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@ -15,7 +15,7 @@ TORCH_COMPILE_KWARGS = "torch_compile_kwargs"
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def apply_torch_compile_factory(compiled_module_dict: dict[str, Callable]) -> Callable:
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'''
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Create a wrapper that will refer to the compiled_diffusion_model
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Create a wrapper that will refer to the compiled_diffusion_model.
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'''
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def apply_torch_compile_wrapper(executor: WrapperExecutor, *args, **kwargs):
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try:
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@ -37,7 +37,7 @@ def set_torch_compile_wrapper(model: ModelPatcher, backend: str, options: Option
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Perform torch.compile that will be applied at sample time for either the whole model or specific params of the BaseModel instance.
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When keys is None, it will default to using ["diffusion_model"], compiling the whole diffusion_model.
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When a list of keys is provided, it will perform torch.compile on only the selected params.
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When a list of keys is provided, it will perform torch.compile on only the selected modules.
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'''
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torch.compile()
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# clear out any other torch.compile wrappers
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@ -64,5 +64,7 @@ def set_torch_compile_wrapper(model: ModelPatcher, backend: str, options: Option
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wrapper_func = apply_torch_compile_factory(
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compiled_module_dict=compiled_modules,
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)
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# store wrapper to run on BaseModel's apply_model function
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model.add_wrapper_with_key(WrappersMP.APPLY_MODEL, COMPILE_KEY, wrapper_func)
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# keep compile kwargs for reference
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model.model_options[TORCH_COMPILE_KWARGS] = compile_kwargs
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