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Refactor sampling related code.

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comfyanonymous
2023-09-27 16:45:22 -04:00
parent fff491b032
commit bf3fc2f1b7
3 changed files with 33 additions and 26 deletions
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24
comfy/sample.py
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@@ -70,25 +70,29 @@ def cleanup_additional_models(models):
if hasattr(m, 'cleanup'):
m.cleanup()
def sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False, noise_mask=None, sigmas=None, callback=None, disable_pbar=False, seed=None):
device = comfy.model_management.get_torch_device()
def prepare_sampling(model, noise_shape, positive, negative, noise_mask):
device = model.load_device
if noise_mask is not None:
noise_mask = prepare_mask(noise_mask, noise.shape, device)
noise_mask = prepare_mask(noise_mask, noise_shape, device)
real_model = None
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)
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)
latent_image = latent_image.to(device)
positive_copy = broadcast_cond(positive, noise.shape[0], device)
negative_copy = broadcast_cond(negative, noise.shape[0], device)
positive_copy = broadcast_cond(positive, noise_shape[0], device)
negative_copy = broadcast_cond(negative, noise_shape[0], device)
return real_model, positive_copy, negative_copy, noise_mask, models
sampler = comfy.samplers.KSampler(real_model, steps=steps, device=device, sampler=sampler_name, scheduler=scheduler, denoise=denoise, model_options=model.model_options)
def sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False, noise_mask=None, sigmas=None, callback=None, disable_pbar=False, seed=None):
real_model, positive_copy, negative_copy, noise_mask, models = prepare_sampling(model, noise.shape, positive, negative, noise_mask)
noise = noise.to(model.load_device)
latent_image = latent_image.to(model.load_device)
sampler = comfy.samplers.KSampler(real_model, steps=steps, device=model.load_device, sampler=sampler_name, scheduler=scheduler, denoise=denoise, model_options=model.model_options)
samples = sampler.sample(noise, positive_copy, negative_copy, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed)
samples = samples.cpu()