diff --git a/TODO.md b/TODO.md
index 10ba415fb..e543fe3b6 100644
--- a/TODO.md
+++ b/TODO.md
@@ -55,3 +55,4 @@ Tech that can be integrated as part of the core workflow...
 - localization
 - docker
 - port `p.all_hr_prompts`
+- test `lyco_patch_lora`
diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py
index e650f469f..cd61c5175 100644
--- a/extensions-builtin/Lora/scripts/lora_script.py
+++ b/extensions-builtin/Lora/scripts/lora_script.py
@@ -61,11 +61,6 @@ shared.options_templates.update(shared.options_section(('extra_networks', "Extra
 }))
 
 
-shared.options_templates.update(shared.options_section(('compatibility', "Compatibility"), {
-    "lora_functional": shared.OptionInfo(False, "Lora: use old method that takes longer when you have multiple Loras active and produces same results as kohya-ss/sd-webui-additional-networks extension"),
-}))
-
-
 def create_lora_json(obj: lora.LoraOnDisk):
     return {
         "name": obj.name,
diff --git a/javascript/style.css b/javascript/style.css
index af4680a42..4c667d584 100644
--- a/javascript/style.css
+++ b/javascript/style.css
@@ -227,7 +227,7 @@ div#extras_scale_to_tab div.form{
     float: left;
     display: block;
     margin-left: 0;
-    width: 10em;
+    width: 14em;
 }
 
 #settings > div.tab-nav button{
diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index 6e658f6c9..8ed2b0dd7 100644
--- a/modules/cmd_args.py
+++ b/modules/cmd_args.py
@@ -90,6 +90,7 @@ def compatibility_args(opts, args):
     group.add_argument("--sub-quad-chunk-threshold", help=argparse.SUPPRESS, default=opts.sub_quad_chunk_threshold)
     group.add_argument("--lora-dir", help=argparse.SUPPRESS, default=opts.lora_dir)
     group.add_argument("--lyco-dir", help=argparse.SUPPRESS, default=opts.lyco_dir)
+    group.add_argument("--lyco-patch-lora", help=argparse.SUPPRESS, default=opts.lyco_patch_lora)
     group.add_argument("--enable-console-prompts", help=argparse.SUPPRESS, action='store_true', default=False)
     group.add_argument("--safe", help=argparse.SUPPRESS, action='store_true', default=False)
 
diff --git a/modules/shared.py b/modules/shared.py
index 9a51316bf..c29be04ae 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -282,22 +282,43 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_checkpoint_cache": OptionInfo(0, "Number of cached model checkpoints", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     "sd_vae_checkpoint_cache": OptionInfo(0, "Number of cached VAE checkpoints", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     "sd_vae": OptionInfo("Automatic", "Select VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list),
-    "sd_vae_sliced_encode": OptionInfo(False, "During HR fix, encode each image in a batch separately"),
+    "sd_vae_sliced_encode": OptionInfo(False, "Enable splitting of hires batch processing"),
     "stream_load": OptionInfo(False, "When loading models attempt stream loading optimized for slow or network storage"),
     "model_reuse_dict": OptionInfo(False, "When loading models attempt to reuse previous model dictionary"),
     "cross_attention_optimization": OptionInfo(cross_attention_optimization_default, "Cross-attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention() }),
     "cross_attention_options": OptionInfo([], "Cross-attention advanced options", gr.CheckboxGroup, lambda: {"choices": ['xFormers enable flash Attention', 'SDP disable memory attention']}),
-    "sub_quad_q_chunk_size": OptionInfo(512, "Sub-quadratic cross-attention query chunk size for the  layer optimization to use", gr.Slider, {"minimum": 16, "maximum": 8192, "step": 8}),
-    "sub_quad_kv_chunk_size": OptionInfo(512, "Sub-quadratic cross-attentionkv chunk size for the sub-quadratic cross-attention layer optimization to use", gr.Slider, {"minimum": 0, "maximum": 8192, "step": 8}),
-    "sub_quad_chunk_threshold": OptionInfo(80, "Sub-quadratic cross-attention percentage of VRAM chunking threshold", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1}),
+    "sub_quad_q_chunk_size": OptionInfo(512, "Sub-quadratic cross-attention query chunk size", gr.Slider, {"minimum": 16, "maximum": 8192, "step": 8}),
+    "sub_quad_kv_chunk_size": OptionInfo(512, "Sub-quadratic cross-attention kv chunk size", gr.Slider, {"minimum": 0, "maximum": 8192, "step": 8}),
+    "sub_quad_chunk_threshold": OptionInfo(80, "Sub-quadratic cross-attention chunking threshold", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1}),
     "prompt_attention": OptionInfo("Full parser", "Prompt attention parser", gr.Radio, lambda: {"choices": ["Full parser", "Compel parser", "A1111 parser", "Fixed attention"] }),
     "prompt_mean_norm": OptionInfo(True, "Prompt attention mean normalization"),
-    "always_batch_cond_uncond": OptionInfo(False, "Disables conditional batching that is enabled to save memory with --medvram or --lowvram"),
+    "always_batch_cond_uncond": OptionInfo(False, "Disable conditional batching enabled on low memory systems"),
     "enable_quantization": OptionInfo(True, "Enable samplers quantization for sharper and cleaner results"),
     "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
     "sd_backend": OptionInfo("Original", "Stable Diffusion backend (experimental)", gr.Radio, lambda: {"choices": ["Original", "Diffusers"] }),
 }))
 
+options_templates.update(options_section(('cuda', "Compute Settings"), {
+    "memmon_poll_rate": OptionInfo(2, "VRAM usage polls per second during generation", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
+    "precision": OptionInfo("Autocast", "Precision type", gr.Radio, lambda: {"choices": ["Autocast", "Full"]}),
+    "cuda_dtype": OptionInfo("FP32" if sys.platform == "darwin" else "FP16", "Device precision type", gr.Radio, lambda: {"choices": ["FP32", "FP16", "BF16"]}),
+    "no_half": OptionInfo(False, "Use full precision for model (--no-half)", None, None, None),
+    "no_half_vae": OptionInfo(False, "Use full precision for VAE (--no-half-vae)"),
+    "upcast_sampling": OptionInfo(True if sys.platform == "darwin" or cmd_opts.use_ipex else False, "Enable upcast sampling"),
+    "upcast_attn": OptionInfo(False, "Enable upcast cross attention layer"),
+    "disable_nan_check": OptionInfo(True, "Disable NaN check in produced images/latent spaces"),
+    "rollback_vae": OptionInfo(False, "Attempt to roll back VAE when produced NaN values, requires NaN check (experimental)"),
+    "opt_channelslast": OptionInfo(False, "Use channels last as torch memory format "),
+    "cudnn_benchmark": OptionInfo(False, "Enable full-depth cuDNN benchmark feature"),
+    "cuda_allow_tf32": OptionInfo(True, "Allow TF32 math ops"),
+    "cuda_allow_tf16_reduced": OptionInfo(True, "Allow TF16 reduced precision math ops"),
+    "cuda_compile": OptionInfo(False, "Enable model compile (experimental)"),
+    "cuda_compile_mode": OptionInfo("none", "Model compile mode (experimental)", gr.Radio, lambda: {"choices": ['none', 'inductor', 'cudagraphs', 'aot_ts_nvfuser', 'hidet', 'ipex']}),
+    "cuda_compile_verbose": OptionInfo(False, "Model compile verbose mode"),
+    "cuda_compile_errors": OptionInfo(True, "Model compile suppress errors"),
+    "disable_gc": OptionInfo(False, "Disable Torch memory garbage collection (experimental)"),
+}))
+
 options_templates.update(options_section(('system-paths', "System Paths"), {
     "temp_dir": OptionInfo("", "Directory for temporary images; leave empty for default"),
     "clean_temp_dir_at_start": OptionInfo(True, "Cleanup non-default temporary directory when starting webui"),
@@ -353,16 +374,16 @@ options_templates.update(options_section(('saving-images', "Image Options"), {
 }))
 
 options_templates.update(options_section(('image-processing', "Image Processing"), {
-    "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors"),
-    "img2img_fix_steps": OptionInfo(False, "For image processing do exactly the amount of steps as specified"),
-    "img2img_background_color": OptionInfo("#ffffff", "With img2img fill image's transparent parts with this color", ui_components.FormColorPicker, {}),
+    "img2img_color_correction": OptionInfo(False, "Apply color correction to match original colors"),
+    "img2img_fix_steps": OptionInfo(False, "For image processing do exact number of steps as specified"),
+    "img2img_background_color": OptionInfo("#ffffff", "Image transparent color fill", ui_components.FormColorPicker, {}),
     "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.1, "maximum": 1.5, "step": 0.01}),
+    "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for image processing", gr.Slider, {"minimum": 0.1, "maximum": 1.5, "step": 0.01}),
     "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 8, "step": 1, "visible": False}),
 }))
 
 
-options_templates.update(options_section(('saving-paths', "Image Paths"), {
+options_templates.update(options_section(('saving-paths', "Output Paths"), {
     "outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs),
     "outdir_txt2img_samples": OptionInfo("outputs/text", 'Output directory for txt2img images', component_args=hide_dirs),
     "outdir_img2img_samples": OptionInfo("outputs/image", 'Output directory for img2img images', component_args=hide_dirs),
@@ -374,83 +395,6 @@ options_templates.update(options_section(('saving-paths', "Image Paths"), {
     "outdir_init_images": OptionInfo("outputs/init-images", "Directory for saving init images when using img2img", component_args=hide_dirs),
 }))
 
-options_templates.update(options_section(('cuda', "Compute Settings"), {
-    "memmon_poll_rate": OptionInfo(2, "VRAM usage polls per second during generation", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
-    "precision": OptionInfo("Autocast", "Precision type", gr.Radio, lambda: {"choices": ["Autocast", "Full"]}),
-    "cuda_dtype": OptionInfo("FP32" if sys.platform == "darwin" else "FP16", "Device precision type", gr.Radio, lambda: {"choices": ["FP32", "FP16", "BF16"]}),
-    "no_half": OptionInfo(False, "Use full precision for model (--no-half)", None, None, None),
-    "no_half_vae": OptionInfo(False, "Use full precision for VAE (--no-half-vae)"),
-    "upcast_sampling": OptionInfo(True if sys.platform == "darwin" or cmd_opts.use_ipex else False, "Enable upcast sampling"),
-    "upcast_attn": OptionInfo(False, "Enable upcast cross attention layer"),
-    "disable_nan_check": OptionInfo(True, "Disable NaN check in produced images/latent spaces"),
-    "rollback_vae": OptionInfo(False, "Attempt to roll back VAE when produced NaN values, requires NaN check (experimental)"),
-    "opt_channelslast": OptionInfo(False, "Use channels last as torch memory format "),
-    "cudnn_benchmark": OptionInfo(False, "Enable full-depth cuDNN benchmark feature"),
-    "cuda_allow_tf32": OptionInfo(True, "Allow TF32 math ops"),
-    "cuda_allow_tf16_reduced": OptionInfo(True, "Allow TF16 reduced precision math ops"),
-    "cuda_compile": OptionInfo(False, "Enable model compile (experimental)"),
-    "cuda_compile_mode": OptionInfo("none", "Model compile mode (experimental)", gr.Radio, lambda: {"choices": ['none', 'inductor', 'cudagraphs', 'aot_ts_nvfuser', 'hidet', 'ipex']}),
-    "cuda_compile_verbose": OptionInfo(False, "Model compile verbose mode"),
-    "cuda_compile_errors": OptionInfo(True, "Model compile suppress errors"),
-    "disable_gc": OptionInfo(False, "Disable Torch memory garbage collection (experimental)"),
-}))
-
-options_templates.update(options_section(('upscaling', "Upscaling"), {
-    "upscaler_for_img2img": OptionInfo("None", "Default upscaler for image resize operations", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
-    "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Real-ESRGAN available models", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}),
-    "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers (0 = no tiling)", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
-    "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap in pixels for ESRGAN upscalers", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
-    "SCUNET_tile": OptionInfo(256, "Tile size for SCUNET upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
-    "SCUNET_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SCUNET upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}),    
-    "use_old_hires_fix_width_height": OptionInfo(False, "Hires fix uses width & height to set final resolution rather than first pass"),
-    "dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers"),
-}))
-
-options_templates.update(options_section(('face-restoration', "Face restoration"), {
-    "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
-    "code_former_weight": OptionInfo(0.2, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
-    "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
-}))
-
-options_templates.update(options_section(('training', "Training"), {
-    "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible"),
-    "pin_memory": OptionInfo(True, "Pin training dataset to memory"),
-    "save_optimizer_state": OptionInfo(False, "Saves resumable optimizer state when training embedding or hypernetwork"),
-    "save_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts"),
-    "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
-    "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
-    "embeddings_templates_dir": OptionInfo(os.path.join(paths.script_path, 'train', 'templates'), "Embeddings train templates directory"),
-    "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
-    "training_write_csv_every": OptionInfo(0, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
-    "training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging"),
-    "training_tensorboard_save_images": OptionInfo(False, "Save generated images within tensorboard"),
-    "training_tensorboard_flush_every": OptionInfo(120, "How often, in seconds, to flush the pending tensorboard events and summaries to disk"),
-}))
-
-options_templates.update(options_section(('interrogate', "Interrogate Options"), {
-    "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
-    "interrogate_return_ranks": OptionInfo(True, "Interrogate: include ranks of model tags matches in results"),
-    "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
-    "interrogate_clip_min_length": OptionInfo(32, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
-    "interrogate_clip_max_length": OptionInfo(192, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
-    "interrogate_clip_dict_limit": OptionInfo(2048, "CLIP: maximum number of lines in text file (0 = No limit)"),
-    "interrogate_clip_skip_categories": OptionInfo(["artists", "movements", "flavors"], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types),
-    "interrogate_deepbooru_score_threshold": OptionInfo(0.65, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
-    "deepbooru_sort_alpha": OptionInfo(False, "Interrogate: deepbooru sort alphabetically"),
-    "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
-    "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),
-    "deepbooru_filter_tags": OptionInfo("", "filter out those tags from deepbooru output (separated by comma)"),
-}))
-
-options_templates.update(options_section(('extra_networks', "Extra Networks"), {
-    "extra_networks_default_view": OptionInfo("cards", "Default view for Extra Networks", gr.Dropdown, {"choices": ["cards", "thumbs"]}),
-    "extra_networks_default_multiplier": OptionInfo(1.0, "Multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"),
-    "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"),
-    "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"),
-    "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
-}))
-
 options_templates.update(options_section(('ui', "User interface"), {
     "gradio_theme": OptionInfo("black-orange", "UI theme", gr.Dropdown, lambda: {"choices": list_themes()}, refresh=refresh_themes),
     "theme_style": OptionInfo("Auto", "Theme mode", gr.Radio, {"choices": ["Auto", "Dark", "Light"]}),
@@ -484,7 +428,7 @@ options_templates.update(options_section(('ui', "Live previews"), {
     "live_preview_refresh_period": OptionInfo(250, "Progressbar/preview update period, in milliseconds")
 }))
 
-options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
+options_templates.update(options_section(('sampler-params', "Sampler Settings"), {
     "show_samplers": OptionInfo(["Euler a", "UniPC", "DDIM", "DPM++ 2M SDE", "DPM++ 2M SDE Karras", "DPM2 Karras", "DPM++ 2M Karras"], "Show samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers() if x.name != "PLMS"]}),
     "fallback_sampler": OptionInfo("Euler a", "Secondary sampler", gr.Dropdown, lambda: {"choices": ["None"] + [x.name for x in list_samplers()]}),
     "xyz_fallback_sampler": OptionInfo("None", "Force latent upscaler sampler", gr.Dropdown, lambda: {"choices": ["None"] + [x.name for x in list_samplers()]}),
@@ -503,6 +447,73 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"),
 }))
 
+options_templates.update(options_section(('postprocessing', "Postprocessing"), {
+    'postprocessing_enable_in_main_ui': OptionInfo([], "Enable addtional postprocessing operations", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
+    'postprocessing_operation_order': OptionInfo([], "Postprocessing operation order", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
+    'upscaling_max_images_in_cache': OptionInfo(5, "Maximum number of images in upscaling cache", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
+}))
+
+options_templates.update(options_section(('training', "Training"), {
+    "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible"),
+    "pin_memory": OptionInfo(True, "Pin training dataset to memory"),
+    "save_optimizer_state": OptionInfo(False, "Saves resumable optimizer state when training embedding or hypernetwork"),
+    "save_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts"),
+    "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
+    "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
+    "embeddings_templates_dir": OptionInfo(os.path.join(paths.script_path, 'train', 'templates'), "Embeddings train templates directory"),
+    "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
+    "training_write_csv_every": OptionInfo(0, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
+    "training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging"),
+    "training_tensorboard_save_images": OptionInfo(False, "Save generated images within tensorboard"),
+    "training_tensorboard_flush_every": OptionInfo(120, "How often, in seconds, to flush the pending tensorboard events and summaries to disk"),
+}))
+
+options_templates.update(options_section(('interrogate', "Interrogate"), {
+    "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
+    "interrogate_return_ranks": OptionInfo(True, "Interrogate: include ranks of model tags matches in results"),
+    "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
+    "interrogate_clip_min_length": OptionInfo(32, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
+    "interrogate_clip_max_length": OptionInfo(192, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
+    "interrogate_clip_dict_limit": OptionInfo(2048, "CLIP: maximum number of lines in text file (0 = No limit)"),
+    "interrogate_clip_skip_categories": OptionInfo(["artists", "movements", "flavors"], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types),
+    "interrogate_deepbooru_score_threshold": OptionInfo(0.65, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
+    "deepbooru_sort_alpha": OptionInfo(False, "Interrogate: deepbooru sort alphabetically"),
+    "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
+    "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),
+    "deepbooru_filter_tags": OptionInfo("", "filter out those tags from deepbooru output (separated by comma)"),
+}))
+
+options_templates.update(options_section(('upscaling', "Upscaling"), {
+    "upscaler_for_img2img": OptionInfo("None", "Default upscaler for image resize operations", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
+    "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Real-ESRGAN available models", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}),
+    "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers (0 = no tiling)", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
+    "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap in pixels for ESRGAN upscalers", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
+    "SCUNET_tile": OptionInfo(256, "Tile size for SCUNET upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
+    "SCUNET_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SCUNET upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}),    
+    "use_old_hires_fix_width_height": OptionInfo(False, "Hires fix uses width & height to set final resolution rather than first pass"),
+    "dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers"),
+    "lyco_patch_lora": OptionInfo(False, "Use LyCoris handler for all Lora types", gr.Checkbox, { "visible": False }), # TODO: lyco-patch-lora
+    "lora_functional": OptionInfo(False, "Use Kohya method for handling multiple Loras", gr.Checkbox, { "visible": False }),
+}))
+
+# options_templates.update(options_section(('lora', "Lora"), {
+# }))
+
+options_templates.update(options_section(('face-restoration', "Face restoration"), {
+    "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
+    "code_former_weight": OptionInfo(0.2, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
+    "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
+}))
+
+options_templates.update(options_section(('extra_networks', "Extra Networks"), {
+    "extra_networks_default_view": OptionInfo("cards", "Default view for Extra Networks", gr.Dropdown, {"choices": ["cards", "thumbs"]}),
+    "extra_networks_default_multiplier": OptionInfo(1.0, "Multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+    "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"),
+    "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"),
+    "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"),
+    "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
+}))
+
 options_templates.update(options_section(('token_merging', 'Token Merging'), {
     "token_merging": OptionInfo(False, "Enable redundant token merging via tomesd for speed and memory improvements", gr.Checkbox),
     "token_merging_ratio": OptionInfo(0.5, "Token merging Ratio. Higher merging ratio = faster generation, smaller VRAM usage, lower quality.", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1}),
@@ -517,12 +528,6 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), {
     "token_merging_stride_y": OptionInfo(2, "Stride - Y", gr.Slider, {"minimum": 2, "maximum": 8, "step": 2})
 }))
 
-options_templates.update(options_section(('postprocessing', "Postprocessing"), {
-    'postprocessing_enable_in_main_ui': OptionInfo([], "Enable postprocessing operations in txt2img and img2img tabs", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
-    'postprocessing_operation_order': OptionInfo([], "Postprocessing operation order", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
-    'upscaling_max_images_in_cache': OptionInfo(5, "Maximum number of images in upscaling cache", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
-}))
-
 options_templates.update(options_section((None, "Hidden options"), {
     "disabled_extensions": OptionInfo([], "Disable these extensions"),
     "disable_all_extensions": OptionInfo("none", "Disable all extensions (preserves the list of disabled extensions)", gr.Radio, {"choices": ["none", "user", "all"]}),