68 lines
3.4 KiB
Python
68 lines
3.4 KiB
Python
import torch
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import comfy.samplers
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import comfy.sample
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import comfy.utils
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import latent_preview
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"""
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PrepackKsamplerAdvanced: 完全照抄 ComfyUI 原生 KSamplerAdvanced 實現
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"""
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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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class PrepackKsamplerAdvanced:
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@classmethod
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def INPUT_TYPES(s):
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return {"required":
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{"model": ("MODEL",),
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"add_noise": (["enable", "disable"], ),
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"noise_seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True}),
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"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
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"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step":0.1, "round": 0.01}),
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"sampler_name": (comfy.samplers.KSampler.SAMPLERS, ),
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"scheduler": (comfy.samplers.KSampler.SCHEDULERS, ),
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"positive": ("CONDITIONING", ),
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"negative": ("CONDITIONING", ),
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"latent_image": ("LATENT", ),
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"start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000}),
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"end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000}),
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"return_with_leftover_noise": (["disable", "enable"], ),
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}
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}
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "sample"
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CATEGORY = "💀Prepack"
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DESCRIPTION = "Advanced KSampler that returns latent instead of decoded image, matching native behavior exactly."
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def sample(self, model, add_noise, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0):
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force_full_denoise = True
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if return_with_leftover_noise == "enable":
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force_full_denoise = False
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disable_noise = False
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if add_noise == "disable":
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disable_noise = True
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return common_ksampler(model, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_at_step, last_step=end_at_step, force_full_denoise=force_full_denoise)
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