[pkgsrc/trunk]: pkgsrc py-autograd: remove

To: pkgsrc-changes-hg%NetBSD.org@localhost
Subject: [pkgsrc/trunk]: pkgsrc py-autograd: remove
From: wiz <wiz%pkgsrc.org@localhost>
Date: Thu, 17 Feb 2022 12:11:28 +0000
details:   https://anonhg.NetBSD.org/pkgsrc/rev/a53c11a40cc6
branches:  trunk
changeset: 374258:a53c11a40cc6
user:      wiz <wiz%pkgsrc.org@localhost>
date:      Thu Feb 17 10:54:56 2022 +0000

description:
py-autograd: remove

This project is not being developed any longer upstream.
No users in pkgsrc.

There is a successor project, JAX, in case anyone's interested.

diffstat:

 doc/CHANGES-2022          |    3 +-
 math/Makefile             |    3 +-
 math/py-autograd/DESCR    |    8 ---
 math/py-autograd/Makefile |   20 -------
 math/py-autograd/PLIST    |  120 ----------------------------------------------
 math/py-autograd/distinfo |    5 -
 6 files changed, 3 insertions(+), 156 deletions(-)

diffs (200 lines):

diff -r 0653a7ccffca -r a53c11a40cc6 doc/CHANGES-2022
--- a/doc/CHANGES-2022  Thu Feb 17 10:48:39 2022 +0000
+++ b/doc/CHANGES-2022  Thu Feb 17 10:54:56 2022 +0000
@@ -1,4 +1,4 @@
-$NetBSD: CHANGES-2022,v 1.1037 2022/02/17 10:48:39 wiz Exp $
+$NetBSD: CHANGES-2022,v 1.1038 2022/02/17 10:54:56 wiz Exp $
 
 Changes to the packages collection and infrastructure in 2022:
 
@@ -1362,3 +1362,4 @@
        Updated devel/py-tox to 3.24.5 [adam 2022-02-17]
        Updated biology/py-biopython to 1.79 [wiz 2022-02-17]
        Updated cad/py-gds to 1.6.11 [wiz 2022-02-17]
+       Removed math/py-autograd [wiz 2022-02-17]
diff -r 0653a7ccffca -r a53c11a40cc6 math/Makefile
--- a/math/Makefile     Thu Feb 17 10:48:39 2022 +0000
+++ b/math/Makefile     Thu Feb 17 10:54:56 2022 +0000
@@ -1,4 +1,4 @@
-# $NetBSD: Makefile,v 1.535 2022/02/17 09:16:36 wiz Exp $
+# $NetBSD: Makefile,v 1.536 2022/02/17 10:54:56 wiz Exp $
 
 COMMENT=       Mathematics
 
@@ -371,7 +371,6 @@
 SUBDIR+=       py-astroML
 SUBDIR+=       py-astropy
 SUBDIR+=       py-astropy-helpers
-SUBDIR+=       py-autograd
 SUBDIR+=       py-bottleneck
 SUBDIR+=       py-cdecimal
 SUBDIR+=       py-claripy
diff -r 0653a7ccffca -r a53c11a40cc6 math/py-autograd/DESCR
--- a/math/py-autograd/DESCR    Thu Feb 17 10:48:39 2022 +0000
+++ /dev/null   Thu Jan 01 00:00:00 1970 +0000
@@ -1,8 +0,0 @@
-Autograd can automatically differentiate native Python and Numpy
-code. It can handle a large subset of Python's features, including
-loops, ifs, recursion and closures, and it can even take derivatives
-of derivatives of derivatives. It uses reverse-mode differentiation
-(a.k.a. backpropagation), which means it can efficiently take
-gradients of scalar-valued functions with respect to array-valued
-arguments. The main intended application is gradient-based
-optimization.
diff -r 0653a7ccffca -r a53c11a40cc6 math/py-autograd/Makefile
--- a/math/py-autograd/Makefile Thu Feb 17 10:48:39 2022 +0000
+++ /dev/null   Thu Jan 01 00:00:00 1970 +0000
@@ -1,20 +0,0 @@
-# $NetBSD: Makefile,v 1.7 2022/01/04 20:54:13 wiz Exp $
-
-DISTNAME=      autograd-1.3
-PKGNAME=       ${PYPKGPREFIX}-${DISTNAME}
-PKGREVISION=   2
-CATEGORIES=    math python
-MASTER_SITES=  ${MASTER_SITE_PYPI:=a/autograd/}
-
-MAINTAINER=    pkgsrc-users%NetBSD.org@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
-
-.include "../../lang/python/egg.mk"
-.include "../../math/py-numpy/buildlink3.mk"
-.include "../../mk/bsd.pkg.mk"
diff -r 0653a7ccffca -r a53c11a40cc6 math/py-autograd/PLIST
--- a/math/py-autograd/PLIST    Thu Feb 17 10:48:39 2022 +0000
+++ /dev/null   Thu Jan 01 00:00:00 1970 +0000
@@ -1,120 +0,0 @@
-@comment $NetBSD: PLIST,v 1.3 2020/04/27 19:03:26 adam Exp $
-${PYSITELIB}/${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 -r 0653a7ccffca -r a53c11a40cc6 math/py-autograd/distinfo
--- a/math/py-autograd/distinfo Thu Feb 17 10:48:39 2022 +0000
+++ /dev/null   Thu Jan 01 00:00:00 1970 +0000
@@ -1,5 +0,0 @@
-$NetBSD: distinfo,v 1.5 2021/10/26 10:56:00 nia Exp $
-
-BLAKE2s (autograd-1.3.tar.gz) = 71c89d7e38aab29d04cf183b63d198335ba4f64a03f83ad9de8e985c49137856
-SHA512 (autograd-1.3.tar.gz) = 6cffa84dc489cb4eca2e2ae2a0866cfeccc3ad1717f90b582fdb0530d8f1a4cc9cc6801db6ad1584587b3df84826cb2b6f5d08f665038f6978ab1451042a8195
-Size (autograd-1.3.tar.gz) = 38257 bytes
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