Deploying to gh-pages from @ 8a51663 🚀

Advantages_Data_Types.html

@@ -15151,10 +15151,10 @@ <h1 id="Why-%CE%A6ML-has-Precision-Management">Why &#934;<sub>ML</sub> has Preci
 
 
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-<pre>2024-10-07 13:18:43.639278: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
-2024-10-07 13:18:43.678354: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+<pre>2024-10-18 15:39:40.496459: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
+2024-10-18 15:39:40.535114: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
 To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
-2024-10-07 13:18:44.499773: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+2024-10-18 15:39:41.372838: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 </pre>
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Convert.html

@@ -15617,7 +15617,7 @@ <h2 id="Converting-Tensors">Converting Tensors<a class="anchor-link" href="#Conv
 
 
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-<pre>2024-10-07 13:18:56.679526: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+<pre>2024-10-18 15:39:53.379507: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 </pre>
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Devices.html

@@ -15188,7 +15188,7 @@ <h2 id="Compute-Devices">Compute Devices<a class="anchor-link" href="#Compute-De
 
 
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-<pre>[torch device &#39;CPU&#39; (CPU &#39;cpu&#39;) | 15990 MB | 4 processors | ]</pre>
+<pre>[torch device &#39;CPU&#39; (CPU &#39;cpu&#39;) | 15981 MB | 4 processors | ]</pre>
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@@ -15240,7 +15240,7 @@ <h2 id="Compute-Devices">Compute Devices<a class="anchor-link" href="#Compute-De
 
 
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-<pre>[numpy device &#39;CPU&#39; (CPU &#39;CPU&#39;) | 15990 MB | 4 processors | ]</pre>
+<pre>[numpy device &#39;CPU&#39; (CPU &#39;CPU&#39;) | 15981 MB | 4 processors | ]</pre>
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@@ -15407,7 +15407,7 @@ <h2 id="Moving-Tensors-to-a-Different-Device">Moving Tensors to a Different Devi
 
 
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-<pre>torch device &#39;CPU&#39; (CPU &#39;cpu&#39;) | 15990 MB | 4 processors | </pre>
+<pre>torch device &#39;CPU&#39; (CPU &#39;cpu&#39;) | 15981 MB | 4 processors | </pre>
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Examples.html

@@ -15780,7 +15780,7 @@ <h3 id="JIT-compilation">JIT compilation<a class="anchor-link" href="#JIT-compil
 
 
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-<pre>2024-10-07 13:19:19.983997: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+<pre>2024-10-18 15:40:16.644768: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 </pre>
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Introduction.html

@@ -15349,7 +15349,7 @@ <h2 id="Usage-without-%CE%A6ML's-Tensors">Usage without &#934;<sub>ML</sub>'s Te
 
 
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-<pre>2024-10-07 13:19:30.722591: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
+<pre>2024-10-18 15:40:27.860015: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
 </pre>
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Linear_Solves.html

@@ -16021,13 +16021,13 @@ <h2 id="Obtaining-Additional-Information-about-a-Solve">Obtaining Additional Inf
 
 
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-<pre>factor_ilu: auto-selecting iterations=1 (eager mode) for matrix <span class="ansi-blue-intense-fg">(2.000, 0.000)</span>; <span class="ansi-blue-intense-fg">(0.000, 1.000)</span> <span class="ansi-green-intense-fg">(b_vecᶜ=2, ~b_vecᵈ=2)</span> (DEBUG), 2024-10-07 13:19:46,518n
+<pre>factor_ilu: auto-selecting iterations=1 (eager mode) for matrix <span class="ansi-blue-intense-fg">(2.000, 0.000)</span>; <span class="ansi-blue-intense-fg">(0.000, 1.000)</span> <span class="ansi-green-intense-fg">(b_vecᶜ=2, ~b_vecᵈ=2)</span> (DEBUG), 2024-10-18 15:40:44,416n
 
-TorchScript -&gt; run compiled forward &#39;_matrix_solve_forward&#39; with args [((2,), False)] (DEBUG), 2024-10-07 13:19:46,533n
+TorchScript -&gt; run compiled forward &#39;_matrix_solve_forward&#39; with args [((2,), False)] (DEBUG), 2024-10-18 15:40:44,431n
 
-Running forward pass of custom op forward &#39;_matrix_solve_forward&#39; given args (&#39;y&#39;,) containing 1 native tensors (DEBUG), 2024-10-07 13:19:46,534n
+Running forward pass of custom op forward &#39;_matrix_solve_forward&#39; given args (&#39;y&#39;,) containing 1 native tensors (DEBUG), 2024-10-18 15:40:44,431n
 
-Performing linear solve scipy-CG with tolerance <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (rel), <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (abs), max_iterations=<span class="ansi-blue-intense-fg">1000</span> with backend torch (DEBUG), 2024-10-07 13:19:46,538n
+Performing linear solve scipy-CG with tolerance <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (rel), <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (abs), max_iterations=<span class="ansi-blue-intense-fg">1000</span> with backend torch (DEBUG), 2024-10-18 15:40:44,435n
 
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@@ -16155,11 +16155,11 @@ <h2 id="Linear-Solves-with-Native-Tensors">Linear Solves with Native Tensors<a c
 
 
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-<pre>TorchScript -&gt; run compiled forward &#39;_matrix_solve_forward&#39; with args [((2,), False), ((2, 2), False)] (DEBUG), 2024-10-07 13:19:46,562n
+<pre>TorchScript -&gt; run compiled forward &#39;_matrix_solve_forward&#39; with args [((2,), False), ((2, 2), False)] (DEBUG), 2024-10-18 15:40:44,458n
 
-Running forward pass of custom op forward &#39;_matrix_solve_forward&#39; given args (&#39;y&#39;, &#39;matrix&#39;) containing 2 native tensors (DEBUG), 2024-10-07 13:19:46,562n
+Running forward pass of custom op forward &#39;_matrix_solve_forward&#39; given args (&#39;y&#39;, &#39;matrix&#39;) containing 2 native tensors (DEBUG), 2024-10-18 15:40:44,458n
 
-Performing linear solve auto with tolerance <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (rel), <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (abs), max_iterations=<span class="ansi-blue-intense-fg">1000</span> with backend torch (DEBUG), 2024-10-07 13:19:46,566n
+Performing linear solve auto with tolerance <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (rel), <span class="ansi-yellow-intense-fg">float64</span> <span class="ansi-blue-intense-fg">1e-05</span> (abs), max_iterations=<span class="ansi-blue-intense-fg">1000</span> with backend torch (DEBUG), 2024-10-18 15:40:44,461n
 
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Matrices.html

@@ -15291,17 +15291,28 @@ <h2 id="Primal-and-Dual-Dimensions">Primal and Dual Dimensions<a class="anchor-l
 
 
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-<div class="jp-OutputArea-child jp-OutputArea-executeResult">
+<div class="jp-OutputArea-child">
 
-    <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[4]:</div>
+    <div class="jp-OutputPrompt jp-OutputArea-prompt"></div>
 
 
+<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
+<pre>
+<span class="ansi-red-fg">---------------------------------------------------------------------------</span>
+<span class="ansi-red-fg">AssertionError</span>                            Traceback (most recent call last)
+Cell <span class="ansi-green-fg">In[4], line 2</span>
+<span class="ansi-green-intense-fg ansi-bold">      1</span> vector <span style="color: rgb(98,98,98)">=</span> wrap([<span style="color: rgb(98,98,98)">2</span>, <span style="color: rgb(98,98,98)">3</span>], channel(<span style="color: rgb(175,0,0)">&#39;</span><span style="color: rgb(175,0,0)">vector_dim</span><span style="color: rgb(175,0,0)">&#39;</span>))
+<span class="ansi-green-fg">----&gt; 2</span> <span class="ansi-yellow-bg">matrix</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg" style="color: rgb(98,98,98)">@</span><span class="ansi-yellow-bg"> </span><span class="ansi-yellow-bg">vector</span>
 
+File <span class="ansi-green-fg">/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/phiml/math/_tensors.py:797</span>, in <span class="ansi-cyan-fg">Tensor.__matmul__</span><span class="ansi-blue-fg">(self, other)</span>
+<span class="ansi-green-intense-fg ansi-bold">    795</span> <span class="ansi-bold" style="color: rgb(0,135,0)">if</span> <span class="ansi-bold" style="color: rgb(175,0,255)">not</span> match_primal:
+<span class="ansi-green-intense-fg ansi-bold">    796</span>     <span class="ansi-bold" style="color: rgb(0,135,0)">assert</span> non_batch(other)<span style="color: rgb(98,98,98)">.</span>non_dual<span style="color: rgb(98,98,98)">.</span>rank <span style="color: rgb(98,98,98)">==</span> <span style="color: rgb(98,98,98)">1</span>, <span style="color: rgb(175,0,0)">f</span><span style="color: rgb(175,0,0)">&#34;</span><span style="color: rgb(175,0,0)">Cannot multiply </span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span><span style="color: rgb(0,135,0)">self</span><span style="color: rgb(98,98,98)">.</span>shape<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span style="color: rgb(175,0,0)"> @ </span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>other<span style="color: rgb(98,98,98)">.</span>shape<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span style="color: rgb(175,0,0)"> because arg2 does not have appropriate non-dual dimensions</span><span style="color: rgb(175,0,0)">&#34;</span>
+<span class="ansi-green-fg">--&gt; 797</span>     <span class="ansi-bold" style="color: rgb(0,135,0)">assert</span> non_batch(other)<span style="color: rgb(98,98,98)">.</span>non_dual<span style="color: rgb(98,98,98)">.</span>size <span style="color: rgb(98,98,98)">==</span> match_primal<span style="color: rgb(98,98,98)">.</span>volume, <span style="color: rgb(175,0,0)">f</span><span style="color: rgb(175,0,0)">&#34;</span><span style="color: rgb(175,0,0)">Cannot multiply </span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span><span style="color: rgb(0,135,0)">self</span><span style="color: rgb(98,98,98)">.</span>shape<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span style="color: rgb(175,0,0)"> @ </span><span class="ansi-bold" style="color: rgb(175,95,135)">{</span>other<span style="color: rgb(98,98,98)">.</span>shape<span class="ansi-bold" style="color: rgb(175,95,135)">}</span><span style="color: rgb(175,0,0)"> because dual dims of arg1 have no match</span><span style="color: rgb(175,0,0)">&#34;</span>
+<span class="ansi-green-intense-fg ansi-bold">    798</span>     match_primal <span style="color: rgb(98,98,98)">=</span> non_batch(other)<span style="color: rgb(98,98,98)">.</span>non_dual
+<span class="ansi-green-intense-fg ansi-bold">    799</span> match_dual <span style="color: rgb(98,98,98)">=</span> <span style="color: rgb(0,135,0)">self</span><span style="color: rgb(98,98,98)">.</span>shape<span style="color: rgb(98,98,98)">.</span>dual<span style="color: rgb(98,98,98)">.</span>only(match_primal<span style="color: rgb(98,98,98)">.</span>as_dual(), reorder<span style="color: rgb(98,98,98)">=</span><span class="ansi-bold" style="color: rgb(0,135,0)">True</span>)
 
-<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-blue-intense-fg">(0, -5)</span>; <span class="ansi-blue-intense-fg">(5, 0)</span> <span class="ansi-green-intense-fg">(~colsᵈ=2, rowsᶜ=2)</span> <span class="ansi-yellow-intense-fg">int64</span></pre>
+<span class="ansi-red-fg">AssertionError</span>: Cannot multiply (~colsᵈ=2, rowsᶜ=2) @ (vector_dimᶜ=2) because dual dims of arg1 have no match</pre>
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-
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N_Dimensional.html

@@ -15250,7 +15250,7 @@ <h2 id="Grids">Grids<a class="anchor-link" href="#Grids">&#182;</a></h2><p>Grids
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-blue-intense-fg">(0.787, 0.494, 0.858, 0.550, 0.611)</span> along <span class="ansi-green-intense-fg">xˢ</span></pre>
+<pre><span class="ansi-blue-intense-fg">(0.698, 0.528, 0.577, 0.605, 0.211)</span> along <span class="ansi-green-intense-fg">xˢ</span></pre>
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 </div>
@@ -15289,7 +15289,7 @@ <h2 id="Grids">Grids<a class="anchor-link" href="#Grids">&#182;</a></h2><p>Grids
 
 
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-<pre><span class="ansi-green-intense-fg">(xˢ=3, yˢ=3)</span> <span class="ansi-blue-intense-fg">0.639 ± 0.091</span> <span class="ansi-white-fg">(5e-01...8e-01)</span></pre>
+<pre><span class="ansi-green-intense-fg">(xˢ=3, yˢ=3)</span> <span class="ansi-blue-intense-fg">0.752 ± 0.100</span> <span class="ansi-white-fg">(6e-01...9e-01)</span></pre>
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 </div>
@@ -15328,7 +15328,7 @@ <h2 id="Grids">Grids<a class="anchor-link" href="#Grids">&#182;</a></h2><p>Grids
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-green-intense-fg">(xˢ=16, yˢ=16, zˢ=16)</span> <span class="ansi-blue-intense-fg">0.495 ± 0.117</span> <span class="ansi-white-fg">(1e-01...9e-01)</span></pre>
+<pre><span class="ansi-green-intense-fg">(xˢ=16, yˢ=16, zˢ=16)</span> <span class="ansi-blue-intense-fg">0.503 ± 0.119</span> <span class="ansi-white-fg">(2e-01...9e-01)</span></pre>
 </div>
 
 </div>
@@ -15479,7 +15479,7 @@ <h2 id="Grids">Grids<a class="anchor-link" href="#Grids">&#182;</a></h2><p>Grids
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-blue-intense-fg">((3.3001955+0j), (-0.035190728-0.2234173j), (-0.4055171-0.4473677j), (-0.4055171+0.4473677j), (-0.035190728+0.2234173j))</span> along <span class="ansi-green-intense-fg">xˢ</span> <span class="ansi-yellow-intense-fg">complex64</span></pre>
+<pre><span class="ansi-blue-intense-fg">((2.6199124+0j), (-0.09480272-0.920777j), (-0.57512814+0.26343295j), (-0.57512814-0.26343295j), (-0.09480272+0.920777j))</span> along <span class="ansi-green-intense-fg">xˢ</span> <span class="ansi-yellow-intense-fg">complex64</span></pre>
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 </div>
@@ -15518,7 +15518,7 @@ <h2 id="Grids">Grids<a class="anchor-link" href="#Grids">&#182;</a></h2><p>Grids
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-green-intense-fg">(xˢ=3, yˢ=3)</span> <span class="ansi-yellow-intense-fg">complex64</span> <span class="ansi-blue-intense-fg">|...| &lt; 5.749040126800537</span></pre>
+<pre><span class="ansi-green-intense-fg">(xˢ=3, yˢ=3)</span> <span class="ansi-yellow-intense-fg">complex64</span> <span class="ansi-blue-intense-fg">|...| &lt; 6.769155502319336</span></pre>
 </div>
 
 </div>
@@ -15557,7 +15557,7 @@ <h2 id="Grids">Grids<a class="anchor-link" href="#Grids">&#182;</a></h2><p>Grids
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-green-intense-fg">(xˢ=16, yˢ=16, zˢ=16)</span> <span class="ansi-yellow-intense-fg">complex64</span> <span class="ansi-blue-intense-fg">|...| &lt; 2026.6904296875</span></pre>
+<pre><span class="ansi-green-intense-fg">(xˢ=16, yˢ=16, zˢ=16)</span> <span class="ansi-yellow-intense-fg">complex64</span> <span class="ansi-blue-intense-fg">|...| &lt; 2058.6142578125</span></pre>
 </div>
 
 </div>
@@ -15672,7 +15672,7 @@ <h2 id="Dimensions-as-Components">Dimensions as Components<a class="anchor-link"
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-green-intense-fg">(othersⁱ=4, pointsⁱ=4)</span> <span class="ansi-blue-intense-fg">0.293 ± 0.267</span> <span class="ansi-white-fg">(0e+00...7e-01)</span></pre>
+<pre><span class="ansi-green-intense-fg">(othersⁱ=4, pointsⁱ=4)</span> <span class="ansi-blue-intense-fg">0.200 ± 0.164</span> <span class="ansi-white-fg">(0e+00...5e-01)</span></pre>
 </div>
 
 </div>
@@ -15711,7 +15711,7 @@ <h2 id="Dimensions-as-Components">Dimensions as Components<a class="anchor-link"
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-green-intense-fg">(othersⁱ=4, pointsⁱ=4)</span> <span class="ansi-blue-intense-fg">0.458 ± 0.369</span> <span class="ansi-white-fg">(0e+00...1e+00)</span></pre>
+<pre><span class="ansi-green-intense-fg">(othersⁱ=4, pointsⁱ=4)</span> <span class="ansi-blue-intense-fg">0.416 ± 0.302</span> <span class="ansi-white-fg">(0e+00...9e-01)</span></pre>
 </div>
 
 </div>
@@ -15750,7 +15750,7 @@ <h2 id="Dimensions-as-Components">Dimensions as Components<a class="anchor-link"
 
 
 <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
-<pre><span class="ansi-green-intense-fg">(othersⁱ=4, pointsⁱ=4)</span> <span class="ansi-blue-intense-fg">0.569 ± 0.390</span> <span class="ansi-white-fg">(0e+00...1e+00)</span></pre>
+<pre><span class="ansi-green-intense-fg">(othersⁱ=4, pointsⁱ=4)</span> <span class="ansi-blue-intense-fg">0.468 ± 0.340</span> <span class="ansi-white-fg">(0e+00...1e+00)</span></pre>
 </div>
 
 </div>