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Workaround pad problem on mps

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When using `torch.nn.functional.pad` with tensor that size is
larger than 2^16 (65526), the output tensor would be broken.

This patch moves tensor to CPU to workaround the problem.
It doesn't too much impacts in terms of speed of vea on mps.
This commit is contained in:
Yoshimasa Niwa 2024-11-05 12:46:13 +09:00
parent 78f9e7b896
commit 5ca4bbf319
1 changed files with 10 additions and 2 deletions
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12
mochi_preview/vae/model.py
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@ -94,6 +94,14 @@ class StridedSafeConv3d(torch.nn.Conv3d):
raise NotImplementedError raise NotImplementedError
def mps_safe_pad(input, pad, mode):
if input.device.type == "mps" and input.numel() >= 2 ** 16:
device = input.device
input = input.to(device="cpu")
output = F.pad(input, pad, mode=mode)
return output.to(device=device)
else:
return F.pad(input, pad, mode=mode)
class ContextParallelConv3d(SafeConv3d): class ContextParallelConv3d(SafeConv3d):
def __init__( def __init__(
@ -136,9 +144,9 @@ class ContextParallelConv3d(SafeConv3d):
# Apply padding. # Apply padding.
mode = "constant" if self.padding_mode == "zeros" else self.padding_mode mode = "constant" if self.padding_mode == "zeros" else self.padding_mode
if self.context_parallel: if self.context_parallel:
x = F.pad(x, (0, 0, 0, 0, pad_front, pad_back), mode=mode) x = mps_safe_pad(x, (0, 0, 0, 0, pad_front, pad_back), mode=mode)
else: else:
x = F.pad(x, (0, 0, 0, 0, pad_front, 0), mode=mode) x = mps_safe_pad(x, (0, 0, 0, 0, pad_front, 0), mode=mode)
return super().forward(x) return super().forward(x)