[Bugfix] Fix torch dynamo fixes caused by replace_parameters (#8748)
This commit is contained in:
parent
2529d09b5a
commit
72fc97a0f1
@ -21,13 +21,17 @@ def replace_parameter(mod: torch.nn.Module, name: str,
|
||||
new: Union[torch.Tensor, torch.nn.Parameter]) -> None:
|
||||
|
||||
old = getattr(mod, name)
|
||||
if old.dtype == new.dtype and \
|
||||
if type(old) is type(new) and old.dtype == new.dtype and \
|
||||
old.untyped_storage().nbytes() == new.untyped_storage().nbytes():
|
||||
# If we can just update in-place to avoid re-registering
|
||||
# can be faster if the underlying storage is the same
|
||||
update_tensor_inplace(old, new)
|
||||
else:
|
||||
# Fallback re-register parameter
|
||||
# Fallback re-register parameter, convert to Parameter if necessary
|
||||
# this not only ensures we don't register a tensor as a parameter, but
|
||||
# also ensures that all parameter subclasses get re-registered as
|
||||
# parameters for `torch.compile` compatibility
|
||||
if not isinstance(new, torch.nn.Parameter):
|
||||
new = torch.nn.Parameter(new)
|
||||
mod.register_parameter(name, torch.nn.Parameter(new))
|
||||
new = torch.nn.Parameter(new, requires_grad=False)
|
||||
mod.register_parameter(name,
|
||||
torch.nn.Parameter(new, requires_grad=False))
|
||||
|
||||
Loading…
Reference in New Issue
Block a user