einops

einops-package

Perform tensor operations using a concise yet expressive syntax inspired by the Python library of the same name. Reshape, rearrange, and combine multidimensional arrays for scientific computing, machine learning, and data analysis. Einops simplifies complex manipulations, making code more maintainable and intuitive. The original implementation is demonstrated in Rogozhnikov (2022) <a href="https://openreview.net/forum?id=oapKSVM2bcj">https://openreview.net/forum?id=oapKSVM2bcj</a>.

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Perform tensor operations using a concise yet expressive syntax inspired by the Python library of the same name.
Reshape, rearrange, and combine multidimensional arrays for scientific computing, machine learning, and data analysis.
Einops simplifies complex manipulations, making code more maintainable and intuitive.
The original implementation is demonstrated in Rogozhnikov (2022) <https://openreview.net/forum?id=oapKSVM2bcj>.

Qile Yang

Flexible, Powerful, and Readable Tensor Operations

einops-package function

Maintainer: Qile Yang <a href="/link/qile.yang%40berkeley.edu?package=einops&version=0.2.1" data-mini-rdoc="einops::qile.yang@berkeley.edu">qile.yang@berkeley.edu</a> (<a href="https://orcid.org/0009-0005-0148-2499">ORCID</a>) [copyright holder]

Author

Perform tensor operations using a concise yet expressive syntax inspired by the Python library of the same name. Reshape, rearrange, and combine multidimensional arrays for scientific computing, machine learning, and data analysis. Einops simplifies complex manipulations, making code more maintainable and intuitive. The original implementation is demonstrated in Rogozhnikov (2022) <a href='https://openreview.net/forum?id=oapKSVM2bcj'>https://openreview.net/forum?id=oapKSVM2bcj</a>.

einops: Flexible, Powerful, and Readable Tensor Operations — einops-package

Maintainer: Qile Yang <a href='mailto:qile.yang@berkeley.edu'>qile.yang@berkeley.edu</a> (<a href='https://orcid.org/0009-0005-0148-2499'>ORCID</a>) [copyright holder]

einops-package: einops: Flexible, Powerful, and Readable Tensor Operations

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