Open KillyTheNetTerminal opened 2 weeks ago
Can confirm the same error on a RTX 3050 / Intel Core i7-11800H notebook. The only difference is this line:
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!
exactly cause you have Nvidea and Cuda
working on CPU but slow as hell. i3-9100f
Same problem for me
Exception during processing!!! Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!
Traceback (most recent call last):
File "C:\Users\<myuser>\Downloads\comfyui\ComfyUI\execution.py", line 151, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
Seems to work for me on:
│Total VRAM 11980 MB, total RAM 64140 MB
│pytorch version: 2.3.0+cu121
│Set vram state to: NORMAL_VRAM
│Device: cuda:0 NVIDIA GeForce RTX 4070 : cudaMallocAsync
│VAE dtype: torch.bfloat16
│Using pytorch cross attention
Nvidia + CUDA
Can confirm the same error on a RTX 3050 / Intel Core i7-11800H notebook. The only difference is this line:
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!
I have the same error too..
A fresh manual install with nightly pytorch (other not tested) helped me overcome this problem. 1050ti 4gb + 32gb RAM
A fresh manual install with nightly pytorch (other not tested) helped me overcome this problem. 1050ti 4gb + 32gb RAM
can we just update the pytorch in the current install? and how is 4gb vram handling sd3 btw?
A fresh manual install with nightly pytorch (other not tested) helped me overcome this problem. 1050ti 4gb + 32gb RAM
can we just update the pytorch in the current install? and how is 4gb vram handling sd3 btw?
Maybe? I did not test. About performance: 30 s/it for 1024x1024 with dualCLIP.
Guys the issue is fixed, please do an update!
Guys the issue is fixed, please do an update!
update Comfy UI?
yes it works now, update comfyui (I use manager) very slow per it. There's is a way to speed up this?
You should not use dpmpp_2m, karras
.
Just use euler, sgm_uniform
.
karras is bad for SD3.
You should not use
dpmpp_2m, karras
. Just useeuler, sgm_uniform
.karras is bad for SD3.
the official recommendation is dpm though, isn't euler too random according to sd3 architecture?
You should not use
dpmpp_2m, karras
. Just useeuler, sgm_uniform
. karras is bad for SD3.the official recommendation is dpm though, isn't euler too random according to sd3 architecture?
https://comfyanonymous.github.io/ComfyUI_examples/sd3/
Official example is suggesting euler, sgm_uniform
.
In my test.
dpmpp_2m sampler is ok.
but the scheduler must be one of normal, simple, sgm_uniform, ddim_uniform.
the same, the image is still noisy
Try on cpu mode.
Same issue with just getting noisy generated images. 7900 XTX also running using DirectML.
Perhaps SD3 is not working with AMD GPUs/DirectML yet.
Same issue, i nail it down a little bit to variable named out in sampling_function in samplers.py being different on cpu/directml. Here a crazy path to it. nodes.py -> samplers.py -> KSampler.sample -> sample(diferent one) -> CFGGuider.sample ->CFGGuider.inner_sample (sampler.sample(self, sigmas...)) -> sampler = sampler_object(self.sampler just a name) -> sampler_object -> ksampler -> KSAMPLER.sample(self, model_wrap, sigmas, extra_args...) -> model_k = KSamplerX0Inpaint(model_wrap, sigmas) -> model_wrap is self in sampler.sample so CFGGuider() call return self.predict_noise() -> sampling_function(model) -> cfg_function(model) -> out. It is different on cpu/directml. Why? I don't know.
If anyone wants to get a working SD3 with AMD GPUs in the mean time, look up the ComfyUI Zluda fork and use that instead. Working great.
Just be warned that the first generation takes a little while as a bunch of databases are being processed. Similar to if you've ever used A1111 and Zluda, you had that same wait time for your first generation after installing it.
I never try and set up zluda for comfyui, this speed ups generations? compared to directml? how can I test this?
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(inputx, 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)![imagen_2024-06-12_085506430](https://github.com/comfyanonymous/ComfyUI/assets/120438550/c1697001-a5fe-4293-8a9c-5a28a192423b)