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too many values to unpack (expected 3) #57
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comfy version: 5eb98f0 2024-06-14 06:51:14 |
Acly
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Jun 14, 2024
Works now with latest version. |
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When i try the inpainting with the example work flow, here's the error:
Error occurred when executing KSampler:
too many values to unpack (expected 3)
File "/root/ComfyUI/execution.py", line 151, in recursive_execute
File "/root/ComfyUI/custom_nodes/comfyui-inpaint-nodes/nodes.py", line 65, in calculate_weight_patched
output_data, output_ui = get_output_data(obj, input_data_all)
File "/root/ComfyUI/execution.py", line 81, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "/root/ComfyUI/execution.py", line 74, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "/root/ComfyUI/nodes.py", line 1355, in sample
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
File "/root/ComfyUI/nodes.py", line 1325, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "/root/ComfyUI/custom_nodes/ComfyUI-Advanced-ControlNet/adv_control/control_reference.py", line 47, in refcn_sample
return orig_comfy_sample(model, *args, **kwargs)
File "/root/ComfyUI/custom_nodes/ComfyUI-Advanced-ControlNet/adv_control/utils.py", line 111, in uncond_multiplier_check_cn_sample
return orig_comfy_sample(model, *args, **kwargs)
File "/root/ComfyUI/custom_nodes/ComfyUI-AnimateDiff-Evolved/animatediff/sampling.py", line 313, in motion_sample
return orig_comfy_sample(model, noise, *args, **kwargs)
File "/root/ComfyUI/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 "/root/ComfyUI/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 "/root/ComfyUI/custom_nodes/ComfyUI_smZNodes/smZNodes.py", line 1446, in KSampler_sample
return _KSampler_sample(*args, **kwargs)
File "/root/ComfyUI/comfy/samplers.py", line 794, 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 "/root/ComfyUI/custom_nodes/ComfyUI_smZNodes/smZNodes.py", line 1469, in sample
return _sample(*args, **kwargs)
File "/root/ComfyUI/comfy/samplers.py", line 696, in sample
return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "/root/ComfyUI/comfy/samplers.py", line 673, in sample
self.inner_model, self.conds, self.loaded_models = comfy.sampler_helpers.prepare_sampling(self.model_patcher, noise.shape, self.conds)
File "/root/ComfyUI/comfy/sampler_helpers.py", line 64, in prepare_sampling
comfy.model_management.load_models_gpu([model] + models, model.memory_required([noise_shape[0] * 2] + list(noise_shape[1:])) + inference_memory)
File "/root/ComfyUI/comfy/model_management.py", line 464, in load_models_gpu
cur_loaded_model = loaded_model.model_load(lowvram_model_memory, force_patch_weights=force_patch_weights)
File "/root/ComfyUI/comfy/model_management.py", line 306, in model_load
raise e
File "/root/ComfyUI/comfy/model_management.py", line 300, in model_load
self.real_model = self.model.patch_model_lowvram(device_to=patch_model_to, lowvram_model_memory=lowvram_model_memory, force_patch_weights=force_patch_weights)
File "/root/ComfyUI/comfy/model_patcher.py", line 334, in patch_model_lowvram
self.patch_weight_to_device(weight_key, device_to)
File "/root/ComfyUI/comfy/model_patcher.py", line 266, in patch_weight_to_device
alpha, v, strength_model = p
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