|
import gradio as gr |
|
from easygui import msgbox |
|
import subprocess |
|
import os |
|
from .common_gui import ( |
|
get_saveasfilename_path, |
|
get_any_file_path, |
|
get_file_path, |
|
) |
|
|
|
from library.custom_logging import setup_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_lora( |
|
model_tuned, |
|
model_org, |
|
save_to, |
|
save_precision, |
|
dim, |
|
v2, |
|
conv_dim, |
|
device, |
|
): |
|
|
|
if model_tuned == '': |
|
msgbox('Invalid finetuned model file') |
|
return |
|
|
|
if model_org == '': |
|
msgbox('Invalid base model file') |
|
return |
|
|
|
|
|
if not os.path.isfile(model_tuned): |
|
msgbox('The provided finetuned model is not a file') |
|
return |
|
|
|
if not os.path.isfile(model_org): |
|
msgbox('The provided base model is not a file') |
|
return |
|
|
|
run_cmd = ( |
|
f'{PYTHON} "{os.path.join("networks","extract_lora_from_models.py")}"' |
|
) |
|
run_cmd += f' --save_precision {save_precision}' |
|
run_cmd += f' --save_to "{save_to}"' |
|
run_cmd += f' --model_org "{model_org}"' |
|
run_cmd += f' --model_tuned "{model_tuned}"' |
|
run_cmd += f' --dim {dim}' |
|
run_cmd += f' --device {device}' |
|
if conv_dim > 0: |
|
run_cmd += f' --conv_dim {conv_dim}' |
|
if v2: |
|
run_cmd += f' --v2' |
|
|
|
log.info(run_cmd) |
|
|
|
|
|
if os.name == 'posix': |
|
os.system(run_cmd) |
|
else: |
|
subprocess.run(run_cmd) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def gradio_extract_lora_tab(headless=False): |
|
with gr.Tab('Extract LoRA'): |
|
gr.Markdown( |
|
'This utility can extract a LoRA 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) |
|
model_ext = gr.Textbox(value='*.ckpt *.safetensors', visible=False) |
|
model_ext_name = gr.Textbox(value='Model types', visible=False) |
|
|
|
with gr.Row(): |
|
model_tuned = gr.Textbox( |
|
label='Finetuned model', |
|
placeholder='Path to the finetuned model to extract', |
|
interactive=True, |
|
) |
|
button_model_tuned_file = gr.Button( |
|
folder_symbol, |
|
elem_id='open_folder_small', |
|
visible=(not headless), |
|
) |
|
button_model_tuned_file.click( |
|
get_file_path, |
|
inputs=[model_tuned, model_ext, model_ext_name], |
|
outputs=model_tuned, |
|
show_progress=False, |
|
) |
|
|
|
model_org = gr.Textbox( |
|
label='Stable Diffusion base model', |
|
placeholder='Stable Diffusion original model: ckpt or safetensors file', |
|
interactive=True, |
|
) |
|
button_model_org_file = gr.Button( |
|
folder_symbol, |
|
elem_id='open_folder_small', |
|
visible=(not headless), |
|
) |
|
button_model_org_file.click( |
|
get_file_path, |
|
inputs=[model_org, model_ext, model_ext_name], |
|
outputs=model_org, |
|
show_progress=False, |
|
) |
|
with gr.Row(): |
|
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, |
|
) |
|
save_precision = gr.Dropdown( |
|
label='Save precision', |
|
choices=['fp16', 'bf16', 'float'], |
|
value='float', |
|
interactive=True, |
|
) |
|
with gr.Row(): |
|
dim = gr.Slider( |
|
minimum=4, |
|
maximum=1024, |
|
label='Network Dimension (Rank)', |
|
value=128, |
|
step=1, |
|
interactive=True, |
|
) |
|
conv_dim = gr.Slider( |
|
minimum=0, |
|
maximum=1024, |
|
label='Conv Dimension (Rank)', |
|
value=128, |
|
step=1, |
|
interactive=True, |
|
) |
|
v2 = gr.Checkbox(label='v2', value=False, interactive=True) |
|
device = gr.Dropdown( |
|
label='Device', |
|
choices=[ |
|
'cpu', |
|
'cuda', |
|
], |
|
value='cuda', |
|
interactive=True, |
|
) |
|
|
|
extract_button = gr.Button('Extract LoRA model') |
|
|
|
extract_button.click( |
|
extract_lora, |
|
inputs=[ |
|
model_tuned, |
|
model_org, |
|
save_to, |
|
save_precision, |
|
dim, |
|
v2, |
|
conv_dim, |
|
device, |
|
], |
|
show_progress=False, |
|
) |
|
|