Node 2.0 ksampler(efficient) NaN errors
Opened this issue · 3 comments
Old workflows can't load. NaN appears on node configs
Change the values, also change the values for vae_decode, denoise, scheduler, sampler name, seed, cfg, and steps. I'm getting a different error after this is I select randomize when I use a separate seed node (primitive). I have to restart the entire workflow make sure its selected to fixed and it runs again. It loads with the values in the wrong boxes for some reason.
(It only happens when I change the seed)
this is the error I'm receiving: Error occurred when executing KSampler (Efficient):
Input type (torch.cuda.HalfTensor) and weight type (torch.HalfTensor) should be the same
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 153, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 83, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "D:\ComfyUI_windows_portable\ComfyUI\execution.py", line 76, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\efficiency-nodes-comfyui\efficiency_nodes.py", line 700, in sample
samples, images, gifs, preview = process_latent_image(model, seed, steps, cfg, sampler_name, scheduler,
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\efficiency-nodes-comfyui\efficiency_nodes.py", line 533, in process_latent_image
samples = KSampler().sample(model, seed, steps, cfg, sampler_name, scheduler, positive, negative,
File "D:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 1237, in sample
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
File "D:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 1207, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui-prompt-control\prompt_control\hijack.py", line 35, in pc_sample
r = cb(orig_sampler, *args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui-prompt-control\prompt_control\node_lora.py", line 104, in sampler_cb
s = orig_sampler(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 22, in informative_sample
raise e
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 9, in informative_sample
return original_sample(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 110, in animatediff_sample
return orig_comfy_sample(model, *args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\sample.py", line 97, in sample
samples = sampler.sample(noise, positive_copy, negative_copy, 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_windows_portable\ComfyUI\custom_nodes\comfyui-prompt-control\prompt_control\hijack.py", line 79, in sample
return super().sample(
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI_smZNodes_init_.py", line 131, in KSampler_sample
return KSampler_sample(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 781, 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_windows_portable\ComfyUI\custom_nodes\ComfyUI_smZNodes_init.py", line 139, in sample
return sample(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 686, in sample
samples = sampler.sample(model_wrap, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 638, in sample
samples = getattr(k_diffusion_sampling, "sample{}".format(sampler_name))(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **extra_options)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\k_diffusion\sampling.py", line 580, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 326, in forward
out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, model_options=model_options, seed=seed)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in call_impl
return forward_call(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\k_diffusion\external.py", line 129, in forward
eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\k_diffusion\external.py", line 155, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI_smZNodes\smZNodes.py", line 809, in apply_model
out = super().apply_model(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 314, in apply_model
out = sampling_function(self.inner_model.apply_model, x, timestep, uncond, cond, cond_scale, model_options=model_options, seed=seed)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 292, in sampling_function
cond, uncond = calc_cond_uncond_batch(model_function, cond, uncond, x, timestep, max_total_area, model_options)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\samplers.py", line 268, in calc_cond_uncond_batch
output = model_function(input_x, timestep, **c).chunk(batch_chunks)
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI_smZNodes\modules\sd_hijack_utils.py", line 17, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\ComfyUI_smZNodes\modules\sd_hijack_utils.py", line 28, in call
return self.__orig_func(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\model_base.py", line 64, in apply_model
return self.diffusion_model(xc, t, context=context, y=c_adm, control=control, transformer_options=transformer_options).float()
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 625, in forward
h = forward_timestep_embed(module, h, emb, context, transformer_options)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 54, in forward_timestep_embed
x = layer(x, emb)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 219, in forward
return checkpoint(
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\util.py", line 123, in checkpoint
return func(*inputs)
File "D:\ComfyUI_windows_portable\ComfyUI\comfy\ldm\modules\diffusionmodules\openaimodel.py", line 232, in _forward
h = self.in_layers(x)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\container.py", line 217, in forward
input = module(input)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\conv.py", line 463, in forward
return self._conv_forward(input, self.weight, self.bias)
File "D:\ComfyUI_windows_portable\python_embeded\lib\site-packages\torch\nn\modules\conv.py", line 459, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
Close
I got errors too. I can't even load old workflows which has Ksampler (Efficient). It becomes one big mess like this. (ComfyUI & all nodes are updated)
And when I load new Ksample Efficient in a new workflow it's pretty slow (10x slower than normal Ksampler)
Yes changing the values again fixes the workflow but the whole idea of the workflow is to have same values as before. As a workaround I installed image info node so I can read the old values of the workflow image and then put them in ksampler again.