feat(ops): Add keras.ops.numpy.rot90 operation (#20723) #20745
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Adds a new operation to rotate tensors by 90 degrees in the specified plane: - Implements rot90 operation in keras.ops.image module - Adds support for multiple rotations (k parameter) and custom axes - Matches numpy.rot90 behavior and API for consistency - Adds comprehensive test coverage including batch images support - Handles input validation for tensor dimensions and axes - Supports symbolic tensor execution The operation follows the same interface as numpy.rot90 and tf.image.rot90: rot90(array, k=1, axes=(0, 1))
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #20745 +/- ##
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- Coverage 81.95% 81.94% -0.01%
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Files 553 553
Lines 51458 51530 +72
Branches 7961 7977 +16
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+ Hits 42174 42228 +54
- Misses 7346 7361 +15
- Partials 1938 1941 +3
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Add implementations of rot90() for multiple backend frameworks: - JAX backend implementation - NumPy backend implementation - PyTorch backend implementation
fchollet
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Jan 10, 2025
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Thanks for the PR!
rot90 is a numpy op: https://numpy.org/doc/stable/reference/generated/numpy.rot90.html
So please move the code to e.g. keras/src/backend/jax/numpy.py (and so on) and export the op to keras.ops.rot90 as well as keras.ops.numpy.rot90.
Move rot90 operation to numpy.py files in backend implementations since it's a numpy op (https://numpy.org/doc/stable/reference/generated/numpy.rot90.html). Now exported as both keras.ops.rot90 and keras.ops.numpy.rot90.
Resolved the 'Invalid dtype: object' error by explicitly using to avoid naming conflicts with the custom function.
Replace tf.experimental.numpy.rot90 with core TF ops for XLA compatibility. Use convert_to_tensor for input handling.
harshaljanjani
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fchollet
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Jan 13, 2025
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Adds a new operation to rotate tensors by 90 degrees in the specified plane:
keras.ops.rot90fortf.image.rot90#20723