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Torch device (#4755)

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This commit is contained in:
Patrick von Platen
2023-08-25 11:13:32 +02:00
committed by GitHub
parent 470d51c8ed
commit cdacd8f1dd
1 changed files with 2 additions and 2 deletions
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4
src/diffusers/pipelines/pipeline_utils.py
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@@ -694,14 +694,14 @@ class DiffusionPipeline(ConfigMixin, PushToHubMixin):
pipeline_is_sequentially_offloaded = any(
module_is_sequentially_offloaded(module) for _, module in self.components.items()
)
if pipeline_is_sequentially_offloaded and torch.device(torch_device).type == "cuda":
if pipeline_is_sequentially_offloaded and torch_device and torch.device(torch_device).type == "cuda":
raise ValueError(
"It seems like you have activated sequential model offloading by calling `enable_sequential_cpu_offload`, but are now attempting to move the pipeline to GPU. This is not compatible with offloading. Please, move your pipeline `.to('cpu')` or consider removing the move altogether if you use sequential offloading."
)
# Display a warning in this case (the operation succeeds but the benefits are lost)
pipeline_is_offloaded = any(module_is_offloaded(module) for _, module in self.components.items())
if pipeline_is_offloaded and torch.device(torch_device).type == "cuda":
if pipeline_is_offloaded and torch_device and torch.device(torch_device).type == "cuda":
logger.warning(
f"It seems like you have activated model offloading by calling `enable_model_cpu_offload`, but are now manually moving the pipeline to GPU. It is strongly recommended against doing so as memory gains from offloading are likely to be lost. Offloading automatically takes care of moving the individual components {', '.join(self.components.keys())} to GPU when needed. To make sure offloading works as expected, you should consider moving the pipeline back to CPU: `pipeline.to('cpu')` or removing the move altogether if you use offloading."
)