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48 changes: 33 additions & 15 deletions src/diffusers/models/modeling_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -99,21 +99,39 @@ def find_tensor_attributes(module: torch.nn.Module) -> List[Tuple[str, Tensor]]:


def get_parameter_dtype(parameter: torch.nn.Module) -> torch.dtype:
try:
return next(parameter.parameters()).dtype
except StopIteration:
try:
return next(parameter.buffers()).dtype
except StopIteration:
# For torch.nn.DataParallel compatibility in PyTorch 1.5

def find_tensor_attributes(module: torch.nn.Module) -> List[Tuple[str, Tensor]]:
tuples = [(k, v) for k, v in module.__dict__.items() if torch.is_tensor(v)]
return tuples

gen = parameter._named_members(get_members_fn=find_tensor_attributes)
first_tuple = next(gen)
return first_tuple[1].dtype
"""
Returns the first found floating dtype in parameters if there is one, otherwise returns the last dtype it found.
"""
last_dtype = None
for param in parameter.parameters():
last_dtype = param.dtype
if param.is_floating_point():
return param.dtype

for buffer in parameter.buffers():
last_dtype = buffer.dtype
if buffer.is_floating_point():
return buffer.dtype

if last_dtype is not None:
# if no floating dtype was found return whatever the first dtype is
return last_dtype

# For nn.DataParallel compatibility in PyTorch > 1.5
def find_tensor_attributes(module: nn.Module) -> List[Tuple[str, Tensor]]:
tuples = [(k, v) for k, v in module.__dict__.items() if torch.is_tensor(v)]
return tuples

gen = parameter._named_members(get_members_fn=find_tensor_attributes)
last_tuple = None
for tuple in gen:
last_tuple = tuple
if tuple[1].is_floating_point():
return tuple[1].dtype

if last_tuple is not None:
# fallback to the last dtype
return last_tuple[1].dtype


class ModelMixin(torch.nn.Module, PushToHubMixin):
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