torch.repeat cast short ints to int32#390
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ev-br merged 2 commits intodata-apis:mainfrom Feb 17, 2026
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Otherwise, "repeat_interleave is not implemented for Char" etc.
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Pull request overview
This PR implements a workaround for PyTorch issue #151311 where torch.repeat_interleave rejects short integer dtypes (int8 and int16). The fix adds type casting logic to convert these dtypes to int32 before calling the underlying PyTorch function. The PR also removes corresponding xfail entries from test configuration files now that the tests are expected to pass.
Changes:
- Added dtype casting workaround in the
repeatfunction to convert int8/int16 tensors to int32 - Removed test xfails for
test_repeatfrom torch and numpy test configuration files
Reviewed changes
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Show a summary per file
| File | Description |
|---|---|
| array_api_compat/torch/_aliases.py | Added dtype check and casting logic to convert int8/int16 repeats arguments to int32 before calling torch.repeat_interleave |
| torch-xfails.txt | Removed xfail entry and comment for test_repeat now that the workaround is implemented |
| numpy-xfails.txt | Removed xfail entry and comment for test_repeat (uint64 issue appears to be resolved in test suite) |
| numpy-dev-xfails.txt | Removed xfail entry and comment for test_repeat |
| numpy-1-26-xfails.txt | Removed xfail entry and comment for test_repeat |
| numpy-1-22-xfails.txt | Removed xfail entry and comment for test_repeat |
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A workaround for pytorch/pytorch#151311
A matching test update is data-apis/array-api-tests#424