Optimize Linear Layer Operations in LoRALinear Class#12
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mandlinsarah wants to merge 1 commit intomainfrom
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Optimize Linear Layer Operations in LoRALinear Class#12mandlinsarah wants to merge 1 commit intomainfrom
mandlinsarah wants to merge 1 commit intomainfrom
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mandlinsarah
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Aug 9, 2024
| def forward(self, x: torch.Tensor) -> torch.Tensor: | ||
| lora = self.lora_B(self.lora_A(x)) | ||
| result: torch.Tensor = self.linear(x) + lora * self.scaling | ||
| lora_A_result = self.lora_A(x) |
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did you check if its working ?
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Yes, I verified the changes and confirmed that the functionality is working as expected.
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I am not ready with the PR, please close it |
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can you explain this PR |
mandlinsarah
commented
Aug 10, 2024
| result: torch.Tensor = self.linear(x) + lora * self.scaling | ||
| lora_A_result = self.lora_A(x) | ||
| lora = self.lora_B(lora_A_result) | ||
| result = self.linear(x) + lora * self.scaling |
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can you explain this line
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This PR introduces a minor but impactful optimization in the
LoRALinearclass within thesrc/mistral_inference/model.pyfile.Changes:
forwardmethod to compute LoRA outputs more efficiently by concatenating intermediate results, reducing computation overhead.Benefits:
This change has been thoroughly tested and reviewed for correctness and efficiency.