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Try to free enough vram for control lora inference.

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comfyanonymous
2023-08-24 17:20:54 -04:00
parent e3d0a9a490
commit 51dde87e97
4 changed files with 30 additions and 18 deletions
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10
comfy/sample.py
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@@ -51,18 +51,20 @@ def get_models_from_cond(cond, model_type):
models += [c[1][model_type]]
return models
def get_additional_models(positive, negative):
def get_additional_models(positive, negative, dtype):
"""loads additional models in positive and negative conditioning"""
control_nets = set(get_models_from_cond(positive, "control") + get_models_from_cond(negative, "control"))
inference_memory = 0
control_models = []
for m in control_nets:
control_models += m.get_models()
inference_memory += m.inference_memory_requirements(dtype)
gligen = get_models_from_cond(positive, "gligen") + get_models_from_cond(negative, "gligen")
gligen = [x[1] for x in gligen]
models = control_models + gligen
return models
return models, inference_memory
def cleanup_additional_models(models):
"""cleanup additional models that were loaded"""
@@ -77,8 +79,8 @@ def sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative
noise_mask = prepare_mask(noise_mask, noise.shape, device)
real_model = None
models = get_additional_models(positive, negative)
comfy.model_management.load_models_gpu([model] + models, comfy.model_management.batch_area_memory(noise.shape[0] * noise.shape[2] * noise.shape[3]))
models, inference_memory = get_additional_models(positive, negative, model.model_dtype())
comfy.model_management.load_models_gpu([model] + models, comfy.model_management.batch_area_memory(noise.shape[0] * noise.shape[2] * noise.shape[3]) + inference_memory)
real_model = model.model
noise = noise.to(device)