| import gradio as gr |
| from os import path |
| from backend.lora import ( |
| get_lora_models, |
| get_active_lora_weights, |
| update_lora_weights, |
| load_lora_weight, |
| ) |
| from state import get_settings, get_context |
| from frontend.utils import get_valid_lora_model |
| from models.interface_types import InterfaceType |
|
|
|
|
| _MAX_LORA_WEIGHTS = 5 |
|
|
| _custom_lora_sliders = [] |
| _custom_lora_names = [] |
| _custom_lora_columns = [] |
|
|
| app_settings = get_settings() |
|
|
|
|
| def on_click_update_weight(*lora_weights): |
| update_weights = [] |
| active_weights = get_active_lora_weights() |
| if not len(active_weights): |
| gr.Warning("No active LoRAs, first you need to load LoRA model") |
| return |
| for idx, lora in enumerate(active_weights): |
| update_weights.append( |
| ( |
| lora[0], |
| lora_weights[idx], |
| ) |
| ) |
| if len(update_weights) > 0: |
| update_lora_weights( |
| get_context(InterfaceType.WEBUI).lcm_text_to_image.pipeline, |
| app_settings.settings.lcm_diffusion_setting, |
| update_weights, |
| ) |
|
|
|
|
| def on_click_load_lora(lora_name, lora_weight): |
| if app_settings.settings.lcm_diffusion_setting.use_openvino: |
| gr.Warning("Currently LoRA is not supported in OpenVINO.") |
| return |
| lora_models_map = get_lora_models( |
| app_settings.settings.lcm_diffusion_setting.lora.models_dir |
| ) |
|
|
| |
| settings = app_settings.settings.lcm_diffusion_setting |
| settings.lora.fuse = False |
| settings.lora.enabled = False |
| print(f"Selected Lora Model :{lora_name}") |
| print(f"Lora weight :{lora_weight}") |
| settings.lora.path = lora_models_map[lora_name] |
| settings.lora.weight = lora_weight |
| if not path.exists(settings.lora.path): |
| gr.Warning("Invalid LoRA model path!") |
| return |
| pipeline = get_context(InterfaceType.WEBUI).lcm_text_to_image.pipeline |
| if not pipeline: |
| gr.Warning("Pipeline not initialized. Please generate an image first.") |
| return |
| settings.lora.enabled = True |
| load_lora_weight( |
| get_context(InterfaceType.WEBUI).lcm_text_to_image.pipeline, |
| settings, |
| ) |
|
|
| |
| global _MAX_LORA_WEIGHTS |
| values = [] |
| labels = [] |
| rows = [] |
| active_weights = get_active_lora_weights() |
| for idx, lora in enumerate(active_weights): |
| labels.append(f"{lora[0]}: ") |
| values.append(lora[1]) |
| rows.append(gr.Row.update(visible=True)) |
| for i in range(len(active_weights), _MAX_LORA_WEIGHTS): |
| labels.append(f"Update weight") |
| values.append(0.0) |
| rows.append(gr.Row.update(visible=False)) |
| return labels + values + rows |
|
|
|
|
| def get_lora_models_ui() -> None: |
| with gr.Blocks() as ui: |
| gr.HTML( |
| "Download and place your LoRA model weights in <b>lora_models</b> folders and restart App" |
| ) |
| with gr.Row(): |
| with gr.Column(): |
| with gr.Row(): |
| lora_models_map = get_lora_models( |
| app_settings.settings.lcm_diffusion_setting.lora.models_dir |
| ) |
| valid_model = get_valid_lora_model( |
| list(lora_models_map.values()), |
| app_settings.settings.lcm_diffusion_setting.lora.path, |
| app_settings.settings.lcm_diffusion_setting.lora.models_dir, |
| ) |
| if valid_model != "": |
| valid_model_path = lora_models_map[valid_model] |
| app_settings.settings.lcm_diffusion_setting.lora.path = ( |
| valid_model_path |
| ) |
| else: |
| app_settings.settings.lcm_diffusion_setting.lora.path = "" |
|
|
| lora_model = gr.Dropdown( |
| lora_models_map.keys(), |
| label="LoRA model", |
| info="LoRA model weight to load (You can use Lora models from Civitai or Hugging Face .safetensors format)", |
| value=valid_model, |
| interactive=True, |
| ) |
|
|
| lora_weight = gr.Slider( |
| 0.0, |
| 1.0, |
| value=app_settings.settings.lcm_diffusion_setting.lora.weight, |
| step=0.05, |
| label="Initial Lora weight", |
| interactive=True, |
| ) |
| load_lora_btn = gr.Button( |
| "Load selected LoRA", |
| elem_id="load_lora_button", |
| scale=0, |
| ) |
|
|
| with gr.Row(): |
| gr.Markdown( |
| "## Loaded LoRA models", |
| show_label=False, |
| ) |
| update_lora_weights_btn = gr.Button( |
| "Update LoRA weights", |
| elem_id="load_lora_button", |
| scale=0, |
| ) |
|
|
| global _MAX_LORA_WEIGHTS |
| global _custom_lora_sliders |
| global _custom_lora_names |
| global _custom_lora_columns |
| for i in range(0, _MAX_LORA_WEIGHTS): |
| new_row = gr.Column(visible=False) |
| _custom_lora_columns.append(new_row) |
| with new_row: |
| lora_name = gr.Markdown( |
| "Lora Name", |
| show_label=True, |
| ) |
| lora_slider = gr.Slider( |
| 0.0, |
| 1.0, |
| step=0.05, |
| label="LoRA weight", |
| interactive=True, |
| visible=True, |
| ) |
|
|
| _custom_lora_names.append(lora_name) |
| _custom_lora_sliders.append(lora_slider) |
|
|
| load_lora_btn.click( |
| fn=on_click_load_lora, |
| inputs=[lora_model, lora_weight], |
| outputs=[ |
| *_custom_lora_names, |
| *_custom_lora_sliders, |
| *_custom_lora_columns, |
| ], |
| ) |
|
|
| update_lora_weights_btn.click( |
| fn=on_click_update_weight, |
| inputs=[*_custom_lora_sliders], |
| outputs=None, |
| ) |
|
|
