feat: corrcoef instance method for pytorch frontend and test function added #27032
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Thank you for this PR, here is the CI results: This pull request does not result in any additional test failures. Congratulations! |
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hmahmood24
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Hey @sharjeelnawaz8182, thanks a lot for the PR. However, we need to fix the tests first in order to merge the PR. Please run your tests locally using pytest first to see if they're passing or not. I tested them locally and they were failing for me for all the backends.
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@hmahmood24 |
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Hey @sharjeelnawaz8182, thanks for the PR. Requesting minor changes. Let me know if the tests still fail after this. Also, it would be helpful if you can share the logs of the test failures here so we can take a look at fixing them. Thanks!
| min_value=1, | ||
| shared_dtype=True, |
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We don't need to keep these arguments. You can remove these
| init_tree="torch.tensor", | ||
| method_name="corrcoef", | ||
| dtype_and_x=helpers.dtype_and_values( | ||
| available_dtypes=helpers.get_dtypes("float"), |
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We prefer using "valid" instead of "float" here. Of course you'll then have to update the @with_unsupported_dtypes decorator to correctly flag all the invalid dtypes or inversely use the @with_supported_dtypes to just define the valid dtypes
| init_all_as_kwargs_np={ | ||
| "data": x[0], | ||
| }, | ||
| method_input_dtypes=[], |
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We need to pass input_dtype over here as well
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Closing this PR since it has been stale for more than 2 weeks now. |
PR Description
Related Issue
Closes #26843
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