| 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,
|
| )
|
|
|
