28 lines
1.3 KiB
Python
28 lines
1.3 KiB
Python
import torch
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import comfy.utils
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import comfy.sample
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import latent_preview
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def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False):
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latent_image = latent["samples"]
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latent_image = comfy.sample.fix_empty_latent_channels(model, latent_image)
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if disable_noise:
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noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
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else:
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batch_inds = latent["batch_index"] if "batch_index" in latent else None
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noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)
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noise_mask = None
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if "noise_mask" in latent:
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noise_mask = latent["noise_mask"]
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callback = latent_preview.prepare_callback(model, steps)
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disable_pbar = not comfy.utils.PROGRESS_BAR_ENABLED
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samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
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denoise=denoise, disable_noise=disable_noise, start_step=start_step, last_step=last_step,
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force_full_denoise=force_full_denoise, noise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
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out = latent.copy()
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out["samples"] = samples
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return (out, )
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