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1 change: 0 additions & 1 deletion .zenodo.json
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,6 @@
"fitting",
"scipy",
"numpy",
"pytorch",
"jax",
"auto-differentiation"
],
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5 changes: 2 additions & 3 deletions CITATION.cff
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Expand Up @@ -26,7 +26,6 @@ keywords:
- fitting
- scipy
- numpy
- pytorch
- jax
- auto-differentiation
license: "Apache-2.0"
Expand All @@ -37,8 +36,8 @@ 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 PyTorch and JAX in order
to make use of features such as autodifferentiation and GPU acceleration.
computational graph libraries such as JAX in order to make use of features
such as automatic differentiation and GPU acceleration.
references:
- type: article
authors:
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6 changes: 2 additions & 4 deletions README.rst
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Expand Up @@ -28,9 +28,8 @@ 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”
[`arXiv:1007.1727 <https://arxiv.org/abs/1007.1727>`__]. The aim is also
to support modern computational graph libraries such as PyTorch and
JAX in order to make use of features such as autodifferentiation
and GPU acceleration.
to support modern computational graph libraries such as JAX in order to
make use of features such as automatic differentiation and GPU acceleration.

..
Comment: JupyterLite segment goes here in docs
Expand Down Expand Up @@ -144,7 +143,6 @@ Implemented variations:

Computational Backends:
- ☑ NumPy
- ☑ PyTorch
- ☑ JAX

Optimizers:
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5 changes: 1 addition & 4 deletions docker/gpu/install_backend.sh
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Expand Up @@ -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}" == "torch" ]]; then
# shellcheck disable=SC2102
python3 -m pip install --no-cache-dir .[xmlio,torch]
elif [[ "${backend}" == "jax" ]]; then
if [[ "${backend}" == "jax" ]]; then
python3 -m pip install --no-cache-dir .[xmlio]
python3 -m pip install --no-cache-dir "$(get_JAXLIB_GPU_WHEEL)"
python3 -m pip install --no-cache-dir jax
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1 change: 0 additions & 1 deletion docs/api.rst
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Expand Up @@ -65,7 +65,6 @@ The computational backends that :code:`pyhf` provides interfacing for the vector
:nosignatures:

numpy_backend.numpy_backend
pytorch_backend.pytorch_backend
jax_backend.jax_backend

Optimizers
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3 changes: 0 additions & 3 deletions docs/conf.py
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Expand Up @@ -146,7 +146,6 @@ def setup(app):
# today_fmt = '%B %d, %Y'

autodoc_mock_imports = [
'torch',
'jax',
'iminuit',
]
Expand Down Expand Up @@ -195,13 +194,11 @@ def setup(app):
'examples/notebooks/StatError.ipynb',
'examples/notebooks/histogrammar.ipynb',
'examples/notebooks/histosys.ipynb',
'examples/notebooks/histosys-pytorch.ipynb',
'examples/notebooks/importxml.ipynb',
'examples/notebooks/multichannel-coupled-normsys.ipynb',
'examples/notebooks/multichannel-normsys.ipynb',
'examples/notebooks/normsys.ipynb',
'examples/notebooks/pullplot.ipynb',
'examples/notebooks/pytorch_tests_onoff.ipynb',
]

# The reST default role (used for this markup: `text`) to use for all
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134 changes: 0 additions & 134 deletions docs/examples/notebooks/histosys-pytorch.ipynb

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