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freebsd-ports/math/py-autograd/Makefile

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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 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. WWW: https://github.com/HIPS/autograd
2019-02-27 23:11:15 +01:00
# $FreeBSD$
PORTNAME= autograd
math/py-autograd: update to 1.3
2019-11-02 17:18:40 +01:00
DISTVERSION= 1.3
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 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. WWW: https://github.com/HIPS/autograd
2019-02-27 23:11:15 +01:00
CATEGORIES= math python
MASTER_SITES= CHEESESHOP
PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX}
MAINTAINER= rm@FreeBSD.org
COMMENT= Efficiently computes derivatives of numpy code
LICENSE= MIT
RUN_DEPENDS= ${PYNUMPY} \
${PYTHON_PKGNAMEPREFIX}future>=0.15.2:devel/py-future@${PY_FLAVOR}
USES= python
USE_PYTHON= autoplist distutils
NO_ARCH= yes
.include <bsd.port.mk>
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