Error occurred when executing KSampler: 0

Question

Error occurred when executing KSampler:

0

File "D:\comfyui\ComfyUI-aki-v1.3\execution.py", line 151, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "D:\comfyui\ComfyUI-aki-v1.3\execution.py", line 81, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "D:\comfyui\ComfyUI-aki-v1.3\execution.py", line 74, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "D:\comfyui\ComfyUI-aki-v1.3\nodes.py", line 1372, in sample
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
File "D:\comfyui\ComfyUI-aki-v1.3\nodes.py", line 1342, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 9, in informative_sample
return original_sample(*args, **kwargs) # This code helps interpret error messages that occur within exceptions but does not have any impact on other operations.
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 248, in motion_sample
return orig_comfy_sample(model, noise, *args, **kwargs)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\sample.py", line 43, in sample
samples = sampler.sample(noise, positive, negative, 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)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 801, in sample
return sample(self.model, noise, positive, negative, cfg, self.device, sampler, sigmas, self.model_options, latent_image=latent_image, denoise_mask=denoise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 703, in sample
return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 690, in sample
output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 669, in inner_sample
samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 574, in sample
samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **self.extra_options)
File "D:\comfyui\ComfyUI-aki-v1.3\python\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\k_diffusion\sampling.py", line 600, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 297, in call
out = self.inner_model(x, sigma, model_options=model_options, seed=seed)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 656, in call
return self.predict_noise(*args, **kwargs)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 659, in predict_noise
return sampling_function(self.inner_model, x, timestep, self.conds.get("negative", None), self.conds.get("positive", None), self.cfg, model_options=model_options, seed=seed)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 277, in sampling_function
out = calc_cond_batch(model, conds, x, timestep, model_options)
File "D:\comfyui\ComfyUI-aki-v1.3\comfy\samplers.py", line 200, in calc_cond_batch
c['control'] = control.get_control(input_x, timestep_, c, len(cond_or_uncond))
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 468, in get_control_inject
return self.get_control_advanced(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 32, in get_control_advanced
return self.sliding_get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 37, in sliding_get_control
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 468, in get_control_inject
return self.get_control_advanced(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 32, in get_control_advanced
return self.sliding_get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 37, in sliding_get_control
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 468, in get_control_inject
return self.get_control_advanced(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 32, in get_control_advanced
return self.sliding_get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 37, in sliding_get_control
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 468, in get_control_inject
return self.get_control_advanced(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 32, in get_control_advanced
return self.sliding_get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 37, in sliding_get_control
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 468, in get_control_inject
return self.get_control_advanced(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 32, in get_control_advanced
return self.sliding_get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 37, in sliding_get_control
control_prev = self.previous_controlnet.get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 468, in get_control_inject
return self.get_control_advanced(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 32, in get_control_advanced
return self.sliding_get_control(x_noisy, t, cond, batched_number)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\control.py", line 79, in sliding_get_control
return self.control_merge(None, control, control_prev, output_dtype)
File "D:\comfyui\ComfyUI-aki-v1.3\custom_nodes\ComfyUI-Advanced-ControlNet\adv_control\utils.py", line 575, in control_merge_inject
x = control_output[i]

Answer 1

引自免费微信小程序：皆我百晓生

在执行 KSampler 时出现了错误：0。这个错误表明可能遇到了一个与 KSampler 运行相关的特定问题。

为了更好地理解并解决这个问题，我们可以采取以下几个步骤：

步骤 1: 检查输入数据

确保您的输入数据（包括 input_data_all）是正确的格式，并且包含所有必要的信息。例如，如果您正在尝试使用一个生成器，确认它已准备好接收来自其他模块的数据流。

步骤 2: 检查网络结构

检查 KSampler 中定义的网络结构是否正确。确保您使用的模型、噪声以及任何额外参数都适用于当前的 KSampler 实例。

步骤 3: 确认输出数据

检查 get_output_data() 函数中的逻辑，确保返回了正确的输出数据。如果出现问题，请查看函数的具体实现，看是否有任何错误或未处理的情况。

步骤 4: 检查异常处理

确保您的程序包含了适当的异常处理机制。当遇到 KSampler 错误时，应该有适当的错误处理逻辑来捕获这些错误，并提供可读的反馈给用户。

步骤 5: 分析错误日志

查看 KSampler 的错误日志文件，这通常会为您提供有关错误发生的原因和进一步分析所需的信息。

步骤 6: 调试代码

如果以上方法都无法解决问题，您可以考虑重构或调试部分关键的部分，比如代码路径的选择，或者具体到某些函数或块的逻辑。在进行这些操作之前，确保备份好原始代码以防万一。

结论

通过遵循上述步骤，你应该能更准确地定位和解决 KSampler 的错误。同时，在进行调试过程中，保持清晰的文档记录可以帮助追踪问题的发生过程。如果你对如何解决特定问题感到困惑，可以提供更多细节以便于针对性的帮助。