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import gradio as gr
import subprocess
import os
import sys
from .common_gui import (
get_saveasfilename_path,
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" # 📂
refresh_symbol = "\U0001f504" # 🔄
save_style_symbol = "\U0001f4be" # 💾
document_symbol = "\U0001F4C4" # 📄
PYTHON = sys.executable
def svd_merge_lora(
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,
new_rank,
new_conv_rank,
device,
):
# Check if the output file already exists
if os.path.isfile(save_to):
log.info(f"Output file '{save_to}' already exists. Aborting.")
return
# Check if the ratio total is equal to one. If not normalise to 1
total_ratio = ratio_a + ratio_b + ratio_c + ratio_d
if total_ratio != 1:
ratio_a /= total_ratio
ratio_b /= total_ratio
ratio_c /= total_ratio
ratio_d /= total_ratio
run_cmd = [
rf"{PYTHON}",
rf"{scriptdir}/sd-scripts/networks/svd_merge_lora.py",
"--save_precision",
save_precision,
"--precision",
precision,
"--save_to",
save_to,
]
# Variables for model paths and their ratios
models = []
ratios = []
# Add non-empty models and their ratios to the command
def add_model(model_path, ratio):
if not os.path.isfile(model_path):
log.info(f"The provided model at {model_path} is not a file")
return False
models.append(fr"{model_path}")
ratios.append(str(ratio))
return True
if lora_a_model and add_model(lora_a_model, ratio_a):
pass
if lora_b_model and add_model(lora_b_model, ratio_b):
pass
if lora_c_model and add_model(lora_c_model, ratio_c):
pass
if lora_d_model and add_model(lora_d_model, ratio_d):
pass
if models and ratios: # Ensure we have valid models and ratios before appending
run_cmd.extend(["--models"] + models)
run_cmd.extend(["--ratios"] + ratios)
run_cmd.extend(
["--device", device, "--new_rank", str(new_rank), "--new_conv_rank", str(new_conv_rank)]
)
# Log the command
log.info(" ".join(run_cmd))
env = setup_environment()
# Run the command
subprocess.run(run_cmd, env=env)
###
# Gradio UI
###
def gradio_svd_merge_lora_tab(headless=False):
current_save_dir = os.path.join(scriptdir, "outputs")
current_a_model_dir = current_save_dir
current_b_model_dir = current_save_dir
current_c_model_dir = current_save_dir
current_d_model_dir = current_save_dir
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=[".pt", ".safetensors"], all=True))
with gr.Tab("Merge LoRA (SVD)"):
gr.Markdown(
"This utility can merge two LoRA networks together into a new LoRA."
)
lora_ext = gr.Textbox(value="*.safetensors *.pt", visible=False)
lora_ext_name = gr.Textbox(value="LoRA model types", visible=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 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 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="Merge ratio model A",
minimum=0,
maximum=1,
step=0.01,
value=0.25,
interactive=True,
)
ratio_b = gr.Slider(
label="Merge ratio model B",
minimum=0,
maximum=1,
step=0.01,
value=0.25,
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 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 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="Merge ratio model C",
minimum=0,
maximum=1,
step=0.01,
value=0.25,
interactive=True,
)
ratio_d = gr.Slider(
label="Merge ratio model D",
minimum=0,
maximum=1,
step=0.01,
value=0.25,
interactive=True,
)
with gr.Row():
new_rank = gr.Slider(
label="New Rank",
minimum=1,
maximum=1024,
step=1,
value=128,
interactive=True,
)
new_conv_rank = gr.Slider(
label="New Conv Rank",
minimum=1,
maximum=1024,
step=1,
value=128,
interactive=True,
)
with gr.Group(), gr.Row():
save_to = gr.Dropdown(
label="Save to (path for the new LoRA 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 headless),
)
button_save_to.click(
get_saveasfilename_path,
inputs=[save_to, lora_ext, lora_ext_name],
outputs=save_to,
show_progress=False,
)
save_to.change(
fn=lambda path: gr.Dropdown(choices=[""] + list_save_to(path)),
inputs=save_to,
outputs=save_to,
show_progress=False,
)
with gr.Group(), gr.Row():
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="float",
interactive=True,
)
device = gr.Radio(
label="Device",
choices=[
"cpu",
"cuda",
],
value="cuda",
interactive=True,
)
convert_button = gr.Button("Merge model")
convert_button.click(
svd_merge_lora,
inputs=[
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,
new_rank,
new_conv_rank,
device,
],
show_progress=False,
)
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