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Honor model dtype in load_checkpoint #920

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Merged
sgugger merged 2 commits into from
Dec 20, 2022
Merged

Honor model dtype in load_checkpoint #920

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5fe8d02
Honor model dtype in
sgugger Dec 13, 2022
3311ce6
Move dtype logic to set_module_tensor_to_device
sgugger Dec 19, 2022
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21 changes: 17 additions & 4 deletions src/accelerate/utils/modeling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,11 @@ def dtype_byte_size(dtype: torch.dtype):


def set_module_tensor_to_device(
module: nn.Module, tensor_name: str, device: Union[int, str, torch.device], value: Optional[torch.Tensor] = None
module: nn.Module,
tensor_name: str,
device: Union[int, str, torch.device],
value: Optional[torch.Tensor] = None,
dtype: Optional[Union[str, torch.dtype]] = None,
):
"""
A helper function to set a given tensor (parameter of buffer) of a module on a specific device (note that doing
Expand All @@ -97,6 +101,9 @@ def set_module_tensor_to_device(
device (`int`, `str` or `torch.device`): The device on which to set the tensor.
value (`torch.Tensor`, *optional*): The value of the tensor (useful when going from the meta device to any
other device).
dtype (`torch.dtype`, *optional*):
If passed along the value of the parameter will be cast to this `dtype`. Otherwise, `value` will be cast to
the dtype of the existing parameter in the model.
"""
# Recurse if needed
if "." in tensor_name:
Expand All @@ -116,6 +123,13 @@ def set_module_tensor_to_device(
if old_value.device == torch.device("meta") and device not in ["meta", torch.device("meta")] and value is None:
raise ValueError(f"{tensor_name} is on the meta device, we need a `value` to put in on {device}.")

if value is not None:
if dtype is None:
# For compatibility with PyTorch load_state_dict which converts state dict dtype to existing dtype in model
value = value.to(old_value.dtype)
elif str(value.dtype).startswith(("torch.uint", "torch.int", "torch.bool")):
value = value.to(dtype)

with torch.no_grad():
if value is None:
new_value = old_value.to(device)
Expand Down Expand Up @@ -680,8 +694,7 @@ def load_checkpoint_in_model(
else:
for param_name, param in checkpoint.items():
module_name = param_name
if dtype is not None and not str(param.dtype).startswith(("torch.uint", "torch.int", "torch.bool")):
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@sgugger sgugger Dec 19, 2022

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This is moved to set_module_tensor_to_device.

param = param.to(dtype)

while len(module_name) > 0 and module_name not in device_map:
module_name = ".".join(module_name.split(".")[:-1])
if module_name == "" and "" not in device_map:
Expand All @@ -696,7 +709,7 @@ def load_checkpoint_in_model(
set_module_tensor_to_device(model, param_name, "meta")
offload_weight(param, param_name, state_dict_folder, index=state_dict_index)
else:
set_module_tensor_to_device(model, param_name, param_device, value=param)
set_module_tensor_to_device(model, param_name, param_device, value=param, dtype=dtype)

# Force Python to clean up.
del checkpoint
Expand Down