Make ops consistent and test ops consistency. #21334
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #21334 +/- ##
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- Coverage 82.65% 82.65% -0.01%
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Files 565 565
Lines 54823 54833 +10
Branches 8514 8515 +1
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+ Hits 45315 45323 +8
- Misses 7414 7417 +3
+ Partials 2094 2093 -1
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Added tests to verify that: - All the parameters in the op class `call` (dynamic / tensor parameters) and `__init__` (static / non-tensor parameters) match the parameters in the op function - the names should match - default values should match - the order should be consistent, usually with the static parameters all at the end - Ops are exported in `keras.ops` - Ops are exported in their module, e.g. `keras.ops.numpy` - Ops are implemented in every backend - The backend implementation has the same signature as the op wrapper (same parameters in the same order with the same default values) Note about default values: only the default values declared in the common op function are used by users, which is why those values were not changed and were applied to the class and backend implementations. - The default values for the class `__init__` are not used because the op function passes all parameters when constructing the class. - The default values for the backend implementation are not used, because the common op function passes all parameters when calling the backend implementation. The exception to this is when an op implementation calls another op directly. Therefore: - The defaults on the backend implementations are just a reminder for the implementer - The defaults on the class `__init__` are mostly a reminder, but can also serve as a forward compatibility mechanism when deserializing a model after a parameter is added. Fixed all inconsistencies, mostly inconsistent default values.
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fchollet
approved these changes
Jun 2, 2025
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Added tests to verify that:
call(dynamic / tensor parameters) and__init__(static / non-tensor parameters) match the parameters in the op functionkeras.opskeras.ops.numpyNote about default values: only the default values declared in the common op 8000 function are used by users, which is why those values were not changed and were applied to the class and backend implementations.
__init__are not used because the op function passes all parameters when constructing the class.Therefore:
__init__are mostly a reminder, but can also serve as a forward compatibility mechanism when deserializing a model after a parameter is added.Fixed all inconsistencies, mostly inconsistent default values.