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lora : raise error if lm_head is ignored #9103

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Merged
merged 3 commits into from
Sep 12, 2024
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lora : raise error if lm_head is ignored #9103

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lora : raise error if lm_head is ignored
ngxson Aug 20, 2024
f3a3033
fix style
ngxson Aug 20, 2024
fa0c2bd
clarify comment
ngxson Aug 28, 2024
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8 changes: 7 additions & 1 deletion convert_lora_to_gguf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -363,7 +363,13 @@ def get_tensors(self) -> Iterator[tuple[str, Tensor]]:
yield (name, cast(torch.Tensor, LoraTorchTensor(tensor.A, tensor.B)))

def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
dest = super().modify_tensors(data_torch, name, bid)
dest = list(super().modify_tensors(data_torch, name, bid))
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Is it needed to recast to a list super().modify_tensors(data_torch, name, bid)?

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Without this, pyright will not pass: https://github.com/ggerganov/llama.cpp/actions/runs/10472198558/job/29001100132

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@compilade compilade Aug 20, 2024 •
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Yes, this is needed because it can also be a Generator (when modify_tensors uses yield).

# some archs may have the same tensor for lm_head and output (tie word embeddings)
# in this case, adapters targeting lm_head will fail when using llama-export-lora
# therefore, we ignore them for now
# see: https://github.com/ggerganov/llama.cpp/issues/9065
if name == "lm_head.weight" and len(dest) == 0:
raise ValueError("lm_head is present in adapter, but is ignored in base model")
for dest_name, dest_data in dest:
assert isinstance(dest_data, LoraTorchTensor)
lora_a, lora_b = dest_data.get_lora_A_B()
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