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Try to free memory for both cond+uncond before inference.

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comfyanonymous 2023-11-27 14:55:40 -05:00
parent be71bb5e13
commit 13fdee6abf
2 changed files with 3 additions and 3 deletions
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4
comfy/model_base.py
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@ -166,8 +166,8 @@ class BaseModel(torch.nn.Module):
def memory_required(self, input_shape): def memory_required(self, input_shape):
if comfy.model_management.xformers_enabled() or comfy.model_management.pytorch_attention_flash_attention(): if comfy.model_management.xformers_enabled() or comfy.model_management.pytorch_attention_flash_attention():
#TODO: this needs to be tweaked #TODO: this needs to be tweaked
area = max(input_shape[0], 3) * input_shape[2] * input_shape[3] area = input_shape[0] * input_shape[2] * input_shape[3]
return (area * comfy.model_management.dtype_size(self.get_dtype()) / 60) * (1024 * 1024) return (area * comfy.model_management.dtype_size(self.get_dtype()) / 50) * (1024 * 1024)
else: else:
#TODO: this formula might be too aggressive since I tweaked the sub-quad and split algorithms to use less memory. #TODO: this formula might be too aggressive since I tweaked the sub-quad and split algorithms to use less memory.
area = input_shape[0] * input_shape[2] * input_shape[3] area = input_shape[0] * input_shape[2] * input_shape[3]

2
comfy/sample.py
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@ -83,7 +83,7 @@ def prepare_sampling(model, noise_shape, positive, negative, noise_mask):
real_model = None real_model = None
models, inference_memory = get_additional_models(positive, negative, model.model_dtype()) models, inference_memory = get_additional_models(positive, negative, model.model_dtype())
comfy.model_management.load_models_gpu([model] + models, model.memory_required(noise_shape) + inference_memory) comfy.model_management.load_models_gpu([model] + models, model.memory_required([noise_shape[0] * 2] + list(noise_shape[1:])) + inference_memory)
real_model = model.model real_model = model.model
return real_model, positive, negative, noise_mask, models return real_model, positive, negative, noise_mask, models