bananasss00 / ComfyUI_bitsandbytes_NF4-Lora

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All input tensors need to be on the same GPU, but found some tensors to not be on a GPU: #1

Open CorradoF opened 1 month ago

CorradoF commented 1 month ago

This doesn't happen with the classic old nf4 loader https://github.com/comfyanonymous/ComfyUI_bitsandbytes_NF4

Same error with 2 different nodes, SamplerCustomAdvance and UltimateSDUpscale no Lora were present in these 2 different workflow, I was testing the node before adding them

All input tensors need to be on the same GPU, but found some tensors to not be on a GPU: [(torch.Size([1, 98304]), device(type='cuda', index=0)), (torch.Size([3072]), device(type='cpu')), (torch.Size([3072, 64]), device(type='cuda', index=0))]


1

loaded completely 0.0 6385.7255964279175 True 0%| | 0/30 [00:00<?, ?it/s] !!! Exception during processing !!! All input tensors need to be on the same GPU, but found some tensors to not be on a GPU: [(torch.Size([1, 98304]), device(type='cuda', index=0)), (torch.Size([3072]), device(type='cpu')), (torch.Size([3072, 64]), device(type='cuda', index=0))] Traceback (most recent call last): File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 323, in execute output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 198, in get_output_data return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 169, in _map_node_over_list process_inputs(input_dict, i) File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 158, in process_inputs results.append(getattr(obj, func)(inputs)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy_extras\nodes_custom_sampler.py", line 633, in sample samples = guider.sample(noise.generate_noise(latent), latent_image, sampler, sigmas, denoise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=noise.seed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 716, in sample output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 695, in inner_sample samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI-TiledDiffusion\utils.py", line 34, in KSAMPLER_sample return orig_fn(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 600, in sample samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, self.extra_options) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context return func(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\k_diffusion\sampling.py", line 155, in sample_euler denoised = model(x, sigma_hat * s_in, extra_args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 299, in call out = self.inner_model(x, sigma, model_options=model_options, seed=seed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 682, in call return self.predict_noise(*args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 685, 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 "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 279, in sampling_function out = calc_cond_batch(model, conds, x, timestep, model_options) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 228, in calc_cond_batch output = model.apply_model(inputx, timestep, c).chunk(batch_chunks) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\model_base.py", line 142, in apply_model model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, *extra_conds).float() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl return forward_call(*args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\ldm\flux\model.py", line 159, in forward out = self.forward_orig(img, img_ids, context, txt_ids, timestep, y, guidance, control) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\ldm\flux\model.py", line 104, in forward_orig img = self.img_in(img) ^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl return self._call_impl(*args, *kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl return forward_call(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_bitsandbytes_NF4-Lora__init.py", line 341, in forward return functional_linear_4bits(x, self.weight, self.bias) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_bitsandbytes_NF4-Lora\init__.py", line 23, in functional_linear_4bits out = bnb.matmul_4bit(x, weight.t(), bias=bias, quant_state=weight.quant_state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\autograd_functions.py", line 579, in matmul_4bit return MatMul4Bit.apply(A, B, out, bias, quant_state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\autograd\function.py", line 574, in apply return super().apply(*args, **kwargs) # type: ignore[misc] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\autograd_functions.py", line 509, in forward output = torch.nn.functional.linear(A, F.dequantize_4bit(B, quant_state).to(A.dtype).t(), bias) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\functional.py", line 1380, in dequantize_4bit is_on_gpu([A, absmax, out]) File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\functional.py", line 446, in is_on_gpu raise TypeError( TypeError: All input tensors need to be on the same GPU, but found some tensors to not be on a GPU: [(torch.Size([1, 98304]), device(type='cuda', index=0)), (torch.Size([3072]), device(type='cpu')), (torch.Size([3072, 64]), device(type='cuda', index=0))]

Prompt executed in 70.00 seconds


2

Requested to load FluxClipModel_ Loading 1 new model loaded completely 0.0 4778.66552734375 True [Flux (6.2gb)] partially_unload: cpu, memory_to_free=1.4gb / result=1.4gb Unloading models for lowram load. [Flux (6.2gb)] partially_unload: cpu, memory_to_free=0.1gb / result=0.1gb 0 models unloaded. Canva size: 2560x2560 Image size: 1280x1280 Scale factor: 2 Upscaling iteration 1 with scale factor 2 Tile size: 1024x1024 Tiles amount: 9 Grid: 3x3 Redraw enabled: True Seams fix mode: NONE 0%| | 0/5 [00:00<?, ?it/s] !!! Exception during processing !!! All input tensors need to be on the same GPU, but found some tensors to not be on a GPU: [(torch.Size([1, 98304]), device(type='cuda', index=0)), (torch.Size([3072]), device(type='cpu')), (torch.Size([3072, 64]), device(type='cuda', index=0))] Traceback (most recent call last): File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 323, in execute output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 198, in get_output_data return_values = _map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 169, in _map_node_over_list process_inputs(input_dict, i) File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\execution.py", line 158, in process_inputs results.append(getattr(obj, func)(inputs)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUIUltimateSDUpscale\nodes.py", line 151, in upscale processed = script.run(p=self.sdprocessing, =None, tile_width=self.tile_width, tile_height=self.tile_height, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_UltimateSDUpscale\repositories\ultimate_sd_upscale\scripts\ultimate-upscale.py", line 565, in run upscaler.process() File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_UltimateSDUpscale\repositories\ultimate_sd_upscale\scripts\ultimate-upscale.py", line 138, in process self.image = self.redraw.start(self.p, self.image, self.rows, self.cols) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_UltimateSDUpscale\repositories\ultimate_sd_upscale\scripts\ultimate-upscale.py", line 245, in start return self.linear_process(p, image, rows, cols) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_UltimateSDUpscale\repositories\ultimate_sd_upscale\scripts\ultimate-upscale.py", line 180, in linear_process processed = processing.process_images(p) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_UltimateSDUpscale\modules\processing.py", line 173, in process_images samples = sample(p.model, p.seed, p.steps, p.cfg, p.sampler_name, p.scheduler, positive_cropped, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_UltimateSDUpscale\modules\processing.py", line 109, in sample (samples,) = common_ksampler(model, seed, steps, cfg, sampler_name, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\nodes.py", line 1404, in common_ksampler samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\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 "L:\ComfyUI_nvidia\ComfyCoreProgram\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 "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI-TiledDiffusion\utils.py", line 51, in KSampler_sample return orig_fn(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 829, 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 "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 729, in sample return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 716, in sample output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 695, in inner_sample samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI-TiledDiffusion\utils.py", line 34, in KSAMPLER_sample return orig_fn(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 600, in sample samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, self.extra_options) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\utils_contextlib.py", line 116, in decorate_context return func(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\k_diffusion\sampling.py", line 1033, in sample_deis denoised = model(x_cur, t_cur * s_in, *extra_args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 299, in call out = self.inner_model(x, sigma, model_options=model_options, seed=seed) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 682, in call return self.predict_noise(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 685, 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 "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 279, in sampling_function out = calc_cond_batch(model, conds, x, timestep, model_options) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\samplers.py", line 228, in calc_cond_batch output = model.apply_model(inputx, timestep, c).chunk(batch_chunks) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\model_base.py", line 142, in apply_model model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, extra_conds).float() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl return self._call_impl(*args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl return forward_call(*args, *kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\ldm\flux\model.py", line 159, in forward out = self.forward_orig(img, img_ids, context, txt_ids, timestep, y, guidance, control) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\comfy\ldm\flux\model.py", line 104, in forward_orig img = self.img_in(img) ^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\nn\modules\module.py", line 1562, in _call_impl return forward_call(*args, *kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_bitsandbytes_NF4-Lora__init.py", line 341, in forward return functional_linear_4bits(x, self.weight, self.bias) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\ComfyUI\custom_nodes\ComfyUI_bitsandbytes_NF4-Lora\init__.py", line 23, in functional_linear_4bits out = bnb.matmul_4bit(x, weight.t(), bias=bias, quant_state=weight.quant_state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\autograd_functions.py", line 579, in matmul_4bit return MatMul4Bit.apply(A, B, out, bias, quant_state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\torch\autograd\function.py", line 574, in apply return super().apply(args, **kwargs) # type: ignore[misc] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\autograd_functions.py", line 509, in forward output = torch.nn.functional.linear(A, F.dequantize_4bit(B, quant_state).to(A.dtype).t(), bias) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\functional.py", line 1380, in dequantize_4bit is_on_gpu([A, absmax, out]) File "L:\ComfyUI_nvidia\ComfyCoreProgram\python_embeded\Lib\site-packages\bitsandbytes\functional.py", line 446, in is_on_gpu raise TypeError( TypeError: All input tensors need to be on the same GPU, but found some tensors to not be on a GPU: [(torch.Size([1, 98304]), device(type='cuda', index=0)), (torch.Size([3072]), device(type='cpu')), (torch.Size([3072, 64]), device(type='cuda', index=0))]

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