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import gradio as gr
from easygui import msgbox
import subprocess
import os
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 extract_dylora(
model,
save_to,
unit,
):
# Check for caption_text_input
if model == '':
msgbox('Invalid DyLoRA model file')
return
# Check if source model exist
if not os.path.isfile(model):
msgbox('The provided DyLoRA model is not a file')
return
run_cmd = (
f'{PYTHON} "{os.path.join("networks","extract_lora_from_dylora.py")}"'
)
run_cmd += f' --save_to "{save_to}"'
run_cmd += f' --model "{model}"'
run_cmd += f' --unit {unit}'
log.info(run_cmd)
# Run the command
if os.name == 'posix':
os.system(run_cmd)
else:
subprocess.run(run_cmd)
log.info('Done extracting DyLoRA...')
###
# Gradio UI
###
def gradio_extract_dylora_tab(headless=False):
with gr.Tab('Extract DyLoRA'):
gr.Markdown(
'This utility can extract a DyLoRA network from a finetuned model.'
)
lora_ext = gr.Textbox(value='*.safetensors *.pt', visible=False)
lora_ext_name = gr.Textbox(value='LoRA model types', visible=False)
with gr.Row():
model = gr.Textbox(
label='DyLoRA model',
placeholder='Path to the DyLoRA model to extract from',
interactive=True,
)
button_model_file = gr.Button(
folder_symbol,
elem_id='open_folder_small',
visible=(not headless),
)
button_model_file.click(
get_file_path,
inputs=[model, lora_ext, lora_ext_name],
outputs=model,
show_progress=False,
)
save_to = gr.Textbox(
label='Save to',
placeholder='path where to save the extracted LoRA model...',
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,
)
unit = gr.Slider(
minimum=1,
maximum=256,
label='Network Dimension (Rank)',
value=1,
step=1,
interactive=True,
)
extract_button = gr.Button('Extract LoRA model')
extract_button.click(
extract_dylora,
inputs=[
model,
save_to,
unit,
],
show_progress=False,
)
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