[js/webgpu] Simplify the Resize shader when noScale is true #18321
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satyajandhyala
approved these changes
Nov 7, 2023
guschmue
approved these changes
Nov 7, 2023
kleiti
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to kleiti/onnxruntime
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Mar 22, 2024
…t#18321) ### Description For Resize, when `noScale` is true, the shader can become very simple, which is not related with `attributes.mode` anymore. So we should remove those parts of shader code for simplification. This PR can also fix microsoft#18311 since the `noScale` are all true in that model. However, microsoft#18311 also exposes that the Resize implementation for `linear` mode has bug. It seems that the currently implementation always treat the input as either 2d or 4d tensor, however, the actual input is 3d tensor, that's why the shader compilation is failed. We may need to fix it in a separate PR.
siweic0
pushed a commit
to siweic0/onnxruntime-web
that referenced
this pull request
May 9, 2024
…t#18321) ### Description For Resize, when `noScale` is true, the shader can become very simple, which is not related with `attributes.mode` anymore. So we should remove those parts of shader code for simplification. This PR can also fix microsoft#18311 since the `noScale` are all true in that model. However, microsoft#18311 also exposes that the Resize implementation for `linear` mode has bug. It seems that the currently implementation always treat the input as either 2d or 4d tensor, however, the actual input is 3d tensor, that's why the shader compilation is failed. We may need to fix it in a separate PR.
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Description
For Resize, when
noScaleis true, the shader can become very simple, which is not related withattributes.modeanymore. So we should remove those parts of shader code for simplification.This PR can also fix #18311 since the
noScaleare all true in that model.However, #18311 also exposes that the Resize implementation for
linearmode has bug. It seems that the currently implementation always treat the input as either 2d or 4d tensor, however, the actual input is 3d tensor, that's why the shader compilation is failed. We may need to fix it in a separate PR.