# Standard library imports import os import subprocess import sys import json # Third-party imports import gradio as gr from easygui import msgbox # Local module imports from .common_gui import get_saveasfilename_path, get_file_path, scriptdir, list_files, create_refresh_button from .custom_logging import setup_logging # Set up logging log = setup_logging() folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 save_style_symbol = '\U0001f4be' # 💾 document_symbol = '\U0001F4C4' # 📄 PYTHON = sys.executable def check_model(model): if not model: return True if not os.path.isfile(model): msgbox(f'The provided {model} is not a file') return False return True def verify_conditions(sd_model, lora_models): lora_models_count = sum(1 for model in lora_models if model) if sd_model and lora_models_count >= 1: return True elif not sd_model and lora_models_count >= 2: return True return False class GradioMergeLoRaTab: def __init__(self, headless=False): self.headless = headless self.build_tab() def save_inputs_to_json(self, file_path, inputs): with open(file_path, 'w') as file: json.dump(inputs, file) log.info(f'Saved inputs to {file_path}') def load_inputs_from_json(self, file_path): with open(file_path, 'r') as file: inputs = json.load(file) log.info(f'Loaded inputs from {file_path}') return inputs def build_tab(self): current_sd_model_dir = os.path.join(scriptdir, "outputs") current_save_dir = os.path.join(scriptdir, "outputs") current_a_model_dir = current_sd_model_dir current_b_model_dir = current_sd_model_dir current_c_model_dir = current_sd_model_dir current_d_model_dir = current_sd_model_dir def list_sd_models(path): nonlocal current_sd_model_dir current_sd_model_dir = path return list(list_files(path, exts=[".ckpt", ".safetensors"], all=True)) def list_a_models(path): nonlocal current_a_model_dir current_a_model_dir = path return list(list_files(path, exts=[".pt", ".safetensors"], all=True)) def list_b_models(path): nonlocal current_b_model_dir current_b_model_dir = path return list(list_files(path, exts=[".pt", ".safetensors"], all=True)) def list_c_models(path): nonlocal current_c_model_dir current_c_model_dir = path return list(list_files(path, exts=[".pt", ".safetensors"], all=True)) def list_d_models(path): nonlocal current_d_model_dir current_d_model_dir = path return list(list_files(path, exts=[".pt", ".safetensors"], all=True)) def list_save_to(path): nonlocal current_save_dir current_save_dir = path return list(list_files(path, exts=[".ckpt", ".safetensors"], all=True)) with gr.Tab('Merge LoRA'): gr.Markdown( 'This utility can merge up to 4 LoRA together or alternatively merge up to 4 LoRA into a SD checkpoint.' ) lora_ext = gr.Textbox(value='*.safetensors *.pt', visible=False) lora_ext_name = gr.Textbox(value='LoRA model types', visible=False) ckpt_ext = gr.Textbox(value='*.safetensors *.ckpt', visible=False) ckpt_ext_name = gr.Textbox(value='SD model types', visible=False) with gr.Group(), gr.Row(): sd_model = gr.Dropdown( label='SD Model (Optional. Stable Diffusion model path, if you want to merge it with LoRA files)', interactive=True, choices=[""] + list_sd_models(current_sd_model_dir), value="", allow_custom_value=True, ) create_refresh_button(sd_model, lambda: None, lambda: {"choices": list_sd_models(current_sd_model_dir)}, "open_folder_small") sd_model_file = gr.Button( folder_symbol, elem_id='open_folder_small', elem_classes=['tool'], visible=(not self.headless), ) sd_model_file.click( get_file_path, inputs=[sd_model, ckpt_ext, ckpt_ext_name], outputs=sd_model, show_progress=False, ) sdxl_model = gr.Checkbox(label='SDXL model', value=False) sd_model.change( fn=lambda path: gr.Dropdown(choices=[""] + list_sd_models(path)), inputs=sd_model, outputs=sd_model, show_progress=False, ) with gr.Group(), gr.Row(): lora_a_model = gr.Dropdown( label='LoRA model "A" (path to the LoRA A model)', interactive=True, choices=[""] + list_a_models(current_a_model_dir), value="", allow_custom_value=True, ) create_refresh_button(lora_a_model, lambda: None, lambda: {"choices": list_a_models(current_a_model_dir)}, "open_folder_small") button_lora_a_model_file = gr.Button( folder_symbol, elem_id='open_folder_small', elem_classes=['tool'], visible=(not self.headless), ) button_lora_a_model_file.click( get_file_path, inputs=[lora_a_model, lora_ext, lora_ext_name], outputs=lora_a_model, show_progress=False, ) lora_b_model = gr.Dropdown( label='LoRA model "B" (path to the LoRA B model)', interactive=True, choices=[""] + list_b_models(current_b_model_dir), value="", allow_custom_value=True, ) create_refresh_button(lora_b_model, lambda: None, lambda: {"choices": list_b_models(current_b_model_dir)}, "open_folder_small") button_lora_b_model_file = gr.Button( folder_symbol, elem_id='open_folder_small', elem_classes=['tool'], visible=(not self.headless), ) button_lora_b_model_file.click( get_file_path, inputs=[lora_b_model, lora_ext, lora_ext_name], outputs=lora_b_model, show_progress=False, ) lora_a_model.change( fn=lambda path: gr.Dropdown(choices=[""] + list_a_models(path)), inputs=lora_a_model, outputs=lora_a_model, show_progress=False, ) lora_b_model.change( fn=lambda path: gr.Dropdown(choices=[""] + list_b_models(path)), inputs=lora_b_model, outputs=lora_b_model, show_progress=False, ) with gr.Row(): ratio_a = gr.Slider( label='Model A merge ratio (eg: 0.5 mean 50%)', minimum=0, maximum=1, step=0.01, value=0.0, interactive=True, ) ratio_b = gr.Slider( label='Model B merge ratio (eg: 0.5 mean 50%)', minimum=0, maximum=1, step=0.01, value=0.0, interactive=True, ) with gr.Group(), gr.Row(): lora_c_model = gr.Dropdown( label='LoRA model "C" (path to the LoRA C model)', interactive=True, choices=[""] + list_c_models(current_c_model_dir), value="", allow_custom_value=True, ) create_refresh_button(lora_c_model, lambda: None, lambda: {"choices": list_c_models(current_c_model_dir)}, "open_folder_small") button_lora_c_model_file = gr.Button( folder_symbol, elem_id='open_folder_small', elem_classes=['tool'], visible=(not self.headless), ) button_lora_c_model_file.click( get_file_path, inputs=[lora_c_model, lora_ext, lora_ext_name], outputs=lora_c_model, show_progress=False, ) lora_d_model = gr.Dropdown( label='LoRA model "D" (path to the LoRA D model)', interactive=True, choices=[""] + list_d_models(current_d_model_dir), value="", allow_custom_value=True, ) create_refresh_button(lora_d_model, lambda: None, lambda: {"choices": list_d_models(current_d_model_dir)}, "open_folder_small") button_lora_d_model_file = gr.Button( folder_symbol, elem_id='open_folder_small', elem_classes=['tool'], visible=(not self.headless), ) button_lora_d_model_file.click( get_file_path, inputs=[lora_d_model, lora_ext, lora_ext_name], outputs=lora_d_model, show_progress=False, ) lora_c_model.change( fn=lambda path: gr.Dropdown(choices=[""] + list_c_models(path)), inputs=lora_c_model, outputs=lora_c_model, show_progress=False, ) lora_d_model.change( fn=lambda path: gr.Dropdown(choices=[""] + list_d_models(path)), inputs=lora_d_model, outputs=lora_d_model, show_progress=False, ) with gr.Row(): ratio_c = gr.Slider( label='Model C merge ratio (eg: 0.5 mean 50%)', minimum=0, maximum=1, step=0.01, value=0.0, interactive=True, ) ratio_d = gr.Slider( label='Model D merge ratio (eg: 0.5 mean 50%)', minimum=0, maximum=1, step=0.01, value=0.0, interactive=True, ) with gr.Group(), gr.Row(): save_to = gr.Dropdown( label='Save to (path for the file to save...)', interactive=True, choices=[""] + list_save_to(current_d_model_dir), value="", allow_custom_value=True, ) create_refresh_button(save_to, lambda: None, lambda: {"choices": list_save_to(current_save_dir)}, "open_folder_small") button_save_to = gr.Button( folder_symbol, elem_id='open_folder_small', elem_classes=['tool'], visible=(not self.headless), ) button_save_to.click( get_saveasfilename_path, inputs=[save_to, lora_ext, lora_ext_name], outputs=save_to, show_progress=False, ) precision = gr.Radio( label='Merge precision', choices=['fp16', 'bf16', 'float'], value='float', interactive=True, ) save_precision = gr.Radio( label='Save precision', choices=['fp16', 'bf16', 'float'], value='fp16', interactive=True, ) save_to.change( fn=lambda path: gr.Dropdown(choices=[""] + list_save_to(path)), inputs=save_to, outputs=save_to, show_progress=False, ) merge_button = gr.Button('Merge model') merge_button.click( self.merge_lora, inputs=[ sd_model, sdxl_model, lora_a_model, lora_b_model, lora_c_model, lora_d_model, ratio_a, ratio_b, ratio_c, ratio_d, save_to, precision, save_precision, ], show_progress=False, ) def merge_lora( self, sd_model, sdxl_model, lora_a_model, lora_b_model, lora_c_model, lora_d_model, ratio_a, ratio_b, ratio_c, ratio_d, save_to, precision, save_precision, ): log.info('Merge model...') models = [ sd_model, lora_a_model, lora_b_model, lora_c_model, lora_d_model, ] lora_models = models[1:] ratios = [ratio_a, ratio_b, ratio_c, ratio_d] if not verify_conditions(sd_model, lora_models): log.info( 'Warning: Either provide at least one LoRa model along with the sd_model or at least two LoRa models if no sd_model is provided.' ) return for model in models: if not check_model(model): return if not sdxl_model: run_cmd = fr'"{PYTHON}" "{scriptdir}/sd-scripts/networks/merge_lora.py"' else: run_cmd = ( fr'"{PYTHON}" "{scriptdir}/sd-scripts/networks/sdxl_merge_lora.py"' ) if sd_model: run_cmd += fr' --sd_model "{sd_model}"' run_cmd += f' --save_precision {save_precision}' run_cmd += f' --precision {precision}' run_cmd += fr' --save_to "{save_to}"' # Create a space-separated string of non-empty models (from the second element onwards), enclosed in double quotes models_cmd = ' '.join([fr'"{model}"' for model in lora_models if model]) # Create a space-separated string of non-zero ratios corresponding to non-empty LoRa models valid_ratios = [ ratios[i] for i, model in enumerate(lora_models) if model ] ratios_cmd = ' '.join([str(ratio) for ratio in valid_ratios]) if models_cmd: run_cmd += f' --models {models_cmd}' run_cmd += f' --ratios {ratios_cmd}' log.info(run_cmd) env = os.environ.copy() env['PYTHONPATH'] = fr"{scriptdir}{os.pathsep}{scriptdir}/sd-scripts{os.pathsep}{env.get('PYTHONPATH', '')}" # Run the command subprocess.run(run_cmd, shell=True, env=env) log.info('Done merging...')