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

[K.I.A.Derouiche <kamel.derouiche%gmail.com@localhost>]

Module Name:	pkgsrc-wip
Committed By:	K.I.A.Derouiche <kamel.derouiche%gmail.com@localhost>
Pushed By:	jihbed
Date:		Mon Oct 26 14:56:03 2020 +0100
Changeset:	15d8ed2f0d6991ac03c563d36e7f8253d51fe659

Added Files:
	py-autograd/DESCR
	py-autograd/Makefile
	py-autograd/PLIST
	py-autograd/distinfo

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

To see a diff of this commit:
https://wip.pkgsrc.org/cgi-bin/gitweb.cgi?p=pkgsrc-wip.git;a=commitdiff;h=15d8ed2f0d6991ac03c563d36e7f8253d51fe659

Please note that diffs are not public domain; they are subject to the
copyright notices on the relevant files.

diffstat:
 py-autograd/DESCR    |  10 +++++
 py-autograd/Makefile |  20 +++++++++
 py-autograd/PLIST    | 120 +++++++++++++++++++++++++++++++++++++++++++++++++++
 py-autograd/distinfo |   6 +++
 4 files changed, 156 insertions(+)

diffs:
diff --git a/py-autograd/DESCR b/py-autograd/DESCR
new file mode 100644
index 0000000000..80e526c34a
--- /dev/null
+++ b/py-autograd/DESCR
@@ -0,0 +1,10 @@
+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
diff --git a/py-autograd/Makefile b/py-autograd/Makefile
new file mode 100644
index 0000000000..886f02115c
--- /dev/null
+++ b/py-autograd/Makefile
@@ -0,0 +1,20 @@
+# $NetBSD$
+
+DISTNAME=	autograd-1.3
+PKGNAME=	${PYPKGPREFIX}-${DISTNAME}
+CATEGORIES=	math python
+MASTER_SITES=	${MASTER_SITE_PYPI:=a/autograd/}
+
+MAINTAINER=	jihbed.research%gmail.com@localhost
+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"
diff --git a/py-autograd/PLIST b/py-autograd/PLIST
new file mode 100644
index 0000000000..bec6fef33d
--- /dev/null
+++ b/py-autograd/PLIST
@@ -0,0 +1,120 @@
+@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
diff --git a/py-autograd/distinfo b/py-autograd/distinfo
new file mode 100644
index 0000000000..97593dbb53
--- /dev/null
+++ b/py-autograd/distinfo
@@ -0,0 +1,6 @@
+$NetBSD$
+
+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