[sharktank] Use reshape instead of view #681
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Fixes `RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.` by using `reshape`. which occurs when running `tests/layers/mmdit_test.py` with Python 3.11.10 and `torch==2.5.1+cpu`.
ScottTodd
requested review from
sogartar and
archana-ramalingam
and removed request for
ScottTodd
sogartar
reviewed
Dec 12, 2024
| @@ -41,7 +41,7 @@ def attention(q, k, v, pe): | |||
| q=q, k=k, v=v, a=None, is_causal=True, scale=None | |||
| ) | |||
| x = ops.permute(x, (0, 2, 1, 3)) | |||
| x = x.view(x.shape[0], x.shape[1], -1) | |||
| x = x.reshape(x.shape[0], x.shape[1], -1) | |||
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I played a bit with this example. What is going on is that the scaled dot product attention is returning an non-contiguous tensor.
In torch 2.5.1
x.shape = torch.Size([3, 24, 1536, 128]), x.stride() = (4718592, 196608, 128, 1)
While in torch 2.3.0 it produces
x.shape = torch.Size([3, 24, 1536, 128]), x.stride() = (4718592, 128, 3072, 1)
I guess by accident in 2.3.0 the stride was such that it allowed for the view.
I think on a lot of operations we implicitly assume that they will produce contiguous tensors. It seems that the doc does not state this, but I would bet that even if this was the intention on a lot of ops, it would not be stated.
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Thanks for reviewing and testing!
sogartar
approved these changes
Dec 12, 2024
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Fixes
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.by usingreshapewhich occurs when runningtests/layers/mmdit_test.pywith Python 3.11.10 andtorch==2.5.1+cpu.