191 lines
5.3 KiB
Python
191 lines
5.3 KiB
Python
import gradio as gr
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from easygui import msgbox
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import subprocess
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import os
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from .common_gui import (
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get_saveasfilename_path,
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get_any_file_path,
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get_file_path,
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)
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folder_symbol = '\U0001f4c2' # 📂
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refresh_symbol = '\U0001f504' # 🔄
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save_style_symbol = '\U0001f4be' # 💾
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document_symbol = '\U0001F4C4' # 📄
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PYTHON = 'python3' if os.name == 'posix' else './venv/Scripts/python.exe'
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def svd_merge_lora(
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lora_a_model,
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lora_b_model,
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ratio,
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save_to,
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precision,
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save_precision,
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new_rank,
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new_conv_rank,
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device,
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):
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# Check for caption_text_input
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if lora_a_model == '':
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msgbox('Invalid model A file')
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return
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if lora_b_model == '':
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msgbox('Invalid model B file')
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return
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# Check if source model exist
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if not os.path.isfile(lora_a_model):
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msgbox('The provided model A is not a file')
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return
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if not os.path.isfile(lora_b_model):
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msgbox('The provided model B is not a file')
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return
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ratio_a = ratio
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ratio_b = 1 - ratio
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run_cmd = f'{PYTHON} "{os.path.join("networks","svd_merge_lora.py")}"'
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run_cmd += f' --save_precision {save_precision}'
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run_cmd += f' --precision {precision}'
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run_cmd += f' --save_to "{save_to}"'
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run_cmd += f' --models "{lora_a_model}" "{lora_b_model}"'
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run_cmd += f' --ratios {ratio_a} {ratio_b}'
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run_cmd += f' --device {device}'
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run_cmd += f' --new_rank "{new_rank}"'
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run_cmd += f' --new_conv_rank "{new_conv_rank}"'
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print(run_cmd)
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# Run the command
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if os.name == 'posix':
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os.system(run_cmd)
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else:
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subprocess.run(run_cmd)
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###
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# Gradio UI
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###
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def gradio_svd_merge_lora_tab():
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with gr.Tab('Merge LoRA (SVD)'):
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gr.Markdown('This utility can merge two LoRA networks together.')
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lora_ext = gr.Textbox(value='*.safetensors *.pt', visible=False)
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lora_ext_name = gr.Textbox(value='LoRA model types', visible=False)
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with gr.Row():
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lora_a_model = gr.Textbox(
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label='LoRA model "A"',
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placeholder='Path to the LoRA A model',
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interactive=True,
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)
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button_lora_a_model_file = gr.Button(
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folder_symbol, elem_id='open_folder_small'
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)
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button_lora_a_model_file.click(
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get_file_path,
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inputs=[lora_a_model, lora_ext, lora_ext_name],
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outputs=lora_a_model,
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show_progress=False,
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)
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lora_b_model = gr.Textbox(
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label='LoRA model "B"',
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placeholder='Path to the LoRA B model',
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interactive=True,
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)
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button_lora_b_model_file = gr.Button(
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folder_symbol, elem_id='open_folder_small'
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)
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button_lora_b_model_file.click(
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get_file_path,
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inputs=[lora_b_model, lora_ext, lora_ext_name],
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outputs=lora_b_model,
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show_progress=False,
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)
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with gr.Row():
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ratio = gr.Slider(
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label='Merge ratio (eg: 0.7 mean 70% of model A and 30% of model B',
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minimum=0,
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maximum=1,
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step=0.01,
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value=0.5,
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interactive=True,
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)
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new_rank = gr.Slider(
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label='New Rank',
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minimum=1,
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maximum=1024,
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step=1,
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value=128,
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interactive=True,
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)
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new_conv_rank = gr.Slider(
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label='New Conv Rank',
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minimum=1,
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maximum=1024,
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step=1,
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value=128,
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interactive=True,
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)
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with gr.Row():
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save_to = gr.Textbox(
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label='Save to',
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placeholder='path for the file to save...',
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interactive=True,
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)
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button_save_to = gr.Button(
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folder_symbol, elem_id='open_folder_small'
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)
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button_save_to.click(
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get_saveasfilename_path,
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inputs=[save_to, lora_ext, lora_ext_name],
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outputs=save_to,
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show_progress=False,
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)
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precision = gr.Dropdown(
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label='Merge precision',
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choices=['fp16', 'bf16', 'float'],
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value='float',
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interactive=True,
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)
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save_precision = gr.Dropdown(
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label='Save precision',
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choices=['fp16', 'bf16', 'float'],
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value='float',
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interactive=True,
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)
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device = gr.Dropdown(
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label='Device',
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choices=[
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'cpu',
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'cuda',
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],
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value='cuda',
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interactive=True,
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)
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convert_button = gr.Button('Merge model')
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convert_button.click(
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svd_merge_lora,
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inputs=[
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lora_a_model,
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lora_b_model,
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ratio,
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save_to,
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precision,
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save_precision,
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new_rank,
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new_conv_rank,
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device,
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],
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show_progress=False,
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)
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