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Documentation Fix: torch.empty_like memory preservation by morrison-turnansky · Pull Request #158050 · pytorch/pytorch · GitHub
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updated docs for torch.empty_like to reflect view and dense memory behavior

Fixes #158022

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pytorch-bot bot commented Jul 10, 2025

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/158050

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✅ You can merge normally! (1 Unrelated Failure)

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@pytorch-bot pytorch-bot bot added the release notes: python_frontend python frontend release notes category label Jul 10, 2025
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@ngimel Please let me know if the changes are sufficient.

If the input tensor is dense (i.e., non-overlapping strided),
its memory format (including strides) is retained.
Otherwise (e.g., a non-dense view like a stepped slice),
the output is converted to the dense (contiguous) format.
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contiguous is not correct, because stride permutation is preserved

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@ngimel Thank you, I have updated the PR to reflect this.

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cyyever commented Jul 14, 2025

@pytorchbot merge

@pytorch-bot pytorch-bot bot added the ciflow/trunk Trigger trunk jobs on your pull request label Jul 14, 2025
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empty_like(tensor, memory_format=torch.preserve_format) does not preserve strides for views

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