py36-autograd - Efficiently computes derivatives of numpy code

Property Value
Distribution FreeBSD 11
Repository FreeBSD Ports Latest amd64
Package filename py36-autograd-1.2_1.txz
Package name py36-autograd
Package version 1.2
Package release 1
Package architecture amd64
Package type txz
Category math python
License MIT
Download size 80.98 KB
Installed size 514.35 KB
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.


Package Version Architecture Repository
py36-autograd-1.2_1.txz 1.2 i386 FreeBSD Ports Latest
py36-autograd-1.2_1.txz 1.2 i386 FreeBSD Ports Quarterly
py36-autograd-1.2_1.txz 1.2 amd64 FreeBSD Ports Quarterly
py36-autograd - - -


Name Value
py36-future = 0.17.1_1
py36-numpy = 1.16.4_1,1
py36-setuptools = 41.0.1
python36 = 3.6.9


Type URL
Binary Package py36-autograd-1.2_1.txz
Source Package math/py-autograd

Install Howto

Install py36-autograd txz package:

# pkg install py36-autograd

See Also

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