Repository: stable-diffusion-webui
Issue: [Bug]: Sizes of tensors must match except in dimension 0
Labels: bug-report

### Checklist

- [ ] The issue exists after disabling all extensions
- [ ] The issue exists on a clean installation of webui
- [ ] The issue is caused by an extension, but I believe it is caused by a bug in the webui
- [ ] The issue exists in the current version of the webui
- [ ] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet

### What happened?

I'm having a strange issue where sometimes an instance will throw up a "size of tensors"  error.  Often it works fine, then subsequent generations, with no changes, throw up the error.  restarting the CMD window usually (but not always) fixes it, but then it can happen again.  If I have several browser windows open with SD, some might give the error, but others do not.    I tried changing the model, in case the one I was using was corrupted or something, but I got the same issue

### Steps to reproduce the problem

intermittent, but happens when I click generate 

### What should have happened?

it should generate without error

### What browsers do you use to access the UI ?

Mozilla Firefox

### Sysinfo

{
    "Platform": "Windows-10-10.0.19045-SP0",
    "Python": "3.10.6",
    "Version": "v1.7.0",
    "Commit": "cf2772fab0af5573da775e7437e6acdca424f26e",
    "Script path": "C:\\AI\\Image AI\\SDNEW\\webui",
    "Data path": "C:\\AI\\Image AI\\SDNEW\\webui",
    "Extensions dir": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions",
    "Checksum": "4e6a90e49e2ce7e352f5453ee967299ff6b3dacc9e7344db71f371bdf499f0bd",
    "Commandline": [
        "launch.py",
        "--listen",
        "--enable-insecure-extension-access",
        "--reinstall-xformers",
        "--xformers",
        "--no-half",
        "--no-half-vae",
        "--medvram",
        "--medvram-sdxl",
        "--update-all-extensions"
    ],
    "Torch env info": "'NoneType' object has no attribute 'splitlines'",
    "Exceptions": [
        {
            "exception": "Sizes of tensors must match except in dimension 0. Expected size 1280 but got size 768 for tensor number 1 in the list.",
            "traceback": [
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\txt2img.py, line 55, txt2img",
                    "processed = processing.process_images(p)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 734, process_images",
                    "res = process_images_inner(p)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-controlnet\\scripts\\batch_hijack.py, line 42, processing_process_images_hijack",
                    "return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 857, process_images_inner",
                    "p.setup_conds()"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 1308, setup_conds",
                    "super().setup_conds()"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 470, setup_conds",
                    "self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 455, get_conds_with_caching",
                    "cache[1] = function(shared.sd_model, required_prompts, steps, hires_steps, shared.opts.use_old_scheduling)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\prompt_parser.py, line 261, get_multicond_learned_conditioning",
                    "learned_conditioning = get_learned_conditioning(model, prompt_flat_list, steps, hires_steps, use_old_scheduling)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\prompt_parser.py, line 188, get_learned_conditioning",
                    "conds = model.get_learned_conditioning(texts)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_models_xl.py, line 31, get_learned_conditioning",
                    "c = self.conditioner(sdxl_conds, force_zero_embeddings=['txt'] if force_zero_negative_prompt else [])"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1538, _call_impl",
                    "result = forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\repositories\\generative-models\\sgm\\modules\\encoders\\modules.py, line 141, forward",
                    "emb_out = embedder(batch[embedder.input_key])"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack_clip.py, line 234, forward",
                    "z = self.process_tokens(tokens, multipliers)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack_clip.py, line 273, process_tokens",
                    "z = self.encode_with_transformers(tokens)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack_open_clip.py, line 57, encode_with_transformers",
                    "d = self.wrapped.encode_with_transformer(tokens)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\repositories\\generative-models\\sgm\\modules\\encoders\\modules.py, line 467, encode_with_transformer",
                    "x = self.model.token_embedding(text)  # [batch_size, n_ctx, d_model]"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack.py, line 359, forward",
                    "tensor = torch.cat([tensor[0:offset + 1], emb[0:emb_len], tensor[offset + 1 + emb_len:]])"
                ]
            ]
        },
        {
            "exception": "Sizes of tensors must match except in dimension 0. Expected size 1280 but got size 768 for tensor number 1 in the list.",
            "traceback": [
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\call_queue.py, line 36, f",
                    "res = func(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\txt2img.py, line 55, txt2img",
                    "processed = processing.process_images(p)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 734, process_images",
                    "res = process_images_inner(p)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-controlnet\\scripts\\batch_hijack.py, line 42, processing_process_images_hijack",
                    "return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 857, process_images_inner",
                    "p.setup_conds()"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 1308, setup_conds",
                    "super().setup_conds()"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 470, setup_conds",
                    "self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\processing.py, line 455, get_conds_with_caching",
                    "cache[1] = function(shared.sd_model, required_prompts, steps, hires_steps, shared.opts.use_old_scheduling)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\prompt_parser.py, line 261, get_multicond_learned_conditioning",
                    "learned_conditioning = get_learned_conditioning(model, prompt_flat_list, steps, hires_steps, use_old_scheduling)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\prompt_parser.py, line 188, get_learned_conditioning",
                    "conds = model.get_learned_conditioning(texts)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_models_xl.py, line 31, get_learned_conditioning",
                    "c = self.conditioner(sdxl_conds, force_zero_embeddings=['txt'] if force_zero_negative_prompt else [])"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1538, _call_impl",
                    "result = forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\repositories\\generative-models\\sgm\\modules\\encoders\\modules.py, line 141, forward",
                    "emb_out = embedder(batch[embedder.input_key])"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack_clip.py, line 234, forward",
                    "z = self.process_tokens(tokens, multipliers)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack_clip.py, line 273, process_tokens",
                    "z = self.encode_with_transformers(tokens)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack_open_clip.py, line 57, encode_with_transformers",
                    "d = self.wrapped.encode_with_transformer(tokens)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\repositories\\generative-models\\sgm\\modules\\encoders\\modules.py, line 467, encode_with_transformer",
                    "x = self.model.token_embedding(text)  # [batch_size, n_ctx, d_model]"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\system\\python\\lib\\site-packages\\torch\\nn\\modules\\module.py, line 1501, _call_impl",
                    "return forward_call(*args, **kwargs)"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\sd_hijack.py, line 359, forward",
                    "tensor = torch.cat([tensor[0:offset + 1], emb[0:emb_len], tensor[offset + 1 + emb_len:]])"
                ]
            ]
        },
        {
            "exception": "Expecting value: line 1 column 1 (char 0)",
            "traceback": [
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\ui_common.py, line 50, save_files",
                    "data = json.loads(js_data)"
                ],
                [
                    "json\\__init__.py, line 346, loads",
                    ""
                ],
                [
                    "json\\decoder.py, line 337, decode",
                    ""
                ],
                [
                    "json\\decoder.py, line 355, raw_decode",
                    ""
                ]
            ]
        },
        {
            "exception": "Expecting value: line 1 column 1 (char 0)",
            "traceback": [
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\call_queue.py, line 57, f",
                    "res = list(func(*args, **kwargs))"
                ],
                [
                    "C:\\AI\\Image AI\\SDNEW\\webui\\modules\\ui_common.py, line 50, save_files",
                    "data = json.loads(js_data)"
                ],
                [
                    "json\\__init__.py, line 346, loads",
                    ""
                ],
                [
                    "json\\decoder.py, line 337, decode",
                    ""
                ],
                [
                    "json\\decoder.py, line 355, raw_decode",
                    ""
                ]
            ]
        }
    ],
    "CPU": {
        "model": "Intel64 Family 6 Model 94 Stepping 3, GenuineIntel",
        "count logical": 8,
        "count physical": 4
    },
    "RAM": {
        "total": "32GB",
        "used": "26GB",
        "free": "6GB"
    },
    "Extensions": [
        {
            "name": "a1111-sd-webui-tagcomplete",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\a1111-sd-webui-tagcomplete",
            "version": "231b121f",
            "branch": "main",
            "remote": "https://github.com/DominikDoom/a1111-sd-webui-tagcomplete.git"
        },
        {
            "name": "adetailer",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\adetailer",
            "version": "92692191",
            "branch": "main",
            "remote": "https://github.com/Bing-su/adetailer.git"
        },
        {
            "name": "clip-interrogator-ext",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\clip-interrogator-ext",
            "version": "0f1a4591",
            "branch": "main",
            "remote": "https://github.com/pharmapsychotic/clip-interrogator-ext.git"
        },
        {
            "name": "sd-webui-aspect-ratio-helper",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-aspect-ratio-helper",
            "version": "99fcf9b0",
            "branch": "main",
            "remote": "https://github.com/thomasasfk/sd-webui-aspect-ratio-helper.git"
        },
        {
            "name": "sd-webui-controlnet",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-controlnet",
            "version": "a52e607b",
            "branch": "main",
            "remote": "https://github.com/Mikubill/sd-webui-controlnet.git"
        },
        {
            "name": "sd-webui-deepdanbooru-object-recognition",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-deepdanbooru-object-recognition",
            "version": "5b3e7cbf",
            "branch": "main",
            "remote": "https://github.com/Jibaku789/sd-webui-deepdanbooru-object-recognition.git"
        },
        {
            "name": "sd-webui-prompt-all-in-one",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-prompt-all-in-one",
            "version": "658ae822",
            "branch": "main",
            "remote": "https://github.com/Physton/sd-webui-prompt-all-in-one"
        },
        {
            "name": "sd-webui-reactor",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-reactor",
            "version": "4b1cfc70",
            "branch": "main",
            "remote": "https://github.com/Gourieff/sd-webui-reactor"
        },
        {
            "name": "sd-webui-segment-anything",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-segment-anything",
            "version": "d80220ec",
            "branch": "master",
            "remote": "https://github.com/continue-revolution/sd-webui-segment-anything.git"
        },
        {
            "name": "sdwebui-close-confirmation-dialogue",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sdwebui-close-confirmation-dialogue",
            "version": "f7cfa87d",
            "branch": "main",
            "remote": "https://github.com/w-e-w/sdwebui-close-confirmation-dialogue.git"
        },
        {
            "name": "stable-diffusion-webui-model-toolkit",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\stable-diffusion-webui-model-toolkit",
            "version": "cf824587",
            "branch": "master",
            "remote": "https://github.com/arenasys/stable-diffusion-webui-model-toolkit.git"
        }
    ],
    "Inactive extensions": [
        {
            "name": "sd-webui-animatediff",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd-webui-animatediff",
            "version": "55ecff36",
            "branch": "master",
            "remote": "https://github.com/continue-revolution/sd-webui-animatediff.git"
        },
        {
            "name": "sd_smartprocess-subfolder-upscale",
            "path": "C:\\AI\\Image AI\\SDNEW\\webui\\extensions\\sd_smartprocess-subfolder-upscale",
            "version": "5750d94f",
            "branch": "main",
            "remote": "https://github.com/baejun10/sd_smartprocess-subfolder-upscale"
        }
    ],
    "Environment": {
        "COMMANDLINE_ARGS": " --listen --enable-insecure-extension-access --reinstall-xformers --xformers --no-half --no-half-vae --medvram --medvram-sdxl --update-all-extensions ",
        "GRADIO_ANALYTICS_ENABLED": "False",
        "XFORMERS_PACKAGE": "xformers==0.0.21"
    },
    "Config": {
        "samples_save": true,
        "samples_format": "jpg",
        "samples_filename_pattern": "",
        "save_images_add_number": true,
        "grid_save": false,
        "grid_format": "png",
        "grid_extended_filename": false,
        "grid_only_if_multiple": true,
        "grid_prevent_empty_spots": false,
        "grid_zip_filename_pattern": "",
        "n_rows": -1,
        "font": "",
        "grid_text_active_color": "#000000",
        "grid_text_inactive_color": "#999999",
        "grid_background_color": "#ffffff",
        "enable_pnginfo": true,
        "save_txt": true,
        "save_images_before_face_restoration": false,
        "save_images_before_highres_fix": true,
        "save_images_before_color_correction": false,
        "save_mask": false,
        "save_mask_composite": false,
        "jpeg_quality": 80,
        "webp_lossless": false,
        "export_for_4chan": true,
        "img_downscale_threshold": 4.0,
        "target_side_length": 4000,
        "img_max_size_mp": 200,
        "use_original_name_batch": true,
        "use_upscaler_name_as_suffix": false,
        "save_selected_only": true,
        "save_init_img": false,
        "temp_dir": "",
        "clean_temp_dir_at_start": false,
        "save_incomplete_images": false,
        "outdir_samples": "P:\\imgsrc\\SD images",
        "outdir_txt2img_samples": "outputs/txt2img-images",
        "outdir_img2img_samples": "outputs/img2img-images",
        "outdir_extras_samples": "outputs/extras-images",
        "outdir_grids": "",
        "outdir_txt2img_grids": "outputs/txt2img-grids",
        "outdir_img2img_grids": "outputs/img2img-grids",
        "outdir_save": "log/images",
        "outdir_init_images": "outputs/init-images",
        "save_to_dirs": true,
        "grid_save_to_dirs": true,
        "use_save_to_dirs_for_ui": false,
        "directories_filename_pattern": "[date]",
        "directories_max_prompt_words": 11,
        "ESRGAN_tile": 192,
        "ESRGAN_tile_overlap": 11,
        "realesrgan_enabled_models": [
            "R-ESRGAN 4x+",
            "R-ESRGAN 4x+ Anime6B"
        ],
        "upscaler_for_img2img": "4x-UltraSharp",
        "face_restoration": false,
        "face_restoration_model": "CodeFormer",
        "code_former_weight": 0.5,
        "face_restoration_unload": false,
        "auto_launch_browser": "Disable",
        "show_warnings": false,
        "show_gradio_deprecation_warnings": true,
        "memmon_poll_rate": 8,
        "samples_log_stdout": false,
        "multiple_tqdm": true,
        "print_hypernet_extra": false,
        "list_hidden_files": true,
        "disable_mmap_load_safetensors": false,
        "hide_ldm_prints": true,
        "api_enable_requests": true,
        "api_forbid_local_requests": true,
        "api_useragent": "",
        "unload_models_when_training": false,
        "pin_memory": false,
        "save_optimizer_state": false,
        "save_training_settings_to_txt": true,
        "dataset_filename_word_regex": "",
        "dataset_filename_join_string": " ",
        "training_image_repeats_per_epoch": 1,
        "training_write_csv_every": 500,
        "training_xattention_optimizations": false,
        "training_enable_tensorboard": false,
        "training_tensorboard_save_images": false,
        "training_tensorboard_flush_every": 120,
        "sd_model_checkpoint": "SDXL_1.0\\OpenDalleV1.1.safetensors [673887ace8]",
        "sd_checkpoints_limit": 2,
        "sd_checkpoints_keep_in_cpu": true,
        "sd_checkpoint_cache": 0,
        "sd_unet": "Automatic",
        "enable_quantization": false,
        "enable_emphasis": true,
        "enable_batch_seeds": true,
        "comma_padding_backtrack": 20,
        "CLIP_stop_at_last_layers": 2,
        "upcast_attn": true,
        "randn_source": "GPU",
        "tiling": false,
        "hires_fix_refiner_pass": "second pass",
        "sdxl_crop_top": 0,
        "sdxl_crop_left": 0,
        "sdxl_refiner_low_aesthetic_score": 2.5,
        "sdxl_refiner_high_aesthetic_score": 6.0,
        "sd_vae_explanation": "<abbr title='Variational autoencoder'>VAE</abbr> is a neural network that transforms a standard <abbr title='red/green/blue'>RGB</abbr>\nimage into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling\n(i.e. when the progress bar is between empty and full). For txt2img, VAE is used to create a resulting image after the sampling is finished.\nFor img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling.",
        "sd_vae_checkpoint_cache": 0,
        "sd_vae": "None",
        "sd_vae_overrides_per_model_preferences": true,
        "auto_vae_precision": true,
        "sd_vae_encode_method": "Full",
        "sd_vae_decode_method": "Full",
        "inpainting_mask_weight": 1.0,
        "initial_noise_multiplier": 1.0,
        "img2img_extra_noise": 0.0,
        "img2img_color_correction": true,
        "img2img_fix_steps": false,
        "img2img_background_color": "#ffffff",
        "img2img_editor_height": 720,
        "img2img_sketch_default_brush_color": "#ffffff",
        "img2img_inpaint_mask_brush_color": "#ffffff",
        "img2img_inpaint_sketch_default_brush_color": "#ffffff",
        "return_mask": false,
        "return_mask_composite": false,
        "cross_attention_optimization": "Automatic",
        "s_min_uncond": 0.0,
        "token_merging_ratio": 0.0,
        "token_merging_ratio_img2img": 0.0,
        "token_merging_ratio_hr": 0.0,
        "pad_cond_uncond": true,
        "persistent_cond_cache": true,
        "batch_cond_uncond": true,
        "use_old_emphasis_implementation": false,
        "use_old_karras_scheduler_sigmas": false,
        "no_dpmpp_sde_batch_determinism": false,
        "use_old_hires_fix_width_height": false,
        "dont_fix_second_order_samplers_schedule": false,
        "hires_fix_use_firstpass_conds": false,
        "use_old_scheduling": false,
        "interrogate_keep_models_in_memory": false,
        "interrogate_return_ranks": false,
        "interrogate_clip_num_beams": 1,
        "interrogate_clip_min_length": 24,
        "interrogate_clip_max_length": 180,
        "interrogate_clip_dict_limit": 1500,
        "interrogate_clip_skip_categories": [],
        "interrogate_deepbooru_score_threshold": 0.5,
        "deepbooru_sort_alpha": true,
        "deepbooru_use_spaces": true,
        "deepbooru_escape": true,
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        "extra_networks_show_hidden_directories": true,
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        "insightface==0.7.3",
        "iopath==0.1.9",
        "ipython==8.6.0",
        "jedi==0.19.1",
        "jinja2==3.1.2",
        "jmespath==0.10.0",
        "joblib==1.3.2",
        "jsonmerge==1.8.0",
        "jsonschema-specifications==2023.7.1",
        "jsonschema==4.19.1",
        "keras==2.15.0",
        "kiwisolver==1.4.5",
        "kornia==0.6.7",
        "lark==1.1.2",
        "lazy-loader==0.3",
        "libclang==16.0.6",
        "lightning-utilities==0.9.0",
        "llvmlite==0.41.0",
        "lmdb==1.4.1",
        "lpips==0.1.4",
        "lxml==4.9.3",
        "mapbox-earcut==1.0.1",
        "markdown-it-py==3.0.0",
        "markdown==3.4.4",
        "markupsafe==2.1.3",
        "matplotlib-inline==0.1.6",
        "matplotlib==3.8.0",
        "mdurl==0.1.2",
        "mediapipe==0.10.9",
        "ml-dtypes==0.2.0",
        "mpmath==1.3.0",
        "multidict==6.0.4",
        "multiprocess==0.70.15",
        "networkx==3.1",
        "numba==0.58.0",
        "numpy==1.23.5",
        "nvidia-cublas-cu11==11.11.3.6",
        "nvidia-cuda-nvrtc-cu11==11.8.89",
        "nvidia-cuda-runtime-cu11==11.8.89",
        "oauthlib==3.2.2",
        "omegaconf==2.2.3",
        "onnx-graphsurgeon==0.3.27",
        "onnx==1.14.1",
        "onnxruntime-gpu==1.16.1",
        "onnxruntime==1.15.1",
        "open-clip-torch==2.20.0",
        "openai==0.28.0",
        "opencv-contrib-python==4.8.0.76",
        "opencv-python-headless==4.8.0.76",
        "opencv-python==4.8.0.76",
        "opt-einsum==3.3.0",
        "orjson==3.9.7",
        "packaging==23.1",
        "pandas==2.1.1",
        "parso==0.8.3",
        "pathos==0.3.1",
        "pickleshare==0.7.5",
        "piexif==1.1.3",
        "pillow==9.5.0",
        "pip==23.2.1",
        "platformdirs==3.10.0",
        "polygraphy==0.49.0",
        "portalocker==2.8.2",
        "pox==0.3.3",
        "ppft==1.7.6.7",
        "prettytable==3.9.0",
        "prompt-toolkit==3.0.41",
        "protobuf==3.20.3",
        "psutil==5.9.5",
        "pure-eval==0.2.2",
        "py-cpuinfo==9.0.0",
        "pyasn1-modules==0.3.0",
        "pyasn1==0.5.0",
        "pycollada==0.8",
        "pycparser==2.21",
        "pydantic==1.10.12",
        "pydub==0.25.1",
        "pyexecjs==1.5.1",
        "pygifsicle==1.0.7",
        "pygments==2.16.1",
        "pyparsing==3.1.1",
        "pyreadline3==3.4.1",
        "pysocks==1.7.1",
        "python-dateutil==2.8.2",
        "python-multipart==0.0.6",
        "pytorch-lightning==1.9.4",
        "pytz==2023.3.post1",
        "pywavelets==1.4.1",
        "pywin32==306",
        "pyyaml==6.0.1",
        "qudida==0.0.4",
        "realesrgan==0.3.0",
        "referencing==0.30.2",
        "regex==2023.8.8",
        "reportlab==4.0.5",
        "requests-oauthlib==1.3.1",
        "requests==2.31.0",
        "resize-right==0.0.2",
        "rich==13.5.3",
        "rpds-py==0.10.3",
        "rsa==4.9",
        "rtree==1.1.0",
        "s3transfer==0.6.2",
        "safetensors==0.3.1",
        "scikit-image==0.21.0",
        "scikit-learn==1.3.1",
        "scipy==1.11.2",
        "seaborn==0.12.1",
        "segment-anything==1.0",
        "semantic-version==2.10.0",
        "sentencepiece==0.1.99",
        "setuptools==68.2.2",
        "shapely==2.0.2",
        "six==1.16.0",
        "smmap==5.0.1",
        "sniffio==1.3.0",
        "sounddevice==0.4.6",
        "soupsieve==2.5",
        "stack-data==0.6.3",
        "starlette==0.26.1",
        "supervision==0.15.0",
        "support-developer==1.0.5",
        "svg.path==6.3",
        "svglib==1.5.1",
        "sympy==1.12",
        "tabulate==0.9.0",
        "tb-nightly==2.15.0a20230922",
        "tensorboard-data-server==0.7.1",
        "tensorboard==2.15.1",
        "tensorflow-estimator==2.15.0",
        "tensorflow-intel==2.15.0",
        "tensorflow-io-gcs-filesystem==0.31.0",
        "tensorflow==2.15.0",
        "tensorrt-bindings==9.0.1.post11.dev4",
        "tensorrt-libs==9.0.1.post11.dev4",
        "tensorrt==9.0.1.post11.dev4",
        "termcolor==2.3.0",
        "thop==0.1.1.post2209072238",
        "threadpoolctl==3.2.0",
        "tifffile==2023.9.18",
        "timm==0.9.2",
        "tinycss2==1.2.1",
        "tokenizers==0.13.3",
        "tomesd==0.1.3",
        "tomli==2.0.1",
        "toolz==0.12.0",
        "torch==2.0.1+cu118",
        "torchdiffeq==0.2.3",
        "torchmetrics==1.1.2",
        "torchsde==0.2.6",
        "torchvision==0.15.2+cu118",
        "tqdm==4.66.1",
        "traitlets==5.13.0",
        "trampoline==0.1.2",
        "transformers==4.30.2",
        "trimesh==4.0.8",
        "typing-extensions==4.8.0",
        "tzdata==2023.3",
        "ultralytics==8.0.232",
        "urllib3==1.26.16",
        "uvicorn==0.23.2",
        "wcwidth==0.2.6",
        "webencodings==0.5.1",
        "websockets==11.0.3",
        "werkzeug==2.3.7",
        "wheel==0.41.2",
        "wrapt==1.14.1",
        "xformers==0.0.20",
        "xxhash==3.4.1",
        "yacs==0.1.8",
        "yapf==0.40.1",
        "yarl==1.9.2",
        "zipp==3.17.0"
    ]
}

### Console logs

```Shell
** Error completing request                                                                     | 0/20 [00:00<?, ?it/s]
*** Arguments: ('task(tleklbpm7ss5nel)', "A highres photo of a beautiful Irish girl with long voluminous straight brown hair and green eyes, on top of a tall building,with a cityscape behind her.  There's a stunning bokeh effect in the background,", 'fat,ugly,visible hands,daytime,daylight,', [], 15, 'DPM++ 2M Karras', 1, 2, 9, 576, 1032, True, 0.67, 1.25, '4x-UltraSharp', 20, 0, 0, 'realisticVisionV60B1_v50VAE [df24466969]', 'Use same sampler', '', '', ['Face restoration: True'], <gradio.routes.Request object at 0x000001C317181D20>, 0, False, '', 0.8, -1, True, -1, 0.86, 0, 0, False, 'CodeFormer', 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': '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': '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': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', inpaint_crop_input_image=False, hr_option='Both', save_detected_map=True, advanced_weighting=None), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', inpaint_crop_input_image=False, hr_option='Both', save_detected_map=True, advanced_weighting=None), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', inpaint_crop_input_image=False, hr_option='Both', save_detected_map=True, advanced_weighting=None), None, True, '0', '0', 'inswapper_128.onnx', 'CodeFormer', 1, True, '8x_NMKD-Faces_160000_G', 4.4, 1, False, True, 1, 0, 0, False, 0.5, True, False, 'CPU', True, 1, 'Kelly2.safetensors', '', None, False, False, 0, None, [], 0, False, [], [], False, 0, 1, False, False, 0, None, [], -2, False, [], False, 0, None, None, False, False, 'positive', 'comma', 0, False, False, 'start', '', 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 "C:\AI\Image AI\SDNEW\webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "C:\AI\Image AI\SDNEW\webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "C:\AI\Image AI\SDNEW\webui\modules\txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "C:\AI\Image AI\SDNEW\webui\modules\processing.py", line 734, in process_images
        res = process_images_inner(p)
      File "C:\AI\Image AI\SDNEW\webui\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 "C:\AI\Image AI\SDNEW\webui\modules\processing.py", line 857, in process_images_inner
        p.setup_conds()
      File "C:\AI\Image AI\SDNEW\webui\modules\processing.py", line 1308, in setup_conds
        super().setup_conds()
      File "C:\AI\Image AI\SDNEW\webui\modules\processing.py", line 470, in setup_conds
        self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data)
      File "C:\AI\Image AI\SDNEW\webui\modules\processing.py", line 455, in get_conds_with_caching
        cache[1] = function(shared.sd_model, required_prompts, steps, hires_steps, shared.opts.use_old_scheduling)
      File "C:\AI\Image AI\SDNEW\webui\modules\prompt_parser.py", line 261, in get_multicond_learned_conditioning
        learned_conditioning = get_learned_conditioning(model, prompt_flat_list, steps, hires_steps, use_old_scheduling)
      File "C:\AI\Image AI\SDNEW\webui\modules\prompt_parser.py", line 188, in get_learned_conditioning
        conds = model.get_learned_conditioning(texts)
      File "C:\AI\Image AI\SDNEW\webui\modules\sd_models_xl.py", line 31, in get_learned_conditioning
        c = self.conditioner(sdxl_conds, force_zero_embeddings=['txt'] if force_zero_negative_prompt else [])
      File "C:\AI\Image AI\SDNEW\system\python\lib\site-packages\torch\nn\modules\module.py", line 1538, in _call_impl
        result = forward_call(*args, **kwargs)
      File "C:\AI\Image AI\SDNEW\webui\repositories\generative-models\sgm\modules\encoders\modules.py", line 141, in forward
        emb_out = embedder(batch[embedder.input_key])
      File "C:\AI\Image AI\SDNEW\system\python\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\AI\Image AI\SDNEW\webui\modules\sd_hijack_clip.py", line 234, in forward
        z = self.process_tokens(tokens, multipliers)
      File "C:\AI\Image AI\SDNEW\webui\modules\sd_hijack_clip.py", line 273, in process_tokens
        z = self.encode_with_transformers(tokens)
      File "C:\AI\Image AI\SDNEW\webui\modules\sd_hijack_open_clip.py", line 57, in encode_with_transformers
        d = self.wrapped.encode_with_transformer(tokens)
      File "C:\AI\Image AI\SDNEW\webui\repositories\generative-models\sgm\modules\encoders\modules.py", line 467, in encode_with_transformer
        x = self.model.token_embedding(text)  # [batch_size, n_ctx, d_model]
      File "C:\AI\Image AI\SDNEW\system\python\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\AI\Image AI\SDNEW\webui\modules\sd_hijack.py", line 359, in forward
        tensor = torch.cat([tensor[0:offset + 1], emb[0:emb_len], tensor[offset + 1 + emb_len:]])
    RuntimeError: Sizes of tensors must match except in dimension 0. Expected size 1280 but got size 768 for tensor number 1 in the list.
```


### Additional information

_No response_