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python3-autograd Subpackage of python-autograd

Efficiently computes derivatives of numpy code

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.

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Release Stable Testing
Fedora Rawhide 1.5-2.fc39 -
Fedora 38 1.5-1.fc38 1.5-1.fc38
Fedora 37 1.5-1.fc37 -
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You can contact the maintainers of this package via email at python-autograd dash maintainers at fedoraproject dot org.

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