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):
latent_image = latent["samples"]
latent_image = comfy.sample.fix_empty_latent_channels(model, latent_image)
if disable_noise:
noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
else:
batch_inds = latent["batch_index"] if "batch_index" in latent else None
noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)
noise_mask = None
if "noise_mask" in latent:
noise_mask = latent["noise_mask"]
callback = latent_preview.prepare_callback(model, steps)
disable_pbar = not comfy.utils.PROGRESS_BAR_ENABLED
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
denoise=denoise, disable_noise=disable_noise, start_step=start_step, last_step=last_step,
force_full_denoise=force_full_denoise, noise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
out = latent.copy()
out["samples"] = samples
return (out, )
class KSampler:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": ("MODEL", {"tooltip": "用于对输入潜空间数据进行去噪的模型。"}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True, "tooltip": "用于创建噪声的随机种子。"}),
"steps": ("INT", {"default": 20, "min": 1, "max": 10000, "tooltip": "去噪过程中使用的步数。"}),
"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step":0.1, "round": 0.01, "tooltip": "无分类器引导比例，用于平衡创造性与对提示词的遵循程度。值越高，生成的图像与提示词越匹配，但过高会负面影响质量。"}),
"sampler_name": (comfy.samplers.KSampler.SAMPLERS, {"tooltip": "采样时使用的算法，会影响生成结果的质量、速度和风格。"}),
"scheduler": (comfy.samplers.KSampler.SCHEDULERS, {"tooltip": "调度器控制如何逐步移除噪声以形成图像。"}),
"positive": ("CONDITIONING", {"tooltip": "描述你希望在图像中包含的属性的条件。"}),
"negative": ("CONDITIONING", {"tooltip": "描述你希望从图像中排除的属性的条件。"}),
"latent_image": ("LATENT", {"tooltip": "要去噪的潜空间图像。"}),
"denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "应用的去噪程度，较低的值将保持初始图像的结构，允许进行图生图采样。"}),
}
}
RETURN_TYPES = ("LATENT",)
OUTPUT_TOOLTIPS = ("去噪后的潜空间数据。",)
FUNCTION = "sample"
CATEGORY = "sampling"
DESCRIPTION = "使用提供的模型、正向和负向条件对潜空间图像进行去噪。"
def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0):
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
