[OpenVINO backend] Support for numpy.eigh #22363
[OpenVINO backend] Support for numpy.eigh #22363andersendsa wants to merge 3 commits intokeras-team:masterfrom
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Summary of ChangesHello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request introduces support for the Highlights
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Code Review
This pull request adds support for numpy.eigh to the OpenVINO backend by providing a NumPy-based implementation for eager tensors. The approach is sound, and the error handling for symbolic tensors is appropriate. My review includes a suggestion to ensure the return type is consistent with other backend operations by wrapping the output in OpenVINOKerasTensor instances, which is crucial for maintaining the backend's abstraction layer.
| return ( | ||
| ov_opset.constant(w).output(0), | ||
| ov_opset.constant(v).output(0), | ||
| ) |
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For consistency with other operations in the OpenVINO backend (e.g., inv, norm), this function should return a tuple of OpenVINOKerasTensor instances instead of raw ov.Output objects. This ensures that the results remain within the Keras backend tensor abstraction, allowing subsequent Keras operations to work correctly on them.
| return ( | |
| ov_opset.constant(w).output(0), | |
| ov_opset.constant(v).output(0), | |
| ) | |
| return ( | |
| OpenVINOKerasTensor(ov_opset.constant(w).output(0)), | |
| OpenVINOKerasTensor(ov_opset.constant(v).output(0)), | |
| ) |
References
- According to the Keras API design guidelines, objects that perform similar functions should have consistent APIs. Other linear algebra functions in this backend return
OpenVINOKerasTensorinstances, andeighshould follow this pattern for consistency. (link)
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Please address the gemini reviews given here.
Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #22363 +/- ##
==========================================
+ Coverage 82.95% 83.01% +0.05%
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Files 595 596 +1
Lines 66040 66702 +662
Branches 10305 10383 +78
==========================================
+ Hits 54785 55373 +588
- Misses 8639 8692 +53
- Partials 2616 2637 +21
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hi @hertschuh this pr passes all the tests and is ready for review |
| return ( | ||
| ov_opset.constant(w).output(0), | ||
| ov_opset.constant(v).output(0), | ||
| ) |
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Please address the gemini reviews given here.
| @@ -348,7 +348,6 @@ LayerTest::test_stateless_call | |||
| LinalgOpsCorrectnessTest::test_cholesky | |||
| LinalgOpsCorrectnessTest::test_det | |||
| LinalgOpsCorrectnessTest::test_eig | |||
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Could we implement eig as well in this PR?
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sure will do it
keras/src/backend/openvino/linalg.py
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| a = convert_to_tensor(a) | ||
| try: | ||
| a_np = convert_to_numpy(a) |
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We do the implementations using OpenVINO opsets specifically
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will change it asap
andersendsa
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hi @hertschuh i have done the changes and the pr passes all the tests and is ready for review |
| a_evaluated = OpenVINOKerasTensor(a_ov) | ||
| try: | ||
| a_np = convert_to_numpy(a_evaluated) | ||
| except Exception as e: | ||
| raise ValueError( | ||
| "eigh is only supported for static eager tensors " | ||
| "in the openvino backend. Received a dynamic or symbolic tensor." | ||
| ) from e | ||
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I don't understand why this would be needed. Also, we don't want numpy on the execution path, otherwise something that could run on GPU would run on CPU with NumPy instead of OV.
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Details :
Implement numpy.eigh operation for the OpenVINO backend.
Closes issue : openvinotoolkit/openvino#34520