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Open Source Computer Vision Library
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Add Support for Einsum Layer #24037 ### This PR adding support for [Einsum Layer](https://pytorch.org/docs/stable/generated/torch.einsum.html) (in progress). This PR is currently not to be merged but only reviewed. Test cases are located in [#1090](https://github.com/opencv/opencv_extra/pull/1090)RP in OpenCV extra **DONE**: - [x] 2-5D GMM support added - [x] Matrix transpose support added - [x] Reduction type comupte 'ij->j' - [x] 2nd shape computation - during forward **Next PRs**: - [ ] Broadcasting reduction "...ii ->...i" - [ ] Add lazy shape deduction. "...ij, ...jk->...ik" - [ ] Add implicit output computation support. "bij,bjk ->" (output subscripts should be "bik") - [ ] Add support for CUDA backend - [ ] BatchWiseMultiply optimize **Later in 5.x version (requires support for 1D matrices)**: - [ ] Add 1D vector multiplication support - [ ] Inter product "i, i" (problems with 1D shapes) ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake |
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OpenCV: Open Source Computer Vision Library
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