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convert : identify missing model files
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@ -132,12 +132,14 @@ class Model:
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def get_tensors(self) -> Iterator[tuple[str, Tensor]]:
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tensor_names_from_parts: set[str] = set()
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if len(self.part_names) > 1:
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index_name = "model.safetensors" if self.is_safetensors else "pytorch_model.bin"
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index_name += ".index.json"
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index_file = self.dir_model / index_name
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if index_file.is_file():
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self.tensor_names = set()
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index_name = "model.safetensors" if self.is_safetensors else "pytorch_model.bin"
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index_name += ".index.json"
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logger.info(f"gguf: loading model weight map from '{index_name}'")
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with open(self.dir_model / index_name, "r", encoding="utf-8") as f:
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with open(index_file, "r", encoding="utf-8") as f:
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index: dict[str, Any] = json.load(f)
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weight_map = index.get("weight_map")
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if weight_map is None or not isinstance(weight_map, dict):
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@ -145,6 +147,7 @@ class Model:
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self.tensor_names.update(weight_map.keys())
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else:
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self.tensor_names = tensor_names_from_parts
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weight_map = {}
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for part_name in self.part_names:
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logger.info(f"gguf: loading model part '{part_name}'")
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@ -171,9 +174,17 @@ class Model:
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data = LazyTorchTensor.from_eager(data)
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yield name, data
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# only verify tensor name presence; it doesn't matter if they are not in the right files
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if len(sym_diff := tensor_names_from_parts.symmetric_difference(self.tensor_names)) > 0:
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raise ValueError(f"Mismatch between weight map and model parts for tensor names: {sym_diff}")
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# verify tensor name presence and identify potentially missing files
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if len(tensor_names_from_parts.symmetric_difference(self.tensor_names)) > 0:
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missing = sorted(self.tensor_names.difference(tensor_names_from_parts))
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extra = sorted(tensor_names_from_parts.difference(self.tensor_names))
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missing_files = sorted(set(weight_map[n] for n in missing if n in weight_map))
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if len(extra) == 0 and len(missing_files) > 0:
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raise ValueError(f"Missing or incomplete model files: {missing_files}")
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else:
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raise ValueError("Mismatch between weight map and model parts for tensor names:\n"
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f"Missing tensors: {missing}\n"
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f"Extra tensors: {extra}")
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def format_tensor_name(self, key: gguf.MODEL_TENSOR, bid: int | None = None, suffix: str = ".weight") -> str:
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if key not in gguf.MODEL_TENSORS[self.model_arch]:
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