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# Standard library imports
import os
import subprocess
# Third-party imports
import gradio as gr
from easygui import msgbox
# Local module imports
from .common_gui import get_saveasfilename_path, get_file_path
from library.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 = 'python3' if os.name == 'posix' else './venv/Scripts/python.exe'
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
def merge_lora(
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 = f'{PYTHON} "{os.path.join("networks","merge_lora.py")}"'
else:
run_cmd = f'{PYTHON} "{os.path.join("networks","sdxl_merge_lora.py")}"'
if sd_model:
run_cmd += f' --sd_model "{sd_model}"'
run_cmd += f' --save_precision {save_precision}'
run_cmd += f' --precision {precision}'
run_cmd += f' --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([f'"{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)
# Run the command
if os.name == 'posix':
os.system(run_cmd)
else:
subprocess.run(run_cmd)
log.info('Done merging...')
###
# Gradio UI
###
def gradio_merge_lora_tab(headless=False):
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.Row():
sd_model = gr.Textbox(
label='SD Model',
placeholder='(Optional) Stable Diffusion model',
interactive=True,
info='Provide a SD file path IF you want to merge it with LoRA files',
)
sd_model_file = gr.Button(
folder_symbol,
elem_id='open_folder_small',
visible=(not 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)
with gr.Row():
lora_a_model = gr.Textbox(
label='LoRA model "A"',
placeholder='Path to the LoRA A model',
interactive=True,
)
button_lora_a_model_file = gr.Button(
folder_symbol,
elem_id='open_folder_small',
visible=(not 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.Textbox(
label='LoRA model "B"',
placeholder='Path to the LoRA B model',
interactive=True,
)
button_lora_b_model_file = gr.Button(
folder_symbol,
elem_id='open_folder_small',
visible=(not 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,
)
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.Row():
lora_c_model = gr.Textbox(
label='LoRA model "C"',
placeholder='Path to the LoRA C model',
interactive=True,
)
button_lora_c_model_file = gr.Button(
folder_symbol,
elem_id='open_folder_small',
visible=(not 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.Textbox(
label='LoRA model "D"',
placeholder='Path to the LoRA D model',
interactive=True,
)
button_lora_d_model_file = gr.Button(
folder_symbol,
elem_id='open_folder_small',
visible=(not 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,
)
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.Row():
save_to = gr.Textbox(
label='Save to',
placeholder='path for the file to save...',
interactive=True,
)
button_save_to = gr.Button(
folder_symbol,
elem_id='open_folder_small',
visible=(not headless),
)
button_save_to.click(
get_saveasfilename_path,
inputs=[save_to, lora_ext, lora_ext_name],
outputs=save_to,
show_progress=False,
)
precision = gr.Dropdown(
label='Merge precision',
choices=['fp16', 'bf16', 'float'],
value='float',
interactive=True,
)
save_precision = gr.Dropdown(
label='Save precision',
choices=['fp16', 'bf16', 'float'],
value='fp16',
interactive=True,
)
merge_button = gr.Button('Merge model')
merge_button.click(
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,
)
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