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| # Handle scales based on their dimensionality | ||
| if all(t.scale.ndim == 0 for t in tensors): | ||
| # Use the maximum scale value from all tensors for numerical stability | ||
| stacked_scale = torch.max(torch.cat([t.scale for t in tensors])) |
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would this change numerics if max_scale != original scale? I would have expected something like a rescale of the data if the scale is changed.
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