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stable-diffusion-3-medium

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Error occurred when executing KSampler:

Expected all tensors to be on the same device, but found at least two devices, privateuseone:0 and cpu!

File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\execution.py", line 151, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\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 "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\execution.py", line 74, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\nodes.py", line 1355, in sample
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\nodes.py", line 1325, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\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 "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\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 "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 696, in sample
return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 683, in sample
output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 662, in inner_sample
samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 567, in sample
samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **self.extra_options)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comf\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\k_diffusion\sampling.py", line 137, in sample_euler
denoised = model(x, sigma_hat * s_in, **extra_args)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 291, in call
out = self.inner_model(x, sigma, model_options=model_options, seed=seed)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 649, in call
return self.predict_noise(*args, **kwargs)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 652, 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 "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 277, in sampling_function
out = calc_cond_batch(model, conds, x, timestep, model_options)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\samplers.py", line 226, in calc_cond_batch
output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\model_base.py", line 103, in apply_model
model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comf\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comf\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\ldm\modules\diffusionmodules\mmdit.py", line 961, in forward
return super().forward(x, timesteps, context=context, y=y)
File "C:\Users\WarMa\OneDrive\Escritorio\SD\comfyuai\ComfyUI\comfy\ldm\modules\diffusionmodules\mmdit.py", line 937, in forward
x = self.x_embedder(x) + self.cropped_pos_embed(hw, device=x.device).to(dtype=x.dtype)