Startup time: 46.8s (prepare environment: 25.9s, import torch: 4.7s, import gradio: 1.0s, setup paths: 0.5s, initialize shared: 0.2s, other imports: 0.5s, setup codeformer: 0.3s, load scripts: 8.4s, create ui: 4.1s, gradio launch: 0.6s, app_started_callback: 0.5s).Loading VAE weights specifiedin settings: E:\sd-webui-aki\sd-webui-aki-v4\models\VAE\vae-ft-mse-840000-ema-pruned.safetensorsApplying attention optimization: xformers... done.Model loadedin 6.5s (load weights from disk: 0.6s, create model: 0.9s, apply weights to model: 4.3s, load VAE: 0.4s, calculate empty prompt: 0.1s).refresh_uiRestoring base VAEApplying attention optimization: xformers... done.VAE weights loaded.2023-11-25 18:37:19,315 - ControlNet - INFO - Loading model: control_v11f1p_sd15_depth [cfd03158]2023-11-25 18:37:19,995 - ControlNet - INFO - Loaded state_dict from [E:\sd-webui-aki\sd-webui-aki-v4\models\ControlNet\control_v11f1p_sd15_depth.pth]2023-11-25 18:37:19,996 - ControlNet - INFO - controlnet_default_config2023-11-25 18:37:22,842 - ControlNet - INFO - ControlNet model control_v11f1p_sd15_depth [cfd03158] loaded.2023-11-25 18:37:23,008 - ControlNet - INFO - Loading preprocessor: depth2023-11-25 18:37:23,010 - ControlNet - INFO - preprocessor resolution = 8962023-11-25 18:37:27,343 - ControlNet - INFO - ControlNet Hooked - Time = 8.4580018520355220: 640x384 1 face, 78.0msSpeed: 4.0ms preprocess, 78.0ms inference, 29.0ms postprocess per image at shape (1, 3, 640, 384)2023-11-25 18:37:50,189 - ControlNet - INFO - Loading model from cache: control_v11f1p_sd15_depth [cfd03158]2023-11-25 18:37:50,192 - ControlNet - INFO - Loading preprocessor: depth2023-11-25 18:37:50,192 - ControlNet - INFO - preprocessor resolution = 8962023-11-25 18:37:50,279 - ControlNet - INFO - ControlNet Hooked - Time = 0.229001522064208982023-11-25 18:38:30,791 - AnimateDiff - INFO - AnimateDiff process start.2023-11-25 18:38:30,791 - AnimateDiff - INFO - Loading motion module mm_sd_v15_v2.ckpt from E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-animatediff\model\mm_sd_v15_v2.ckpt2023-11-25 18:38:31,574 - AnimateDiff - INFO - Guessed mm_sd_v15_v2.ckpt architecture: MotionModuleType.AnimateDiffV22023-11-25 18:38:33,296 - AnimateDiff - WARNING - Missing keys<All keys matched successfully>2023-11-25 18:38:34,243 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet middle block.2023-11-25 18:38:34,245 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet input blocks.2023-11-25 18:38:34,245 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet output blocks.2023-11-25 18:38:34,246 - AnimateDiff - INFO - Setting DDIM alpha.2023-11-25 18:38:34,254 - AnimateDiff - INFO - Injection finished.2023-11-25 18:38:34,254 - AnimateDiff - INFO - Hacking loral to support motion lora2023-11-25 18:38:34,254 - AnimateDiff - INFO - Hacking CFGDenoiser forward function.2023-11-25 18:38:34,254 - AnimateDiff - INFO - Hacking ControlNet.*** Error completing request*** Arguments: ('task(8jna2axn6nwg2d4)', '1 sex girl, big breasts, solo, high heels, skirt, thigh strap, squatting, black footwear, long hair, closed eyes, multicolored hair, red hair, black shirt, sleeveless, black skirt, full body, shirt, lips, brown hair, black hair, sleeveless shirt, bare shoulders, crop top, midriff, grey background, simple background, ', 'bad hands, normal quality, ((monochrome)), ((grayscale)), ((strabismus)), ng_deepnegative_v1_75t, (bad-hands-5:1.3), (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad_prompt, badhandv4, EasyNegative, ', [], 20, 'Euler a', 1, 1, 7, 1600, 896, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x0000024A8CCB4670>, 0, False, '', 0.8, -1, False, -1, 0, 0, 0, True, 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': 'Euler a', '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_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': 'Euler a', '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', False, 1.6, 0.97, 0.4, 0, 20, 0, 12, '', True, False, False, False, 512, False, True, ['Face'], False, '{\n    "face_detector": "RetinaFace",\n    "rules": {\n        "then": {\n            "face_processor": "img2img",\n            "mask_generator": {\n                "name": "BiSeNet",\n                "params": {\n                    "fallback_ratio": 0.1\n                }\n            }\n        }\n    }\n}', 'None', 40, <animatediff_utils.py.AnimateDiffProcess object at 0x0000024A8CC58940>, False, False, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, None, 'Refresh models', <scripts.animatediff_ui.AnimateDiffProcess object at 0x0000024A3BD73F10>, UiControlNetUnit(enabled=True, module='depth_midas', model='control_v11f1p_sd15_depth [cfd03158]', weight=1, image={'image': array([[[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        [[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        [[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        ...,******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]],******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]],******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]]], dtype=uint8),'mask': array([[[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        ...,******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]]], dtype=uint8)}, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=True, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), False, '', 0.5, True, False, '', 'Lerp', False, False, 1, 0.15, False, 'OUT', ['OUT'], 5, 0, 'Bilinear', False, 'Bilinear', False, 'Lerp', '', '', False, False, None, True, '🔄', False, False, 'Matrix', 'Columns', 'Mask', 'Prompt', '1,1', '0.2', False, False, False, 'Attention', [False], '0', '0', '0.4', None, '0', '0', False, False, False, 0, None, [], 0, False, [], [], False, 0, 1, False, False, 0, None, [], -2, False, [], False, 0, None, None, False, False, False, False, False, False, False, False, '1:1,1:2,1:2', '0:0,0:0,0:1', '0.2,0.8,0.8', 20, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, 5, 'all', 'all', 'all', '', '', '', '1', 'none', False, '', '', 'comma', '', True, '', '20', 'all', 'all', 'all', 'all', 0, '', 1.6, 0.97, 0.4, 0, 20, 0, 12, '', True, False, False, False, 512, False, True, ['Face'], False, '{\n    "face_detector": "RetinaFace",\n    "rules": {\n        "then": {\n            "face_processor": "img2img",\n            "mask_generator": {\n                "name": "BiSeNet",\n                "params": {\n                    "fallback_ratio": 0.1\n                }\n            }\n        }\n    }\n}', 'None', 40, None, None, False, None, None, False, None, None, False, 50, [], 30, '', 4, [], 1, '', '', '', '') {}    Traceback (most recent call last):      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 57,in f        res= list(func(*args,**kwargs))      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 36,in f        res= func(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\txt2img.py", line 55,in txt2img        processed= processing.process_images(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-prompt-history\lib_history\image_process_hijacker.py", line 21,in process_images        res= original_function(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\processing.py", line 732,in process_images        res= process_images_inner(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-animatediff\scripts\animatediff_cn.py", line 77,in hacked_processing_process_images_hijack        assert global_input_frames,'No input images found for ControlNet module'    AssertionError: No input images foundfor ControlNet module提示：Python 运行时抛出了一个异常。请检查疑难解答页面。---2023-11-25 18:39:52,611 - AnimateDiff - INFO - AnimateDiff process start.2023-11-25 18:39:52,611 - AnimateDiff - INFO - Motion module already injected. Trying to restore.2023-11-25 18:39:52,612 - AnimateDiff - INFO - Restoring DDIM alpha.2023-11-25 18:39:52,612 - AnimateDiff - INFO - Removing motion module from SD1.5 UNet input blocks.2023-11-25 18:39:52,612 - AnimateDiff - INFO - Removing motion module from SD1.5 UNet output blocks.2023-11-25 18:39:52,612 - AnimateDiff - INFO - Removing motion module from SD1.5 UNet middle block.2023-11-25 18:39:52,612 - AnimateDiff - INFO - Removal finished.2023-11-25 18:39:52,650 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet middle block.2023-11-25 18:39:52,650 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet input blocks.2023-11-25 18:39:52,650 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet output blocks.2023-11-25 18:39:52,650 - AnimateDiff - INFO - Setting DDIM alpha.2023-11-25 18:39:52,656 - AnimateDiff - INFO - Injection finished.2023-11-25 18:39:52,656 - AnimateDiff - INFO - AnimateDiff LoRA already hacked2023-11-25 18:39:52,656 - AnimateDiff - INFO - CFGDenoiser already hacked2023-11-25 18:39:52,657 - AnimateDiff - INFO - Hacking ControlNet.2023-11-25 18:39:52,657 - AnimateDiff - INFO - BatchHijack already hacked.2023-11-25 18:39:52,657 - AnimateDiff - INFO - ControlNet Main Entry already hacked.2023-11-25 18:39:52,697 - ControlNet - INFO - Loading model from cache: control_v11f1p_sd15_depth [cfd03158]2023-11-25 18:39:55,575 - ControlNet - INFO - Loading preprocessor: depth2023-11-25 18:39:55,576 - ControlNet - INFO - preprocessor resolution= 4482023-11-25 18:40:03,478 - ControlNet - INFO - ControlNet Hooked - Time= 10.787747859954834*** Error completing request*** Arguments: ('task(pud1kvh3lzj0ocs)', '1 sex girl, big breasts, solo, high heels, skirt, thigh strap, squatting, black footwear, long hair, closed eyes, multicolored hair, red hair, black shirt, sleeveless, black skirt, full body, shirt, lips, brown hair, black hair, sleeveless shirt, bare shoulders, crop top, midriff, grey background, simple background, ', 'bad hands, normal quality, ((monochrome)), ((grayscale)), ((strabismus)), ng_deepnegative_v1_75t, (bad-hands-5:1.3), (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad_prompt, badhandv4, EasyNegative, ', [], 20, 'Euler a', 1, 1, 7, 800, 448, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x0000024A8CCB7DC0>, 0, False, '', 0.8, -1, False, -1, 0, 0, 0, True, 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': 'Euler a', '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_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': 'Euler a', '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', False, 1.6, 0.97, 0.4, 0, 20, 0, 12, '', True, False, False, False, 512, False, True, ['Face'], False, '{\n    "face_detector": "RetinaFace",\n    "rules": {\n        "then": {\n            "face_processor": "img2img",\n            "mask_generator": {\n                "name": "BiSeNet",\n                "params": {\n                    "fallback_ratio": 0.1\n                }\n            }\n        }\n    }\n}', 'None', 40, <animatediff_utils.py.AnimateDiffProcess object at 0x0000024A8CC58940>, False, False, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, None, 'Refresh models', <scripts.animatediff_ui.AnimateDiffProcess object at 0x0000024AB1539DB0>, UiControlNetUnit(enabled=True, module='depth_midas', model='control_v11f1p_sd15_depth [cfd03158]', weight=1, image={'image': array([[[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        [[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        [[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        ...,******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]],******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]],******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]]], dtype=uint8),'mask': array([[[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        ...,******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]]], dtype=uint8)}, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=True, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), False, '', 0.5, True, False, '', 'Lerp', False, False, 1, 0.15, False, 'OUT', ['OUT'], 5, 0, 'Bilinear', False, 'Bilinear', False, 'Lerp', '', '', False, False, None, True, '🔄', False, False, 'Matrix', 'Columns', 'Mask', 'Prompt', '1,1', '0.2', False, False, False, 'Attention', [False], '0', '0', '0.4', None, '0', '0', False, False, False, 0, None, [], 0, False, [], [], False, 0, 1, False, False, 0, None, [], -2, False, [], False, 0, None, None, False, False, False, False, False, False, False, False, '1:1,1:2,1:2', '0:0,0:0,0:1', '0.2,0.8,0.8', 20, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, 5, 'all', 'all', 'all', '', '', '', '1', 'none', False, '', '', 'comma', '', True, '', '20', 'all', 'all', 'all', 'all', 0, '', 1.6, 0.97, 0.4, 0, 20, 0, 12, '', True, False, False, False, 512, False, True, ['Face'], False, '{\n    "face_detector": "RetinaFace",\n    "rules": {\n        "then": {\n            "face_processor": "img2img",\n            "mask_generator": {\n                "name": "BiSeNet",\n                "params": {\n                    "fallback_ratio": 0.1\n                }\n            }\n        }\n    }\n}', 'None', 40, None, None, False, None, None, False, None, None, False, 50, [], 30, '', 4, [], 1, '', '', '', '') {}    Traceback (most recent call last):      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 57,in f        res= list(func(*args,**kwargs))      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 36,in f        res= func(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\txt2img.py", line 55,in txt2img        processed= processing.process_images(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-prompt-history\lib_history\image_process_hijacker.py", line 21,in process_images        res= original_function(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\processing.py", line 732,in process_images        res= process_images_inner(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-animatediff\scripts\animatediff_cn.py", line 118,in hacked_processing_process_images_hijackreturn getattr(processing,'__controlnet_original_process_images_inner')(p,*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\processing.py", line 867,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"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 420,in process_samplereturn process.sample_before_CN_hack(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\processing.py", line 1140,in sample        samples= self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_samplers_kdiffusion.py", line 235,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"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_samplers_common.py", line 261,in launch_samplingreturnfunc()      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_samplers_kdiffusion.py", line 235,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"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\utils\_contextlib.py", line 115,in decorate_contextreturn func(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\k-diffusion\k_diffusion\sampling.py", line 145,in sample_euler_ancestral        denoised= model(x, sigmas[i]* s_in,**extra_args)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-animatediff\scripts\animatediff_infv2v.py", line 269,in mm_cfg_forward        x_out[a:b]= self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\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"E:\sd-webui-aki\sd-webui-aki-v4\repositories\k-diffusion\k_diffusion\external.py", line 138,in get_epsreturn self.inner_model.apply_model(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_hijack_utils.py", line 17,in<lambda>        setattr(resolved_obj, func_path[-1], lambda*args,**kwargs: self(*args,**kwargs))      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_hijack_utils.py", line 26,in __call__return self.__sub_func(self.__orig_func,*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_hijack_unet.py", line 48,in apply_modelreturn orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond,**kwargs).float()      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858,in apply_model        x_recon = self.model(x_noisy, t,**cond)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335,in forward        out = self.diffusion_model(x, t, context=cc)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 827,in forward_webui        raise e      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 824,in forward_webuireturn forward(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 561,in forward        control = param.control_model(x=x_in, hint=hint, timesteps=timesteps, context=context, y=y)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\cldm.py", line 31,in forwardreturn self.control_model(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\cldm.py", line 300,in forward        guided_hint = self.input_hint_block(hint, emb, context)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\generative-models\sgm\modules\diffusionmodules\openaimodel.py", line 102,in forward        x = layer(x)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions-builtin\Lora\networks.py", line 444,in network_Conv2d_forwardreturn originals.Conv2d_forward(self, input)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\conv.py", line 463,in forwardreturn self._conv_forward(input, self.weight, self.bias)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\conv.py", line 459,in _conv_forwardreturn F.conv2d(input, weight, bias, self.stride,    RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argumentforargument weightin method wrapper_CUDA___slow_conv2d_forward)提示：Python 运行时抛出了一个异常。请检查疑难解答页面。---2023-11-25 18:43:26,500 - AnimateDiff - INFO - AnimateDiff process start.2023-11-25 18:43:26,501 - AnimateDiff - INFO - Motion module already injected. Trying to restore.2023-11-25 18:43:26,501 - AnimateDiff - INFO - Restoring DDIM alpha.2023-11-25 18:43:26,502 - AnimateDiff - INFO - Removing motion module from SD1.5 UNet input blocks.2023-11-25 18:43:26,503 - AnimateDiff - INFO - Removing motion module from SD1.5 UNet output blocks.2023-11-25 18:43:26,503 - AnimateDiff - INFO - Removing motion module from SD1.5 UNet middle block.2023-11-25 18:43:26,503 - AnimateDiff - INFO - Removal finished.2023-11-25 18:43:26,519 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet middle block.2023-11-25 18:43:26,519 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet input blocks.2023-11-25 18:43:26,519 - AnimateDiff - INFO - Injecting motion module mm_sd_v15_v2.ckpt into SD1.5 UNet output blocks.2023-11-25 18:43:26,520 - AnimateDiff - INFO - Setting DDIM alpha.2023-11-25 18:43:26,522 - AnimateDiff - INFO - Injection finished.2023-11-25 18:43:26,522 - AnimateDiff - INFO - AnimateDiff LoRA already hacked2023-11-25 18:43:26,522 - AnimateDiff - INFO - CFGDenoiser already hacked2023-11-25 18:43:26,522 - AnimateDiff - INFO - Hacking ControlNet.2023-11-25 18:43:26,522 - AnimateDiff - INFO - BatchHijack already hacked.2023-11-25 18:43:26,522 - AnimateDiff - INFO - ControlNet Main Entry already hacked.2023-11-25 18:43:26,736 - ControlNet - INFO - Loading model from cache: control_v11f1p_sd15_depth [cfd03158]2023-11-25 18:43:28,938 - ControlNet - INFO - Loading preprocessor: depth2023-11-25 18:43:28,939 - ControlNet - INFO - preprocessor resolution = 4482023-11-25 18:43:38,425 - ControlNet - INFO - ControlNet Hooked - Time = 11.88900351524353*** Error completing request*** Arguments: ('task(ugw097u8h16i04e)', '1 sex girl, big breasts, solo, high heels, skirt, thigh strap, squatting, black footwear, long hair, closed eyes, multicolored hair, red hair, black shirt, sleeveless, black skirt, full body, shirt, lips, brown hair, black hair, sleeveless shirt, bare shoulders, crop top, midriff, grey background, simple background, ', 'bad hands, normal quality, ((monochrome)), ((grayscale)), ((strabismus)), ng_deepnegative_v1_75t, (bad-hands-5:1.3), (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad_prompt, badhandv4, EasyNegative, ', [], 20, 'Euler a', 1, 1, 7, 800, 448, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x0000024A8CC5E950>, 0, False, '', 0.8, -1, False, -1, 0, 0, 0, True, 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': 'Euler a', '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_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': 'Euler a', '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', False, 1.6, 0.97, 0.4, 0, 20, 0, 12, '', True, False, False, False, 512, False, True, ['Face'], False, '{\n    "face_detector": "RetinaFace",\n    "rules": {\n        "then": {\n            "face_processor": "img2img",\n            "mask_generator": {\n                "name": "BiSeNet",\n                "params": {\n                    "fallback_ratio": 0.1\n                }\n            }\n        }\n    }\n}', 'None', 40, <animatediff_utils.py.AnimateDiffProcess object at 0x0000024A8CC58940>, False, False, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, 'LoRA', 'None', 1, 1, None, 'Refresh models', <scripts.animatediff_ui.AnimateDiffProcess object at 0x0000024A8CC59F60>, UiControlNetUnit(enabled=True, module='depth_midas', model='control_v11f1p_sd15_depth [cfd03158]', weight=1, image={'image': array([[[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        [[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        [[183, 187, 189],***         [183, 187, 189],***         [183, 187, 189],***         ...,***         [185, 189, 191],***         [185, 189, 191],***         [185, 189, 191]],******        ...,******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]],******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]],******        [[223, 224, 227],***         [223, 224, 227],***         [223, 224, 227],***         ...,***         [227, 227, 227],***         [227, 227, 227],***         [227, 227, 227]]], dtype=uint8),'mask': array([[[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        ...,******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]],******        [[0, 0, 0],***         [0, 0, 0],***         [0, 0, 0],***         ...,***         [0, 0, 0],***         [0, 0, 0],***         [0, 0, 0]]], dtype=uint8)}, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=True, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=512, threshold_a=64, threshold_b=64, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), False, '', 0.5, True, False, '', 'Lerp', False, False, 1, 0.15, False, 'OUT', ['OUT'], 5, 0, 'Bilinear', False, 'Bilinear', False, 'Lerp', '', '', False, False, None, True, '🔄', False, False, 'Matrix', 'Columns', 'Mask', 'Prompt', '1,1', '0.2', False, False, False, 'Attention', [False], '0', '0', '0.4', None, '0', '0', False, False, False, 0, None, [], 0, False, [], [], False, 0, 1, False, False, 0, None, [], -2, False, [], False, 0, None, None, False, False, False, False, False, False, False, False, '1:1,1:2,1:2', '0:0,0:0,0:1', '0.2,0.8,0.8', 20, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, 5, 'all', 'all', 'all', '', '', '', '1', 'none', False, '', '', 'comma', '', True, '', '20', 'all', 'all', 'all', 'all', 0, '', 1.6, 0.97, 0.4, 0, 20, 0, 12, '', True, False, False, False, 512, False, True, ['Face'], False, '{\n    "face_detector": "RetinaFace",\n    "rules": {\n        "then": {\n            "face_processor": "img2img",\n            "mask_generator": {\n                "name": "BiSeNet",\n                "params": {\n                    "fallback_ratio": 0.1\n                }\n            }\n        }\n    }\n}', 'None', 40, None, None, False, None, None, False, None, None, False, 50, [], 30, '', 4, [], 1, '', '', '', '') {}    Traceback (most recent call last):      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 57,in f        res= list(func(*args,**kwargs))      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\call_queue.py", line 36,in f        res= func(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\txt2img.py", line 55,in txt2img        processed= processing.process_images(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-prompt-history\lib_history\image_process_hijacker.py", line 21,in process_images        res= original_function(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\processing.py", line 732,in process_images        res= process_images_inner(p)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-animatediff\scripts\animatediff_cn.py", line 118,in hacked_processing_process_images_hijackreturn getattr(processing,'__controlnet_original_process_images_inner')(p,*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\processing.py", line 867,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"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 420,in process_samplereturn process.sample_before_CN_hack(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\processing.py", line 1140,in sample        samples= self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_samplers_kdiffusion.py", line 235,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"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_samplers_common.py", line 261,in launch_samplingreturnfunc()      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_samplers_kdiffusion.py", line 235,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"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\utils\_contextlib.py", line 115,in decorate_contextreturn func(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\k-diffusion\k_diffusion\sampling.py", line 145,in sample_euler_ancestral        denoised= model(x, sigmas[i]* s_in,**extra_args)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-animatediff\scripts\animatediff_infv2v.py", line 269,in mm_cfg_forward        x_out[a:b]= self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\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"E:\sd-webui-aki\sd-webui-aki-v4\repositories\k-diffusion\k_diffusion\external.py", line 138,in get_epsreturn self.inner_model.apply_model(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_hijack_utils.py", line 17,in<lambda>        setattr(resolved_obj, func_path[-1], lambda*args,**kwargs: self(*args,**kwargs))      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_hijack_utils.py", line 26,in __call__return self.__sub_func(self.__orig_func,*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\modules\sd_hijack_unet.py", line 48,in apply_modelreturn orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond,**kwargs).float()      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858,in apply_model        x_recon = self.model(x_noisy, t,**cond)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335,in forward        out = self.diffusion_model(x, t, context=cc)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 827,in forward_webui        raise e      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 824,in forward_webuireturn forward(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\hook.py", line 561,in forward        control = param.control_model(x=x_in, hint=hint, timesteps=timesteps, context=context, y=y)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\cldm.py", line 31,in forwardreturn self.control_model(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions\sd-webui-controlnet\scripts\cldm.py", line 300,in forward        guided_hint = self.input_hint_block(hint, emb, context)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\repositories\generative-models\sgm\modules\diffusionmodules\openaimodel.py", line 102,in forward        x = layer(x)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501,in _call_implreturn forward_call(*args,**kwargs)      File"E:\sd-webui-aki\sd-webui-aki-v4\extensions-builtin\Lora\networks.py", line 444,in network_Conv2d_forwardreturn originals.Conv2d_forward(self, input)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\conv.py", line 463,in forwardreturn self._conv_forward(input, self.weight, self.bias)      File"E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\conv.py", line 459,in _conv_forwardreturn F.conv2d(input, weight, bias, self.stride,    RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argumentforargument weightin method wrapper_CUDA___slow_conv2d_forward)提示：Python 运行时抛出了一个异常。请检查疑难解答页面。---