3 files changed, 35 insertions, 0 deletions

diff --git a/math/py-autograd/Makefile b/math/py-autograd/Makefile
new file mode 100644
index 000000000000..9e9f5b8da2b3
--- /dev/null
+++ b/math/py-autograd/Makefile
@@ -0,0 +1,22 @@
+# $FreeBSD$
+
+PORTNAME=	autograd
+DISTVERSION=	1.2
+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>
diff --git a/math/py-autograd/distinfo b/math/py-autograd/distinfo
new file mode 100644
index 000000000000..1cee31731d1c
--- /dev/null
+++ b/math/py-autograd/distinfo
@@ -0,0 +1,3 @@
+TIMESTAMP = 1551302910
+SHA256 (autograd-1.2.tar.gz) = a08bfa6d539b7a56e7c9f4d0881044afbef5e75f324a394c2494de963ea4a47d
+SIZE (autograd-1.2.tar.gz) = 32540
diff --git a/math/py-autograd/pkg-descr b/math/py-autograd/pkg-descr
new file mode 100644
index 000000000000..6f472f4ef6f7
--- /dev/null
+++ b/math/py-autograd/pkg-descr
@@ -0,0 +1,10 @@
+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