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import gradio as gr | |
import subprocess | |
import os | |
import sys | |
from .common_gui import ( | |
get_file_path, | |
scriptdir, | |
list_files, | |
create_refresh_button, setup_environment | |
) | |
from .custom_logging import setup_logging | |
# Set up logging | |
log = setup_logging() | |
folder_symbol = "\U0001f4c2" # π | |
refresh_symbol = "\U0001f504" # π | |
save_style_symbol = "\U0001f4be" # πΎ | |
document_symbol = "\U0001F4C4" # π | |
PYTHON = sys.executable | |
def verify_lora( | |
lora_model, | |
): | |
# verify for caption_text_input | |
if lora_model == "": | |
log.info("Invalid model A file") | |
return | |
# verify if source model exist | |
if not os.path.isfile(lora_model): | |
log.info("The provided model A is not a file") | |
return | |
run_cmd = [ | |
rf"{PYTHON}", | |
rf"{scriptdir}/sd-scripts/networks/check_lora_weights.py", | |
rf"{lora_model}", | |
] | |
# run_cmd = rf'"{PYTHON}" "{scriptdir}/sd-scripts/networks/check_lora_weights.py" "{lora_model}"' | |
# Reconstruct the safe command string for display | |
command_to_run = " ".join(run_cmd) | |
log.info(f"Executing command: {command_to_run}") | |
# Set the environment variable for the Python path | |
env = setup_environment() | |
# Run the command using subprocess.Popen for asynchronous handling | |
process = subprocess.Popen( | |
run_cmd, | |
stdout=subprocess.PIPE, | |
stderr=subprocess.PIPE, | |
env=env, | |
) | |
output, error = process.communicate() | |
return (output.decode(), error.decode()) | |
### | |
# Gradio UI | |
### | |
def gradio_verify_lora_tab(headless=False): | |
current_model_dir = os.path.join(scriptdir, "outputs") | |
def list_models(path): | |
nonlocal current_model_dir | |
current_model_dir = path | |
return list(list_files(path, exts=[".pt", ".safetensors"], all=True)) | |
with gr.Tab("Verify LoRA"): | |
gr.Markdown( | |
"This utility can verify a LoRA network to make sure it is properly trained." | |
) | |
lora_ext = gr.Textbox(value="*.pt *.safetensors", visible=False) | |
lora_ext_name = gr.Textbox(value="LoRA model types", visible=False) | |
with gr.Group(), gr.Row(): | |
lora_model = gr.Dropdown( | |
label="LoRA model (path to the LoRA model to verify)", | |
interactive=True, | |
choices=[""] + list_models(current_model_dir), | |
value="", | |
allow_custom_value=True, | |
) | |
create_refresh_button( | |
lora_model, | |
lambda: None, | |
lambda: {"choices": list_models(current_model_dir)}, | |
"open_folder_small", | |
) | |
button_lora_model_file = gr.Button( | |
folder_symbol, | |
elem_id="open_folder_small", | |
elem_classes=["tool"], | |
visible=(not headless), | |
) | |
button_lora_model_file.click( | |
get_file_path, | |
inputs=[lora_model, lora_ext, lora_ext_name], | |
outputs=lora_model, | |
show_progress=False, | |
) | |
verify_button = gr.Button("Verify", variant="primary") | |
lora_model.change( | |
fn=lambda path: gr.Dropdown(choices=[""] + list_models(path)), | |
inputs=lora_model, | |
outputs=lora_model, | |
show_progress=False, | |
) | |
lora_model_verif_output = gr.Textbox( | |
label="Output", | |
placeholder="Verification output", | |
interactive=False, | |
lines=1, | |
max_lines=10, | |
) | |
lora_model_verif_error = gr.Textbox( | |
label="Error", | |
placeholder="Verification error", | |
interactive=False, | |
lines=1, | |
max_lines=10, | |
) | |
verify_button.click( | |
verify_lora, | |
inputs=[ | |
lora_model, | |
], | |
outputs=[lora_model_verif_output, lora_model_verif_error], | |
show_progress=False, | |
) | |