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[modular] error early in enable_auto_cpu_offload #12578

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[modular] error early in enable_auto_cpu_offload #12578

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26 changes: 19 additions & 7 deletions src/diffusers/modular_pipelines/components_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,7 +160,10 @@ def __call__(self, hooks, model_id, model, execution_device):
if len(hooks) == 0:
return []

current_module_size = model.get_memory_footprint()
try:
current_module_size = model.get_memory_footprint()
except AttributeError:
raise AttributeError(f"Do not know how to compute memory footprint of `{model.__class__.__name__}.")

device_type = execution_device.type
device_module = getattr(torch, device_type, torch.cuda)
Expand Down Expand Up @@ -703,19 +706,28 @@ def enable_auto_cpu_offload(self, device: Union[str, int, torch.device] = None,
if not is_accelerate_available():
raise ImportError("Make sure to install accelerate to use auto_cpu_offload")

# TODO: add a warning if mem_get_info isn't available on `device`.
if device is None:
device = get_device()
if not isinstance(device, torch.device):
device = torch.device(device)

device_type = device.type
device_module = getattr(torch, device_type, torch.cuda)
if not hasattr(device_module, "mem_get_info"):
raise NotImplementedError(
f"`enable_auto_cpu_offload() relies on the `mem_get_info()` method. It's not implemented for {str(device.type)}."
)

if device.index is None:
device = torch.device(f"{device.type}:{0}")

for name, component in self.components.items():
if isinstance(component, torch.nn.Module) and hasattr(component, "_hf_hook"):
remove_hook_from_module(component, recurse=True)

self.disable_auto_cpu_offload()
offload_strategy = AutoOffloadStrategy(memory_reserve_margin=memory_reserve_margin)
if device is None:
device = get_device()
device = torch.device(device)
if device.index is None:
device = torch.device(f"{device.type}:{0}")

all_hooks = []
for name, component in self.components.items():
if isinstance(component, torch.nn.Module):
Expand Down
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