WebUI Forge Issue

[gsurus]

This error was thrown when trying to generate an image in WebUI Forge, much like #37 but errors in a different script in the code.

Begin to load 1 model
[Memory Management] Current Free GPU Memory (MB) =  6739.7339878082275
[Memory Management] Model Memory (MB) =  2144.3546981811523
[Memory Management] Minimal Inference Memory (MB) =  1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) =  3571.379289627075
Moving model(s) has taken 0.33 seconds
To load target model SDXL
Begin to load 1 model
[Memory Management] Current Free GPU Memory (MB) =  7032.910161972046
[Memory Management] Model Memory (MB) =  4897.086494445801
[Memory Management] Minimal Inference Memory (MB) =  1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) =  1111.8236675262451
Moving model(s) has taken 1.35 seconds
  0%|                                                                                                      | 0/30 [00:00<?, ?it/s]To load target model AutoencoderKL
Begin to load 1 model
[Memory Management] Current Free GPU Memory (MB) =  7002.897306442261
[Memory Management] Model Memory (MB) =  319.11416244506836
[Memory Management] Minimal Inference Memory (MB) =  1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) =  5659.783143997192
Moving model(s) has taken 0.88 seconds
  0%|                                                                                                      | 0/30 [00:01<?, ?it/s] Traceback (most recent call last):
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules_forge\main_thread.py", line 37, in loop
    task.work()
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules_forge\main_thread.py", line 26, in work
    self.result = self.func(*self.args, **self.kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\txt2img.py", line 111, in txt2img_function
    processed = processing.process_images(p)
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\processing.py", line 752, in process_images
    res = process_images_inner(p)
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\processing.py", line 922, in process_images_inner
    samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
  File "C:\MachineLearning\stable-diffusion-webui-forge\extensions\sd-webui-fabric\scripts\marking.py", line 29, in process_sample
    return process.sample_before_CN_hack(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\processing.py", line 1275, in sample
    samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\sd_samplers_kdiffusion.py", line 251, in sample
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\sd_samplers_common.py", line 263, in launch_sampling
    return func()
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\sd_samplers_kdiffusion.py", line 251, in <lambda>
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\repositories\k-diffusion\k_diffusion\sampling.py", line 668, in sample_dpmpp_3m_sde
    denoised = model(x, sigmas[i] * s_in, **extra_args)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules\sd_samplers_cfg_denoiser.py", line 182, in forward
    denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
  File "C:\MachineLearning\stable-diffusion-webui-forge\modules_forge\forge_sampler.py", line 88, in forge_sample
    denoised = sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options, seed)
  File "C:\MachineLearning\stable-diffusion-webui-forge\ldm_patched\modules\samplers.py", line 289, in sampling_function
    cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond_, x, timestep, model_options)
  File "C:\MachineLearning\stable-diffusion-webui-forge\ldm_patched\modules\samplers.py", line 258, in calc_cond_uncond_batch
    output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
  File "C:\MachineLearning\stable-diffusion-webui-forge\ldm_patched\modules\model_base.py", line 90, in apply_model
    model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\extensions\sd-webui-fabric\scripts\patching.py", line 257, in new_forward
    _ = self._fabric_old_forward(zs, ts, **ctx_args)
  File "C:\MachineLearning\stable-diffusion-webui-forge\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 854, in forward
    emb = self.time_embed(t_emb)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\container.py", line 215, in forward
    input = module(input)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\ldm_patched\modules\ops.py", line 98, in forward
    return super().forward(*args, **kwargs)
  File "C:\MachineLearning\stable-diffusion-webui-forge\extensions\a1111-sd-webui-lycoris\l_networks.py", line 509, in network_Linear_forward
    return originals.Linear_forward(self, input)
  File "C:\MachineLearning\stable-diffusion-webui-forge\venv\lib\site-packages\torch\nn\modules\linear.py", line 114, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument mat1 in method wrapper_CUDA_addmm)
Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument mat1 in method wrapper_CUDA_addmm)
*** Error completing request
*** Arguments: ('task(wx43oaw0ut38ohh)', <gradio.routes.Request object at 0x0000025A444214B0>, 'cinematic, real life, outside, beach, sunset', '(watermark:1.5), (text:1.5), makeup, teeth, source_cartoon, source_anime, score_4, score_5, score_6, (big eyes)', [], 30, 'DPM++ 3M SDE Karras', 1, 1, 4, 1216, 832, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], 0, -1, False, -1, 0, 0, 0, False, '', 0.8, False, False, {'ad_model': 'face_yolov8n.pt', 'ad_model_classes': '', 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, False, 'keyword prompt', 'keyword1, keyword2', 'None', 'textual inversion first', 'None', '0.7', 'None', True, False, 1, False, False, False, 1.1, 1.5, 100, 0.7, False, False, True, False, False, 0, 'Gustavosta/MagicPrompt-Stable-Diffusion', '', ['01b2df89a97554c5.png'], [], True, 0, 0.8, 0, 0.8, 0.5, False, False, 0.5, 8192, -1.0, False, 'NONE:0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0\nALL:1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1\nINS:1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0\nIND:1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0\nINALL:1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0\nMIDD:1,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,0\nOUTD:1,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0\nOUTS:1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1\nOUTALL:1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1\nALL0.5:0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', True, 0, 'values', '0,0.25,0.5,0.75,1', 'Block ID', 'IN05-OUT05', 'none', '', '0.5,1', 'BASE,IN00,IN01,IN02,IN03,IN04,IN05,IN06,IN07,IN08,IN09,IN10,IN11,M00,OUT00,OUT01,OUT02,OUT03,OUT04,OUT05,OUT06,OUT07,OUT08,OUT09,OUT10,OUT11', 1.0, 'black', '20', False, 'ATTNDEEPON:IN05-OUT05:attn:1\n\nATTNDEEPOFF:IN05-OUT05:attn:0\n\nPROJDEEPOFF:IN05-OUT05:proj:0\n\nXYZ:::1', False, False, 1, ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=None, mask_image=None, hr_option='Both', enabled=False, module='None', model='None', weight=1, image=None, resize_mode='Crop and Resize', processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=None, mask_image=None, hr_option='Both', enabled=False, module='None', model='None', weight=1, image=None, resize_mode='Crop and Resize', processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), ControlNetUnit(input_mode=<InputMode.SIMPLE: 'simple'>, use_preview_as_input=False, batch_image_dir='', batch_mask_dir='', batch_input_gallery=[], batch_mask_gallery=[], generated_image=None, mask_image=None, hr_option='Both', enabled=False, module='None', model='None', weight=1, image=None, resize_mode='Crop and Resize', processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), False, 7, 1, 'Constant', 0, 'Constant', 0, 1, 'enable', 'MEAN', 'AD', 1, False, 1.01, 1.02, 0.99, 0.95, False, 0.5, 2, False, 256, 2, 0, False, False, 3, 2, 0, 0.35, True, 'bicubic', 'bicubic', False, 0, 'anisotropic', 0, 'reinhard', 100, 0, 'subtract', 0, 0, 'gaussian', 'add', 0, 100, 127, 0, 'hard_clamp', 5, 0, 'None', 'None', False, 'MultiDiffusion', 768, 768, 64, 4, False, False, False, False, None, None, '', '', '', '', 'Auto rename', {'label': 'Upload avatars config'}, 'Open outputs directory', 'Export to WebUI style', True, {'label': 'Presets'}, {'label': 'QC preview'}, '', [], 'Select', 'QC scan', 'Show pics', None, False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False, False, True, False, True, True, 'Create in UI', False, '', False, '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', '', 'Positive', 0, ', ', 'Generate and always save', 32) {}
    Traceback (most recent call last):
      File "C:\MachineLearning\stable-diffusion-webui-forge\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
    TypeError: 'NoneType' object is not iterable

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