Repository: huggingface/transformers
Pull request: Improve performance of `load_state_dict`

# What does this PR do?

We avoid executing `get_slice` unless `map_location == "meta"` to improve the performance when loading a model with a large number of tensors.

Even though we avoid the dtype check in Python, the dtype will be checked at https://github.com/huggingface/safetensors/blob/7d5af853631628137a79341ddc5611d18a17f3fe/bindings/python/src/lib.rs#L1186

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Fixes #37887


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Changed files:
filename: src/transformers/modeling_utils.py
patch: @@ -507,13 +507,14 @@ def load_state_dict(
                 )
             state_dict = {}
             for k in f.keys():
-                k_dtype = f.get_slice(k).get_dtype()
-                if k_dtype in str_to_torch_dtype:
-                    dtype = str_to_torch_dtype[k_dtype]
-                else:
-                    raise ValueError(f"Cannot load safetensors of unknown dtype {k_dtype}")
                 if map_location == "meta":
-                    state_dict[k] = torch.empty(size=f.get_slice(k).get_shape(), dtype=dtype, device="meta")
+                    _slice = f.get_slice(k)
+                    k_dtype = _slice.get_dtype()
+                    if k_dtype in str_to_torch_dtype:
+                        dtype = str_to_torch_dtype[k_dtype]
+                    else:
+                        raise ValueError(f"Cannot load safetensors of unknown dtype {k_dtype}")
+                    state_dict[k] = torch.empty(size=_slice.get_shape(), dtype=dtype, device="meta")
                 else:
                     state_dict[k] = f.get_tensor(k)
             return state_dict