test rowwise fp32 #2431
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test rowwise fp32 #2431
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2431
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vkuzo
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Jun 24, 2025
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| if convert_dtypes_for_rowwise_scaled_mm and is_rowwise_scaling: | ||
| output_dtype = torch.bfloat16 | ||
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instead of adding a flag, TBH I think we can just enable this on-by-default, like this:
file issue in PyTorch core to add float32 output to scaled_mm
output_dtype_to_use = output_dtype
if is_rowwise_scaling:
# work around torch._scaled_mm not having float32 output type
# TODO(issue number): remove this once torch._scaled_mm supports float32 output
output_dtype_to_use = torch.bfloat16
output = torch._scaled_mm(..., output_dtype_to_use, ...)
...
if is_rowwise_scaling and output_dtype == torch.float32:
# work around torch._scaled_mm not having float32 output type
# TODO(issue number): remove this once torch._scaled_mm supports float32 output
output = output.to(orig_dtype)There was a problem hiding this comment.
makes sense, I'll change to enable by default and file an issue.
vkuzo
reviewed
Jun 24, 2025
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Updated to enable the workaround by default. Included fp16 and fp32 dtypes in the existing test cases. The additional changes are formatting things generated by linter. The pytorch issue: pytorch/pytorch#156771 |
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@y-sq , maybe export again? |
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Jul 3, 2025
…ytorch#2431) Summary: Running rowwise scaling on fp32 tensors got the error, P1794222725 ``` RuntimeError: Only bf16 high precision output types are supported for row-wise scaling. ``` This pr adds an option to explicitly use bfloat16 as the output of rowwise_scaled, and cast it back to the original precision. It can be enabled by setting ``` config = dataclasses.replace(config, convert_dtypes_for_rowwise_scaled_mm=True) ``` Differential Revision: D73552660
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This pull request was exported from Phabricator. Differential Revision: D73552660 |
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@vkuzo sorry there were some un-synced files between github and fbcode so the previous export all failed. The pr should be updated now. |
y-sq
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Jul 3, 2025
…ytorch#2431) Summary: Running rowwise scaling on fp32 tensors got the error, P1794222725 ``` RuntimeError: Only bf16 high precision output types are supported for row-wise scaling. ``` This pr adds an option to explicitly use bfloat16 as the output of rowwise_scaled, and cast it back to the original precision. It can be enabled by setting ``` config = dataclasses.replace(config, convert_dtypes_for_rowwise_scaled_mm=True) ``` Differential Revision: D73552660
|
This pull request was exported from Phabricator. Differential Revision: D73552660 |
y-sq
added a commit
to y-sq/ao
that referenced
this pull request
Jul 3, 2025
…ytorch#2431) Summary: Running rowwise scaling on fp32 tensors got the error, P1794222725 ``` RuntimeError: Only bf16 high precision output types are supported for row-wise scaling. ``` This pr adds an option to explicitly use bfloat16 as the output of rowwise_scaled, and cast it back to the original precision. It can be enabled by setting ``` config = dataclasses.replace(config, convert_dtypes_for_rowwise_scaled_mm=True) ``` Differential Revision: D73552660
|
This pull request was exported from Phabricator. Differential Revision: D73552660 |
y-sq
added a commit
to y-sq/ao
that referenced
this pull request
Jul 3, 2025
…ytorch#2431) Summary: Running rowwise scaling on fp32 tensors got the error, P1794222725 ``` RuntimeError: Only bf16 high precision output types are supported for row-wise scaling. ``` This pr adds an option to explicitly use bfloat16 as the output of rowwise_scaled, and cast it back to the original precision. It can be enabled by setting ``` config = dataclasses.replace(config, convert_dtypes_for_rowwise_scaled_mm=True) ``` Differential Revision: D73552660
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y-sq
added a commit
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that referenced
this pull request
Jul 3, 2025
…ytorch#2431) Summary: Running rowwise scaling on fp32 tensors got the error, P1794222725 ``` RuntimeError: Only bf16 high precision output types are supported for row-wise scaling. ``` This pr adds an option to explicitly use bfloat16 as the output of rowwise_scaled, and cast it back to the original precision. It can be enabled by setting ``` config = dataclasses.replace(config, convert_dtypes_for_rowwise_scaled_mm=True) ``` Differential Revision: D73552660
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This pull request was exported from Phabricator. Differential Revision: D73552660 |
…ytorch#2431) Summary: Pull Request resolved: pytorch#2431 Running rowwise scaling on fp32 tensors got the error, P1794222725 ``` RuntimeError: Only bf16 high precision output types are supported for row-wise scaling. ``` This pr adds an option to explicitly use bfloat16 as the output of rowwise_scaled, and cast it back to the original precision. It can be enabled by setting ``` config = dataclasses.replace(config, convert_dtypes_for_rowwise_scaled_mm=True) ``` Differential Revision: D73552660
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This pull request was exported from Phabricator. Differential Revision: D73552660 |
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Summary:
Running rowwise scaling on fp32 tensors got the error, P1794222725
This pr adds an option to explicitly use bfloat16 as the output of rowwise_scaled, and cast it back to the original precision.
It can be enabled by setting
Differential Revision: D73552660