Fix sample validation for complex types #1973
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Pull request overview
This PR fixes type validation for complex generic types in the experimental dataset module. The validation logic was incorrectly handling generic type annotations, causing validation errors for fields with list-type specifications.
Key Changes:
- Fixed
_validate_attribute_typeto use the origin type for generic type validation - Added test coverage for samples with list-type fields
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.
| File | Description |
|---|---|
| src/datumaro/experimental/dataset.py | Updated type validation to handle generic types by checking the origin type |
| tests/unit/experimental/test_sample.py | Added test for creating samples with list-type fields to verify the validation fix |
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leoll2
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Fix looks good to me, only one comment
Signed-off-by: Jort Bergfeld <[email protected]>
Signed-off-by: Jort Bergfeld <[email protected]>
Signed-off-by: Jort Bergfeld <[email protected]>
Signed-off-by: Jort Bergfeld <[email protected]>
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AlbertvanHouten
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This pull request fixes a problem with type validation in the experimental dataset and sample modules. When we use the is_list boolean of score_field, a complex ndarray type is generated that includes an Any type, which is not accepted by isinstance. To circumvent problems with complex types, whenever isintance fails with a type error, we only validate against the origin type (ndarray instead of ndarray[float32], for example)
Type validation improvements
_validate_attribute_typemethod insrc/datumaro/experimental/dataset.pyto correctly handle type validation for generic types by usingoriginwhen available, improving support for complex type annotations.Test enhancements
test_sample_with_is_list, intests/unit/experimental/test_sample.pyto verify that samples with list-type fields (usingis_list=Trueinscore_field) are created without validation errors.Resolves #1971