feat: Remove support for TensorFlow (#2609)

* Remove support for TensorFlow from the codebase.
   - This is a breaking change.
   - Remove the TensorFlow backend and optimize/opt_tflow.py.
* Remove use of TensorFlow from the tests.
   - Remove TensorFlow lower bounds from tests/constraints.txt.
* Remove all docs and examples that mention or use TensorFlow.
* Remove mentions of TensorFlow in all parts of the website and REAMDE
  except for historical purposes like the release notes, JOSS paper, and
  notes about early pyhf research in FAQs.

Co-authored-by: Giordon Stark <[email protected]>

Author: matthewfeickert

.zenodo.json

@@ -28,7 +28,6 @@
       "fitting",
       "scipy",
       "numpy",
-      "tensorflow",
       "pytorch",
       "jax",
       "auto-differentiation"

CITATION.cff

@@ -26,7 +26,6 @@ keywords:
   - fitting
   - scipy
   - numpy
-  - tensorflow
   - pytorch
   - jax
   - auto-differentiation
@@ -38,7 +37,7 @@ abstract: |
   of that statistical model for multi-bin histogram-based analysis and its
   interval estimation is based on the asymptotic formulas of "Asymptotic
   formulae for likelihood-based tests of new physics". pyhf supports modern
-  computational graph libraries such as TensorFlow, PyTorch, and JAX in order
+  computational graph libraries such as PyTorch and JAX in order
   to make use of features such as autodifferentiation and GPU acceleration.
 references:
   - type: article

README.rst

@@ -29,7 +29,7 @@ on the asymptotic formulas of “Asymptotic formulae for likelihood-based
 tests of new physics”
 [`arXiv:1007.1727 <https://arxiv.org/abs/1007.1727>`__]. The aim is also
 to support modern computational graph libraries such as PyTorch and
-TensorFlow in order to make use of features such as autodifferentiation
+JAX in order to make use of features such as autodifferentiation
 and GPU acceleration.
 
 ..
@@ -145,7 +145,6 @@ Implemented variations:
 Computational Backends:
   - ☑ NumPy
   - ☑ PyTorch
-  - ☑ TensorFlow
   - ☑ JAX
 
 Optimizers:

docker/gpu/Dockerfile

@@ -13,7 +13,7 @@ RUN apt-get update -y && \
 COPY . /code
 COPY ./docker/gpu/install_backend.sh /code/install_backend.sh
 WORKDIR /code
-ARG BACKEND=tensorflow
+ARG BACKEND=jax
 RUN python3 -m pip --no-cache-dir install --upgrade pip wheel && \
     /bin/bash install_backend.sh ${BACKEND} && \
     python3 -m pip list

docker/gpu/install_backend.sh

@@ -18,10 +18,7 @@ function get_JAXLIB_GPU_WHEEL {
 function install_backend() {
   # 1: the backend option name in setup.py
   local backend="${1}"
-  if [[ "${backend}" == "tensorflow" ]]; then
-    # shellcheck disable=SC2102
-    python3 -m pip install --no-cache-dir .[xmlio,tensorflow]
-  elif [[ "${backend}" == "torch" ]]; then
+  if [[ "${backend}" == "torch" ]]; then
     # shellcheck disable=SC2102
     python3 -m pip install --no-cache-dir .[xmlio,torch]
   elif [[ "${backend}" == "jax" ]]; then

docs/api.rst

@@ -66,7 +66,6 @@ The computational backends that :code:`pyhf` provides interfacing for the vector
 
    numpy_backend.numpy_backend
    pytorch_backend.pytorch_backend
-   tensorflow_backend.tensorflow_backend
    jax_backend.jax_backend
 
 Optimizers

docs/conf.py

@@ -146,11 +146,9 @@ def setup(app):
 # today_fmt = '%B %d, %Y'
 
 autodoc_mock_imports = [
-    'tensorflow',
     'torch',
     'jax',
     'iminuit',
-    'tensorflow_probability',
 ]
 
 
@@ -195,7 +193,6 @@ def setup(app):
     'examples/notebooks/ImpactPlot.ipynb',
     'examples/notebooks/Recast.ipynb',
     'examples/notebooks/StatError.ipynb',
-    'examples/notebooks/example-tensorflow.ipynb',
     'examples/notebooks/histogrammar.ipynb',
     'examples/notebooks/histosys.ipynb',
     'examples/notebooks/histosys-pytorch.ipynb',
@@ -205,7 +202,6 @@ def setup(app):
     'examples/notebooks/normsys.ipynb',
     'examples/notebooks/pullplot.ipynb',
     'examples/notebooks/pytorch_tests_onoff.ipynb',
-    'examples/notebooks/tensorflow-limit.ipynb',
 ]
 
 # The reST default role (used for this markup: `text`) to use for all

docs/examples/experiments/edwardpyhf.ipynb

@@ -26,15 +26,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import pyhf\n",
     "from pyhf import Model\n",
-    "from pyhf.simplemodels import uncorrelated_background\n",
-    "\n",
-    "import tensorflow as tf"
+    "from pyhf.simplemodels import uncorrelated_background"
    ]
   },
   {
@@ -78,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -89,9 +87,6 @@
       "# NumPy\n",
       "<class 'numpy.ndarray'> [-23.57960517]\n",
       "\n",
-      "# TensorFlow\n",
-      "<class 'tensorflow.python.framework.ops.Tensor'> Tensor(\"Reshape_1:0\", shape=(1,), dtype=float32)\n",
-      "\n",
       "# PyTorch\n",
       "<class 'torch.Tensor'> tensor([-23.5796])\n"
      ]
@@ -100,12 +95,10 @@
    "source": [
     "backends = [\n",
     "    pyhf.tensor.numpy_backend(),\n",
-    "    pyhf.tensor.tensorflow_backend(session=tf.Session()),\n",
     "    pyhf.tensor.pytorch_backend(),\n",
     "]\n",
     "names = [\n",
     "    'NumPy',\n",
-    "    'TensorFlow',\n",
     "    'PyTorch',\n",
     "]\n",
     "\n",