Efficiently computes derivatives of numpy code
2.47 MB
built 2026-10-29 13:19:08 GMT
Description
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.
Dependencies
20 totalRequires17
- (python3dist(tomli) if python3-devel < 3.11)
- pyproject-rpm-macros
- python3-devel
- python3-devel
- python3dist(hatchling)
- python3dist(numpy) < 3~~
- python3dist(packaging)
- python3dist(pip) >= 19
- python3dist(pytest)
- python3dist(pytest-xdist)
- python3dist(scipy)
- python3dist(tomcli)
- rpmlib(CompressedFileNames) <= 3.0.4-1
- rpmlib(DynamicBuildRequires) <= 4.15.0-1
- rpmlib(FileDigests) <= 4.6.0-1
- rpmlib(RichDependencies) <= 4.12.0-1
- rpmlib(TildeInVersions) <= 4.10.0-1
Provides3
- python-autograd-doc = 1.8.0-6.fc45
- python3-autograd = 1.8.0-6.fc45
- python3-autograd+scipy = 1.8.0-6.fc45
ObsoletesNo Obsoletes
ConflictsNo Conflicts
RecommendsNo Recommends
SuggestsNo Suggests
SupplementsNo Supplements
EnhancesNo Enhances
Files
2Name ![]() |
Size |
|---|---|
| autograd-1.8.0.tar.gz | 2.44 MB |
| python-autograd.spec | 6.81 KB |
Files 1–2 of 2
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