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[loading] Free up tensors faster inside ConversionOps #46110

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Merged
Cyrilvallez merged 1 commit into from
May 20, 2026
Merged

[loading] Free up tensors faster inside ConversionOps #46110

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18 changes: 13 additions & 5 deletions src/transformers/core_model_loading.py
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Original file line number Diff line number Diff line change
Expand Up @@ -161,7 +161,10 @@ def convert(
for source_pattern in source_patterns:
if source_pattern not in input_dict:
continue
tensors = input_dict[source_pattern]
# Immediately free the input_dict, so that we do not keep many copies simultaneously - otherwise we have to
# wait for this function to return to be able to clean-up, which will not get garbage collected as fast as if
# everything is freed right now
tensors = input_dict.pop(source_pattern)
if isinstance(tensors, list):
all_tensors.extend(tensors)
else:
Expand Down Expand Up @@ -197,15 +200,20 @@ def convert(
target_patterns: list[str],
**kwargs,
) -> dict[str, torch.Tensor]:
input_size = len(input_dict)
merged: dict[str, torch.Tensor] = {}
for source_pattern, tensors in input_dict.items():
target_pattern = self.get_target_pattern(input_dict, source_pattern, target_patterns)
for source_pattern in list(input_dict.keys()):
# Immediately free the input dict, so that we do not keep many copies simultaneously - otherwise we have to
# wait for this function to return to be able to clean-up, and if the size of the input_dict is larger than 1
# (such as the MoEs' gate_proj/up_proj merging), we are wasting quite some memory
tensors = input_dict.pop(source_pattern)
target_pattern = self.get_target_pattern(input_size, source_pattern, target_patterns)
merged[target_pattern] = torch.stack(tensors, dim=self.dim)
return merged

def get_target_pattern(self, input_dict: dict, source_pattern: str, target_patterns: list[str]) -> str:
def get_target_pattern(self, input_size: int, source_pattern: str, target_patterns: list[str]) -> str:
# Here it's a single operation, so we use the target
if len(input_dict) == 1:
if input_size == 1:
if len(target_patterns) == 1:
return target_patterns[0]
else:
Expand Down
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