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# Copyright 2013-2024 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack.package import *
class PyAutograd(PythonPackage):
"""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. For more information, check out the tutorial and the
examples directory."""
homepage = "https://github.com/HIPS/autograd"
pypi = "autograd/autograd-1.3.tar.gz"
license("MIT")
version("1.3", sha256="a15d147577e10de037de3740ca93bfa3b5a7cdfbc34cfb9105429c3580a33ec4")
depends_on("py-setuptools", type="build")
depends_on("py-future@0.15.2:", type=("build", "run"))
depends_on("py-numpy@1.12:", type=("build", "run"))
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