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import gradio as gr |
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from shared.utils.plugins import WAN2GPPlugin |
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import json |
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class ConfigTabPlugin(WAN2GPPlugin): |
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def __init__(self): |
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super().__init__() |
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self.name = "Configuration Tab" |
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self.version = "1.1.0" |
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self.description = "Lets you adjust all your performance and UI options for WAN2GP" |
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def setup_ui(self): |
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self.request_global("args") |
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self.request_global("server_config") |
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self.request_global("server_config_filename") |
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self.request_global("attention_mode") |
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self.request_global("compile") |
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self.request_global("default_profile") |
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self.request_global("vae_config") |
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self.request_global("boost") |
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self.request_global("preload_model_policy") |
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self.request_global("transformer_quantization") |
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self.request_global("transformer_dtype_policy") |
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self.request_global("transformer_types") |
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self.request_global("text_encoder_quantization") |
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self.request_global("attention_modes_installed") |
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self.request_global("attention_modes_supported") |
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self.request_global("displayed_model_types") |
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self.request_global("memory_profile_choices") |
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self.request_global("save_path") |
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self.request_global("image_save_path") |
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self.request_global("quit_application") |
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self.request_global("release_model") |
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self.request_global("get_sorted_dropdown") |
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self.request_global("app") |
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self.request_global("fl") |
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self.request_global("is_generation_in_progress") |
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self.request_global("generate_header") |
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self.request_global("generate_dropdown_model_list") |
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self.request_global("get_unique_id") |
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self.request_global("enhancer_offloadobj") |
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self.request_component("header") |
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self.request_component("model_family") |
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self.request_component("model_base_type_choice") |
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self.request_component("model_choice") |
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self.request_component("refresh_form_trigger") |
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self.request_component("state") |
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self.request_component("resolution") |
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self.add_tab( |
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tab_id="configuration", |
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label="Configuration", |
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component_constructor=self.create_config_ui, |
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position=4 |
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) |
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def create_config_ui(self): |
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with gr.Column(): |
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with gr.Tabs(): |
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with gr.Tab("General"): |
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_, _, dropdown_choices = self.get_sorted_dropdown(self.displayed_model_types, None, None, False) |
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self.transformer_types_choices = gr.Dropdown( |
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choices=dropdown_choices, value=self.transformer_types, |
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label="Selectable Generative Models (leave empty for all)", multiselect=True |
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) |
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self.model_hierarchy_type_choice = gr.Dropdown( |
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choices=[ |
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("Two Levels: Model Family > Models & Finetunes", 0), |
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("Three Levels: Model Family > Models > Finetunes", 1), |
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], |
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value=self.server_config.get("model_hierarchy_type", 1), |
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label="Models Hierarchy In User Interface", |
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interactive=not self.args.lock_config |
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) |
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self.fit_canvas_choice = gr.Dropdown( |
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choices=[ |
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("Dimensions are Pixel Budget (preserves aspect ratio, may exceed dimensions)", 0), |
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("Dimensions are Max Width/Height (preserves aspect ratio, fits within box)", 1), |
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("Dimensions are Exact Output (crops input to fit exact dimensions)", 2), |
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], |
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value=self.server_config.get("fit_canvas", 0), |
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label="Input Image/Video Sizing Behavior", |
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interactive=not self.args.lock_config |
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) |
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def check_attn(mode): |
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if mode not in self.attention_modes_installed: return " (NOT INSTALLED)" |
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if mode not in self.attention_modes_supported: return " (NOT SUPPORTED)" |
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return "" |
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self.attention_choice = gr.Dropdown( |
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choices=[ |
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("Auto: Best available (sage2 > sage > sdpa)", "auto"), |
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("sdpa: Default, always available", "sdpa"), |
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(f'flash{check_attn("flash")}: High quality, requires manual install', "flash"), |
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(f'xformers{check_attn("xformers")}: Good quality, less VRAM, requires manual install', "xformers"), |
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(f'sage{check_attn("sage")}: ~30% faster, requires manual install', "sage"), |
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(f'sage2/sage2++{check_attn("sage2")}: ~40% faster, requires manual install', "sage2"), |
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] + ([(f'radial{check_attn("radial")}: Experimental, may be faster, requires manual install', "radial")] if self.args.betatest else []) + [ |
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(f'sage3{check_attn("sage3")}: >50% faster, may have quality trade-offs, requires manual install', "sage3"), |
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], |
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value=self.attention_mode, label="Attention Type", interactive=not self.args.lock_config |
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) |
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self.preload_model_policy_choice = gr.CheckboxGroup( |
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[("Preload Model on App Launch","P"), ("Preload Model on Switch", "S"), ("Unload Model when Queue is Done", "U")], |
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value=self.preload_model_policy, label="Model Loading/Unloading Policy" |
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) |
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self.clear_file_list_choice = gr.Dropdown( |
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choices=[("None", 0), ("Keep last video", 1), ("Keep last 5 videos", 5), ("Keep last 10", 10), ("Keep last 20", 20), ("Keep last 30", 30)], |
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value=self.server_config.get("clear_file_list", 5), label="Keep Previous Generations in Gallery" |
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) |
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self.display_stats_choice = gr.Dropdown( |
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choices=[("Disabled", 0), ("Enabled", 1)], |
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value=self.server_config.get("display_stats", 0), label="Display real-time RAM/VRAM stats (requires restart)" |
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) |
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self.max_frames_multiplier_choice = gr.Dropdown( |
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choices=[("Default", 1), ("x2", 2), ("x3", 3), ("x4", 4), ("x5", 5), ("x6", 6), ("x7", 7)], |
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value=self.server_config.get("max_frames_multiplier", 1), label="Max Frames Multiplier (requires restart)" |
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) |
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default_paths = self.fl.default_checkpoints_paths |
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checkpoints_paths_text = "\n".join(self.server_config.get("checkpoints_paths", default_paths)) |
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self.checkpoints_paths_choice = gr.Textbox( |
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label="Model Checkpoint Folders (One Path per Line. First is Default Download Path)", |
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value=checkpoints_paths_text, |
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lines=3, |
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interactive=not self.args.lock_config |
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) |
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self.UI_theme_choice = gr.Dropdown( |
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choices=[("Blue Sky (Default)", "default"), ("Classic Gradio", "gradio")], |
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value=self.server_config.get("UI_theme", "default"), label="UI Theme (requires restart)" |
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) |
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self.queue_color_scheme_choice = gr.Dropdown( |
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choices=[ |
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("Pastel (Unique color for each item)", "pastel"), |
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("Alternating Grey Shades", "alternating_grey"), |
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], |
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value=self.server_config.get("queue_color_scheme", "pastel"), |
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label="Queue Color Scheme" |
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) |
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with gr.Tab("Performance"): |
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self.quantization_choice = gr.Dropdown(choices=[("Scaled Int8 (recommended)", "int8"), ("16-bit (no quantization)", "bf16")], value=self.transformer_quantization, label="Transformer Model Quantization (if available)") |
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self.transformer_dtype_policy_choice = gr.Dropdown(choices=[("Auto (Best for Hardware)", ""), ("FP16", "fp16"), ("BF16", "bf16")], value=self.transformer_dtype_policy, label="Transformer Data Type (if available)") |
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self.mixed_precision_choice = gr.Dropdown(choices=[("16-bit only (less VRAM)", "0"), ("Mixed 16/32-bit (better quality)", "1")], value=self.server_config.get("mixed_precision", "0"), label="Transformer Engine Precision") |
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self.text_encoder_quantization_choice = gr.Dropdown(choices=[("16-bit (more RAM, better quality)", "bf16"), ("8-bit (less RAM, slightly lower quality)", "int8")], value=self.text_encoder_quantization, label="Text Encoder Precision") |
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self.VAE_precision_choice = gr.Dropdown(choices=[("16-bit (faster, less VRAM)", "16"), ("32-bit (slower, better for sliding window)", "32")], value=self.server_config.get("vae_precision", "16"), label="VAE Encoding/Decoding Precision") |
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self.compile_choice = gr.Dropdown(choices=[("On (up to 20% faster, requires Triton)", "transformer"), ("Off", "")], value=self.compile, label="Compile Transformer Model", interactive=not self.args.lock_config) |
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self.depth_anything_v2_variant_choice = gr.Dropdown(choices=[("Large (more precise, slower)", "vitl"), ("Big (less precise, faster)", "vitb")], value=self.server_config.get("depth_anything_v2_variant", "vitl"), label="Depth Anything v2 VACE Preprocessor") |
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self.vae_config_choice = gr.Dropdown(choices=[("Auto", 0), ("Disabled (fastest, high VRAM)", 1), ("256x256 Tiles (for >=8GB VRAM)", 2), ("128x128 Tiles (for >=6GB VRAM)", 3)], value=self.vae_config, label="VAE Tiling (to reduce VRAM usage)") |
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self.boost_choice = gr.Dropdown(choices=[("ON", 1), ("OFF", 2)], value=self.boost, label="Boost (~10% speedup for ~1GB VRAM)") |
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self.profile_choice = gr.Dropdown(choices=self.memory_profile_choices, value=self.default_profile, label="Memory Profile (Advanced)") |
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self.preload_in_VRAM_choice = gr.Slider(0, 40000, value=self.server_config.get("preload_in_VRAM", 0), step=100, label="VRAM (MB) for Preloaded Models (0=profile default)") |
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self.release_RAM_btn = gr.Button("Force Unload Models from RAM") |
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with gr.Tab("Extensions"): |
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self.enhancer_enabled_choice = gr.Dropdown(choices=[("Off", 0), ("Florence 2 + LLama 3.2", 1), ("Florence 2 + Llama Joy (uncensored)", 2)], value=self.server_config.get("enhancer_enabled", 0), label="Prompt Enhancer (requires 8-14GB extra download)") |
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self.enhancer_mode_choice = gr.Dropdown(choices=[("Automatic on Generation", 0), ("On-Demand Button Only", 1)], value=self.server_config.get("enhancer_mode", 0), label="Prompt Enhancer Usage") |
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self.mmaudio_enabled_choice = gr.Dropdown(choices=[("Off", 0), ("Enabled (unloads after use)", 1), ("Enabled (persistent in RAM)", 2)], value=self.server_config.get("mmaudio_enabled", 0), label="MMAudio Soundtrack Generation (requires 10GB extra download)") |
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with gr.Tab("Outputs"): |
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self.video_output_codec_choice = gr.Dropdown(choices=[("x265 CRF 28 (Balanced)", 'libx265_28'), ("x264 Level 8 (Balanced)", 'libx264_8'), ("x265 CRF 8 (High Quality)", 'libx265_8'), ("x264 Level 10 (High Quality)", 'libx264_10'), ("x264 Lossless", 'libx264_lossless')], value=self.server_config.get("video_output_codec", "libx264_8"), label="Video Codec") |
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self.image_output_codec_choice = gr.Dropdown(choices=[("JPEG Q85", 'jpeg_85'), ("WEBP Q85", 'webp_85'), ("JPEG Q95", 'jpeg_95'), ("WEBP Q95", 'webp_95'), ("WEBP Lossless", 'webp_lossless'), ("PNG Lossless", 'png')], value=self.server_config.get("image_output_codec", "jpeg_95"), label="Image Codec") |
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self.audio_output_codec_choice = gr.Dropdown(choices=[("AAC 128 kbit", 'aac_128')], value=self.server_config.get("audio_output_codec", "aac_128"), visible=False, label="Audio Codec to use") |
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self.metadata_choice = gr.Dropdown( |
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choices=[("Export JSON files", "json"), ("Embed metadata in file (Exif/tag)", "metadata"), ("None", "none")], |
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value=self.server_config.get("metadata_type", "metadata"), label="Metadata Handling" |
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) |
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self.embed_source_images_choice = gr.Checkbox( |
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value=self.server_config.get("embed_source_images", False), |
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label="Embed Source Images", |
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info="Saves i2v source images inside MP4 files" |
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) |
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self.video_save_path_choice = gr.Textbox(label="Video Output Folder (requires restart)", value=self.save_path) |
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self.image_save_path_choice = gr.Textbox(label="Image Output Folder (requires restart)", value=self.image_save_path) |
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with gr.Tab("Notifications"): |
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self.notification_sound_enabled_choice = gr.Dropdown(choices=[("On", 1), ("Off", 0)], value=self.server_config.get("notification_sound_enabled", 0), label="Notification Sound") |
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self.notification_sound_volume_choice = gr.Slider(0, 100, value=self.server_config.get("notification_sound_volume", 50), step=5, label="Notification Volume") |
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self.msg = gr.Markdown() |
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with gr.Row(): |
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self.apply_btn = gr.Button("Save Settings") |
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inputs = [ |
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self.state, |
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self.transformer_types_choices, self.model_hierarchy_type_choice, self.fit_canvas_choice, |
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self.attention_choice, self.preload_model_policy_choice, self.clear_file_list_choice, |
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self.display_stats_choice, self.max_frames_multiplier_choice, self.checkpoints_paths_choice, |
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self.UI_theme_choice, self.queue_color_scheme_choice, |
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self.quantization_choice, self.transformer_dtype_policy_choice, self.mixed_precision_choice, |
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self.text_encoder_quantization_choice, self.VAE_precision_choice, self.compile_choice, |
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self.depth_anything_v2_variant_choice, self.vae_config_choice, self.boost_choice, |
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self.profile_choice, self.preload_in_VRAM_choice, |
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self.enhancer_enabled_choice, self.enhancer_mode_choice, self.mmaudio_enabled_choice, |
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self.video_output_codec_choice, self.image_output_codec_choice, self.audio_output_codec_choice, |
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self.metadata_choice, self.embed_source_images_choice, |
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self.video_save_path_choice, self.image_save_path_choice, |
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self.notification_sound_enabled_choice, self.notification_sound_volume_choice, |
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self.resolution |
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] |
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self.apply_btn.click( |
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fn=self._save_changes, |
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inputs=inputs, |
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outputs=[ |
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self.msg, |
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self.header, |
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self.model_family, |
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self.model_base_type_choice, |
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self.model_choice, |
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self.refresh_form_trigger |
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] |
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) |
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def release_ram_and_notify(): |
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self.release_model() |
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gr.Info("Models unloaded from RAM.") |
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self.release_RAM_btn.click(fn=release_ram_and_notify) |
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return [self.release_RAM_btn] |
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def _save_changes(self, state, *args): |
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if self.is_generation_in_progress(): |
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return "<div style='color:red; text-align:center;'>Unable to change config when a generation is in progress.</div>", *[gr.update()]*5 |
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if self.args.lock_config: |
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return "<div style='color:red; text-align:center;'>Configuration is locked by command-line arguments.</div>", *[gr.update()]*5 |
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old_server_config = self.server_config.copy() |
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( |
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transformer_types_choices, model_hierarchy_type_choice, fit_canvas_choice, |
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attention_choice, preload_model_policy_choice, clear_file_list_choice, |
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display_stats_choice, max_frames_multiplier_choice, checkpoints_paths_choice, |
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UI_theme_choice, queue_color_scheme_choice, |
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quantization_choice, transformer_dtype_policy_choice, mixed_precision_choice, |
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text_encoder_quantization_choice, VAE_precision_choice, compile_choice, |
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depth_anything_v2_variant_choice, vae_config_choice, boost_choice, |
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profile_choice, preload_in_VRAM_choice, |
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enhancer_enabled_choice, enhancer_mode_choice, mmaudio_enabled_choice, |
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video_output_codec_choice, image_output_codec_choice, audio_output_codec_choice, |
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metadata_choice, embed_source_images_choice, |
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save_path_choice, image_save_path_choice, |
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notification_sound_enabled_choice, notification_sound_volume_choice, |
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last_resolution_choice |
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) = args |
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if len(checkpoints_paths_choice.strip()) == 0: |
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checkpoints_paths = self.fl.default_checkpoints_paths |
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else: |
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checkpoints_paths = [path.strip() for path in checkpoints_paths_choice.replace("\r", "").split("\n") if len(path.strip()) > 0] |
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self.fl.set_checkpoints_paths(checkpoints_paths) |
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new_server_config = { |
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"attention_mode": attention_choice, "transformer_types": transformer_types_choices, |
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"text_encoder_quantization": text_encoder_quantization_choice, "save_path": save_path_choice, |
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"image_save_path": image_save_path_choice, "compile": compile_choice, "profile": profile_choice, |
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"vae_config": vae_config_choice, "vae_precision": VAE_precision_choice, |
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"mixed_precision": mixed_precision_choice, "metadata_type": metadata_choice, |
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"transformer_quantization": quantization_choice, "transformer_dtype_policy": transformer_dtype_policy_choice, |
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"boost": boost_choice, "clear_file_list": clear_file_list_choice, |
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"preload_model_policy": preload_model_policy_choice, "UI_theme": UI_theme_choice, |
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"fit_canvas": fit_canvas_choice, "enhancer_enabled": enhancer_enabled_choice, |
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"enhancer_mode": enhancer_mode_choice, "mmaudio_enabled": mmaudio_enabled_choice, |
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"preload_in_VRAM": preload_in_VRAM_choice, "depth_anything_v2_variant": depth_anything_v2_variant_choice, |
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"notification_sound_enabled": notification_sound_enabled_choice, |
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"notification_sound_volume": notification_sound_volume_choice, |
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"max_frames_multiplier": max_frames_multiplier_choice, "display_stats": display_stats_choice, |
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"video_output_codec": video_output_codec_choice, "image_output_codec": image_output_codec_choice, |
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"audio_output_codec": audio_output_codec_choice, |
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"model_hierarchy_type": model_hierarchy_type_choice, |
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"checkpoints_paths": checkpoints_paths, |
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"queue_color_scheme": queue_color_scheme_choice, |
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"embed_source_images": embed_source_images_choice, |
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"video_container": "mp4", |
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"last_model_type": state["model_type"], |
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"last_model_per_family": state["last_model_per_family"], |
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"last_model_per_type": state["last_model_per_type"], |
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"last_advanced_choice": state["advanced"], "last_resolution_choice": last_resolution_choice, |
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"last_resolution_per_group": state["last_resolution_per_group"], |
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} |
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if "enabled_plugins" in self.server_config: |
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new_server_config["enabled_plugins"] = self.server_config["enabled_plugins"] |
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if self.args.lock_config: |
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if "attention_mode" in old_server_config: new_server_config["attention_mode"] = old_server_config["attention_mode"] |
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if "compile" in old_server_config: new_server_config["compile"] = old_server_config["compile"] |
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with open(self.server_config_filename, "w", encoding="utf-8") as writer: |
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writer.write(json.dumps(new_server_config, indent=4)) |
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changes = [k for k, v in new_server_config.items() if v != old_server_config.get(k)] |
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no_reload_keys = [ |
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"attention_mode", "vae_config", "boost", "save_path", "image_save_path", |
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"metadata_type", "clear_file_list", "fit_canvas", "depth_anything_v2_variant", |
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"notification_sound_enabled", "notification_sound_volume", "mmaudio_enabled", |
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"max_frames_multiplier", "display_stats", "video_output_codec", "video_container", |
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"embed_source_images", "image_output_codec", "audio_output_codec", "checkpoints_paths", |
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"model_hierarchy_type", "UI_theme", "queue_color_scheme" |
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] |
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needs_reload = not all(change in no_reload_keys for change in changes) |
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self.set_global("server_config", new_server_config) |
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self.set_global("three_levels_hierarchy", new_server_config["model_hierarchy_type"] == 1) |
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self.set_global("attention_mode", new_server_config["attention_mode"]) |
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self.set_global("default_profile", new_server_config["profile"]) |
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self.set_global("compile", new_server_config["compile"]) |
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self.set_global("text_encoder_quantization", new_server_config["text_encoder_quantization"]) |
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self.set_global("vae_config", new_server_config["vae_config"]) |
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self.set_global("boost", new_server_config["boost"]) |
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self.set_global("save_path", new_server_config["save_path"]) |
|
|
self.set_global("image_save_path", new_server_config["image_save_path"]) |
|
|
self.set_global("preload_model_policy", new_server_config["preload_model_policy"]) |
|
|
self.set_global("transformer_quantization", new_server_config["transformer_quantization"]) |
|
|
self.set_global("transformer_dtype_policy", new_server_config["transformer_dtype_policy"]) |
|
|
self.set_global("transformer_types", new_server_config["transformer_types"]) |
|
|
self.set_global("reload_needed", needs_reload) |
|
|
|
|
|
if "enhancer_enabled" in changes or "enhancer_mode" in changes: |
|
|
self.set_global("prompt_enhancer_image_caption_model", None) |
|
|
self.set_global("prompt_enhancer_image_caption_processor", None) |
|
|
self.set_global("prompt_enhancer_llm_model", None) |
|
|
self.set_global("prompt_enhancer_llm_tokenizer", None) |
|
|
if self.enhancer_offloadobj: |
|
|
self.enhancer_offloadobj.release() |
|
|
self.set_global("enhancer_offloadobj", None) |
|
|
|
|
|
model_type = state["model_type"] |
|
|
|
|
|
model_family_update, model_base_type_update, model_choice_update = self.generate_dropdown_model_list(model_type) |
|
|
header_update = self.generate_header(model_type, compile=new_server_config["compile"], attention_mode=new_server_config["attention_mode"]) |
|
|
|
|
|
return ( |
|
|
"<div style='color:green; text-align:center;'>The new configuration has been succesfully applied.</div>", |
|
|
header_update, |
|
|
model_family_update, |
|
|
model_base_type_update, |
|
|
model_choice_update, |
|
|
self.get_unique_id() |
|
|
) |
