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Resolution bucketing and Trainer implementation refactoring (#11117)

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Kohaku-Blueleaf
2025-12-18 11:15:27 +08:00
committed by GitHub
parent ba6080bbab
commit 86dbb89fc9
4 changed files with 738 additions and 232 deletions
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9
comfy/sampler_helpers.py
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@@ -122,20 +122,21 @@ def estimate_memory(model, noise_shape, conds):
minimum_memory_required = model.model.memory_required([noise_shape[0]] + list(noise_shape[1:]), cond_shapes=cond_shapes_min)
return memory_required, minimum_memory_required
def prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None):
def prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None, skip_load_model=False):
executor = comfy.patcher_extension.WrapperExecutor.new_executor(
_prepare_sampling,
comfy.patcher_extension.get_all_wrappers(comfy.patcher_extension.WrappersMP.PREPARE_SAMPLING, model_options, is_model_options=True)
)
return executor.execute(model, noise_shape, conds, model_options=model_options)
return executor.execute(model, noise_shape, conds, model_options=model_options, skip_load_model=skip_load_model)
def _prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None):
def _prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None, skip_load_model=False):
real_model: BaseModel = None
models, inference_memory = get_additional_models(conds, model.model_dtype())
models += get_additional_models_from_model_options(model_options)
models += model.get_nested_additional_models() # TODO: does this require inference_memory update?
memory_required, minimum_memory_required = estimate_memory(model, noise_shape, conds)
comfy.model_management.load_models_gpu([model] + models, memory_required=memory_required + inference_memory, minimum_memory_required=minimum_memory_required + inference_memory)
models_list = [model] if not skip_load_model else []
comfy.model_management.load_models_gpu(models_list + models, memory_required=memory_required + inference_memory, minimum_memory_required=minimum_memory_required + inference_memory)
real_model = model.model
return real_model, conds, models