New package: py-autograd (#19425)

* py-autograd

* add missing dependencies

var/spack/repos/builtin/packages/py-autograd/package.py

@@ -0,0 +1,27 @@
+# Copyright 2013-2020 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)
+
+
+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"
+    url      = "https://pypi.io/packages/source/a/autograd/autograd-1.3.tar.gz"
+
+    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'))