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spack.io : py-autograd
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.
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purl: pkg:spack/py-autograd
License: Other
Latest release: 20 days ago
First release: about 2 years ago
Dependent packages: 4
Stars: 6,221 on GitHub
Forks: 849 on GitHub
See more repository details: repos.ecosyste.ms
Last synced: 17 days ago