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handle weight sharing with init_on_device #2737

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9 changes: 8 additions & 1 deletion src/accelerate/big_modeling.py
Original file line number Diff line number Diff line change
Expand Up @@ -128,7 +128,14 @@ def register_empty_parameter(module, name, param):
param_cls = type(module._parameters[name])
kwargs = module._parameters[name].__dict__
kwargs["requires_grad"] = param.requires_grad
module._parameters[name] = param_cls(module._parameters[name].to(device), **kwargs)
# When we have a case of tensor2 = tensor1, it would call the set_attr
# of param, which in turn would call the register_parameter API.
# In this case, the new param is already on meta-device, since it was moved
# previously when it was initialized. Hence, when resetting, you can
# directly assign that tensor instead of re-init. If you re-init you would
# lose the relationship.
module._parameters[name] = param if param.device == device else \
param_cls(module._parameters[name].to(device), **kwargs)

def register_empty_buffer(module, name, buffer, persistent=True):
old_register_buffer(module, name, buffer, persistent=persistent)
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