enable cpu offloading of new pipelines on XPU & use device agnostic empty to make pipelines work on XPU #11671
+126
−80
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Signed-off-by: YAO Matrix <[email protected]>
Signed-off-by: YAO Matrix <[email protected]>
yao-matrix
commented
Jun 6, 2025
| @@ -193,7 +193,7 @@ def __init__( | |||
| def enable_xformers_memory_efficient_attention(self, attention_op: Optional[Callable] = None): | |||
| self.decoder_pipe.enable_xformers_memory_efficient_attention(attention_op) | |||
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| def enable_sequential_cpu_offload(self, gpu_id: Optional[int] = None, device: Union[torch.device, str] = "cuda"): | |||
| def enable_sequential_cpu_offload(self, gpu_id: Optional[int] = None, device: Union[torch.device, str] = None): | |||
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per discussion in this PR #11288, we change the default to None, so cpu_offloading can work on other accelerators like XPU w/ application code change.
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with such changes, cases like tests/pipelines/wuerstchen/test_wuerstchen_combined.py::WuerstchenCombinedPipelineFastTests::test_cpu_offload_forward_pass_twice, tests/pipelines/kandinsky2_2/test_kandinsky_combined.py::KandinskyV22PipelineImg2ImgCombinedFastTests::test_cpu_offload_forward_pass_twice can pass on XPU
Signed-off-by: YAO Matrix <[email protected]>
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@a-r-r-o-w @DN6 , pls help review, thx very much. |
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