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Fix DLPack stream logic. #150217
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Fix DLPack stream logic. #150217
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/150217
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 476b1ea with merge base 85bfaf8 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Mar 28, 2025
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Apr 22, 2025
This PR fixes the logic for dealing with CUDA and ROCm streams whenever we are trying to create a DLPack capsule from a tensor. In summary, this PR: - Uses the legacy default stream if `tensor.__dlpack__(stream=None)` is called for a CUDA tensor. - Errors if `tensor.__dlpack__(stream=2)` is called for a CUDA tensor: PyTorch doesn't support the per-thread default stream. - Errors if `tensor.__dlpack__(stream=stream)`, where `stream` is 1 or 2, is called for a CUDA tensor using ROCm. For more details, see [the documentation][1]. [1]: https://data-apis.org/array-api/latest/API_specification/generated/array_api.array.__dlpack__.html ghstack-source-id: cc0e31c Pull Request resolved: pytorch/pytorch#150217
msaroufim
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May 14, 2025
albanD
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May 14, 2025
| @@ -1717,23 +1717,37 @@ def __dlpack__(self, stream=None, max_version=None): | |||
| # Stream pointers in CUDA/ROCm are uniquely numbered and can | |||
| # be retrieved from their integer value. | |||
| raise TypeError("stream must be ``int`` or ``none``") | |||
| elif stream is not None and stream != -1: | |||
| elif stream != -1: | |||
| if self.device.type == "cuda": | |||
| # NB: This logic handles the special case values for default | |||
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No update to dlpack.py ? :D
| if is_cuda and stream == 2: | ||
| raise BufferError("per-thread default stream is not supported.") | ||
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| assert is_cuda or (is_rocm and stream not in (1, 2)), ( |
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Shouldn't this be a BufferError like above instead of AssertionError?
| # Only synchronize on different streams | ||
| sync_stream = torch.cuda.current_stream() | ||
| if stream != sync_stream: | ||
| current_stream = torch.cuda.current_stream() |
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Do we care if self.device.index != torch.cuda.current_device() ?
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Stack from ghstack (oldest at bottom):
BufferErrorfor DLPack buffer-related errors. #150691This PR fixes the logic for dealing with CUDA and ROCm streams whenever
we are trying to create a DLPack capsule from a tensor.
In summary, this PR:
tensor.__dlpack__(stream=None)iscalled for a CUDA tensor.
tensor.__dlpack__(stream=2)is called for a CUDA tensor:PyTorch doesn't support the per-thread default stream.
tensor.__dlpack__(stream=stream), wherestreamis 1 or2, is called for a CUDA tensor using ROCm.
For more details, see the documentation.