[DLPACK] Optimize toDLPack Conversion Speed #162111
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/162111
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Previously in pytorchgh-83069, the toDLPack converter introduces a normalization step that changes the strides to 1 when shape[i] == 1 This step, however, calls as_strided during toDLPack, and can slow down the toDLPack about 3x. This causes PyTorch's DLPack conversion to be around 0.6 us overhead per call from the < 0.2us. This PR updates the logic by adding a need_normalize_strides check, to first confirm if the strides normalization is necessary. In most common cases, when the tensor is continguous, such normalization is not necessary. We confirmed that having this additional step would recover the speed of toDLPack to below 0.2us and can help significantly speedup eager mode integration of DLPack with PyTorch. If we detect that there is normalization needs, the older path will be invoked.
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This was referenced Sep 11, 2025
markc-614
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Sep 17, 2025
Previously in pytorchgh-83069, the toDLPack converter introduces a normalization step that changes the strides to 1 when shape[i] == 1 This step, however, calls as_strided during toDLPack, and can slow down the toDLPack about 3x. This causes PyTorch's DLPack conversion to be around 0.6 us overhead per call from the < 0.2us. This PR updates the logic by adding a need_normalize_strides check, to first confirm if the strides normalization is necessary. In most common cases, when the tensor is continguous, such normalization is not necessary. We confirmed that having this additional step would recover the speed of toDLPack to below 0.2us and can help significantly speedup eager mode integration of DLPack with PyTorch. If we detect that there is normalization needs, the older path will be invoked. Fixes pytorch#162113 Pull Request resolved: pytorch#162111 Approved by: https://github.com/msaroufim
mansiag05
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Previously in pytorchgh-83069, the toDLPack converter introduces a normalization step that changes the strides to 1 when shape[i] == 1 This step, however, calls as_strided during toDLPack, and can slow down the toDLPack about 3x. This causes PyTorch's DLPack conversion to be around 0.6 us overhead per call from the < 0.2us. This PR updates the logic by adding a need_normalize_strides check, to first confirm if the strides normalization is necessary. In most common cases, when the tensor is continguous, such normalization is not necessary. We confirmed that having this additional step would recover the speed of toDLPack to below 0.2us and can help significantly speedup eager mode integration of DLPack with PyTorch. If we detect that there is normalization needs, the older path will be invoked. Fixes pytorch#162113 Pull Request resolved: pytorch#162111 Approved by: https://github.com/msaroufim
dsashidh
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Sep 26, 2025
Previously in pytorchgh-83069, the toDLPack converter introduces a normalization step that changes the strides to 1 when shape[i] == 1 This step, however, calls as_strided during toDLPack, and can slow down the toDLPack about 3x. This causes PyTorch's DLPack conversion to be around 0.6 us overhead per call from the < 0.2us. This PR updates the logic by adding a need_normalize_strides check, to first confirm if the strides normalization is necessary. In most common cases, when the tensor is continguous, such normalization is not necessary. We confirmed that having this additional step would recover the speed of toDLPack to below 0.2us and can help significantly speedup eager mode integration of DLPack with PyTorch. If we detect that there is normalization needs, the older path will be invoked. Fixes pytorch#162113 Pull Request resolved: pytorch#162111 Approved by: https://github.com/msaroufim
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Previously in gh-83069, the toDLPack converter introduces a normalization step that changes the strides to 1 when shape[i] == 1
This step, however, calls as_strided during toDLPack, and can slow down the toDLPack about 3x. This causes PyTorch's DLPack conversion to be around 0.6 us overhead per call from the < 0.2us.
This PR updates the logic by adding a need_normalize_strides check, to first confirm if the strides normalization is necessary. In most common cases, when the tensor is continguous, such normalization is not necessary.
We confirmed that having this additional step would recover the speed of toDLPack to below 0.2us and can help significantly speedup eager mode integration of DLPack with PyTorch.
If we detect that there is normalization needs, the older path will be invoked.
Fixes #162113