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skip_load_model -> force_full_load (#11390)

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This should be a bit more clear and less prone to potential breakage if the
logic of the load models changes a bit.
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comfyanonymous 2025-12-17 20:29:32 -08:00 committed by GitHub
parent 86dbb89fc9
commit bf7dc63bd6
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2 changed files with 5 additions and 6 deletions
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9
comfy/sampler_helpers.py
View File

@ -122,21 +122,20 @@ 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) 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 return memory_required, minimum_memory_required
def prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None, skip_load_model=False): def prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None, force_full_load=False):
executor = comfy.patcher_extension.WrapperExecutor.new_executor( executor = comfy.patcher_extension.WrapperExecutor.new_executor(
_prepare_sampling, _prepare_sampling,
comfy.patcher_extension.get_all_wrappers(comfy.patcher_extension.WrappersMP.PREPARE_SAMPLING, model_options, is_model_options=True) 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, skip_load_model=skip_load_model) return executor.execute(model, noise_shape, conds, model_options=model_options, force_full_load=force_full_load)
def _prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None, skip_load_model=False): def _prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None, force_full_load=False):
real_model: BaseModel = None real_model: BaseModel = None
models, inference_memory = get_additional_models(conds, model.model_dtype()) models, inference_memory = get_additional_models(conds, model.model_dtype())
models += get_additional_models_from_model_options(model_options) models += get_additional_models_from_model_options(model_options)
models += model.get_nested_additional_models() # TODO: does this require inference_memory update? models += model.get_nested_additional_models() # TODO: does this require inference_memory update?
memory_required, minimum_memory_required = estimate_memory(model, noise_shape, conds) memory_required, minimum_memory_required = estimate_memory(model, noise_shape, conds)
models_list = [model] if not skip_load_model else [] comfy.model_management.load_models_gpu([model] + models, memory_required=memory_required + inference_memory, minimum_memory_required=minimum_memory_required + inference_memory, force_full_load=force_full_load)
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 real_model = model.model
return real_model, conds, models return real_model, conds, models

2
comfy_extras/nodes_train.py
View File

@ -44,7 +44,7 @@ class TrainGuider(comfy_extras.nodes_custom_sampler.Guider_Basic):
noise.shape, noise.shape,
self.conds, self.conds,
self.model_options, self.model_options,
skip_load_model=True, # skip load model as we manage it in TrainLoraNode.execute() force_full_load=True, # mirror behavior in TrainLoraNode.execute() to keep model loaded
) )
) )
device = self.model_patcher.load_device device = self.model_patcher.load_device