Support XPU DDP training and autocast for LowBitMatmul #9167
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jason-dai
reviewed
Oct 16, 2023
| if isinstance(value, torch.Tensor): | ||
| is_eligible = ( | ||
| value.is_floating_point() | ||
| and value.is_cuda |
hkvision
reviewed
Oct 18, 2023
| @@ -378,8 +385,7 @@ def forward(self, x: torch.Tensor): | |||
| result = result.view(new_shape) | |||
| if self.bias is not None: | |||
| result += self.bias | |||
|
|
|||
| return result.to(x.dtype) | |||
| return result | |||
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This line of change causes this issue: https://github.com/analytics-zoo/nano/issues/639
@yangw1234 Please take a look.
liu-shaojun
pushed a commit
that referenced
this pull request
Mar 25, 2024
* support autocast in low bit matmul * Support XPU DDP training * fix amp
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Description
1. Why the change?
Faster end to end training time using multiple intel GPUs
2. User API changes
None
3. Summary of the change
4. How to test?
Manually tested using 4 PVC 1100 on alpaca dataset