Fix fp8 kv replicate #349
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Fix fp8 kv replicate #349
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Signed-off-by: quic-morteza <[email protected]>
…ic models Signed-off-by: quic-morteza <[email protected]>
ochougul
requested changes
Apr 9, 2025
| @@ -107,7 +107,7 @@ class FP8DeQuantLinearToLinearTransform(ModuleMutatorTransform): | |||
| @classmethod | |||
| def mutate(cls, original_module, parent_module): | |||
| # -- de-quantizing the weights -- | |||
| dequant_weights = original_module.weight.to(torch.float32) * original_module.weight_scale | |||
| dequant_weights = original_module.weight.to(torch.float32) # * original_module.weight_scale | |||
| @@ -121,7 +121,7 @@ def for_fp8_layer(cls, in_features, out_features, activation_quantization_strate | |||
| def forward(self, x): | |||
| # Only inference supported | |||
| with torch.no_grad(): | |||
| dequantized_weights = self.weight.to(torch.float32) * self.weight_scale | |||
| dequantized_weights = self.weight.to(torch.float32) # * self.weight_scale | |||
Comment on lines
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| if layer.bias is not None: | ||
| layer.bias.data = torch.repeat_interleave(layer.bias.data.view(orig_kv_heads, head_dim), repeat, 0).view( | ||
| new_kv_heads * head_dim | ||
| ) |
|
I investigated my code changes further and noticed that the output results are inconsistent with the ground truth. Therefore, my code changes are invalid, and I will close the PR I submitted. |
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This fix is needed is tested successfully for the replicate_kv_heads.py script to operate on FP8-Dynamic models.