Improve error message when Pipeline step is a class instead of instance #32721
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- Add validation in _validate_steps to check for uninstantiated classes - Raise clear TypeError suggesting to use ClassName() instead of ClassName - Add test to verify the improved error message Fixes scikit-learn#32719
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Hi @hexbyte-lab, thanks a lot for your work. I think we already have PR #32565 that fixes this issue in a more generic way. This then would also close issue #32719. @AnneBeyer, can you verify? Your contribution is however very welcome @hexbyte-lab and I hope to see you somewhere else on the repo in future. |
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Reference Issues/PRs
Fixes #32719
What does this implement/fix? Explain your changes.
This PR improves the error message when a user accidentally passes an uninstantiated class to a Pipeline step instead of an instance.
Before (confusing error):
AttributeError: 'numpy.ndarray' object has no attribute '_validate_params'
After (clear error):
TypeError: All steps should be estimator instances (objects), not classes.
Step 'pca' is a class: (PCA). Did you forget parentheses?
Use PCA() instead of PCA.
Changes made:
_validate_steps()to check if a step is a class usinginspect.isclass()TypeErrorwith a helpful messagetest_pipeline_step_class_instead_of_instance()to verify the improved error messageAny other comments?
This is my first contribution to scikit-learn. I've manually reviewed all changes and run the full test suite. All pipeline tests pass (141 passed, 5 skipped). Please let me know if any changes are needed!