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Making gui more modular by dividing it

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This commit is contained in:
bmaltais 2022-12-22 11:51:34 -05:00
parent 6a7e27e100
commit f60c8addd5
8 changed files with 2397 additions and 1756 deletions
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93
dreambooth_gui.py
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@ -11,20 +11,13 @@ import subprocess
import pathlib
import shutil
import argparse
from library.dreambooth_folder_creation_gui import (
gradio_dreambooth_folder_creation_tab,
)
from library.basic_caption_gui import gradio_basic_caption_gui_tab
from library.convert_model_gui import gradio_convert_model_tab
from library.blip_caption_gui import gradio_blip_caption_gui_tab
from library.wd14_caption_gui import gradio_wd14_caption_gui_tab
from library.dataset_balancing_gui import gradio_dataset_balancing_tab
from library.common_gui import (
get_folder_path,
remove_doublequote,
get_file_path,
get_saveasfile_path,
)
from library.utilities import utilities_tab
from easygui import msgbox
folder_symbol = '\U0001f4c2' # 📂
@ -473,6 +466,7 @@ def set_pretrained_model_name_or_path_input(value, v2, v_parameterization):
return value, v2, v_parameterization
def UI(username, password):
css = ''
@ -484,9 +478,37 @@ def UI(username, password):
interface = gr.Blocks(css=css)
with interface:
dummy_true = gr.Label(value=True, visible=False)
dummy_false = gr.Label(value=False, visible=False)
with gr.Tab('Dreambooth'):
(
train_data_dir_input,
reg_data_dir_input,
output_dir_input,
logging_dir_input,
) = dreambooth_tab()
with gr.Tab('Utilities'):
utilities_tab(
train_data_dir_input=train_data_dir_input,
reg_data_dir_input=reg_data_dir_input,
output_dir_input=output_dir_input,
logging_dir_input=logging_dir_input,
enable_copy_info_button=True,
)
# Show the interface
if not username == '':
interface.launch(auth=(username, password))
else:
interface.launch()
def dreambooth_tab(
train_data_dir_input=gr.Textbox(),
reg_data_dir_input=gr.Textbox(),
output_dir_input=gr.Textbox(),
logging_dir_input=gr.Textbox(),
):
dummy_db_true = gr.Label(value=True, visible=False)
dummy_db_false = gr.Label(value=False, visible=False)
gr.Markdown('Enter kohya finetuner parameter using this interface.')
with gr.Accordion('Configuration file', open=False):
with gr.Row():
@ -635,9 +657,7 @@ def UI(username, password):
)
with gr.Tab('Training parameters'):
with gr.Row():
learning_rate_input = gr.Textbox(
label='Learning rate', value=1e-6
)
learning_rate_input = gr.Textbox(label='Learning rate', value=1e-6)
lr_scheduler_input = gr.Dropdown(
label='LR Scheduler',
choices=[
@ -712,9 +732,7 @@ def UI(username, password):
enable_bucket_input = gr.Checkbox(
label='Enable buckets', value=True
)
cache_latent_input = gr.Checkbox(
label='Cache latent', value=True
)
cache_latent_input = gr.Checkbox(label='Cache latent', value=True)
use_8bit_adam_input = gr.Checkbox(
label='Use 8bit adam', value=True
)
@ -735,7 +753,9 @@ def UI(username, password):
shuffle_caption = gr.Checkbox(
label='Shuffle caption', value=False
)
save_state = gr.Checkbox(label='Save training state', value=False)
save_state = gr.Checkbox(
label='Save training state', value=False
)
with gr.Row():
resume = gr.Textbox(
label='Resume from saved training state',
@ -749,20 +769,6 @@ def UI(username, password):
button_run = gr.Button('Train model')
with gr.Tab('Utilities'):
with gr.Tab('Captioning'):
gradio_basic_caption_gui_tab()
gradio_blip_caption_gui_tab()
gradio_wd14_caption_gui_tab()
gradio_dreambooth_folder_creation_tab(
train_data_dir_input,
reg_data_dir_input,
output_dir_input,
logging_dir_input,
)
gradio_dataset_balancing_tab()
gradio_convert_model_tab()
button_open_config.click(
open_configuration,
inputs=[
@ -837,12 +843,10 @@ def UI(username, password):
],
)
save_as = True
not_save_as = False
button_save_config.click(
save_configuration,
inputs=[
dummy_false,
dummy_db_false,
config_file_name,
pretrained_model_name_or_path_input,
v2_input,
@ -883,7 +887,7 @@ def UI(username, password):
button_save_as_config.click(
save_configuration,
inputs=[
dummy_true,
dummy_db_true,
config_file_name,
pretrained_model_name_or_path_input,
v2_input,
@ -959,18 +963,23 @@ def UI(username, password):
],
)
# Show the interface
if not username == '':
interface.launch(auth=(username, password))
else:
interface.launch()
return (
train_data_dir_input,
reg_data_dir_input,
output_dir_input,
logging_dir_input,
)
if __name__ == '__main__':
# torch.cuda.set_per_process_memory_fraction(0.48)
parser = argparse.ArgumentParser()
parser.add_argument("--username", type=str, default='', help="Username for authentication")
parser.add_argument("--password", type=str, default='', help="Password for authentication")
parser.add_argument(
'--username', type=str, default='', help='Username for authentication'
)
parser.add_argument(
'--password', type=str, default='', help='Password for authentication'
)
args = parser.parse_args()

999
fine_tune.py
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File diff suppressed because it is too large Load Diff

57
finetune_gui.py
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@ -6,17 +6,12 @@ import subprocess
import pathlib
import shutil
import argparse
# from easygui import fileopenbox, filesavebox, diropenbox, msgbox
from library.basic_caption_gui import gradio_basic_caption_gui_tab
from library.convert_model_gui import gradio_convert_model_tab
from library.blip_caption_gui import gradio_blip_caption_gui_tab
from library.wd14_caption_gui import gradio_wd14_caption_gui_tab
from library.common_gui import (
get_folder_path,
get_file_path,
get_saveasfile_path,
)
from library.utilities import utilities_tab
folder_symbol = '\U0001f4c2' # 📂
refresh_symbol = '\U0001f504' # 🔄
@ -386,6 +381,7 @@ def remove_doublequote(file_path):
return file_path
def UI(username, password):
css = ''
@ -398,10 +394,23 @@ def UI(username, password):
interface = gr.Blocks(css=css)
with interface:
dummy_true = gr.Label(value=True, visible=False)
dummy_false = gr.Label(value=False, visible=False)
with gr.Tab('Finetuning'):
gr.Markdown('Enter kohya finetuner parameter using this interface.')
with gr.Tab("Finetune"):
finetune_tab()
with gr.Tab("Utilities"):
utilities_tab(enable_dreambooth_tab=False)
# Show the interface
if not username == '':
interface.launch(auth=(username, password))
else:
interface.launch()
def finetune_tab():
dummy_ft_true = gr.Label(value=True, visible=False)
dummy_ft_false = gr.Label(value=False, visible=False)
gr.Markdown(
'Enter kohya finetuner parameter using this interface.'
)
with gr.Accordion('Configuration File Load/Save', open=False):
with gr.Row():
button_open_config = gr.Button(
@ -411,7 +420,8 @@ def UI(username, password):
f'Save {save_style_symbol}', elem_id='open_folder'
)
button_save_as_config = gr.Button(
f'Save as... {save_style_symbol}', elem_id='open_folder'
f'Save as... {save_style_symbol}',
elem_id='open_folder',
)
config_file_name = gr.Textbox(
label='', placeholder='type file path or use buttons...'
@ -720,7 +730,7 @@ def UI(username, password):
button_save_config.click(
save_configuration,
inputs=[
dummy_false,
dummy_ft_false,
config_file_name,
pretrained_model_name_or_path_input,
v2_input,
@ -754,7 +764,7 @@ def UI(username, password):
button_save_as_config.click(
save_configuration,
inputs=[
dummy_true,
dummy_ft_true,
config_file_name,
pretrained_model_name_or_path_input,
v2_input,
@ -785,25 +795,16 @@ def UI(username, password):
outputs=[config_file_name],
)
with gr.Tab('Utilities'):
gradio_basic_caption_gui_tab()
gradio_blip_caption_gui_tab()
gradio_wd14_caption_gui_tab()
gradio_convert_model_tab()
# Show the interface
if not username == '':
interface.launch(auth=(username, password))
else:
interface.launch()
if __name__ == '__main__':
# torch.cuda.set_per_process_memory_fraction(0.48)
parser = argparse.ArgumentParser()
parser.add_argument("--username", type=str, default='', help="Username for authentication")
parser.add_argument("--password", type=str, default='', help="Password for authentication")
parser.add_argument(
'--username', type=str, default='', help='Username for authentication'
)
parser.add_argument(
'--password', type=str, default='', help='Password for authentication'
)
args = parser.parse_args()

58
kohya_gui.py Normal file
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@ -0,0 +1,58 @@
import gradio as gr
import os
import argparse
from dreambooth_gui import dreambooth_tab
from finetune_gui import finetune_tab
from library.utilities import utilities_tab
def UI(username, password):
css = ''
if os.path.exists('./style.css'):
with open(os.path.join('./style.css'), 'r', encoding='utf8') as file:
print('Load CSS...')
css += file.read() + '\n'
interface = gr.Blocks(css=css)
with interface:
with gr.Tab('Dreambooth'):
(
train_data_dir_input,
reg_data_dir_input,
output_dir_input,
logging_dir_input,
) = dreambooth_tab()
with gr.Tab('Finetune'):
finetune_tab()
with gr.Tab('Utilities'):
utilities_tab(
train_data_dir_input=train_data_dir_input,
reg_data_dir_input=reg_data_dir_input,
output_dir_input=output_dir_input,
logging_dir_input=logging_dir_input,
enable_copy_info_button=True,
)
# Show the interface
if not username == '':
interface.launch(auth=(username, password))
else:
interface.launch()
if __name__ == '__main__':
# torch.cuda.set_per_process_memory_fraction(0.48)
parser = argparse.ArgumentParser()
parser.add_argument(
'--username', type=str, default='', help='Username for authentication'
)
parser.add_argument(
'--password', type=str, default='', help='Password for authentication'
)
args = parser.parse_args()
UI(username=args.username, password=args.password)

3
library/common_gui.py
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@ -72,6 +72,9 @@ def get_saveasfile_path(file_path='', defaultextension='.json'):
def add_pre_postfix(
folder='', prefix='', postfix='', caption_file_ext='.caption'
):
if prefix == '' and postfix == '':
return
# set caption extention to default in case it was not provided
if caption_file_ext == '':
caption_file_ext = '.caption'

9
library/dataset_balancing_gui.py
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@ -51,7 +51,12 @@ def dataset_balancing(concept_repeats, folder, insecure):
if match:
# Multiply the repeats value by the number inside the braces
if not images == 0:
repeats = max(1, round(concept_repeats / images * float(match.group(1))))
repeats = max(
1,
round(
concept_repeats / images * float(match.group(1))
),
)
else:
repeats = 0
subdir = subdir[match.end() :]
@ -95,7 +100,7 @@ def warning(insecure):
def gradio_dataset_balancing_tab():
with gr.Tab('Dataset balancing'):
with gr.Tab('Dreambooth Dataset balancing'):
gr.Markdown(
'This utility will ensure that each concept folder in the dataset folder is used equally during the training process of the dreambooth machine learning model, regardless of the number of images in each folder. It will do this by renaming the concept folders to indicate the number of times they should be repeated during training.'
)

24
library/dreambooth_folder_creation_gui.py
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@ -68,14 +68,10 @@ def dreambooth_folder_preparation(
print(f'Copy {util_training_images_dir_input} to {training_dir}...')
shutil.copytree(util_training_images_dir_input, training_dir)
if not util_regularization_images_dir_input == '':
# Create the regularization_dir path
if (
util_class_prompt_input == ''
or not util_regularization_images_repeat_input > 0
):
print(
'Regularization images directory or repeats is missing... not copying regularisation images...'
)
if not util_regularization_images_repeat_input > 0:
print('Repeats is missing... not copying regularisation images...')
else:
regularization_dir = os.path.join(
util_training_dir_output,
@ -94,6 +90,10 @@ def dreambooth_folder_preparation(
shutil.copytree(
util_regularization_images_dir_input, regularization_dir
)
else:
print(
'Regularization images directory is missing... not copying regularisation images...'
)
# create log and model folder
# Check if the log folder exists and create it if it doesn't
@ -110,10 +110,11 @@ def dreambooth_folder_preparation(
def gradio_dreambooth_folder_creation_tab(
train_data_dir_input,
reg_data_dir_input,
output_dir_input,
logging_dir_input,
train_data_dir_input=gr.Textbox(),
reg_data_dir_input=gr.Textbox(),
output_dir_input=gr.Textbox(),
logging_dir_input=gr.Textbox(),
enable_copy_info_button=bool(False),
):
with gr.Tab('Dreambooth folder preparation'):
gr.Markdown(
@ -191,6 +192,7 @@ def gradio_dreambooth_folder_creation_tab(
util_training_dir_output,
],
)
if enable_copy_info_button:
button_copy_info_to_Directories_tab = gr.Button(
'Copy info to Directories Tab'
)

84
library/utilities.py Normal file
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@ -0,0 +1,84 @@
# v1: initial release
# v2: add open and save folder icons
# v3: Add new Utilities tab for Dreambooth folder preparation
# v3.1: Adding captionning of images to utilities
import gradio as gr
import os
import argparse
from library.dreambooth_folder_creation_gui import (
gradio_dreambooth_folder_creation_tab,
)
from library.basic_caption_gui import gradio_basic_caption_gui_tab
from library.convert_model_gui import gradio_convert_model_tab
from library.blip_caption_gui import gradio_blip_caption_gui_tab
from library.wd14_caption_gui import gradio_wd14_caption_gui_tab
from library.dataset_balancing_gui import gradio_dataset_balancing_tab
def utilities_tab(
train_data_dir_input=gr.Textbox(),
reg_data_dir_input=gr.Textbox(),
output_dir_input=gr.Textbox(),
logging_dir_input=gr.Textbox(),
enable_copy_info_button=bool(False),
enable_dreambooth_tab=True,
):
with gr.Tab('Captioning'):
gradio_basic_caption_gui_tab()
gradio_blip_caption_gui_tab()
gradio_wd14_caption_gui_tab()
if enable_dreambooth_tab:
with gr.Tab('Dreambooth'):
gr.Markdown('This section provide Dreambooth specific tools.')
gradio_dreambooth_folder_creation_tab(
train_data_dir_input=train_data_dir_input,
reg_data_dir_input=reg_data_dir_input,
output_dir_input=output_dir_input,
logging_dir_input=logging_dir_input,
enable_copy_info_button=enable_copy_info_button,
)
gradio_dataset_balancing_tab()
gradio_convert_model_tab()
return (
train_data_dir_input,
reg_data_dir_input,
output_dir_input,
logging_dir_input,
)
def UI(username, password):
css = ''
if os.path.exists('./style.css'):
with open(os.path.join('./style.css'), 'r', encoding='utf8') as file:
print('Load CSS...')
css += file.read() + '\n'
interface = gr.Blocks(css=css)
with interface:
utilities_tab()
# Show the interface
if not username == '':
interface.launch(auth=(username, password))
else:
interface.launch()
if __name__ == '__main__':
# torch.cuda.set_per_process_memory_fraction(0.48)
parser = argparse.ArgumentParser()
parser.add_argument(
'--username', type=str, default='', help='Username for authentication'
)
parser.add_argument(
'--password', type=str, default='', help='Password for authentication'
)
args = parser.parse_args()
UI(username=args.username, password=args.password)