors from vertices in the + # ground-truth pose to vertices in the estimated pose. + nn_index = spatial.cKDTree(pred_locs) + nn_dists, _ = nn_index.query(gt_locs, k=1) + + return nn_dists.mean() + + +def compute_auc(errs: Sequence, max_val: float = 0.1, step=0.001): + """Compute the Area Under the Curve (AUC) of the pose tracking errors at + different thresholds. + + Reference: + - https://github.com/NVlabs/FoundationPose/blob/cd3ca4bc080529c53d5e5235212ca476d82bccf7/Utils.py#L255-L266 + + Args: + errs (Sequence): An sequence of pose tracking errors. + max_val (float, optional): The upper bound of the threshold. Defaults to 0.1. + step (float, optional): The step between two threshold. Defaults to 0.001. + """ + from sklearn import metrics + + errs = np.sort(np.array(errs)) + X = np.arange(0, max_val + step, step) + Y = np.ones(len(X)) + for i, x in enumerate(X): + y = (errs <= x).sum() / len(errs) + Y[i] = y + if y >= 1: + break + auc = metrics.auc(X, Y) / (max_val * 1) + return auc diff --git a/tests/gen3d/test_metrics.py b/tests/gen3d/test_metrics.py index 3419de15..08cef305 100644 --- a/tests/gen3d/test_metrics.py +++ b/tests/gen3d/test_metrics.py @@ -1,12 +1,18 @@ +import b3d +import numpy as np import pytest from b3d.chisight.gen3d.metrics import ( FP_RESULTS_ROOT_DIR, + add_err, + adds_err, + compute_auc, foundation_pose_ycbv_result, ) TEST_FP_YCBV_RESULT_DIR = ( FP_RESULTS_ROOT_DIR / "ycbv/2024-07-11-every-50-frames-gt-init" ) +ycb_dir = b3d.get_assets_path() / "bop/ycbv" @pytest.mark.skipif( @@ -22,3 +28,56 @@ def test_loading_precomputed_ycbv_results(): obj_ids_scene_48 = foundation_pose_ycbv_result.get_object_ids(test_scene_id=48) assert len(obj_ids_scene_48) == 5 + + +@pytest.mark.parametrize("error_fn", [add_err, adds_err]) +def test_ground_truth_pose(error_fn): + pred_poses = gt_poses = np.random.rand(100, 4, 4) + vertices = np.random.rand(100, 3) + + all_errors = [] + for pred_pose, gt_pose in zip(pred_poses, gt_poses): + all_errors.append(error_fn(pred_pose, gt_pose, vertices)) + auc_score = compute_auc(all_errors) + + # error should be zero if pred_pose == gt_pose, and AUC should be 1 (highest) + assert np.allclose(all_errors, 0.0) + assert np.isclose(auc_score, 1.0) + + +@pytest.mark.skipif( + not TEST_FP_YCBV_RESULT_DIR.exists() or not ycb_dir.exists(), + reason="FoundationPose tracking result and YCBV dataset not found.", +) +def test_compute_metric(): + # example showing how the metric can be computed + test_scene = 48 + obj_id = 0 + framerate = 50 + num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, test_scene) + image_ids = range(1, num_scenes + 1, framerate) + all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, test_scene, image_ids) + + # get the gt mesh + obj_id_str = str(all_data[0]["object_types"][obj_id] + 1).rjust(6, "0") + print(obj_id_str) + mesh = b3d.Mesh.from_obj_file(ycb_dir / f"models/obj_{obj_id_str}.ply").scale(0.001) + + # load the foundation pose tracking results + fp_result = foundation_pose_ycbv_result.load( + test_scene_id=test_scene, object_id=obj_id + ) + + # start computing the error + all_adds_err = [] + for frame_data, pred_pose in zip(all_data, fp_result): + camera_pose = frame_data["camera_pose"] + obj_pose = frame_data["object_poses"][obj_id] + gt_pose = (camera_pose.inv() @ obj_pose).as_matrix() + all_adds_err.append(adds_err(pred_pose, gt_pose, mesh.vertices)) + + # Note that in many of the paper, the results are aggregated per-object + # (rather than per-scene) + auc = compute_auc(all_adds_err) + + assert auc > 0.5 From bd5fcce0394cea7ca47fbd373fea2510cdf63f55 Mon Sep 17 00:00:00 2001 From: Xiaoyan Wang Date: Tue, 17 Sep 2024 00:05:56 -0400 Subject: [PATCH 32/37] Script to compute quantitative metrics by loading poses from disk (#183) Usage ```bash python ``` This script will load the precomputed pose tracking results on YCB-V dataset and compute the aggregated ADD and ADD-S metrics per object. It will print out the result and store them in a CSV format in the output directory (if not provided, the output directory will be set to the input directory by default) Example outputs: ``` ADD-S ADD 002_master_chef_can 0.865135 0.497027 003_cracker_box 0.686422 0.667845 004_sugar_box 0.980075 0.962711 005_tomato_soup_can 0.568405 0.381333 006_mustard_bottle 0.965702 0.534649 007_tuna_fish_can 0.379667 0.255333 008_pudding_box 0.647143 0.549286 009_gelatin_box 0.480714 0.365000 010_potted_meat_can 0.655817 0.510817 011_banana 0.984375 0.962031 019_pitcher_base 0.976282 0.958077 021_bleach_cleanser 0.966097 0.935419 024_bowl 0.768561 0.113258 025_mug 0.540915 0.395854 035_power_drill 0.757128 0.719007 036_wood_block 0.958243 0.901757 037_scissors 0.971098 0.940854 040_large_marker 0.555329 0.400526 051_large_clamp 0.729881 0.433571 052_extra_large_clamp 0.952831 0.308614 061_foam_brick 0.265658 0.148158 ``` --- scripts/get_ycbv_metrics.py | 109 ++++++++++++++++++++++++++++++++++++ 1 file changed, 109 insertions(+) create mode 100644 scripts/get_ycbv_metrics.py diff --git a/scripts/get_ycbv_metrics.py b/scripts/get_ycbv_metrics.py new file mode 100644 index 00000000..08ee1515 --- /dev/null +++ b/scripts/get_ycbv_metrics.py @@ -0,0 +1,109 @@ +from functools import partial +from pathlib import Path + +import b3d +import fire +import numpy as np +import pandas as pd +from b3d.chisight.gen3d.metrics import ( + add_err, + adds_err, + compute_auc, + foundation_pose_ycbv_result, +) +from b3d.io.data_loader import YCB_MODEL_NAMES +from tqdm.auto import tqdm + +YCB_DIR = b3d.get_assets_path() / "bop/ycbv" + +ALL_METRICS = { + "ADD-S": adds_err, + "ADD": add_err, +} + +FRAME_RATE = 50 + + +def collect_all_scores(get_pose_fn: callable): + # e.g. all_score["ADD"]["002_master_chef_can"] gives the ADD error for the + # object "002_master_chef_can" + all_scores = {} + for metric_name in ALL_METRICS: + all_scores[metric_name] = {obj_name: [] for obj_name in YCB_MODEL_NAMES} + + # preload all gt meshes + meshes = [] + for obj_id in range(len(YCB_MODEL_NAMES)): + obj_id_str = str(obj_id + 1).rjust(6, "0") + meshes.append( + b3d.Mesh.from_obj_file(YCB_DIR / f"models/obj_{obj_id_str}.ply").scale( + 0.001 + ) + ) + + for test_scene_id in range(48, 60): + num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(YCB_DIR, test_scene_id) + image_ids = range(1, num_scenes + 1, FRAME_RATE) + print(f"Processing test scene {test_scene_id}") + all_data = b3d.io.data_loader.get_ycbv_test_images( + YCB_DIR, test_scene_id, image_ids + ) + + object_types = all_data[0]["object_types"] + for idx, obj_id in tqdm(enumerate(object_types), desc="Processing objects"): + obj_name = YCB_MODEL_NAMES[obj_id] + obj_mesh = meshes[obj_id] + pred_poses = get_pose_fn(test_scene_id, idx) + # start computing the error for this object + for frame_data, pred_pose in zip(all_data, pred_poses): + # load ground truth pose + camera_pose = frame_data["camera_pose"] + obj_pose = frame_data["object_poses"][idx] + gt_pose = (camera_pose.inv() @ obj_pose).as_matrix() + # metrics + for metric_name, metric_fn in ALL_METRICS.items(): + all_scores[metric_name][obj_name].append( + metric_fn(pred_pose, gt_pose, obj_mesh.vertices) + ) + + # aggregate results per object + final_results = {} + for metric_name in ALL_METRICS: + final_results[metric_name] = {} + for obj_name in YCB_MODEL_NAMES: + final_results[metric_name][obj_name] = compute_auc( + all_scores[metric_name][obj_name] + ) + + return pd.DataFrame(final_results), all_scores + + +def get_fp_pred_pose(test_scene_id: int, obj_id: int): + return foundation_pose_ycbv_result.load(test_scene_id, obj_id) + + +def get_b3d_pred_pose(result_dir: Path, test_scene_id: int, obj_id: int): + poses = np.load( + result_dir / f"SCENE_{test_scene_id}_OBJECT_INDEX_{obj_id}_POSES.npy", + ) + poses = b3d.Pose(poses["position"], poses["quaternion"]) + return poses.as_matrix() + + +def main(b3d_result_dir: str, output_dir: str | None = None): + result_dir = Path(b3d_result_dir) + if output_dir is None: + output_dir = b3d_result_dir + output_dir = Path(output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + pred_score_getter = partial(get_b3d_pred_pose, result_dir) + # pred_score_getter = get_fp_pred_pose + results_summary, _ = collect_all_scores(pred_score_getter) + print(results_summary) + if output_dir is not None: + results_summary.to_csv(output_dir / "summary.csv") + + +if __name__ == "__main__": + fire.Fire(main) From 90602d6ecb554eae14f796845b3ff8c05e13d79b Mon Sep 17 00:00:00 2001 From: georgematheos Date: Tue, 17 Sep 2024 09:16:46 -0400 Subject: [PATCH 33/37] Make utils for loading ycbv scenes (#179) --- scripts/run_ycbv_evaluation.py | 133 ++++---------------------- src/b3d/chisight/gen3d/dataloading.py | 96 +++++++++++++++++++ src/b3d/chisight/gen3d/inference.py | 32 ++++++- 3 files changed, 148 insertions(+), 113 deletions(-) create mode 100644 src/b3d/chisight/gen3d/dataloading.py diff --git a/scripts/run_ycbv_evaluation.py b/scripts/run_ycbv_evaluation.py index 5a7ab4b6..7e7840b4 100755 --- a/scripts/run_ycbv_evaluation.py +++ b/scripts/run_ycbv_evaluation.py @@ -1,20 +1,18 @@ #!/usr/bin/env python -import os +import copy import b3d.chisight.gen3d.inference as inference +import b3d.chisight.gen3d.settings as settings import fire -import genjax import jax import jax.numpy as jnp -from b3d import Mesh, Pose -from b3d.chisight.gen3d.model import ( - dynamic_object_generative_model, - make_colors_choicemap, - make_depth_nonreturn_prob_choicemap, - make_visibility_prob_choicemap, +from b3d import Pose +from b3d.chisight.gen3d.dataloading import ( + get_initial_state, + load_object_given_scene, + load_scene, ) -from genjax import Pytree from tqdm import tqdm @@ -25,8 +23,6 @@ def run_tracking(scene=None, object=None, debug=False): b3d.utils.rr_init("run_ycbv_evaluation") - ycb_dir = os.path.join(b3d.utils.get_assets_path(), "bop/ycbv") - if scene is None: scenes = range(48, 60) elif isinstance(scene, int): @@ -34,124 +30,37 @@ def run_tracking(scene=None, object=None, debug=False): elif isinstance(scene, list): scenes = scene - import b3d.chisight.gen3d.settings - - hyperparams = b3d.chisight.gen3d.settings.hyperparams - # inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams + hyperparams = copy.deepcopy(settings.hyperparams) for scene_id in scenes: - print(f"Scene {scene_id}") - num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id) - - # image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE) - image_ids = range(1, num_scenes + 1, FRAME_RATE) - all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, image_ids) - - meshes = [ - Mesh.from_obj_file( - os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') - ).scale(0.001) - for id in all_data[0]["object_types"] - ] - - image_height, image_width = all_data[0]["rgbd"].shape[:2] - fx, fy, cx, cy = all_data[0]["camera_intrinsics"] - scaling_factor = 1.0 - renderer = b3d.renderer.renderer_original.RendererOriginal( - image_width * scaling_factor, - image_height * scaling_factor, - fx * scaling_factor, - fy * scaling_factor, - cx * scaling_factor, - cy * scaling_factor, - 0.01, - 4.0, + all_data, meshes, renderer, intrinsics, initial_object_poses = load_scene( + scene_id, FRAME_RATE ) - # initial_camera_pose = all_data[0]["camera_pose"] - initial_object_poses = all_data[0]["object_poses"] - object_indices = ( [object] if object is not None else range(len(initial_object_poses)) ) for OBJECT_INDEX in object_indices: print(f"Object {OBJECT_INDEX} out of {len(initial_object_poses) - 1}") - T = 0 - - template_pose = ( - all_data[T]["camera_pose"].inv() - @ all_data[T]["object_poses"][OBJECT_INDEX] - ) - rendered_rgbd = renderer.render_rgbd_from_mesh( - meshes[OBJECT_INDEX].transform(template_pose) + template_pose, model_vertices, model_colors = load_object_given_scene( + all_data, meshes, renderer, OBJECT_INDEX ) - xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy) - fx, fy, cx, cy = all_data[T]["camera_intrinsics"] - xyz_observed = b3d.xyz_from_depth( - all_data[T]["rgbd"][..., 3], fx, fy, cx, cy - ) - mask = ( - all_data[T]["masks"][OBJECT_INDEX] - * (xyz_observed[..., 2] > 0) - * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) - ) - model_vertices = template_pose.inv().apply(xyz_rendered[mask]) - model_colors = all_data[T]["rgbd"][..., :3][mask] - - subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[ - : min(10000, len(model_vertices)) - ] - model_vertices = model_vertices[subset] - model_colors = model_colors[subset] - - hyperparams["intrinsics"] = { - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - "image_height": Pytree.const(image_height), - "image_width": Pytree.const(image_width), - "near": 0.01, - "far": 3.0, - } + hyperparams["intrinsics"] = intrinsics hyperparams["vertices"] = model_vertices - - num_vertices = model_vertices.shape[0] - previous_state = { - "pose": template_pose, - "colors": model_colors, - "visibility_prob": jnp.ones(num_vertices) - * hyperparams["visibility_prob_kernel"].support[-1], - "depth_nonreturn_prob": jnp.ones(num_vertices) - * hyperparams["depth_nonreturn_prob_kernel"].support[0], - "depth_scale": hyperparams["depth_scale_kernel"].support[0], - "color_scale": hyperparams["color_scale_kernel"].support[0], - } - - choicemap = ( - genjax.ChoiceMap.d( - { - "pose": previous_state["pose"], - "color_scale": previous_state["color_scale"], - "depth_scale": previous_state["depth_scale"], - "rgbd": all_data[T]["rgbd"], - } - ) - ^ make_visibility_prob_choicemap(previous_state["visibility_prob"]) - ^ make_colors_choicemap(previous_state["colors"]) - ^ make_depth_nonreturn_prob_choicemap( - previous_state["depth_nonreturn_prob"] - ) + initial_state = get_initial_state( + template_pose, model_vertices, model_colors, hyperparams ) - key = jax.random.PRNGKey(0) tracking_results = {} - trace = dynamic_object_generative_model.importance( - key, choicemap, (hyperparams, previous_state) - )[0] + inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams # noqa ### Run inference ### + key = jax.random.PRNGKey(156) + trace = inference.get_initial_trace( + key, hyperparams, initial_state, all_data[0]["rgbd"] + ) + for T in tqdm(range(len(all_data))): key = b3d.split_key(key) trace = inference.inference_step_c2f( diff --git a/src/b3d/chisight/gen3d/dataloading.py b/src/b3d/chisight/gen3d/dataloading.py new file mode 100644 index 00000000..907a192b --- /dev/null +++ b/src/b3d/chisight/gen3d/dataloading.py @@ -0,0 +1,96 @@ +import os + +import jax +import jax.numpy as jnp +from genjax import Pytree + +import b3d +from b3d import Mesh + + +def load_scene(scene_id, FRAME_RATE=50): + ycb_dir = os.path.join(b3d.utils.get_assets_path(), "bop/ycbv") + num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id) + + image_ids = range(1, num_scenes + 1, FRAME_RATE) + all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, image_ids) + + meshes = [ + Mesh.from_obj_file( + os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') + ).scale(0.001) + for id in all_data[0]["object_types"] + ] + + image_height, image_width = all_data[0]["rgbd"].shape[:2] + fx, fy, cx, cy = all_data[0]["camera_intrinsics"] + scaling_factor = 1.0 + renderer = b3d.renderer.renderer_original.RendererOriginal( + image_width * scaling_factor, + image_height * scaling_factor, + fx * scaling_factor, + fy * scaling_factor, + cx * scaling_factor, + cy * scaling_factor, + 0.01, + 4.0, + ) + + intrinsics = { + "fx": fx, + "fy": fy, + "cx": cx, + "cy": cy, + "image_height": Pytree.const(image_height), + "image_width": Pytree.const(image_width), + "near": 0.01, + "far": 3.0, + } + + initial_object_poses = all_data[0]["object_poses"] + + return all_data, meshes, renderer, intrinsics, initial_object_poses + + +def load_object_given_scene(all_data, meshes, renderer, OBJECT_INDEX): + T = 0 + fx, fy, cx, cy = all_data[T]["camera_intrinsics"] + + template_pose = ( + all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] + ) + rendered_rgbd = renderer.render_rgbd_from_mesh( + meshes[OBJECT_INDEX].transform(template_pose) + ) + xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy) + + xyz_observed = b3d.xyz_from_depth(all_data[T]["rgbd"][..., 3], fx, fy, cx, cy) + mask = ( + all_data[T]["masks"][OBJECT_INDEX] + * (xyz_observed[..., 2] > 0) + * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) + ) + model_vertices = template_pose.inv().apply(xyz_rendered[mask]) + model_colors = all_data[T]["rgbd"][..., :3][mask] + + subset = jax.random.permutation(jax.random.PRNGKey(0), len(model_vertices))[ + : min(10000, len(model_vertices)) + ] + model_vertices = model_vertices[subset] + model_colors = model_colors[subset] + + return (template_pose, model_vertices, model_colors) + + +def get_initial_state(template_pose, model_vertices, model_colors, hyperparams): + num_vertices = model_vertices.shape[0] + return { + "pose": template_pose, + "colors": model_colors, + "visibility_prob": jnp.ones(num_vertices) + * hyperparams["visibility_prob_kernel"].support[-1], + "depth_nonreturn_prob": jnp.ones(num_vertices) + * hyperparams["depth_nonreturn_prob_kernel"].support[0], + "depth_scale": hyperparams["depth_scale_kernel"].support[0], + "color_scale": hyperparams["color_scale_kernel"].support[0], + } diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py index 86c44b69..8cd8e0f0 100644 --- a/src/b3d/chisight/gen3d/inference.py +++ b/src/b3d/chisight/gen3d/inference.py @@ -15,7 +15,14 @@ propose_other_latents_given_pose, propose_pose, ) -from b3d.chisight.gen3d.model import get_hypers, get_new_state +from b3d.chisight.gen3d.model import ( + dynamic_object_generative_model, + get_hypers, + get_new_state, + make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, + make_visibility_prob_choicemap, +) @Pytree.dataclass @@ -43,6 +50,29 @@ class InferenceHyperparams(Pytree): obs_color_proposal_laplace_scale: float +def get_initial_trace(key, hyperparams, initial_state, initial_observed_rgbd): + """ + Get the initial trace, given the initial state. + """ + choicemap = ( + C.d( + { + "pose": initial_state["pose"], + "color_scale": initial_state["color_scale"], + "depth_scale": initial_state["depth_scale"], + "rgbd": initial_observed_rgbd, + } + ) + ^ make_visibility_prob_choicemap(initial_state["visibility_prob"]) + ^ make_colors_choicemap(initial_state["colors"]) + ^ make_depth_nonreturn_prob_choicemap(initial_state["depth_nonreturn_prob"]) + ) + trace, _ = dynamic_object_generative_model.importance( + key, choicemap, (hyperparams, initial_state) + ) + return trace + + @jax.jit def advance_time(key, trace, observed_rgbd): """ From f4a001cd794e9e453437a43e4386aa84bdac7cd0 Mon Sep 17 00:00:00 2001 From: georgematheos Date: Tue, 17 Sep 2024 14:10:27 -0400 Subject: [PATCH 34/37] Gm/gen3d/eval script improvements (#185) --- .gitignore | 1 + scripts/get_ycbv_metrics.py | 12 +++-- scripts/run_ycbv_evaluation.py | 83 +++++++++++++++++++++++++-------- src/b3d/chisight/gen3d/model.py | 14 ++++-- 4 files changed, 84 insertions(+), 26 deletions(-) diff --git a/.gitignore b/.gitignore index a9c9f1dc..1ceaea2d 100644 --- a/.gitignore +++ b/.gitignore @@ -24,3 +24,4 @@ assets/kitti/* __pycache__/ *.py[cod] docs/* +test_results/ diff --git a/scripts/get_ycbv_metrics.py b/scripts/get_ycbv_metrics.py index 08ee1515..956cb157 100644 --- a/scripts/get_ycbv_metrics.py +++ b/scripts/get_ycbv_metrics.py @@ -84,13 +84,16 @@ def get_fp_pred_pose(test_scene_id: int, obj_id: int): def get_b3d_pred_pose(result_dir: Path, test_scene_id: int, obj_id: int): poses = np.load( - result_dir / f"SCENE_{test_scene_id}_OBJECT_INDEX_{obj_id}_POSES.npy", + result_dir / f"SCENE_{test_scene_id}_OBJECT_INDEX_{obj_id}_POSES.npy.npz", ) poses = b3d.Pose(poses["position"], poses["quaternion"]) return poses.as_matrix() -def main(b3d_result_dir: str, output_dir: str | None = None): +def main(b3d_result_dir: str, output_dir: str | None = None, get_fp_pose: bool = False): + """ + Call this with `b3d_result_dir` as the directory containing `.npy.npz` files. + """ result_dir = Path(b3d_result_dir) if output_dir is None: output_dir = b3d_result_dir @@ -98,7 +101,10 @@ def main(b3d_result_dir: str, output_dir: str | None = None): output_dir.mkdir(parents=True, exist_ok=True) pred_score_getter = partial(get_b3d_pred_pose, result_dir) - # pred_score_getter = get_fp_pred_pose + + if get_fp_pose: + pred_score_getter = get_fp_pred_pose + results_summary, _ = collect_all_scores(pred_score_getter) print(results_summary) if output_dir is not None: diff --git a/scripts/run_ycbv_evaluation.py b/scripts/run_ycbv_evaluation.py index 7e7840b4..af54b6fe 100755 --- a/scripts/run_ycbv_evaluation.py +++ b/scripts/run_ycbv_evaluation.py @@ -1,27 +1,64 @@ #!/usr/bin/env python import copy +import os +import pprint +from datetime import datetime +from pathlib import Path +import b3d import b3d.chisight.gen3d.inference as inference import b3d.chisight.gen3d.settings as settings +import b3d.chisight.gen3d.visualization as viz import fire import jax import jax.numpy as jnp +import rerun as rr from b3d import Pose from b3d.chisight.gen3d.dataloading import ( get_initial_state, load_object_given_scene, load_scene, ) +from b3d.chisight.gen3d.model import viz_trace as rr_viz_trace from tqdm import tqdm -def run_tracking(scene=None, object=None, debug=False): - import b3d +def setup_save_directory(): + # Make a folder, stamped with the current time. + current_time = datetime.now().strftime("%Y-%m-%d--%H:%M") + folder_name = ( + b3d.get_root_path() / "test_results" / "gen3d" / f"gen3d_{current_time}" + ) + Path(folder_name).mkdir(parents=True, exist_ok=True) + video_folder_name = folder_name / "mp4" + npy_folder_name = folder_name / "npy" + rr_folder_name = folder_name / "rr" + os.mkdir(rr_folder_name) + os.mkdir(video_folder_name) + os.mkdir(npy_folder_name) + return folder_name, video_folder_name, npy_folder_name, rr_folder_name + + +def save_hyperparams(folder_name, hyperparams, inference_hyperparams): + hyperparams_file = folder_name / "hyperparams.txt" + with open(hyperparams_file, "w") as f: + f.write("Hyperparameters:\n") + f.write(pprint.pformat(hyperparams)) + f.write("\n\n\nInference Hyperparameters:\n") + f.write(pprint.pformat(inference_hyperparams)) + + +def run_tracking(scene=None, object=None, save_rerun=False, max_n_frames=None): + folder_name, video_folder_name, npy_folder_name, rr_folder_name = ( + setup_save_directory() + ) - FRAME_RATE = 50 + hyperparams = copy.deepcopy(settings.hyperparams) + inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams # noqa + save_hyperparams(folder_name, hyperparams, inference_hyperparams) - b3d.utils.rr_init("run_ycbv_evaluation") + FRAME_RATE = 50 if scene is None: scenes = range(48, 60) @@ -30,8 +67,6 @@ def run_tracking(scene=None, object=None, debug=False): elif isinstance(scene, list): scenes = scene - hyperparams = copy.deepcopy(settings.hyperparams) - for scene_id in scenes: all_data, meshes, renderer, intrinsics, initial_object_poses = load_scene( scene_id, FRAME_RATE @@ -53,7 +88,6 @@ def run_tracking(scene=None, object=None, debug=False): ) tracking_results = {} - inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams # noqa ### Run inference ### key = jax.random.PRNGKey(156) @@ -61,7 +95,18 @@ def run_tracking(scene=None, object=None, debug=False): key, hyperparams, initial_state, all_data[0]["rgbd"] ) - for T in tqdm(range(len(all_data))): + if save_rerun: + rr.init(f"SCENE_{scene_id}_OBJECT_INDEX_{OBJECT_INDEX}") + rr.save( + rr_folder_name / f"SCENE_{scene_id}_OBJECT_INDEX_{OBJECT_INDEX}.rrd" + ) + + if max_n_frames is not None: + maxT = min(max_n_frames, len(all_data)) + else: + maxT = len(all_data) + + for T in tqdm(range(maxT)): key = b3d.split_key(key) trace = inference.inference_step_c2f( key, @@ -76,8 +121,8 @@ def run_tracking(scene=None, object=None, debug=False): ) tracking_results[T] = trace - if debug: - b3d.chisight.gen3d.model.viz_trace( + if save_rerun: + rr_viz_trace( trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, @@ -86,25 +131,25 @@ def run_tracking(scene=None, object=None, debug=False): ) inferred_poses = Pose.stack_poses( - [ - tracking_results[t].get_choices()["pose"] - for t in range(len(all_data)) - ] + [tracking_results[t].get_choices()["pose"] for t in range(maxT)] ) jnp.savez( - f"SCENE_{scene_id}_OBJECT_INDEX_{OBJECT_INDEX}_POSES.npy", + npy_folder_name + / f"SCENE_{scene_id}_OBJECT_INDEX_{OBJECT_INDEX}_POSES.npy", position=inferred_poses.position, quaternion=inferred_poses.quat, ) - import b3d.chisight.gen3d.visualization as viz - viz.make_video_from_traces( - [tracking_results[t] for t in range(len(all_data))], - f"SCENE_{scene_id}_OBJECT_INDEX_{OBJECT_INDEX}.mp4", + [tracking_results[t] for t in range(maxT)], + video_folder_name / f"SCENE_{scene_id}_OBJECT_INDEX_{OBJECT_INDEX}.mp4", scale=0.25, ) + if save_rerun: + rr.disconnect() + print("rerun disconnected") + if __name__ == "__main__": fire.Fire(run_tracking) diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index cb77b925..85877a3f 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -99,7 +99,13 @@ def get_observed_rgbd(trace): ### Visualization Code ### -def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): +def viz_trace( + trace, + t=0, + ground_truth_vertices=None, + ground_truth_pose=None, + log_blueprint=True, +): b3d.rr_set_time(t) hyperparams, _ = trace.get_args() new_state = trace.get_retval()["new_state"] @@ -206,9 +212,9 @@ def viz_trace(trace, t=0, ground_truth_vertices=None, ground_truth_pose=None): b3d.rr_log_pose(ground_truth_pose, "scene/ground_truth_pose") b3d.rr_log_pose(trace.get_choices()["pose"], "scene/inferred_pose") - # if not b3d.get_blueprint_logged(): - # rr.send_blueprint(get_blueprint()) - # b3d.set_blueprint_logged(True) + if not b3d.get_blueprint_logged() and log_blueprint: + rr.send_blueprint(get_blueprint()) + b3d.set_blueprint_logged(True) def get_blueprint(): From 9c07251c72f5e823791e2bf975578ecdcbe639db Mon Sep 17 00:00:00 2001 From: georgematheos Date: Wed, 18 Sep 2024 14:57:31 -0400 Subject: [PATCH 35/37] Inference refactor (#187) --- src/b3d/chisight/gen3d/README.md | 3 + .../gen3d/deprecated/__OLD_inference.py | 241 ------------- src/b3d/chisight/gen3d/hyperparams.py | 15 + src/b3d/chisight/gen3d/inference.py | 341 ------------------ src/b3d/chisight/gen3d/inference/__init__.py | 0 src/b3d/chisight/gen3d/inference/inference.py | 311 ++++++++++++++++ .../point_attribute_proposals.py} | 204 +---------- src/b3d/chisight/gen3d/inference/utils.py | 86 +++++ src/b3d/chisight/gen3d/inference_old.py | 195 ---------- src/b3d/chisight/gen3d/model.py | 26 +- .../chisight/gen3d}/run_ycbv_evaluation.py | 26 +- src/b3d/chisight/gen3d/settings.py | 8 +- .../inference/test_full_inference_alg.py | 294 ++++++--------- .../test_point_attribute_inferences.py | 8 +- tests/gen3d/test_evaluation_script.py | 5 + tests/gen3d/test_visualization.py | 117 ------ 16 files changed, 558 insertions(+), 1322 deletions(-) create mode 100644 src/b3d/chisight/gen3d/README.md delete mode 100644 src/b3d/chisight/gen3d/deprecated/__OLD_inference.py create mode 100644 src/b3d/chisight/gen3d/hyperparams.py delete mode 100644 src/b3d/chisight/gen3d/inference.py create mode 100644 src/b3d/chisight/gen3d/inference/__init__.py create mode 100644 src/b3d/chisight/gen3d/inference/inference.py rename src/b3d/chisight/gen3d/{inference_moves.py => inference/point_attribute_proposals.py} (64%) create mode 100644 src/b3d/chisight/gen3d/inference/utils.py delete mode 100644 src/b3d/chisight/gen3d/inference_old.py rename {scripts => src/b3d/chisight/gen3d}/run_ycbv_evaluation.py (85%) create mode 100644 tests/gen3d/test_evaluation_script.py delete mode 100644 tests/gen3d/test_visualization.py diff --git a/src/b3d/chisight/gen3d/README.md b/src/b3d/chisight/gen3d/README.md new file mode 100644 index 00000000..e77e0b0e --- /dev/null +++ b/src/b3d/chisight/gen3d/README.md @@ -0,0 +1,3 @@ +# Gen3D + +You can run the `run_ycbv_evaluation.py` file as a script to evaluate Gen3D against the YCB-Video dataset. diff --git a/src/b3d/chisight/gen3d/deprecated/__OLD_inference.py b/src/b3d/chisight/gen3d/deprecated/__OLD_inference.py deleted file mode 100644 index 02c439c9..00000000 --- a/src/b3d/chisight/gen3d/deprecated/__OLD_inference.py +++ /dev/null @@ -1,241 +0,0 @@ -import jax -import jax.numpy as jnp -import jax.random -from b3d import Pose -from genjax import ChoiceMapBuilder as C -from genjax import Diff -from genjax import UpdateProblemBuilder as U - -from ..model import ( - make_colors_choicemap, - make_visibility_prob_choicemap, -) - - -@jax.jit -def advance_time(key, trace, observed_rgbd): - """ - Advance to the next timestep, setting the new latent state to the - same thing as the previous latent state, and setting the new - observed RGBD value. - - Returns a trace where previous_state (stored in the arguments) - and new_state (sampled in the choices and returned) are identical. - """ - hyperparams, _ = trace.get_args() - previous_state = trace.get_retval()["new_state"] - trace, _, _, _ = trace.update( - key, - U.g( - (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)), - C.kw(rgbd=observed_rgbd), - ), - ) - return trace - - -@jax.jit -def propose_color_and_visibility(trace, key): - # color_outlier_probability_sweep is (k,) shape array - hyperparams, previous_state = trace.get_args() - previous_visibility = previous_state["visibility_prob"] - previous_colors = previous_state["colors"] - - visibility_values = hyperparams["visibility_prob_kernel"].possible_values - - visibility_sweep = ( - visibility_values[..., None] # (num_outlier_grid_points, 1) - * jnp.ones_like(previous_visibility) # (num_vertices,) - ) # (num_outlier_grid_points, num_vertices) - - visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - - visibility_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( - visibility_prob_kernel.logpdf, - signature="(),()->()", - )(visibility_sweep, previous_visibility) - - info_from_trace = hyperparams["image_likelihood"].info_from_trace - - # We will grid over color values, using a grid that mixes the old and observed - # colors in a set of exact proportions. - # We regard these as coming from uniform proposals where we sample the RGB - # values uniformly between the mixed R, G, and B values with mixtures between - # [0., .125], [.125, .5], [.5, .875], [.875, 1.]. - # So the q scores will be .125^3, .375^3, .375^3, .125^3. - # TODO: we really ought to add a small amount of proposal probability mass - # onto the points at the end, to capture the fact that the posterior could allow - # colors outside the considered interpolation window. - color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) - # num_color_grid_points = len(color_interpolations_per_proposal) - - observed_colors = info_from_trace(trace)["observed_rgbd_masked"][ - ..., :3 - ] # (num_vertices, 3) - color_sweep = observed_colors[None, ...] * color_interpolations_per_proposal[ - :, None, None - ] + previous_colors[None, ...] * ( - 1 - color_interpolations_per_proposal[:, None, None] - ) # (num_color_grid_points, num_vertices, 3) - - color_kernel = hyperparams["color_kernel"] - color_transition_scores_per_sweep_point_and_vertex = jnp.vectorize( - color_kernel.logpdf, - signature="(3),(3)->()", - )(color_sweep, previous_colors) - - # Function takes in color and color outlier probabilities array of shapes (num_vertices,3) and (num_vertices,) respectively - # and gives scores for each vertex (num_vertices,) - def get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities( - colors, visibility - ): - return info_from_trace( - trace.update( - key, - make_colors_choicemap(colors) - ^ make_visibility_prob_choicemap(visibility), - )[0] - )["scores"] - - vmap_version = jax.vmap( - jax.vmap( - get_per_vertex_likelihoods_with_new_color_and_color_outlier_probabilities, - in_axes=(None, 0), - ), - in_axes=(0, None), - ) - - # Vmap over the depth_outlier_probability_sweep_full array to get scores for each vertex for each depth_outlier_probability in the sweep - likelihood_scores_per_sweep_point_and_vertex = vmap_version( - color_sweep, visibility_sweep - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - scores_per_sweep_point_and_vertex = ( - likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points, num_vertices) - + visibility_transition_scores_per_sweep_point_and_vertex[None, ...] - + color_transition_scores_per_sweep_point_and_vertex[:, None, ...] - ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - - unraveled_scores = scores_per_sweep_point_and_vertex.reshape( - -1, scores_per_sweep_point_and_vertex.shape[-1] - ) - normalized_log_probabilities = jax.nn.log_softmax(unraveled_scores, axis=0) - sampled_indices = jax.random.categorical(key, normalized_log_probabilities, axis=0) - - color_sweep_indices, visibility_sweep_indices = jnp.unravel_index( - sampled_indices, scores_per_sweep_point_and_vertex.shape[:2] - ) - - # color_sweep is (num_outlier_grid_points, num_vertices, 3) - # outlier_probability_sweep is (num_outlier_grid_points,) - # color_outlier_probabilities_sweep is (num_outlier_grid_points, num_vertices) - sampled_colors = color_sweep[color_sweep_indices, jnp.arange(color_sweep.shape[1])] - sampled_color_outlier_probabilities = visibility_values[visibility_sweep_indices] - - log_q_color_and_color_outlier_probability = normalized_log_probabilities[ - sampled_indices, jnp.arange(normalized_log_probabilities.shape[1]) - ].sum() - - # log_q = estimate of q(all these colors, all these outliers ; inputs) - # Only source of real randomness = sampling indices. Captured in log_q_color_and_color_outlier_probability. - # But we also want to be careful with the continuous values... - # (1) outlier probs. --> change the model to have discrete grid. [Do later.] - # (2) colors. --> 1/q() - # uniform(old r, 2/3 oldr + 1/3 newr) 0 | uniform(0, 0.1) - # uniform(1/3, 2/3) # .5 | uniform(.1, .9) - # uniform(2/3, 1) # 1 | uniform(.9, 1) - # - # q(c1) * q(c2) * q(c3) - # but we just output c2 - # q(the c values we output, marginalizing over the other choices) - # -> just output q(c2) - - # We will treat this like the case where each sweep is uniform, so the q scores - # are each (oldr - obsr)/3 * (oldg - obsg)/3 * (oldb - obsb)/3. - - hyperparams = trace.get_args()[0] - color_shift_scale = hyperparams["color_kernel"].scale - color_scale = trace.get_choices()["color_scale"] - - d = 1 / (1 / color_shift_scale + 1 / color_scale) - - q_prob_per_vertex = ( - 1.0 / ((jnp.abs(previous_colors - observed_colors) / 3) + 4 * d) - ).prod(-1) - log_q_for_the_color_proposal = jnp.log(q_prob_per_vertex).sum() - - return ( - sampled_colors, - sampled_color_outlier_probabilities, - log_q_color_and_color_outlier_probability + log_q_for_the_color_proposal, - scores_per_sweep_point_and_vertex, - ) - - -@jax.jit -def propose_update(trace, key, pose): - total_log_q = 0.0 - - # Update pose - # pose, log_q_pose = propose_pose( - # trace, key, pose_sample_variance, pose_sample_concentration - # ) - trace = trace.update(key, C["pose"].set(pose))[0] - - # Update color and color outlier probability - sampled_colors, sampled_visibility, log_q, _ = propose_color_and_visibility( - trace, key - ) - trace = trace.update( - key, - make_colors_choicemap(sampled_colors) - ^ make_visibility_prob_choicemap(sampled_visibility), - )[0] - total_log_q += log_q - - return trace, total_log_q - - -@jax.jit -def propose_update_get_score(trace, key, pose): - new_trace, log_q = propose_update(trace, key, pose) - # score is an estimate of P(data, pose | previous state) - return new_trace.get_score() - log_q - - -propose_update_get_score_vmap = jax.jit( - jax.vmap(propose_update_get_score, in_axes=(None, None, 0)) -) - - -def inference_step_without_advance(trace, key): - number = 15000 - current_pose = trace.get_choices()["pose"] - var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] - for var, conc in var_conc: - key = jax.random.split(key, 2)[-1] - keys = jax.random.split(key, number) - poses = Pose.concatenate_poses( - [ - Pose.sample_gaussian_vmf_pose_vmap(keys, current_pose, var, conc), - current_pose[None, ...], - ] - ) - pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( - poses, trace.get_choices()["pose"], var, conc - ) - scores = propose_update_get_score_vmap(trace, key, poses) - scores_pose_q_correction = ( - scores - pose_scores - ) # After this, scores are fair estimates of P(data | previous state) - # and can be used to resample the choice sets. - index = jax.random.categorical(key, scores) - current_pose = poses[index] - trace = propose_update(trace, key, current_pose)[0] - return trace, scores, scores_pose_q_correction - - -def inference_step(trace, key, observed_rgbd): - trace = advance_time(key, trace, observed_rgbd) - trace = inference_step_without_advance(trace, key)[0] - return trace diff --git a/src/b3d/chisight/gen3d/hyperparams.py b/src/b3d/chisight/gen3d/hyperparams.py new file mode 100644 index 00000000..67ebdbaa --- /dev/null +++ b/src/b3d/chisight/gen3d/hyperparams.py @@ -0,0 +1,15 @@ +from genjax import Pytree + + +@Pytree.dataclass +class InferenceHyperparams(Pytree): + n_poses: int = Pytree.static() + obs_color_proposal_laplace_scale: float + prev_color_proposal_laplace_scale: float + + pose_proposal_args: any = Pytree.static( + default_factory=(lambda: [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)]) + ) + + include_q_scores_at_top_level: bool = True + do_stochastic_color_proposals: bool = True diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py deleted file mode 100644 index 8cd8e0f0..00000000 --- a/src/b3d/chisight/gen3d/inference.py +++ /dev/null @@ -1,341 +0,0 @@ -from functools import partial, wraps - -import jax -import jax.numpy as jnp -import jax.random -from genjax import ChoiceMapBuilder as C -from genjax import Diff, Pytree -from genjax import UpdateProblemBuilder as U -from jax.random import split -from tqdm import tqdm - -import b3d -from b3d.chisight.gen3d.inference_moves import ( - get_pose_proposal_density, - propose_other_latents_given_pose, - propose_pose, -) -from b3d.chisight.gen3d.model import ( - dynamic_object_generative_model, - get_hypers, - get_new_state, - make_colors_choicemap, - make_depth_nonreturn_prob_choicemap, - make_visibility_prob_choicemap, -) - - -@Pytree.dataclass -class InferenceHyperparams(Pytree): - """ - Parameters for the inference algorithm. - - n_poses: Number of poses to propose at each timestep. - - do_stochastic_color_proposals: If true, the color proposal will be - absolutely continuous w.r.t. the Lebesgue measure on [0, 1]^3. - If false, the color proposal will consider returning exactly the - old color, and exactly the new color. - - pose_proposal_std: Standard deviation of the position distribution for the pose. - - pose_proposal_conc: Concentration parameter for the orientation distribution for the pose. - - prev_color_proposal_laplace_scale: Scale parameter for proposing point colors - around the previous point RGB. - - obs_color_proposal_laplace_scale: Scale parameter for proposing point colors - around the observed point RGB. - """ - - n_poses: int = Pytree.static() - do_stochastic_color_proposals: bool - pose_proposal_std: float - pose_proposal_conc: float - prev_color_proposal_laplace_scale: float - obs_color_proposal_laplace_scale: float - - -def get_initial_trace(key, hyperparams, initial_state, initial_observed_rgbd): - """ - Get the initial trace, given the initial state. - """ - choicemap = ( - C.d( - { - "pose": initial_state["pose"], - "color_scale": initial_state["color_scale"], - "depth_scale": initial_state["depth_scale"], - "rgbd": initial_observed_rgbd, - } - ) - ^ make_visibility_prob_choicemap(initial_state["visibility_prob"]) - ^ make_colors_choicemap(initial_state["colors"]) - ^ make_depth_nonreturn_prob_choicemap(initial_state["depth_nonreturn_prob"]) - ) - trace, _ = dynamic_object_generative_model.importance( - key, choicemap, (hyperparams, initial_state) - ) - return trace - - -@jax.jit -def advance_time(key, trace, observed_rgbd): - """ - Advance to the next timestep, setting the new latent state to the - same thing as the previous latent state, and setting the new - observed RGBD value. - - Returns a trace where previous_state (stored in the arguments) - and new_state (sampled in the choices and returned) are identical. - """ - trace, _, _, _ = trace.update( - key, - U.g( - ( - Diff.no_change(get_hypers(trace)), - Diff.unknown_change(get_new_state(trace)), - ), - C.kw(rgbd=observed_rgbd), - ), - ) - return trace - - -DEFAULT_C2F_SEQ = [(0.04, 1000.0), (0.02, 1500.0), (0.005, 2000.0)] - - -def inference_step_c2f( - key, n_seq, n_poses_per_sequential_step, old_trace, observed_rgbd, *args, **kwargs -): - """ - Take an inference step using a coarse-to-fine sweep of pose proposals. - At each step of C2F, we propose `n_seq * n_poses_per_sequential_step` poses, - for each pose, propose all the other latents, and then resample one among - these options. That pose is used as the center of the pose proposal - distribution for the next step of C2F. - The final trace is returned. - - Args: - - key: PRNGKey - - n_seq: For each step of C2F, how many parallel batches of poses to propose. - (This is provided so more poses can be considered than can fit into GPU memory.) - - n_poses_per_sequential_step: How many poses to propose in parallel at each step. - (So at each step of C2F, we propose n_seq * n_poses_per_sequential_step poses, - and resample one. Then at the next step of C2F, we propose that many poses - again, but with a narrower proposal distribution.) - - old_trace: The trace from the previous timestep. - - observed_rgbd: The observed RGBD image at the current timestep. - - **kwargs: Kwargs providing each field of InferenceHyperparams - other than `n_poses`, `pose_proposal_std`, and `pose_proposal_conc`. - """ - k1, k2 = split(key) - trace = advance_time(k1, old_trace, observed_rgbd) - return infer_latents_c2f( - k2, n_seq, n_poses_per_sequential_step, trace, *args, **kwargs - ) - - -def infer_latents_c2f( - key, - n_seq, - n_poses_per_sequential_step, - trace, - pose_proposal_std_conc_seq=DEFAULT_C2F_SEQ, - **inference_hyperparam_kwargs, -): - for std, conc in pose_proposal_std_conc_seq: - inference_hyperparams = InferenceHyperparams( - n_poses=n_poses_per_sequential_step, - pose_proposal_std=std, - pose_proposal_conc=conc, - **inference_hyperparam_kwargs, - ) - key, _ = split(key) - trace, _ = infer_latents_using_sequential_proposals( - key, n_seq, trace, inference_hyperparams - ) - - return trace - - -def inference_step_using_sequential_proposals( - key, n_seq, old_trace, observed_rgbd, inference_hyperparams -): - """ - Like `inference_step`, but does `n_seq` sequential proposals - of `inference_hyperparams.n_poses` poses and other latents, - and resamples one among all of these. - Considers n_seq * inference_hyperparams.n_poses proposals in total. - Returns `(trace, weight)`. - """ - k1, k2 = split(key) - trace = advance_time(k1, old_trace, observed_rgbd) - return infer_latents_using_sequential_proposals( - k2, n_seq, trace, inference_hyperparams - ) - - -def infer_latents_using_sequential_proposals(key, n_seq, trace, inference_hyperparams): - shared_args = (trace, inference_hyperparams) - - def get_weight(key): - return infer_latents(key, *shared_args, get_trace=False, get_metadata=False)[0] - - k1, k2 = split(key) - ks = split(k1, n_seq) - weights = [get_weight(k) for k in ks] - - normalized_logps = jax.nn.log_softmax(jnp.array(weights)) - chosen_idx = jax.random.categorical(k2, normalized_logps) - trace, _ = infer_latents(ks[chosen_idx], *shared_args, get_metadata=False) - overall_weight = jax.scipy.special.logsumexp(jnp.array(weights)) - - return trace, overall_weight - - -def inference_step( - key, old_trace, observed_rgbd, inference_hyperparams, *args, **kwargs -): - """ - Perform over the latent state at time T, given the observed - rgbd at this timestep, and the old trace from time T-1. - - Also returns an estimate of the marginal likelihood of - the observed rgbd, given the latent state from time T-1. - - All arguments after `inference_hyperparams` are passed to - `infer_latents`; see `infer_latents` for details. - """ - k1, k2 = split(key) - trace = advance_time(k1, old_trace, observed_rgbd) - return infer_latents(k2, trace, inference_hyperparams, *args, **kwargs) - - -@partial(jax.jit, static_argnums=(3, 4, 5)) -def infer_latents( - key, - trace, - inference_hyperparams, - get_trace=True, - get_weight=True, - get_metadata=True, - # If this is included, we guarantee that this is one of the - # poses in the grid. - use_gt_pose=False, - gt_pose=b3d.Pose.identity(), - # Useful for debugging: turn off - logq in the pose resampling - include_qscores_in_outer_resample=True, -): - """ - Infer the latents at time `T`, given a trace `T` with arguments - containing the prev state (state at `T-1`). - Pose proposals are centered around the trace in the new state - in this trace. - - Args: - - key: PRNGKey - - trace: Partially inferred trace at time `T`. - (E.g. the output of `advance_time`.) - - inference_hyperparams: InferenceHyperparams - - get_trace: Controls whether the inferred trace is in the function's return value. - - get_weight: Controls whether the weight is in the function's return value. - - get_metadata: Controls whether the metadata is in the function's return value. - - use_gt_pose: If true, the value `gt_pose` will be placed as the first - proposed pose, in the pose proposal. (Ie. the function will act as though - it proposed this pose on the first step.) - - gt_pose: The ground truth pose at time T. - """ - _, k2, k3, k4 = split(key, 4) - - pose_generation_keys = split(k2, inference_hyperparams.n_poses) - proposed_poses, log_q_poses = jax.vmap(propose_pose, in_axes=(0, None, None))( - pose_generation_keys, trace, inference_hyperparams - ) - - proposed_poses = jax.tree.map( - lambda x, y: x.at[0].set(jnp.where(use_gt_pose, y, x[0])), - proposed_poses, - gt_pose, - ) - log_q_poses = log_q_poses.at[0].set( - jnp.where( - use_gt_pose, - get_pose_proposal_density(gt_pose, trace, inference_hyperparams), - log_q_poses[0], - ) - ) - - param_generation_keys = split(k3, inference_hyperparams.n_poses) - proposed_traces, log_q_nonpose_latents, other_latents_metadata = jax.vmap( - propose_other_latents_given_pose, in_axes=(0, None, 0, None) - )(param_generation_keys, trace, proposed_poses, inference_hyperparams) - p_scores = jax.vmap(lambda tr: tr.get_score())(proposed_traces) - - scores = jnp.where( - include_qscores_in_outer_resample, - p_scores - log_q_poses - log_q_nonpose_latents, - p_scores, - ) - chosen_index = jax.random.categorical(k4, scores) - new_trace = jax.tree.map(lambda x: x[chosen_index], proposed_traces) - - weight = logmeanexp(scores) - metadata = { - "proposed_poses": proposed_poses, - "chosen_pose_index": chosen_index, - "p_scores": p_scores, - "log_q_poses": log_q_poses, - "log_q_nonpose_latents": log_q_nonpose_latents, - "other_latents_metadata": other_latents_metadata, - } - - ret = () - if get_trace: - ret = (*ret, new_trace) - if get_weight: - ret = (*ret, weight) - if get_metadata: - ret = (*ret, metadata) - - return ret - - -@wraps(inference_step) -def inference_step_noweight(*args): - """ - Same as inference_step, but only returns the new trace - (not the weight). - """ - return inference_step(*args)[0] - - -def run_inference_many_frames( - key, - trace, - all_data, - inference_hyperparams, - use_gt_pose=True, - gt_poses=None, - get_metadata=False, - include_qscores_in_outer_resample=True, -): - traces = [] - if gt_poses is None: - gt_poses = [b3d.Pose.identity()] * len(all_data) - for T in tqdm(len(all_data)): - key = b3d.split_key(key) - trace, _ = inference_step( - key, - trace, - all_data[T]["rgbd"], - inference_hyperparams, - use_gt_pose=use_gt_pose, - gt_pose=gt_poses[T], - get_metadata=get_metadata, - include_qscores_in_outer_resample=include_qscores_in_outer_resample, - ) - traces.append(trace) - return trace - - -### Utils ### - - -def logmeanexp(vec): - vec = jnp.where(jnp.isnan(vec), -jnp.inf, vec) - return jax.scipy.special.logsumexp(vec) - jnp.log(len(vec)) diff --git a/src/b3d/chisight/gen3d/inference/__init__.py b/src/b3d/chisight/gen3d/inference/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/b3d/chisight/gen3d/inference/inference.py b/src/b3d/chisight/gen3d/inference/inference.py new file mode 100644 index 00000000..cc10a22a --- /dev/null +++ b/src/b3d/chisight/gen3d/inference/inference.py @@ -0,0 +1,311 @@ +from functools import partial + +import jax +import jax.numpy as jnp +import jax.random +from genjax import ChoiceMapBuilder as C +from genjax import Diff +from genjax import UpdateProblemBuilder as U +from jax.random import split + +import b3d +from b3d import Pose +from b3d.chisight.gen3d.hyperparams import InferenceHyperparams +from b3d.chisight.gen3d.model import ( + dynamic_object_generative_model, + get_hypers, + get_new_state, + get_prev_state, + make_colors_choicemap, + make_depth_nonreturn_prob_choicemap, + make_visibility_prob_choicemap, +) + +from .point_attribute_proposals import propose_all_pointlevel_attributes +from .utils import logmeanexp, normalize_log_scores, update_field, update_vmapped_fields + + +@partial( + jax.jit, static_argnames=("do_advance_time", "get_all_metadata", "get_all_weights") +) +def inference_step( + key, + trace, + observed_rgbd, + inference_hyperparams: InferenceHyperparams, + *, + gt_pose=b3d.Pose.identity(), + use_gt_pose=False, + do_advance_time=True, + get_all_metadata=False, + get_all_weights=False, +): + if do_advance_time: + key, subkey = split(key) + trace = advance_time(subkey, trace, observed_rgbd) + + @jax.jit + def c2f_step(trace, key, pose_proposal_args): + k1, k2, k3 = split(key, 3) + + # Propose the poses + pose_generation_keys = split(k1, inference_hyperparams.n_poses) + proposed_poses, log_q_poses = jax.vmap(propose_pose, in_axes=(0, None, None))( + pose_generation_keys, trace, pose_proposal_args + ) + proposed_poses, log_q_poses = maybe_swap_in_gt_pose( + proposed_poses, log_q_poses, trace, use_gt_pose, gt_pose, pose_proposal_args + ) + + # Generate the remaining latents to get pose scores + def propose_other_latents_given_pose_and_get_scores( + key, proposed_pose, trace, inference_hyperparams + ): + proposed_trace, log_q, _ = propose_other_latents_given_pose( + key, trace, proposed_pose, inference_hyperparams + ) + return proposed_trace.get_score(), log_q + + param_generation_keys = split(k2, inference_hyperparams.n_poses) + p_scores, log_q_nonpose_latents = jax.lax.map( + lambda x: propose_other_latents_given_pose_and_get_scores( + x[0], x[1], trace, inference_hyperparams + ), + (param_generation_keys, proposed_poses), + ) + + # Scoring + resampling + weights = jnp.where( + inference_hyperparams.include_q_scores_at_top_level, + p_scores - log_q_poses - log_q_nonpose_latents, + p_scores, + ) + + chosen_index = jax.random.categorical(k3, weights) + resampled_trace, _, _ = propose_other_latents_given_pose( + param_generation_keys[chosen_index], + trace, + proposed_poses[chosen_index], + inference_hyperparams, + ) + return ( + resampled_trace, + logmeanexp(weights), + param_generation_keys, + proposed_poses, + weights, + ) + + for pose_proposal_args in inference_hyperparams.pose_proposal_args: + key, subkey = split(key) + trace, weight, keys_to_regenerate_traces, all_poses, all_weights = c2f_step( + trace, subkey, pose_proposal_args + ) + + if get_all_metadata: + metadata = {} # TODO: someone add in getting thee metadata you need + # Please make it relatively clean! + return ( + trace, + weight, + all_weights, + all_poses, + keys_to_regenerate_traces, + metadata, + ) + elif get_all_weights: + (trace, weight, all_weights, all_poses, keys_to_regenerate_traces) + else: + return (trace, weight) + + +def get_trace_generated_during_inference(key, trace, pose, inference_hyperparams): + return propose_other_latents_given_pose(key, trace, pose, inference_hyperparams)[0] + + +def maybe_swap_in_gt_pose( + proposed_poses, log_q_poses, trace, use_gt_pose, gt_pose, pose_proposal_args +): + proposed_poses = jax.tree.map( + lambda x, y: x.at[0].set(jnp.where(use_gt_pose, y, x[0])), + proposed_poses, + gt_pose, + ) + + log_q_poses = log_q_poses.at[0].set( + jnp.where( + use_gt_pose, + get_pose_proposal_density(gt_pose, trace, pose_proposal_args), + log_q_poses[0], + ) + ) + + return proposed_poses, log_q_poses + + +@jax.jit +def advance_time(key, trace, observed_rgbd): + """ + Advance to the next timestep, setting the new latent state to the + same thing as the previous latent state, and setting the new + observed RGBD value. + + Returns a trace where previous_state (stored in the arguments) + and new_state (sampled in the choices and returned) are identical. + """ + trace, _, _, _ = trace.update( + key, + U.g( + ( + Diff.no_change(get_hypers(trace)), + Diff.unknown_change(get_new_state(trace)), + ), + C.kw(rgbd=observed_rgbd), + ), + ) + return trace + + +def get_initial_trace( + key, hyperparams, initial_state, initial_observed_rgbd, get_weight=False +): + """ + Get the initial trace, given the initial state. + The previous state and current state in the trace will be `initial_state`. + """ + choicemap = ( + C.d( + { + "pose": initial_state["pose"], + "color_scale": initial_state["color_scale"], + "depth_scale": initial_state["depth_scale"], + "rgbd": initial_observed_rgbd, + } + ) + ^ make_visibility_prob_choicemap(initial_state["visibility_prob"]) + ^ make_colors_choicemap(initial_state["colors"]) + ^ make_depth_nonreturn_prob_choicemap(initial_state["depth_nonreturn_prob"]) + ) + trace, weight = dynamic_object_generative_model.importance( + key, choicemap, (hyperparams, initial_state) + ) + if get_weight: + return trace, weight + else: + return trace + + +### Inference moves ### + + +def propose_pose(key, advanced_trace, args): + """ + Propose a random pose near the previous timestep's pose. + Returns (proposed_pose, log_proposal_density). + """ + std, conc = args + previous_pose = get_new_state(advanced_trace)["pose"] + pose = Pose.sample_gaussian_vmf_pose(key, previous_pose, std, conc) + log_q = Pose.logpdf_gaussian_vmf_pose(pose, previous_pose, std, conc) + return pose, log_q + + +def get_pose_proposal_density(pose, advanced_trace, args): + """ + Returns the log proposal density of the given pose, conditional upon the previous pose. + """ + std, conc = args + previous_pose = get_prev_state(advanced_trace)["pose"] + return Pose.logpdf_gaussian_vmf_pose(pose, previous_pose, std, conc) + + +def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperparams): + """ + Proposes all latents other than the pose, conditional upon the pose and observed RGBD + in `advanced_trace`. + Returns (proposed_trace, log_q) where `propose_trace` is the new trace with the + proposed latents (and the same pose and observed rgbd as in the given trace). + `log_q` is (a fair estimate of) the log proposal density. + """ + k1, k2, k3, k4 = split(key, 4) + + trace = update_field(k1, advanced_trace, "pose", pose) + + k2a, k2b = split(k2) + ( + colors, + visibility_probs, + depth_nonreturn_probs, + log_q_point_attributes, + point_proposal_metadata, + ) = propose_all_pointlevel_attributes(k2a, trace, inference_hyperparams) + trace = update_vmapped_fields( + k2b, + trace, + ["colors", "visibility_prob", "depth_nonreturn_prob"], + [colors, visibility_probs, depth_nonreturn_probs], + ) + + k3a, k3b = split(k3) + depth_scale, log_q_ds = propose_depth_scale(k3a, trace) + trace = update_field(k3b, trace, "depth_scale", depth_scale) + + k4a, k4b = split(k4) + color_scale, log_q_cs = propose_color_scale(k4a, trace) + trace = update_field(k4b, trace, "color_scale", color_scale) + + log_q = log_q_point_attributes + log_q_ds + log_q_cs + return ( + trace, + log_q, + { + "point_attribute_proposal_metadata": point_proposal_metadata, + "log_q_point_attributes": log_q_point_attributes, + }, + ) + + +def propose_depth_scale(key, trace): + """ + Propose a new global depth scale, conditioned upon the other values in `trace`. + Returns (depth_scale, log_q) where `depth_scale` is the proposed value and + `log_q` is (a fair estimate of) the log proposal density. + """ + k1, k2 = split(key, 2) + + def score_depth_scale(k, depth_scale): + newtr = update_field(k, trace, "depth_scale", depth_scale) + return newtr.get_score() + + support = get_hypers(trace)["depth_scale_kernel"].support + scores = jax.vmap(score_depth_scale, in_axes=(0, 0))( + split(k1, len(support)), support + ) + + normalized_scores = normalize_log_scores(scores) + index = jax.random.categorical(k2, normalized_scores) + + return support[index], normalized_scores[index] + + +def propose_color_scale(key, trace): + """ + Propose a new global color scale, conditioned upon the other values in `trace`. + Returns (color_scale, log_q) where `color_scale` is the proposed value and + `log_q` is (a fair estimate of) the log proposal density. + """ + k1, k2 = split(key, 2) + + def score_color_scale(k, color_scale): + newtr = update_field(k, trace, "color_scale", color_scale) + return newtr.get_score() + + support = get_hypers(trace)["color_scale_kernel"].support + scores = jax.vmap(score_color_scale, in_axes=(0, 0))( + split(k1, len(support)), support + ) + + normalized_scores = normalize_log_scores(scores) + index = jax.random.categorical(k2, normalized_scores) + + return support[index], normalized_scores[index] diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference/point_attribute_proposals.py similarity index 64% rename from src/b3d/chisight/gen3d/inference_moves.py rename to src/b3d/chisight/gen3d/inference/point_attribute_proposals.py index e2cf99eb..4c1dec2a 100644 --- a/src/b3d/chisight/gen3d/inference_moves.py +++ b/src/b3d/chisight/gen3d/inference/point_attribute_proposals.py @@ -1,107 +1,19 @@ import jax import jax.numpy as jnp import jax.random -from genjax import ChoiceMapBuilder as C -from genjax import Diff -from genjax import UpdateProblemBuilder as U from jax.random import split -from b3d import Pose from b3d.modeling_utils import renormalized_color_laplace -from .image_kernel import PixelsPointsAssociation -from .model import ( +from ..image_kernel import PixelsPointsAssociation +from ..model import ( get_hypers, get_n_vertices, get_new_state, get_observed_rgbd, get_prev_state, ) - - -def normalize_log_scores(scores): - """ - Util for constructing log resampling distributions, avoiding NaN issues. - - (Conversely, since there will be no NaNs, this could make it harder to debug.) - """ - val = scores - jax.scipy.special.logsumexp(scores) - return jnp.where( - jnp.any(jnp.isnan(val)), -jnp.log(len(val)) * jnp.ones_like(val), val - ) - - -def propose_pose(key, advanced_trace, inference_hyperparams): - """ - Propose a random pose near the previous timestep's pose. - Returns (proposed_pose, log_proposal_density). - """ - previous_pose = get_new_state(advanced_trace)["pose"] - ih = inference_hyperparams - pose = Pose.sample_gaussian_vmf_pose( - key, previous_pose, ih.pose_proposal_std, ih.pose_proposal_conc - ) - log_q = Pose.logpdf_gaussian_vmf_pose( - pose, previous_pose, ih.pose_proposal_std, ih.pose_proposal_conc - ) - return pose, log_q - - -def get_pose_proposal_density(pose, advanced_trace, inference_hyperparams): - """ - Returns the log proposal density of the given pose, conditional upon the previous pose. - """ - previous_pose = get_prev_state(advanced_trace)["pose"] - ih = inference_hyperparams - return Pose.logpdf_gaussian_vmf_pose( - pose, previous_pose, ih.pose_proposal_std, ih.pose_proposal_conc - ) - - -def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperparams): - """ - Proposes all latents other than the pose, conditional upon the pose and observed RGBD - in `advanced_trace`. - Returns (proposed_trace, log_q) where `propose_trace` is the new trace with the - proposed latents (and the same pose and observed rgbd as in the given trace). - `log_q` is (a fair estimate of) the log proposal density. - """ - k1, k2, k3, k4 = split(key, 4) - - trace = update_field(k1, advanced_trace, "pose", pose) - - k2a, k2b = split(k2) - ( - colors, - visibility_probs, - depth_nonreturn_probs, - log_q_point_attributes, - point_proposal_metadata, - ) = propose_all_pointlevel_attributes(k2a, trace, inference_hyperparams) - trace = update_vmapped_fields( - k2b, - trace, - ["colors", "visibility_prob", "depth_nonreturn_prob"], - [colors, visibility_probs, depth_nonreturn_probs], - ) - - k3a, k3b = split(k3) - depth_scale, log_q_ds = propose_depth_scale(k3a, trace) - trace = update_field(k3b, trace, "depth_scale", depth_scale) - - k4a, k4b = split(k4) - color_scale, log_q_cs = propose_color_scale(k4a, trace) - trace = update_field(k4b, trace, "color_scale", color_scale) - - log_q = log_q_point_attributes + log_q_ds + log_q_cs - return ( - trace, - log_q, - { - "point_attribute_proposal_metadata": point_proposal_metadata, - "log_q_point_attributes": log_q_point_attributes, - }, - ) +from .utils import all_pairs, normalize_log_scores def propose_all_pointlevel_attributes(key, trace, inference_hyperparams): @@ -426,113 +338,3 @@ def propose_vertex_color_given_other_attributes_for_valid_observed_rgb( ## Return return sampled_rgb, overall_score, metadata - - -def propose_depth_scale(key, trace): - """ - Propose a new global depth scale, conditioned upon the other values in `trace`. - Returns (depth_scale, log_q) where `depth_scale` is the proposed value and - `log_q` is (a fair estimate of) the log proposal density. - """ - k1, k2 = split(key, 2) - - def score_depth_scale(k, depth_scale): - newtr = update_field(k, trace, "depth_scale", depth_scale) - return newtr.get_score() - - support = get_hypers(trace)["depth_scale_kernel"].support - scores = jax.vmap(score_depth_scale, in_axes=(0, 0))( - split(k1, len(support)), support - ) - - normalized_scores = normalize_log_scores(scores) - index = jax.random.categorical(k2, normalized_scores) - - return support[index], normalized_scores[index] - - -def propose_color_scale(key, trace): - """ - Propose a new global color scale, conditioned upon the other values in `trace`. - Returns (color_scale, log_q) where `color_scale` is the proposed value and - `log_q` is (a fair estimate of) the log proposal density. - """ - k1, k2 = split(key, 2) - - def score_color_scale(k, color_scale): - newtr = update_field(k, trace, "color_scale", color_scale) - return newtr.get_score() - - support = get_hypers(trace)["color_scale_kernel"].support - scores = jax.vmap(score_color_scale, in_axes=(0, 0))( - split(k1, len(support)), support - ) - - normalized_scores = normalize_log_scores(scores) - index = jax.random.categorical(k2, normalized_scores) - - return support[index], normalized_scores[index] - - -### Utils ### -def update_field(key, trace, fieldname, value): - """ - Update `trace` by changing the value at address `fieldname` to `value`. - Returns a new trace. - """ - return update_fields(key, trace, [fieldname], [value]) - - -def update_fields(key, trace, fieldnames, values): - """ - Update `trace` by changing the values at the addresses in `fieldnames` to the - corresponding values in `values`. Returns a new trace. - """ - hyperparams, previous_state = trace.get_args() - trace, _, _, _ = trace.update( - key, - U.g( - (Diff.no_change(hyperparams), Diff.no_change(previous_state)), - C.kw(**dict(zip(fieldnames, values))), - ), - ) - return trace - - -def update_vmapped_fields(key, trace, fieldnames, values): - """ - For each `fieldname` in fieldnames, and each array `arr` in the - corresponding slot in `values`, updates `trace` at addresses - (0, fieldname) through (len(arr) - 1, fieldname) to the corresponding - values in `arr`. - (That is, this assumes for each fieldname, there is a vmap combinator - sampled at that address in the trace.) - """ - c = C.n() - for addr, val in zip(fieldnames, values): - c = c ^ jax.vmap(lambda idx: C[addr, idx].set(val[idx]))( - jnp.arange(val.shape[0]) - ) - - hyperparams, previous_state = trace.get_args() - trace, _, _, _ = trace.update( - key, - U.g((Diff.no_change(hyperparams), Diff.no_change(previous_state)), c), - ) - return trace - - -def update_vmapped_field(key, trace, fieldname, value): - """ - For information, see `update_vmapped_fields`. - """ - return update_vmapped_fields(key, trace, [fieldname], [value]) - - -def all_pairs(X, Y): - """ - Return an array `ret` of shape (|X| * |Y|, 2) where each row - is a pair of values from X and Y. - That is, `ret[i, :]` is a pair [x, y] for some x in X and y in Y. - """ - return jnp.swapaxes(jnp.stack(jnp.meshgrid(X, Y), axis=-1), 0, 1).reshape(-1, 2) diff --git a/src/b3d/chisight/gen3d/inference/utils.py b/src/b3d/chisight/gen3d/inference/utils.py new file mode 100644 index 00000000..ade6a95e --- /dev/null +++ b/src/b3d/chisight/gen3d/inference/utils.py @@ -0,0 +1,86 @@ +import jax +import jax.numpy as jnp +import jax.random +from genjax import ChoiceMapBuilder as C +from genjax import Diff +from genjax import UpdateProblemBuilder as U + + +def logmeanexp(vec): + vec = jnp.where(jnp.isnan(vec), -jnp.inf, vec) + return jax.scipy.special.logsumexp(vec) - jnp.log(len(vec)) + + +def update_field(key, trace, fieldname, value): + """ + Update `trace` by changing the value at address `fieldname` to `value`. + Returns a new trace. + """ + return update_fields(key, trace, [fieldname], [value]) + + +def update_fields(key, trace, fieldnames, values): + """ + Update `trace` by changing the values at the addresses in `fieldnames` to the + corresponding values in `values`. Returns a new trace. + """ + hyperparams, previous_state = trace.get_args() + trace, _, _, _ = trace.update( + key, + U.g( + (Diff.no_change(hyperparams), Diff.no_change(previous_state)), + C.kw(**dict(zip(fieldnames, values))), + ), + ) + return trace + + +def update_vmapped_fields(key, trace, fieldnames, values): + """ + For each `fieldname` in fieldnames, and each array `arr` in the + corresponding slot in `values`, updates `trace` at addresses + (0, fieldname) through (len(arr) - 1, fieldname) to the corresponding + values in `arr`. + (That is, this assumes for each fieldname, there is a vmap combinator + sampled at that address in the trace.) + """ + c = C.n() + for addr, val in zip(fieldnames, values): + c = c ^ jax.vmap(lambda idx: C[addr, idx].set(val[idx]))( + jnp.arange(val.shape[0]) + ) + + hyperparams, previous_state = trace.get_args() + trace, _, _, _ = trace.update( + key, + U.g((Diff.no_change(hyperparams), Diff.no_change(previous_state)), c), + ) + return trace + + +def update_vmapped_field(key, trace, fieldname, value): + """ + For information, see `update_vmapped_fields`. + """ + return update_vmapped_fields(key, trace, [fieldname], [value]) + + +def all_pairs(X, Y): + """ + Return an array `ret` of shape (|X| * |Y|, 2) where each row + is a pair of values from X and Y. + That is, `ret[i, :]` is a pair [x, y] for some x in X and y in Y. + """ + return jnp.swapaxes(jnp.stack(jnp.meshgrid(X, Y), axis=-1), 0, 1).reshape(-1, 2) + + +def normalize_log_scores(scores): + """ + Util for constructing log resampling distributions, avoiding NaN issues. + + (Conversely, since there will be no NaNs, this could make it harder to debug.) + """ + val = scores - jax.scipy.special.logsumexp(scores) + return jnp.where( + jnp.any(jnp.isnan(val)), -jnp.log(len(val)) * jnp.ones_like(val), val + ) diff --git a/src/b3d/chisight/gen3d/inference_old.py b/src/b3d/chisight/gen3d/inference_old.py deleted file mode 100644 index 712bf9d5..00000000 --- a/src/b3d/chisight/gen3d/inference_old.py +++ /dev/null @@ -1,195 +0,0 @@ -# import jax -# import jax.numpy as jnp -# import jax.random -# from genjax import ChoiceMapBuilder as C - -# import b3d -# from b3d import Pose - -# from .model import ( -# make_colors_choicemap, -# make_depth_nonreturn_prob_choicemap, -# make_visibility_prob_choicemap, -# ) - - -# @jax.jit -# def attribute_proposal( -# key, -# observed_rgbd_for_point, -# latent_rgbd_for_point, -# previous_color, -# previous_visibility_prob, -# previous_dnrp, -# color_scale, -# depth_scale, -# hyperparams, -# inference_hyperparams, -# ): -# image_kernel = hyperparams["image_kernel"] -# vertex_rgbd_kernel = image_kernel.get_rgbd_vertex_kernel() - -# # color_outlier_probability_sweep is (k,) shape array -# depth_nonreturn_prob_kernel = hyperparams["depth_nonreturn_prob_kernel"] -# dnrp_values = depth_nonreturn_prob_kernel.support - -# def likelihood_scorer(dnrp): -# return vertex_rgbd_kernel.logpdf( -# observed_rgbd_for_point, -# latent_rgbd_for_point, -# color_scale, -# depth_scale, -# previous_visibility_prob, -# dnrp, -# hyperparams["intrinsics"], -# ) - -# dnrp = dnrp_values[jnp.argmax(jax.vmap(likelihood_scorer)(dnrp_values))] - -# # color_outlier_probability_sweep is (k,) shape array -# visibility_values = hyperparams["visibility_prob_kernel"].support -# visibility_prob_kernel = hyperparams["visibility_prob_kernel"] - -# visbility_transition_scores = jax.vmap( -# visibility_prob_kernel.logpdf, in_axes=(0, None) -# )(visibility_values, previous_visibility_prob) - -# color_interpolations_per_proposal = jnp.array([0.0, 0.5, 1.0]) -# observed_color = observed_rgbd_for_point[:3] -# color_sweep = ( -# color_interpolations_per_proposal[..., None] * observed_color -# + (1.0 - color_interpolations_per_proposal[..., None]) * previous_color -# ) - -# color_kernel = hyperparams["color_kernel"] -# color_transition_scores = jax.vmap(color_kernel.logpdf, in_axes=(0, None))( -# color_sweep, previous_color -# ) - -# def likelihood_scorer(color, visibility_prob): -# latent_rgbd_adjusted = latent_rgbd_for_point.at[:3].set(color) -# return vertex_rgbd_kernel.logpdf( -# observed_rgbd_for_point, -# latent_rgbd_adjusted, -# color_scale, -# depth_scale, -# visibility_prob, -# dnrp, -# hyperparams["intrinsics"], -# ) - -# vmap_version = jax.vmap( -# jax.vmap( -# likelihood_scorer, -# in_axes=(None, 0), -# ), -# in_axes=(0, None), -# ) - -# likelihood_scores_per_sweep_point_and_vertex = vmap_version( -# color_sweep, visibility_values -# ) - -# scores_color_and_visibility = ( -# likelihood_scores_per_sweep_point_and_vertex # (num_color_grid_points, num_outlier_grid_points) -# + color_transition_scores[:, None, ...] -# + visbility_transition_scores[None, ...] -# ) # (num_color_grid_points, num_outlier_grid_points, num_vertices) - -# idx_color, idx_visibility = jnp.unravel_index( -# jnp.argmax(scores_color_and_visibility.reshape(-1)), -# scores_color_and_visibility.shape, -# ) -# return { -# "colors": color_sweep[idx_color], -# "visibility_prob": visibility_values[idx_visibility], -# "depth_nonreturn_prob": dnrp, -# # "scores": scores_color_and_visibility, -# } - - -# @jax.jit -# def update_vertex_attributes(key, trace, inference_hyperparams): -# hyperparams, previous_state = trace.get_args() - -# latent_rgbd_per_point, observed_rgbd_per_point = ( -# b3d.chisight.gen3d.image_kernel.get_latent_and_observed_correspondences( -# trace.get_retval()["new_state"], -# trace.get_args()[0], -# trace.get_choices()["rgbd"], -# ) -# ) - -# previous_state = trace.get_args()[1] -# previous_color = previous_state["colors"] -# previous_visibility_prob = previous_state["visibility_prob"] -# previous_dnrp = previous_state["depth_nonreturn_prob"] -# color_scale = previous_state["color_scale"] -# depth_scale = previous_state["depth_scale"] - -# keys = jax.random.split(key, len(observed_rgbd_per_point)) - -# sample = jax.vmap( -# attribute_proposal, -# in_axes=(0, 0, 0, 0, 0, 0, None, None, None, None), -# )( -# keys, -# observed_rgbd_per_point, -# latent_rgbd_per_point, -# previous_color, -# previous_visibility_prob, -# previous_dnrp, -# color_scale, -# depth_scale, -# hyperparams, -# inference_hyperparams, -# ) -# trace = trace.update( -# key, -# make_colors_choicemap(sample["colors"]) -# ^ make_visibility_prob_choicemap(sample["visibility_prob"]) -# ^ make_depth_nonreturn_prob_choicemap(sample["depth_nonreturn_prob"]), -# )[0] -# return trace, {} - - -# def update_all(key, trace, pose, inference_hyperparams): -# trace = trace.update(key, C["pose"].set(pose))[0] -# trace, _ = update_vertex_attributes(key, trace, inference_hyperparams) -# return trace - - -# def update_all_get_score(key, trace, pose, inference_hyperparams): -# trace = update_all(key, trace, pose, inference_hyperparams) -# return trace.get_score() - - -# update_all_get_score_vmap = jax.jit( -# jax.vmap(update_all_get_score, in_axes=(0, None, 0, None)) -# ) - - -# def inference_step(trace, key, inference_hyperparams): -# number = 10000 -# current_pose = trace.get_choices()["pose"] -# var_conc = [(0.04, 1000.0), (0.02, 1500.0), (0.01, 2000.0), (0.005, 2000.0)] -# for var, conc in var_conc: -# key = jax.random.split(key, 2)[-1] -# keys = jax.random.split(key, number) -# poses = Pose.concatenate_poses( -# [ -# Pose.sample_gaussian_vmf_pose_vmap(keys[:-1], current_pose, var, conc), -# current_pose[None, ...], -# ] -# ) -# pose_scores = Pose.logpdf_gaussian_vmf_pose_vmap( -# poses, trace.get_choices()["pose"], var, conc -# ) -# scores = update_all_get_score_vmap(keys, trace, poses, inference_hyperparams) -# scores_pose_q_correction = ( -# scores - pose_scores -# ) # After this, scores are fair estimates of P(data | previous state) -# # and can be used to resample the choice sets. -# current_pose = poses[jnp.argmax(scores)] -# trace = update_all(key, trace, current_pose, inference_hyperparams) -# return trace, scores, scores_pose_q_correction diff --git a/src/b3d/chisight/gen3d/model.py b/src/b3d/chisight/gen3d/model.py index 85877a3f..05ef7b1a 100644 --- a/src/b3d/chisight/gen3d/model.py +++ b/src/b3d/chisight/gen3d/model.py @@ -25,25 +25,31 @@ def dynamic_object_generative_model(hyperparams, previous_state): color_scale_kernel = hyperparams["color_scale_kernel"] pose = pose_kernel(previous_state["pose"]) @ "pose" - colors = color_kernel.vmap()(previous_state["colors"]) @ "colors" - visibility_prob = ( + color_for_each_latent_point = ( + color_kernel.vmap()(previous_state["colors"]) @ "colors" + ) + visibility_prob_for_each_latent_point = ( visibility_prob_kernel.vmap()(previous_state["visibility_prob"]) @ "visibility_prob" ) - depth_nonreturn_prob = ( + depth_nonreturn_prob_for_each_latent_point = ( depth_nonreturn_prob_kernel.vmap()(previous_state["depth_nonreturn_prob"]) @ "depth_nonreturn_prob" ) - depth_scale = depth_scale_kernel(previous_state["depth_scale"]) @ "depth_scale" - color_scale = color_scale_kernel(previous_state["color_scale"]) @ "color_scale" + global_depth_scale = ( + depth_scale_kernel(previous_state["depth_scale"]) @ "depth_scale" + ) + global_color_scale = ( + color_scale_kernel(previous_state["color_scale"]) @ "color_scale" + ) new_state = { "pose": pose, - "colors": colors, - "visibility_prob": visibility_prob, - "depth_nonreturn_prob": depth_nonreturn_prob, - "depth_scale": depth_scale, - "color_scale": color_scale, + "colors": color_for_each_latent_point, + "visibility_prob": visibility_prob_for_each_latent_point, + "depth_nonreturn_prob": depth_nonreturn_prob_for_each_latent_point, + "depth_scale": global_depth_scale, + "color_scale": global_color_scale, } if "image_kernel" not in hyperparams: diff --git a/scripts/run_ycbv_evaluation.py b/src/b3d/chisight/gen3d/run_ycbv_evaluation.py similarity index 85% rename from scripts/run_ycbv_evaluation.py rename to src/b3d/chisight/gen3d/run_ycbv_evaluation.py index af54b6fe..967ab2a7 100755 --- a/scripts/run_ycbv_evaluation.py +++ b/src/b3d/chisight/gen3d/run_ycbv_evaluation.py @@ -1,19 +1,20 @@ #!/usr/bin/env python -import copy import os import pprint from datetime import datetime from pathlib import Path -import b3d -import b3d.chisight.gen3d.inference as inference -import b3d.chisight.gen3d.settings as settings -import b3d.chisight.gen3d.visualization as viz import fire import jax import jax.numpy as jnp import rerun as rr +from tqdm import tqdm + +import b3d +import b3d.chisight.gen3d.inference.inference as inference +import b3d.chisight.gen3d.settings as settings +import b3d.chisight.gen3d.visualization as viz from b3d import Pose from b3d.chisight.gen3d.dataloading import ( get_initial_state, @@ -21,7 +22,6 @@ load_scene, ) from b3d.chisight.gen3d.model import viz_trace as rr_viz_trace -from tqdm import tqdm def setup_save_directory(): @@ -54,7 +54,7 @@ def run_tracking(scene=None, object=None, save_rerun=False, max_n_frames=None): setup_save_directory() ) - hyperparams = copy.deepcopy(settings.hyperparams) + hyperparams = settings.hyperparams inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams # noqa save_hyperparams(folder_name, hyperparams, inference_hyperparams) @@ -108,16 +108,8 @@ def run_tracking(scene=None, object=None, save_rerun=False, max_n_frames=None): for T in tqdm(range(maxT)): key = b3d.split_key(key) - trace = inference.inference_step_c2f( - key, - 2, # number of sequential iterations of the parallel pose proposal to consider - 3000, # number of poses to propose in parallel - # So the total number of poses considered at each step of C2F is 5000 * 1 - trace, - all_data[T]["rgbd"], - prev_color_proposal_laplace_scale=0.1, # inference_hyperparams.prev_color_proposal_laplace_scale, - obs_color_proposal_laplace_scale=0.1, # inference_hyperparams.obs_color_proposal_laplace_scale, - do_stochastic_color_proposals=False, + trace, _ = inference.inference_step( + key, trace, all_data[T]["rgbd"], inference_hyperparams ) tracking_results[T] = trace diff --git a/src/b3d/chisight/gen3d/settings.py b/src/b3d/chisight/gen3d/settings.py index ae90104c..39534128 100644 --- a/src/b3d/chisight/gen3d/settings.py +++ b/src/b3d/chisight/gen3d/settings.py @@ -1,8 +1,8 @@ import jax.numpy as jnp import b3d.chisight.gen3d.image_kernel as image_kernel -import b3d.chisight.gen3d.inference as inference import b3d.chisight.gen3d.transition_kernels as transition_kernels +from b3d.chisight.gen3d.hyperparams import InferenceHyperparams from b3d.chisight.gen3d.pixel_kernels.pixel_color_kernels import ( RenormalizedLaplacePixelColorDistribution, UniformPixelColorDistribution, @@ -50,10 +50,8 @@ ), } -inference_hyperparams = inference.InferenceHyperparams( - n_poses=6000, - pose_proposal_std=0.04, - pose_proposal_conc=1000.0, +inference_hyperparams = InferenceHyperparams( + n_poses=4000, do_stochastic_color_proposals=False, prev_color_proposal_laplace_scale=0.1, obs_color_proposal_laplace_scale=0.1, diff --git a/tests/gen3d/inference/test_full_inference_alg.py b/tests/gen3d/inference/test_full_inference_alg.py index 67ee3360..09dceacd 100644 --- a/tests/gen3d/inference/test_full_inference_alg.py +++ b/tests/gen3d/inference/test_full_inference_alg.py @@ -1,191 +1,103 @@ -import os - -import b3d -import b3d.chisight.gen3d.inference as i -import b3d.chisight.gen3d.model -import b3d.chisight.gen3d.settings -import b3d.io.data_loader -import genjax -import jax -import jax.numpy as jnp -from b3d import Mesh -from b3d.chisight.gen3d.model import ( - get_new_state, - make_colors_choicemap, - make_depth_nonreturn_prob_choicemap, - make_visibility_prob_choicemap, -) -from genjax import Pytree -from tqdm import tqdm - - -def test_inference_alg_runs_and_looks_ok(): - scene_id = 49 - FRAME_RATE = 50 - ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") - print(f"Scene {scene_id}") - b3d.reload(b3d.io.data_loader) - num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id) - image_ids = range(1, num_scenes + 1, FRAME_RATE) - all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, image_ids) - - meshes = [ - Mesh.from_obj_file( - os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') - ).scale(0.001) - for id in all_data[0]["object_types"] - ] - - image_height, image_width = all_data[0]["rgbd"].shape[:2] - fx, fy, cx, cy = all_data[0]["camera_intrinsics"] - scaling_factor = 1.0 - renderer = b3d.renderer.renderer_original.RendererOriginal( - image_width * scaling_factor, - image_height * scaling_factor, - fx * scaling_factor, - fy * scaling_factor, - cx * scaling_factor, - cy * scaling_factor, - 0.01, - 2.0, - ) - b3d.viz_rgb(all_data[0]["rgbd"]) - - T = 0 - b3d.rr_set_time(T) - - OBJECT_INDEX = 1 - - template_pose = ( - all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] - ) - rendered_rgbd = renderer.render_rgbd_from_mesh( - meshes[OBJECT_INDEX].transform(template_pose) - ) - xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy) - - fx, fy, cx, cy = all_data[T]["camera_intrinsics"] - xyz_observed = b3d.xyz_from_depth(all_data[T]["rgbd"][..., 3], fx, fy, cx, cy) - mask = ( - all_data[T]["masks"][OBJECT_INDEX] - * (xyz_observed[..., 2] > 0) - * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) - ) - model_vertices = template_pose.inv().apply(xyz_rendered[mask]) - model_colors = all_data[T]["rgbd"][..., :3][mask] - - ### Set up inference hyperparams ### - - hyperparams = b3d.chisight.gen3d.settings.hyperparams - inference_hyperparams = b3d.chisight.gen3d.settings.inference_hyperparams - - hyperparams["intrinsics"] = { - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - "image_height": Pytree.const(image_height), - "image_width": Pytree.const(image_width), - "near": 0.01, - "far": 10.0, - } - hyperparams["vertices"] = model_vertices - - num_vertices = model_vertices.shape[0] - previous_state = { - "pose": template_pose, - "colors": model_colors, - "visibility_prob": jnp.ones(num_vertices) - * hyperparams["visibility_prob_kernel"].support[-1], - "depth_nonreturn_prob": jnp.ones(num_vertices) - * hyperparams["depth_nonreturn_prob_kernel"].support[0], - "depth_scale": hyperparams["depth_scale_kernel"].support[0], - "color_scale": hyperparams["color_scale_kernel"].support[0], - } - - choicemap = ( - genjax.ChoiceMap.d( - { - "pose": previous_state["pose"], - "color_scale": previous_state["color_scale"], - "depth_scale": previous_state["depth_scale"], - "rgbd": all_data[T]["rgbd"], - } - ) - ^ make_visibility_prob_choicemap(previous_state["visibility_prob"]) - ^ make_colors_choicemap(previous_state["colors"]) - ^ make_depth_nonreturn_prob_choicemap(previous_state["depth_nonreturn_prob"]) - ) - - ### Test we can generate a trace ### - key = jax.random.PRNGKey(0) - og_trace, weight = ( - b3d.chisight.gen3d.model.dynamic_object_generative_model.importance( - key, choicemap, (hyperparams, previous_state) - ) - ) - trace = og_trace - assert weight == trace.get_score() - - ### Test one inference step ### - def gt_pose(T): - return ( - all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] - ) - - trace, _ = i.inference_step( - jax.random.PRNGKey(26), - og_trace, - all_data[0]["rgbd"], - inference_hyperparams, - get_metadata=False, - use_gt_pose=True, - gt_pose=gt_pose(0), - ) - - assert ( - jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(0).position) - < 0.004 - ) - - ### Run inference, giving the ground truth pose as a option in the pose proposal grid ### - trace = og_trace - key = jax.random.PRNGKey(21) - for T in tqdm(range(2)): - key = b3d.split_key(key) - trace, _ = i.inference_step( - key, - trace, - all_data[T]["rgbd"], - inference_hyperparams, - use_gt_pose=True, - gt_pose=gt_pose(T), - get_metadata=False, - include_qscores_in_outer_resample=True, - ) - assert ( - jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) - < 0.007 - ) - - ### Real inference run ### - key = jax.random.PRNGKey(123) - trace = og_trace - for T in tqdm(range(2)): - key = b3d.split_key(key) - trace = i.inference_step_c2f( - key, - 1, # number of sequential iterations of the parallel pose proposal to consider - 5000, # number of poses to propose in parallel - # So the total number of poses considered at each step of C2F is 5000 * 1 - trace, - all_data[T]["rgbd"], - prev_color_proposal_laplace_scale=inference_hyperparams.prev_color_proposal_laplace_scale, - obs_color_proposal_laplace_scale=inference_hyperparams.obs_color_proposal_laplace_scale, - do_stochastic_color_proposals=True, - ) - - assert ( - jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) - < 0.01 - ) +# import b3d +# import b3d.chisight.gen3d.inference.inference as inference +# import b3d.chisight.gen3d.model +# import b3d.chisight.gen3d.settings +# import b3d.chisight.gen3d.settings as settings +# import b3d.io.data_loader +# import jax +# import jax.numpy as jnp +# from b3d.chisight.gen3d.dataloading import ( +# get_initial_state, +# load_object_given_scene, +# load_scene, +# ) +# from b3d.chisight.gen3d.model import ( +# get_new_state, +# ) +# from tqdm import tqdm + + +# def test_inference_alg_runs_and_looks_ok(): +# scene_id = 49 +# FRAME_RATE = 50 +# OBJECT_INDEX = 1 + +# hyperparams = settings.hyperparams +# inference_hyperparams = settings.inference_hyperparams + +# all_data, meshes, renderer, intrinsics, _ = load_scene(scene_id, FRAME_RATE) +# template_pose, model_vertices, model_colors = load_object_given_scene( +# all_data, meshes, renderer, OBJECT_INDEX +# ) +# hyperparams["intrinsics"] = intrinsics +# hyperparams["vertices"] = model_vertices + +# initial_state = get_initial_state( +# template_pose, model_vertices, model_colors, hyperparams +# ) + +# ### Test we can generate a trace ### +# key = jax.random.PRNGKey(0) +# og_trace, weight = inference.get_initial_trace( +# key, hyperparams, initial_state, all_data[0]["rgbd"], get_weight=True +# ) +# assert ( +# weight == og_trace.get_score() +# ) # Test that all addresses are constrained in this trace generation + +# ### Test one inference step ### +# def gt_pose(T): +# return ( +# all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] +# ) + +# trace, _ = inference.inference_step( +# jax.random.PRNGKey(26), +# og_trace, +# all_data[0]["rgbd"], +# inference_hyperparams, +# use_gt_pose=True, +# gt_pose=gt_pose(0), +# ) + +# assert ( +# jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(0).position) +# < 0.004 +# ) + +# ### Run inference, giving the ground truth pose as a option in the pose proposal grid ### +# trace = og_trace +# key = jax.random.PRNGKey(21) +# for T in tqdm(range(2)): +# key = b3d.split_key(key) +# trace, _ = inference.inference_step( +# jax.random.PRNGKey(26), +# trace, +# all_data[T]["rgbd"], +# inference_hyperparams, +# use_gt_pose=True, +# gt_pose=gt_pose(T), +# ) + +# assert ( +# jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) +# < 0.007 +# ) + +# ### Real inference run ### +# key = jax.random.PRNGKey(123) +# trace = og_trace +# for T in tqdm(range(2)): +# key = b3d.split_key(key) +# trace, _ = inference.inference_step( +# jax.random.PRNGKey(26), +# trace, +# all_data[T]["rgbd"], +# inference_hyperparams, +# use_gt_pose=False, +# ) + +# assert ( +# jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) +# < 0.01 +# ) diff --git a/tests/gen3d/inference/test_point_attribute_inferences.py b/tests/gen3d/inference/test_point_attribute_inferences.py index 6dfc0343..655732d8 100644 --- a/tests/gen3d/inference/test_point_attribute_inferences.py +++ b/tests/gen3d/inference/test_point_attribute_inferences.py @@ -1,4 +1,4 @@ -import b3d.chisight.gen3d.inference_moves as inference_moves +import b3d.chisight.gen3d.inference.point_attribute_proposals as point_attribute_proposals import b3d.chisight.gen3d.settings import jax import jax.numpy as jnp @@ -38,7 +38,7 @@ def test_visibility_prob_inference(hyperparams_and_inference_hyperparams): def get_visibility_prob_sample( key, observed_rgbd_for_point, previous_visibility_prob ): - sample, _ = inference_moves._propose_a_points_attributes( + sample, _ = point_attribute_proposals._propose_a_points_attributes( key, observed_rgbd_for_point, latent_rgbd_for_point, @@ -105,7 +105,7 @@ def test_depth_nonreturn_prob_inference(hyperparams_and_inference_hyperparams): latent_rgbd_for_point = jnp.concatenate([previous_color, jnp.array([1.0])]) def get_dnr_prob_sample(key, observed_rgbd_for_point, previous_dnrp): - sample, _ = inference_moves._propose_a_points_attributes( + sample, _ = point_attribute_proposals._propose_a_points_attributes( key, observed_rgbd_for_point, latent_rgbd_for_point, @@ -173,7 +173,7 @@ def test_color_prob_inference(hyperparams_and_inference_hyperparams): ) def get_color_sample(key, observed_rgbd_for_point, previous_color): - sample, _ = inference_moves._propose_a_points_attributes( + sample, _ = point_attribute_proposals._propose_a_points_attributes( key, observed_rgbd_for_point, latent_rgbd_for_point, diff --git a/tests/gen3d/test_evaluation_script.py b/tests/gen3d/test_evaluation_script.py new file mode 100644 index 00000000..f2bfaee5 --- /dev/null +++ b/tests/gen3d/test_evaluation_script.py @@ -0,0 +1,5 @@ +from src.b3d.chisight.gen3d.run_ycbv_evaluation import run_tracking + + +def test_run_tracking(): + run_tracking(scene=49, object=1, max_n_frames=5) diff --git a/tests/gen3d/test_visualization.py b/tests/gen3d/test_visualization.py deleted file mode 100644 index 81e91c28..00000000 --- a/tests/gen3d/test_visualization.py +++ /dev/null @@ -1,117 +0,0 @@ -import os - -import b3d -import b3d.chisight.gen3d.model -import b3d.chisight.gen3d.settings -import b3d.io.data_loader -import genjax -import jax -import jax.numpy as jnp -from b3d import Mesh -from b3d.chisight.gen3d.model import ( - make_colors_choicemap, - make_depth_nonreturn_prob_choicemap, - make_visibility_prob_choicemap, -) -from genjax import Pytree - - -def test_visualization(): - b3d.rr_init("test_visualization") - scene_id = 49 - ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") - all_data = b3d.io.data_loader.get_ycbv_test_images(ycb_dir, scene_id, [1]) - OBJECT_INDEX = 0 - id = all_data[0]["object_types"][OBJECT_INDEX] - - mesh = Mesh.from_obj_file( - os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') - ).scale(0.001) - - image_height, image_width = all_data[0]["rgbd"].shape[:2] - fx, fy, cx, cy = all_data[0]["camera_intrinsics"] - scaling_factor = 1.0 - renderer = b3d.renderer.renderer_original.RendererOriginal( - image_width * scaling_factor, - image_height * scaling_factor, - fx * scaling_factor, - fy * scaling_factor, - cx * scaling_factor, - cy * scaling_factor, - 0.01, - 2.0, - ) - b3d.viz_rgb(all_data[0]["rgbd"]) - - T = 0 - b3d.rr_set_time(T) - - template_pose = ( - all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] - ) - rendered_rgbd = renderer.render_rgbd_from_mesh(mesh.transform(template_pose)) - xyz_rendered = b3d.xyz_from_depth(rendered_rgbd[..., 3], fx, fy, cx, cy) - - fx, fy, cx, cy = all_data[T]["camera_intrinsics"] - xyz_observed = b3d.xyz_from_depth(all_data[T]["rgbd"][..., 3], fx, fy, cx, cy) - mask = ( - all_data[T]["masks"][OBJECT_INDEX] - * (xyz_observed[..., 2] > 0) - * (jnp.linalg.norm(xyz_rendered - xyz_observed, axis=-1) < 0.01) - ) - model_vertices = template_pose.inv().apply(xyz_rendered[mask]) - model_colors = all_data[T]["rgbd"][..., :3][mask] - - ### Set up inference hyperparams ### - - hyperparams = b3d.chisight.gen3d.settings.hyperparams - - hyperparams["intrinsics"] = { - "fx": fx, - "fy": fy, - "cx": cx, - "cy": cy, - "image_height": Pytree.const(image_height), - "image_width": Pytree.const(image_width), - "near": 0.01, - "far": 10.0, - } - hyperparams["vertices"] = model_vertices - - num_vertices = model_vertices.shape[0] - previous_state = { - "pose": template_pose, - "colors": model_colors, - "visibility_prob": jnp.ones(num_vertices) - * hyperparams["visibility_prob_kernel"].support[-1], - "depth_nonreturn_prob": jnp.ones(num_vertices) - * hyperparams["depth_nonreturn_prob_kernel"].support[0], - "depth_scale": hyperparams["depth_scale_kernel"].support[0], - "color_scale": hyperparams["color_scale_kernel"].support[0], - } - - choicemap = ( - genjax.ChoiceMap.d( - { - "pose": previous_state["pose"], - "color_scale": previous_state["color_scale"], - "depth_scale": previous_state["depth_scale"], - "rgbd": all_data[T]["rgbd"], - } - ) - ^ make_visibility_prob_choicemap(previous_state["visibility_prob"]) - ^ make_colors_choicemap(previous_state["colors"]) - ^ make_depth_nonreturn_prob_choicemap(previous_state["depth_nonreturn_prob"]) - ) - - key = jax.random.PRNGKey(0) - trace, _ = b3d.chisight.gen3d.model.dynamic_object_generative_model.importance( - key, choicemap, (hyperparams, previous_state) - ) - b3d.chisight.gen3d.model.viz_trace( - trace, - T, - ground_truth_vertices=mesh.vertices, - ground_truth_pose=all_data[T]["camera_pose"].inv() - @ all_data[T]["object_poses"][OBJECT_INDEX], - ) From a8fbb2f001cd8cfbce4a769da2c992ec6482cd63 Mon Sep 17 00:00:00 2001 From: George Matheos Date: Wed, 18 Sep 2024 21:47:51 +0000 Subject: [PATCH 36/37] re-add test_full_inference file --- .../inference/test_full_inference_alg.py | 180 +++++++++--------- 1 file changed, 90 insertions(+), 90 deletions(-) diff --git a/tests/gen3d/inference/test_full_inference_alg.py b/tests/gen3d/inference/test_full_inference_alg.py index 09dceacd..d2d3ec52 100644 --- a/tests/gen3d/inference/test_full_inference_alg.py +++ b/tests/gen3d/inference/test_full_inference_alg.py @@ -1,103 +1,103 @@ -# import b3d -# import b3d.chisight.gen3d.inference.inference as inference -# import b3d.chisight.gen3d.model -# import b3d.chisight.gen3d.settings -# import b3d.chisight.gen3d.settings as settings -# import b3d.io.data_loader -# import jax -# import jax.numpy as jnp -# from b3d.chisight.gen3d.dataloading import ( -# get_initial_state, -# load_object_given_scene, -# load_scene, -# ) -# from b3d.chisight.gen3d.model import ( -# get_new_state, -# ) -# from tqdm import tqdm +import b3d +import b3d.chisight.gen3d.inference.inference as inference +import b3d.chisight.gen3d.model +import b3d.chisight.gen3d.settings +import b3d.chisight.gen3d.settings as settings +import b3d.io.data_loader +import jax +import jax.numpy as jnp +from b3d.chisight.gen3d.dataloading import ( + get_initial_state, + load_object_given_scene, + load_scene, +) +from b3d.chisight.gen3d.model import ( + get_new_state, +) +from tqdm import tqdm -# def test_inference_alg_runs_and_looks_ok(): -# scene_id = 49 -# FRAME_RATE = 50 -# OBJECT_INDEX = 1 +def test_inference_alg_runs_and_looks_ok(): + scene_id = 49 + FRAME_RATE = 50 + OBJECT_INDEX = 1 -# hyperparams = settings.hyperparams -# inference_hyperparams = settings.inference_hyperparams + hyperparams = settings.hyperparams + inference_hyperparams = settings.inference_hyperparams -# all_data, meshes, renderer, intrinsics, _ = load_scene(scene_id, FRAME_RATE) -# template_pose, model_vertices, model_colors = load_object_given_scene( -# all_data, meshes, renderer, OBJECT_INDEX -# ) -# hyperparams["intrinsics"] = intrinsics -# hyperparams["vertices"] = model_vertices + all_data, meshes, renderer, intrinsics, _ = load_scene(scene_id, FRAME_RATE) + template_pose, model_vertices, model_colors = load_object_given_scene( + all_data, meshes, renderer, OBJECT_INDEX + ) + hyperparams["intrinsics"] = intrinsics + hyperparams["vertices"] = model_vertices -# initial_state = get_initial_state( -# template_pose, model_vertices, model_colors, hyperparams -# ) + initial_state = get_initial_state( + template_pose, model_vertices, model_colors, hyperparams + ) -# ### Test we can generate a trace ### -# key = jax.random.PRNGKey(0) -# og_trace, weight = inference.get_initial_trace( -# key, hyperparams, initial_state, all_data[0]["rgbd"], get_weight=True -# ) -# assert ( -# weight == og_trace.get_score() -# ) # Test that all addresses are constrained in this trace generation + ### Test we can generate a trace ### + key = jax.random.PRNGKey(0) + og_trace, weight = inference.get_initial_trace( + key, hyperparams, initial_state, all_data[0]["rgbd"], get_weight=True + ) + assert ( + weight == og_trace.get_score() + ) # Test that all addresses are constrained in this trace generation -# ### Test one inference step ### -# def gt_pose(T): -# return ( -# all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] -# ) + ### Test one inference step ### + def gt_pose(T): + return ( + all_data[T]["camera_pose"].inv() @ all_data[T]["object_poses"][OBJECT_INDEX] + ) -# trace, _ = inference.inference_step( -# jax.random.PRNGKey(26), -# og_trace, -# all_data[0]["rgbd"], -# inference_hyperparams, -# use_gt_pose=True, -# gt_pose=gt_pose(0), -# ) + trace, _ = inference.inference_step( + jax.random.PRNGKey(26), + og_trace, + all_data[0]["rgbd"], + inference_hyperparams, + use_gt_pose=True, + gt_pose=gt_pose(0), + ) -# assert ( -# jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(0).position) -# < 0.004 -# ) + assert ( + jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(0).position) + < 0.004 + ) -# ### Run inference, giving the ground truth pose as a option in the pose proposal grid ### -# trace = og_trace -# key = jax.random.PRNGKey(21) -# for T in tqdm(range(2)): -# key = b3d.split_key(key) -# trace, _ = inference.inference_step( -# jax.random.PRNGKey(26), -# trace, -# all_data[T]["rgbd"], -# inference_hyperparams, -# use_gt_pose=True, -# gt_pose=gt_pose(T), -# ) + ### Run inference, giving the ground truth pose as a option in the pose proposal grid ### + trace = og_trace + key = jax.random.PRNGKey(21) + for T in tqdm(range(2)): + key = b3d.split_key(key) + trace, _ = inference.inference_step( + jax.random.PRNGKey(26), + trace, + all_data[T]["rgbd"], + inference_hyperparams, + use_gt_pose=True, + gt_pose=gt_pose(T), + ) -# assert ( -# jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) -# < 0.007 -# ) + assert ( + jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) + < 0.007 + ) -# ### Real inference run ### -# key = jax.random.PRNGKey(123) -# trace = og_trace -# for T in tqdm(range(2)): -# key = b3d.split_key(key) -# trace, _ = inference.inference_step( -# jax.random.PRNGKey(26), -# trace, -# all_data[T]["rgbd"], -# inference_hyperparams, -# use_gt_pose=False, -# ) + ### Real inference run ### + key = jax.random.PRNGKey(123) + trace = og_trace + for T in tqdm(range(2)): + key = b3d.split_key(key) + trace, _ = inference.inference_step( + jax.random.PRNGKey(26), + trace, + all_data[T]["rgbd"], + inference_hyperparams, + use_gt_pose=False, + ) -# assert ( -# jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) -# < 0.01 -# ) + assert ( + jnp.linalg.norm(get_new_state(trace)["pose"].position - gt_pose(T).position) + < 0.01 + ) From 0c6fde14bf447b34bb8e382e917f5d2010851dbb Mon Sep 17 00:00:00 2001 From: George Matheos Date: Wed, 18 Sep 2024 23:01:57 +0000 Subject: [PATCH 37/37] bug fix --- src/b3d/chisight/particle_system.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/b3d/chisight/particle_system.py b/src/b3d/chisight/particle_system.py index f77fee5c..2980e9bb 100644 --- a/src/b3d/chisight/particle_system.py +++ b/src/b3d/chisight/particle_system.py @@ -287,7 +287,7 @@ def visualize_particle_system( ) for i in range(num_clusters.unwrap()): - b3d.rr_log_pose(f"{viz_prefix}/3D/cluster/{i}", object_poses[t][i]) + b3d.rr_log_pose(object_poses[t][i], channel=f"{viz_prefix}/3D/cluster/{i}") def particle_2d_pixel_coordinates_to_image(pixel_coords, image_height, image_width):