100%|██████████████████████████████████████████████████████████████████████████████████| 36/36 [00:04<00:00, 7.89it/s]
0%| | 0/8 [00:00<?, ?it/s]
*** Error completing request
*** Arguments: ('task(o6gp9seri8repp8)', 'RAW photo, Fujifilm XT3, lighthouse, <lora:epiCRealLife:1>', 'deformed, oversaturated, overcontrasted, asian, chinese, cartoon, cgi, render, illustration, painting, drawing, statue, anime, 2d,', [], 36, 'DPM++ 3M SDE Karras', 1, 1, 10, 512, 768, True, 0.5, 1.65, '4xLSDIR', 8, 0, 0, 'Use same checkpoint', 'DPM++ 2M Karras', '', '', [], <gradio.routes.Request object at 0x0000000F8005F5B0>, 0, False, '', 0.8, 3952135377, False, -1, 0, 0, 0, 0, False, 1, False, False, {'ad_model': 'face_yolov8n.pt', '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_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': 'inpaint_global_harmonious', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', '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_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': 'inpaint_global_harmonious', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, False, 1448, 0, 8, 'DF2K', '4x-UniScaleV2_Sharp', 0.3, 0.1, '', '', 2, 'Noise sync (sharp)', 0.3, 0.05, 0, 'DPM++ 3M SDE', False, 'MultiDiffusion', False, True, 1024, 1024, 96, 96, 48, 4, 'None', 2, False, 10, 1, 1, 64, False, False, False, False, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 2048, 128, True, True, True, False, False, 7, 100, 'Constant', 0, 'Constant', 0, 4, True, 'MEAN', 'AD', 1, <scripts.controlnet_ui.controlnet_ui_group.UiControlNetUnit object at 0x00000000670B9CC0>, <scripts.controlnet_ui.controlnet_ui_group.UiControlNetUnit object at 0x00000000670B8D00>, <scripts.controlnet_ui.controlnet_ui_group.UiControlNetUnit object at 0x00000000670B9BA0>, False, '', 0.5, True, False, '', 'Lerp', False, [], [], False, 0, 0.8, 0, 0.8, 0.5, False, False, 0.5, 8192, -1.0, None, '', None, True, False, False, False, False, False, 0, 0, '0', 0, False, True, 0, 'Portrait of a [gender]', 'blurry', 20, ['DPM++ 2M Karras'], '', None, 1, 1, None, False, False, False, 1, 0, 'Portrait of a [gender]', 'blurry', 20, ['DPM++ 2M Karras'], '', None, '', None, True, False, False, False, False, False, 0, 0, '0', 0, False, True, 0, 'Portrait of a [gender]', 'blurry', 20, ['DPM++ 2M Karras'], '', None, 1, 1, None, False, False, False, 1, 0, 'Portrait of a [gender]', 'blurry', 20, ['DPM++ 2M Karras'], '', None, '', None, True, False, False, False, False, False, 0, 0, '0', 0, False, True, 0, 'Portrait of a [gender]', 'blurry', 20, ['DPM++ 2M Karras'], '', None, 1, 1, None, False, False, False, 1, 0, 'Portrait of a [gender]', 'blurry', 20, ['DPM++ 2M Karras'], '', 'CodeFormer', 1, 1, None, 1, 1, ['After Upscaling/Before Restore Face'], 0, 'Portrait of a [gender]', 'blurry', 20, ['DPM++ 2M Karras'], '', True, 0, 1, 0, 1.2, 0.9, 0, 0.5, 0, 1, 1.4, 0.2, 0, 0.5, 0, 1, 1, 1, 0, 0.5, 0, 1, 0, None, False, '0', '0', 'inswapper_128.onnx', 'CodeFormer', 1, True, 'None', 1, 1, False, True, 1, 0, 0, False, 0.5, False, False, 0, 1, 1, 0, 0, 0, 0, False, 'Straight Abs.', 'Flat', False, 0.75, 1, False, False, 3, 0, False, False, 0, False, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, None, None, False, None, None, False, None, None, False, 50) {}
Traceback (most recent call last):
File "F:\WBC\automatic1111_dev\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "F:\WBC\automatic1111_dev\modules\call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "F:\WBC\automatic1111_dev\modules\txt2img.py", line 55, in txt2img
processed = processing.process_images(p)
File "F:\WBC\automatic1111_dev\modules\processing.py", line 734, in process_images
res = process_images_inner(p)
File "F:\WBC\automatic1111_dev\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 42, in processing_process_images_hijack
return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
File "F:\WBC\automatic1111_dev\modules\processing.py", line 869, 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 "F:\WBC\automatic1111_dev\modules\processing.py", line 1161, in sample
return self.sample_hr_pass(samples, decoded_samples, seeds, subseeds, subseed_strength, prompts)
File "F:\WBC\automatic1111_dev\modules\processing.py", line 1247, in sample_hr_pass
samples = self.sampler.sample_img2img(self, samples, noise, self.hr_c, self.hr_uc, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
File "F:\WBC\automatic1111_dev\modules\sd_samplers_kdiffusion.py", line 188, in sample_img2img
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "F:\WBC\automatic1111_dev\modules\sd_samplers_common.py", line 261, in launch_sampling
return func()
File "F:\WBC\automatic1111_dev\modules\sd_samplers_kdiffusion.py", line 188, in <lambda>
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "F:\WBC\automatic1111_dev\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "F:\WBC\automatic1111_dev\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "F:\WBC\automatic1111_dev\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "F:\WBC\automatic1111_dev\modules\sd_samplers_cfg_denoiser.py", line 169, in forward
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
File "F:\WBC\automatic1111_dev\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "F:\WBC\automatic1111_dev\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
File "F:\WBC\automatic1111_dev\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "F:\WBC\automatic1111_dev\modules\sd_hijack_utils.py", line 17, in <lambda>
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "F:\WBC\automatic1111_dev\modules\sd_hijack_utils.py", line 28, in __call__
return self.__orig_func(*args, **kwargs)
File "F:\WBC\automatic1111_dev\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
x_recon = self.model(x_noisy, t, **cond)
File "F:\WBC\automatic1111_dev\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "F:\WBC\automatic1111_dev\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
out = self.diffusion_model(x, t, context=cc)
File "F:\WBC\automatic1111_dev\venv\lib\site-packages\torch\nn\modules\module.py", line 1538, in _call_impl
result = forward_call(*args, **kwargs)
File "F:\WBC\automatic1111_dev\modules\sd_unet.py", line 89, in UNetModel_forward
return current_unet.forward(x, timesteps, context, *args, **kwargs)
File "F:\WBC\automatic1111_dev\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 84, in forward
raise ValueError(
ValueError: Input shape must be divisible by 64 in both dimensions.
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