Rename project to Φ-ML

.coveragerc

@@ -25,9 +25,9 @@ exclude_also =
 
 
 omit =
-    ml4s/backend/tensorflow/_tf_cuda_resample.py
-    ml4s/backend/tensorflow/_compile_cuda.py
-    ml4s/math/fit.py
+    phiml/backend/tensorflow/_tf_cuda_resample.py
+    phiml/backend/tensorflow/_compile_cuda.py
+    phiml/math/fit.py
 
 
 [run]

.github/workflows/unit-tests.yml

@@ -37,4 +37,4 @@ jobs:
         continue-on-error: true
         run: |
           pylint --rcfile=./tests/.pylintrc tests
-          pylint --rcfile=./ml4s/.pylintrc ml4s
+          pylint --rcfile=./phiml/.pylintrc phiml

.github/workflows/update-gh-pages.yml

@@ -26,7 +26,7 @@ jobs:
           pip list
         
       - name: Build API with pdoc3
-        run: pdoc --html --output-dir docs --force ml4s
+        run: pdoc --html --output-dir docs --force phiml
 
       - name: Build static HTML for Jupyter Notebooks
         run: |

CONTRIBUTING.md

@@ -1,11 +1,11 @@
-# Contributing to ML4Science
+# Contributing to Φ<sub>ML</sub>
 All contributions are welcome!
 You can mail the developers or get in touch on GitHub.
 
 
 ## Types of contributions we're looking for
 
-We're open to all kind of contributions that improve or extend the ML4Science library.
+We're open to all kind of contributions that improve or extend the Φ<sub>ML</sub> library.
 We especially welcome
 
 - Bug fixes
@@ -18,7 +18,7 @@ We especially welcome
 We recommend you to contact the developers before starting your contribution.
 There may already be similar internal work or planned changes that would affect how to code the contribution.
 
-To contribute code, fork ML4Science on GitHub, make your changes, and submit a pull request.
+To contribute code, fork Φ<sub>ML</sub> on GitHub, make your changes, and submit a pull request.
 Make sure that your contribution passes all tests.
 
 
@@ -31,12 +31,12 @@ We would like to add the rule *Concise is better than repetitive.*
 
 We use PyLint for static code analysis with specific configuration files for the
 [tests](../tests/.pylintrc) and the
-[code base](../ml4s/.pylintrc).
+[code base](../phiml/.pylintrc).
 PyLint is part of the automatic testing pipeline.
 The warning log can be viewed online by selecting a `Tests` job and expanding the pylint output.
 
 ### Docstrings
-The [API documentation](https://tum-pbs.github.io/ML4Science/) for ML4Science is generated using [pdoc](https://pdoc3.github.io/pdoc/).
+The [API documentation](https://tum-pbs.github.io/PhiML/) for Φ<sub>ML</sub> is generated using [pdoc](https://pdoc3.github.io/pdoc/).
 We use [Google style docstrings](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings)
 with Markdown formatting.
 

MANIFEST.in

@@ -1,3 +1,3 @@
-include ml4s/VERSION
+include phiml/VERSION
 include documentation/Package_Info.md
-recursive-include ml4s/backend/tf/cuda/build *
+recursive-include phiml/backend/tf/cuda/build *

docs/Convert.ipynb

@@ -9,14 +9,14 @@
     }
    },
    "source": [
-    "# Using Multiple Backends via ML4Science\n",
+    "# Using Multiple Backends via Φ<sub>ML</sub>\n",
     "\n",
-    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Convert.ipynb)\n",
-    "&nbsp; • &nbsp; [🌐 **ML4Science**](https://github.com/tum-pbs/ML4Science)\n",
-    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/ML4Science/)\n",
-    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/ML4Science/ml4s)\n",
+    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Convert.ipynb)\n",
+    "&nbsp; • &nbsp; [🌐 **Φ<sub>ML</sub>**](https://github.com/tum-pbs/PhiML)\n",
+    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/PhiML/)\n",
+    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/PhiML/phiml)\n",
     "&nbsp; • &nbsp; [**▶ Videos**]()\n",
-    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/ML4Science/Examples.html)"
+    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/PhiML/Examples.html)"
    ]
   },
   {
@@ -25,7 +25,7 @@
    "outputs": [],
    "source": [
     "%%capture\n",
-    "!pip install ml4s"
+    "!pip install phiml"
    ],
    "metadata": {
     "collapsed": false,
@@ -39,11 +39,11 @@
    "source": [
     "## How Backends are Chosen\n",
     "\n",
-    "ML4Science can execute your instructions using Jax, PyTorch, TensorFlow or NumPy.\n",
+    "Φ<sub>ML</sub> can execute your instructions using Jax, PyTorch, TensorFlow or NumPy.\n",
     "Which library is used generally depends on what tensors you pass to it.\n",
     "Calling a function with PyTorch tensors will always invoke the corresponding PyTorch routine.\n",
     "\n",
-    "Let's first look at the function [`math.use()`](ml4s/math#ml4s.math.use) which lets you set a global default backend."
+    "Let's first look at the function [`math.use()`](phiml/math#phiml.math.use) which lets you set a global default backend."
    ],
    "metadata": {
     "collapsed": false,
@@ -66,7 +66,7 @@
     }
    ],
    "source": [
-    "from ml4s import math\n",
+    "from phiml import math\n",
     "\n",
     "math.use('jax')"
    ],
@@ -80,7 +80,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "From now on, new tensors created by ML4Science will be backed by Jax arrays."
+    "From now on, new tensors created by Φ<sub>ML</sub> will be backed by Jax arrays."
    ],
    "metadata": {
     "collapsed": false,
@@ -275,7 +275,7 @@
    "source": [
     "## Converting Tensors\n",
     "\n",
-    "We can move tensors between different backends using [`math.convert()`](ml4s/math#ml4s.math.convert).\n",
+    "We can move tensors between different backends using [`math.convert()`](phiml/math#phiml.math.convert).\n",
     "This will use [DLPack](https://github.com/dmlc/dlpack) under-the-hood when converting between ML backends.\n",
     "\n",
     "For the target backend, you can pass the module, module name or Backend object."
@@ -349,9 +349,9 @@
     }
    ],
    "source": [
-    "from ml4s.backend.torch import TORCH\n",
-    "from ml4s.backend.jax import JAX\n",
-    "from ml4s.backend.tensorflow import TENSORFLOW\n",
+    "from phiml.backend.torch import TORCH\n",
+    "from phiml.backend.jax import JAX\n",
+    "from phiml.backend.tensorflow import TENSORFLOW\n",
     "\n",
     "math.convert(jax_tensor, TORCH).default_backend"
    ],
@@ -406,11 +406,11 @@
     "\n",
     "NumPy functions are not differentiable but it nevertheless plays an important role in [representing constants](NumPy_Constants.html) in your code.\n",
     "\n",
-    "[🌐 **ML4Science**](https://github.com/tum-pbs/ML4Science)\n",
-    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/ML4Science/)\n",
-    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/ML4Science/ml4s)\n",
+    "[🌐 **Φ<sub>ML</sub>**](https://github.com/tum-pbs/PhiML)\n",
+    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/PhiML/)\n",
+    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/PhiML/phiml)\n",
     "&nbsp; • &nbsp; [**▶ Videos**]()\n",
-    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/ML4Science/Examples.html)"
+    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/PhiML/Examples.html)"
    ],
    "metadata": {
     "collapsed": false,

docs/Data_Types.ipynb

@@ -3,20 +3,20 @@
   {
    "cell_type": "markdown",
    "source": [
-    "# Data Types in ML4Science\n",
+    "# Data Types in Φ<sub>ML</sub>\n",
     "\n",
-    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Data_Types.ipynb)\n",
-    "&nbsp; • &nbsp; [🌐 **ML4Science**](https://github.com/tum-pbs/ML4Science)\n",
-    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/ML4Science/)\n",
-    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/ML4Science/ml4s)\n",
+    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Data_Types.ipynb)\n",
+    "&nbsp; • &nbsp; [🌐 **Φ<sub>ML</sub>**](https://github.com/tum-pbs/PhiML)\n",
+    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/PhiML/)\n",
+    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/PhiML/phiml)\n",
     "&nbsp; • &nbsp; [**▶ Videos**]()\n",
-    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/ML4Science/Examples.html)\n",
+    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/PhiML/Examples.html)\n",
     "\n",
     "*Need to differentiate but your input is an `int` tensor?\n",
     "Need an `int64` tensor but got `int32`?\n",
     "Need a `tensor` but got an `ndarray`?\n",
     "Want an `ndarray` but your tensor is bound in a computational graph on the GPU?\n",
-    "Worry no longer for ML4Science has you covered!*"
+    "Worry no longer for Φ<sub>ML</sub> has you covered!*"
    ],
    "metadata": {
     "collapsed": false,
@@ -31,7 +31,7 @@
    "outputs": [],
    "source": [
     "%%capture\n",
-    "!pip install ml4s"
+    "!pip install phiml"
    ],
    "metadata": {
     "collapsed": false,
@@ -45,9 +45,9 @@
    "source": [
     "## Floating Point Precision\n",
     "\n",
-    "A major difference between ML4Science and its backends is the handling of floating point (FP) precision.\n",
+    "A major difference between Φ<sub>ML</sub> and its backends is the handling of floating point (FP) precision.\n",
     "NumPy automatically casts arrays to the highest precision and other ML libraries will raise errors if data types do not match.\n",
-    "Instead, ML4Science lets you set the FP precision globally using [`set_global_precision(64)`](ml4s/math/#ml4s.math.set_global_precision)\n",
+    "Instead, Φ<sub>ML</sub> lets you set the FP precision globally using [`set_global_precision(64)`](phiml/math/#phiml.math.set_global_precision)\n",
     "or by context and automatically casts tensors to that precision when needed.\n",
     "The default is FP32 (single precision).\n",
     "Let's set the global precision to FP64 (double precision)!"
@@ -64,7 +64,7 @@
    "execution_count": 5,
    "outputs": [],
    "source": [
-    "from ml4s import math\n",
+    "from phiml import math\n",
     "\n",
     "math.set_global_precision(64)  # double precision"
    ],
@@ -113,7 +113,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "We can run parts of our code with a different precision by executing them within a [`precision`](ml4s/math/#ml4s.math.precision) block:"
+    "We can run parts of our code with a different precision by executing them within a [`precision`](phiml/math/#phiml.math.precision) block:"
    ],
    "metadata": {
     "collapsed": false,
@@ -148,7 +148,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "ML4Science automatically casts tensors to the current precision level during operations.\n",
+    "Φ<sub>ML</sub> automatically casts tensors to the current precision level during operations.\n",
     "Say we have a `float64` tensor but want to run 32-bit operations."
    ],
    "metadata": {
@@ -186,7 +186,7 @@
    "cell_type": "markdown",
    "source": [
     "Here, the tensor was cast to `float32` before applying the `sin` function.\n",
-    "If you want to explicitly cast a tensor to the current precision, use [`math.to_float()`](ml4s/math#ml4s.math.to_float)\n",
+    "If you want to explicitly cast a tensor to the current precision, use [`math.to_float()`](phiml/math#phiml.math.to_float)\n",
     "\n",
     "This system precludes any precision conflicts and you will never accidentally execute code with the wrong precision!"
    ],
@@ -202,7 +202,7 @@
    "source": [
     "## Specifying Data Types\n",
     "\n",
-    "ML4Science provides a unified data type class, [`DType`](ml4s/math#ml4s.math.DType).\n",
+    "Φ<sub>ML</sub> provides a unified data type class, [`DType`](phiml/math#phiml.math.DType).\n",
     "However, you only need to specify the data type when creating a new `Tensor` from scratch.\n",
     "When wrapping an existing tensor, the data type is kept as-is."
    ],
@@ -227,7 +227,7 @@
     }
    ],
    "source": [
-    "from ml4s.math import DType\n",
+    "from phiml.math import DType\n",
     "\n",
     "math.zeros(dtype=DType(float, 16))"
    ],
@@ -361,11 +361,11 @@
    "source": [
     "## Further Reading\n",
     "\n",
-    "[🌐 **ML4Science**](https://github.com/tum-pbs/ML4Science)\n",
-    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/ML4Science/)\n",
-    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/ML4Science/ml4s)\n",
+    "[🌐 **Φ<sub>ML</sub>**](https://github.com/tum-pbs/PhiML)\n",
+    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/PhiML/)\n",
+    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/PhiML/phiml)\n",
     "&nbsp; • &nbsp; [**▶ Videos**]()\n",
-    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/ML4Science/Examples.html)"
+    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/PhiML/Examples.html)"
    ],
    "metadata": {
     "collapsed": false,

docs/Devices.ipynb

@@ -3,14 +3,14 @@
   {
    "cell_type": "markdown",
    "source": [
-    "# Device Handling in ML4Science\n",
+    "# Device Handling in Φ<sub>ML</sub>\n",
     "\n",
-    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Devices.ipynb)\n",
-    "&nbsp; • &nbsp; [🌐 **ML4Science**](https://github.com/tum-pbs/ML4Science)\n",
-    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/ML4Science/)\n",
-    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/ML4Science/ml4s)\n",
+    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Devices.ipynb)\n",
+    "&nbsp; • &nbsp; [🌐 **Φ<sub>ML</sub>**](https://github.com/tum-pbs/PhiML)\n",
+    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/PhiML/)\n",
+    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/PhiML/phiml)\n",
     "&nbsp; • &nbsp; [**▶ Videos**]()\n",
-    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/ML4Science/Examples.html)\n",
+    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/PhiML/Examples.html)\n",
     "\n",
     "This notebook is work in progress. It will explain\n",
     "\n",
@@ -30,9 +30,9 @@
    "outputs": [],
    "source": [
     "%%capture\n",
-    "!pip install ml4s\n",
+    "!pip install phiml\n",
     "\n",
-    "from ml4s import math, backend"
+    "from phiml import math, backend"
    ],
    "metadata": {
     "collapsed": false,
@@ -46,8 +46,8 @@
    "source": [
     "## Compute Devices\n",
     "\n",
-    "ML4Science abstracts [`ComputeDevices`](ml4s/backend/#ml4s.backend.ComputeDevice), such as CPUs, GPUs and TPUs.\n",
-    "You can obtain a list of available devices using [`Backend.list_devices()`](ml4s/backend/#ml4s.backend.Backend.list_devices)"
+    "Φ<sub>ML</sub> abstracts [`ComputeDevices`](phiml/backend/#phiml.backend.ComputeDevice), such as CPUs, GPUs and TPUs.\n",
+    "You can obtain a list of available devices using [`Backend.list_devices()`](phiml/backend/#phiml.backend.Backend.list_devices)"
    ],
    "metadata": {
     "collapsed": false,
@@ -106,7 +106,7 @@
     }
    ],
    "source": [
-    "from ml4s.backend import NUMPY\n",
+    "from phiml.backend import NUMPY\n",
     "NUMPY.list_devices('CPU')"
    ],
    "metadata": {
@@ -161,7 +161,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/holl/PycharmProjects/ML4Science/ml4s/backend/_backend.py:245: RuntimeWarning: torch: Cannot select 'GPU' because no device of this type is available.\n",
+      "/home/holl/PycharmProjects/PhiML/phiml/backend/_backend.py:245: RuntimeWarning: torch: Cannot select 'GPU' because no device of this type is available.\n",
       "  warnings.warn(f\"{self.name}: Cannot select '{device}' because no device of this type is available.\", RuntimeWarning)\n"
      ]
     },
@@ -263,7 +263,7 @@
   {
    "cell_type": "markdown",
    "source": [
-    "[`math.to_device()`](ml4s/math#ml4s.math.to_device) also supports pytrees and data classes that contain tensors."
+    "[`math.to_device()`](phiml/math#phiml.math.to_device) also supports pytrees and data classes that contain tensors."
    ],
    "metadata": {
     "collapsed": false,
@@ -277,13 +277,13 @@
    "source": [
     "## Further Reading\n",
     "\n",
-    "ML4Science also supports [moving tensors to different backend libraries](Convert.html) without copying them.\n",
+    "Φ<sub>ML</sub> also supports [moving tensors to different backend libraries](Convert.html) without copying them.\n",
     "\n",
-    "[🌐 **ML4Science**](https://github.com/tum-pbs/ML4Science)\n",
-    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/ML4Science/)\n",
-    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/ML4Science/ml4s)\n",
+    "[🌐 **Φ<sub>ML</sub>**](https://github.com/tum-pbs/PhiML)\n",
+    "&nbsp; • &nbsp; [📖 **Documentation**](https://tum-pbs.github.io/PhiML/)\n",
+    "&nbsp; • &nbsp; [🔗 **API**](https://tum-pbs.github.io/PhiML/phiml)\n",
     "&nbsp; • &nbsp; [**▶ Videos**]()\n",
-    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/ML4Science/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/ML4Science/Examples.html)"
+    "&nbsp; • &nbsp; [<img src=\"images/colab_logo_small.png\" height=4>](https://colab.research.google.com/github/tum-pbs/PhiML/blob/main/docs/Examples.ipynb) [**Examples**](https://tum-pbs.github.io/PhiML/Examples.html)"
    ],
    "metadata": {
     "collapsed": false,