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wip/py-autograd: import py-autograd-1.3

This commit is contained in:
K.I.A.Derouiche 2020-10-26 14:56:03 +01:00
parent 63a4ed93d5
commit 15d8ed2f0d
4 changed files with 156 additions and 0 deletions
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10
py-autograd/DESCR Normal file
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Autograd can automatically differentiate native Python
and Numpy code. It can handle a large subset of Python
features, including loops, ifs, recursion and closures,
and it can even take derivatives of derivatives of
derivatives. It supports reverse-mode differentiation
(a.k.a. backpropagation), which means it can efficiently
take gradients of scalar-valued functions with respect to
array-valued arguments, as well as forward-mode differentiation,
and the two can be composed arbitrarily. The main intended
application of Autograd is gradient-based optimization

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py-autograd/Makefile Normal file
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# $NetBSD$
DISTNAME= autograd-1.3
PKGNAME= ${PYPKGPREFIX}-${DISTNAME}
CATEGORIES= math python
MASTER_SITES= ${MASTER_SITE_PYPI:=a/autograd/}
MAINTAINER= jihbed.research@gmail.com
HOMEPAGE= https://github.com/HIPS/autograd
COMMENT= Efficiently computes derivatives of numpy code
LICENSE= mit
DEPENDS+= ${PYPKGPREFIX}-future>=0.15.2:../../devel/py-future
USE_LANGUAGES= # none
BUILDLINK_API_DEPENDS.${PYPKGPREFIX}-numpy+= ${PYPKGPREFIX}-numpy>=1.12
.include "../../math/py-numpy/buildlink3.mk"
.include "../../lang/python/egg.mk"
.include "../../mk/bsd.pkg.mk"

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py-autograd/PLIST Normal file
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@comment $NetBSD$
${PYSITELIB}/${EGG_INFODIR}/PKG-INFO
${PYSITELIB}/${EGG_INFODIR}/SOURCES.txt
${PYSITELIB}/${EGG_INFODIR}/dependency_links.txt
${PYSITELIB}/${EGG_INFODIR}/requires.txt
${PYSITELIB}/${EGG_INFODIR}/top_level.txt
${PYSITELIB}/autograd/__init__.py
${PYSITELIB}/autograd/__init__.pyc
${PYSITELIB}/autograd/__init__.pyo
${PYSITELIB}/autograd/builtins.py
${PYSITELIB}/autograd/builtins.pyc
${PYSITELIB}/autograd/builtins.pyo
${PYSITELIB}/autograd/core.py
${PYSITELIB}/autograd/core.pyc
${PYSITELIB}/autograd/core.pyo
${PYSITELIB}/autograd/differential_operators.py
${PYSITELIB}/autograd/differential_operators.pyc
${PYSITELIB}/autograd/differential_operators.pyo
${PYSITELIB}/autograd/extend.py
${PYSITELIB}/autograd/extend.pyc
${PYSITELIB}/autograd/extend.pyo
${PYSITELIB}/autograd/misc/__init__.py
${PYSITELIB}/autograd/misc/__init__.pyc
${PYSITELIB}/autograd/misc/__init__.pyo
${PYSITELIB}/autograd/misc/fixed_points.py
${PYSITELIB}/autograd/misc/fixed_points.pyc
${PYSITELIB}/autograd/misc/fixed_points.pyo
${PYSITELIB}/autograd/misc/flatten.py
${PYSITELIB}/autograd/misc/flatten.pyc
${PYSITELIB}/autograd/misc/flatten.pyo
${PYSITELIB}/autograd/misc/optimizers.py
${PYSITELIB}/autograd/misc/optimizers.pyc
${PYSITELIB}/autograd/misc/optimizers.pyo
${PYSITELIB}/autograd/misc/tracers.py
${PYSITELIB}/autograd/misc/tracers.pyc
${PYSITELIB}/autograd/misc/tracers.pyo
${PYSITELIB}/autograd/numpy/__init__.py
${PYSITELIB}/autograd/numpy/__init__.pyc
${PYSITELIB}/autograd/numpy/__init__.pyo
${PYSITELIB}/autograd/numpy/fft.py
${PYSITELIB}/autograd/numpy/fft.pyc
${PYSITELIB}/autograd/numpy/fft.pyo
${PYSITELIB}/autograd/numpy/linalg.py
${PYSITELIB}/autograd/numpy/linalg.pyc
${PYSITELIB}/autograd/numpy/linalg.pyo
${PYSITELIB}/autograd/numpy/numpy_boxes.py
${PYSITELIB}/autograd/numpy/numpy_boxes.pyc
${PYSITELIB}/autograd/numpy/numpy_boxes.pyo
${PYSITELIB}/autograd/numpy/numpy_jvps.py
${PYSITELIB}/autograd/numpy/numpy_jvps.pyc
${PYSITELIB}/autograd/numpy/numpy_jvps.pyo
${PYSITELIB}/autograd/numpy/numpy_vjps.py
${PYSITELIB}/autograd/numpy/numpy_vjps.pyc
${PYSITELIB}/autograd/numpy/numpy_vjps.pyo
${PYSITELIB}/autograd/numpy/numpy_vspaces.py
${PYSITELIB}/autograd/numpy/numpy_vspaces.pyc
${PYSITELIB}/autograd/numpy/numpy_vspaces.pyo
${PYSITELIB}/autograd/numpy/numpy_wrapper.py
${PYSITELIB}/autograd/numpy/numpy_wrapper.pyc
${PYSITELIB}/autograd/numpy/numpy_wrapper.pyo
${PYSITELIB}/autograd/numpy/random.py
${PYSITELIB}/autograd/numpy/random.pyc
${PYSITELIB}/autograd/numpy/random.pyo
${PYSITELIB}/autograd/scipy/__init__.py
${PYSITELIB}/autograd/scipy/__init__.pyc
${PYSITELIB}/autograd/scipy/__init__.pyo
${PYSITELIB}/autograd/scipy/integrate.py
${PYSITELIB}/autograd/scipy/integrate.pyc
${PYSITELIB}/autograd/scipy/integrate.pyo
${PYSITELIB}/autograd/scipy/linalg.py
${PYSITELIB}/autograd/scipy/linalg.pyc
${PYSITELIB}/autograd/scipy/linalg.pyo
${PYSITELIB}/autograd/scipy/misc.py
${PYSITELIB}/autograd/scipy/misc.pyc
${PYSITELIB}/autograd/scipy/misc.pyo
${PYSITELIB}/autograd/scipy/signal.py
${PYSITELIB}/autograd/scipy/signal.pyc
${PYSITELIB}/autograd/scipy/signal.pyo
${PYSITELIB}/autograd/scipy/special.py
${PYSITELIB}/autograd/scipy/special.pyc
${PYSITELIB}/autograd/scipy/special.pyo
${PYSITELIB}/autograd/scipy/stats/__init__.py
${PYSITELIB}/autograd/scipy/stats/__init__.pyc
${PYSITELIB}/autograd/scipy/stats/__init__.pyo
${PYSITELIB}/autograd/scipy/stats/beta.py
${PYSITELIB}/autograd/scipy/stats/beta.pyc
${PYSITELIB}/autograd/scipy/stats/beta.pyo
${PYSITELIB}/autograd/scipy/stats/chi2.py
${PYSITELIB}/autograd/scipy/stats/chi2.pyc
${PYSITELIB}/autograd/scipy/stats/chi2.pyo
${PYSITELIB}/autograd/scipy/stats/dirichlet.py
${PYSITELIB}/autograd/scipy/stats/dirichlet.pyc
${PYSITELIB}/autograd/scipy/stats/dirichlet.pyo
${PYSITELIB}/autograd/scipy/stats/gamma.py
${PYSITELIB}/autograd/scipy/stats/gamma.pyc
${PYSITELIB}/autograd/scipy/stats/gamma.pyo
${PYSITELIB}/autograd/scipy/stats/multivariate_normal.py
${PYSITELIB}/autograd/scipy/stats/multivariate_normal.pyc
${PYSITELIB}/autograd/scipy/stats/multivariate_normal.pyo
${PYSITELIB}/autograd/scipy/stats/norm.py
${PYSITELIB}/autograd/scipy/stats/norm.pyc
${PYSITELIB}/autograd/scipy/stats/norm.pyo
${PYSITELIB}/autograd/scipy/stats/poisson.py
${PYSITELIB}/autograd/scipy/stats/poisson.pyc
${PYSITELIB}/autograd/scipy/stats/poisson.pyo
${PYSITELIB}/autograd/scipy/stats/t.py
${PYSITELIB}/autograd/scipy/stats/t.pyc
${PYSITELIB}/autograd/scipy/stats/t.pyo
${PYSITELIB}/autograd/test_util.py
${PYSITELIB}/autograd/test_util.pyc
${PYSITELIB}/autograd/test_util.pyo
${PYSITELIB}/autograd/tracer.py
${PYSITELIB}/autograd/tracer.pyc
${PYSITELIB}/autograd/tracer.pyo
${PYSITELIB}/autograd/util.py
${PYSITELIB}/autograd/util.pyc
${PYSITELIB}/autograd/util.pyo
${PYSITELIB}/autograd/wrap_util.py
${PYSITELIB}/autograd/wrap_util.pyc
${PYSITELIB}/autograd/wrap_util.pyo

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py-autograd/distinfo Normal file
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$NetBSD$
SHA1 (autograd-1.3.tar.gz) = 9dc88df4078c111f45731e0934cf8c0fd9a87723
RMD160 (autograd-1.3.tar.gz) = 4566e05e7ca36c37b3b804d60b7610cc8b3c04ef
SHA512 (autograd-1.3.tar.gz) = 6cffa84dc489cb4eca2e2ae2a0866cfeccc3ad1717f90b582fdb0530d8f1a4cc9cc6801db6ad1584587b3df84826cb2b6f5d08f665038f6978ab1451042a8195
Size (autograd-1.3.tar.gz) = 38257 bytes