Make clip_grad_norm_ follow the input's dtype #7205
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JackCaoG
reviewed
Jun 5, 2024
| norm_type = float(norm_type) | ||
| if len(parameters) == 0: | ||
| return torch.tensor(0.) | ||
| dtype = parameters[0].grad.dtype |
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oh man.... I totally forgot we have this patch.
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Not sure if it actually is needed though... haha
JackCaoG
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Jun 5, 2024
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Thanks, Jack! |
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Summary:
The correct clipped value uses fp32 regardless of the input dtype. Let's make it follow the input dtype.
Test Plan:
python test/test_operations.py -v -k test_clip_grad_norm_