autograd 1.8.0

Efficiently computes derivatives of NumPy code.

Stars: 7456, Watchers: 7456, Forks: 937, Open Issues: 189

The HIPS/autograd repo was created 11 years ago and the last code push was Yesterday.
The project is extremely popular with a mindblowing 7456 github stars!

How to Install autograd

You can install autograd using pip

pip install autograd

or add it to a project with poetry

poetry add autograd

Package Details

Author

None

License

The MIT License (MIT)

    Copyright (c) 2025 by the President and Fellows of Harvard University
    
    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:
    
    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.
    
    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE.</dd>

Homepage

None

PyPi:

https://pypi.org/project/autograd/

GitHub Repo:

https://github.com/HIPS/autograd

Classifiers

• Scientific/Engineering

Related Packages

Errors

A list of common autograd errors.

Code Examples

Here are some autograd code examples and snippets.

GitHub Issues

The autograd package has 189 open issues on GitHub

• Convenience: cbrt and atan2.
• feature: add implementation for 'same' mode for convolve
• [BUG] Differentiating autograd.numpy.linalg.norm gives incorrect results
• Numba support

See more issues on GitHub