[NestedTensor] Call contiguous in linear backward #94317
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drisspg
added
module: nestedtensor
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/94317
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| nt = torch.nested.as_nested_tensor([a, b, c]) | ||
| # This implicitly tests to_padded_tensor grads | ||
| d = torch.functional.F.linear(nt, weight, bias) | ||
| d = d.transpose(-1, -2).contiguous() |
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why are we calling contiguous here :b
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can't call to_padded_tensor without it being contiguous but the upward_grad for linear will have been transposed and then that will exercise the new code
mikaylagawarecki
approved these changes
Feb 7, 2023
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@pytorchbot merge |
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Fixes #94303
If in upward grad for linear_backward was discontiguous we would throw a torch check. This updates the implementation to instead call contiguous and changes the check to an internal assert.
cc @cpuhrsch @jbschlosser @bhosmer @mikaylagawarecki