Add support for:
shuffle_caption, save_state, resume, prior_loss_weight, Fix issue with config open and save
This commit is contained in:
bmaltais
parent
1d412726b3
commit
1f1dd5c4de
@ -10,7 +10,9 @@ import os
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import subprocess
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import pathlib
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import shutil
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from library.dreambooth_folder_creation_gui import gradio_dreambooth_folder_creation_tab
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from library.dreambooth_folder_creation_gui import (
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gradio_dreambooth_folder_creation_tab,
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)
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from library.basic_caption_gui import gradio_basic_caption_gui_tab
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from library.convert_model_gui import gradio_convert_model_tab
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from library.blip_caption_gui import gradio_blip_caption_gui_tab
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@ -20,14 +22,14 @@ from library.common_gui import (
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get_folder_path,
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remove_doublequote,
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get_file_path,
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get_saveasfile_path
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get_saveasfile_path,
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)
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from easygui import msgbox
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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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document_symbol = '\U0001F4C4' # 📄
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def save_configuration(
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@ -60,7 +62,11 @@ def save_configuration(
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stop_text_encoder_training,
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use_8bit_adam,
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xformers,
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save_model_as
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save_model_as,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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):
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original_file_path = file_path
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@ -68,22 +74,14 @@ def save_configuration(
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if save_as_bool:
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print('Save as...')
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# file_path = filesavebox(
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# 'Select the config file to save',
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# default='finetune.json',
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# filetypes='*.json',
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# )
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file_path = get_saveasfile_path(file_path)
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else:
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print('Save...')
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if file_path == None or file_path == '':
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# file_path = filesavebox(
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# 'Select the config file to save',
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# default='finetune.json',
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# filetypes='*.json',
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# )
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file_path = get_saveasfile_path(file_path)
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# print(file_path)
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if file_path == None or file_path == '':
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return original_file_path # In case a file_path was provided and the user decide to cancel the open action
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@ -116,7 +114,11 @@ def save_configuration(
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'stop_text_encoder_training': stop_text_encoder_training,
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'use_8bit_adam': use_8bit_adam,
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'xformers': xformers,
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'save_model_as': save_model_as
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'save_model_as': save_model_as,
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'shuffle_caption': shuffle_caption,
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'save_state': save_state,
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'resume': resume,
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'prior_loss_weight': prior_loss_weight,
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}
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# Save the data to the selected file
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@ -155,14 +157,18 @@ def open_configuration(
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stop_text_encoder_training,
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use_8bit_adam,
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xformers,
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save_model_as
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save_model_as,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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):
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original_file_path = file_path
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file_path = get_file_path(file_path)
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# print(file_path)
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if file_path != '' and file_path != None:
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print(file_path)
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if not file_path == '' and not file_path == None:
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# load variables from JSON file
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with open(file_path, 'r') as f:
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my_data = json.load(f)
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@ -204,7 +210,11 @@ def open_configuration(
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my_data.get('stop_text_encoder_training', stop_text_encoder_training),
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my_data.get('use_8bit_adam', use_8bit_adam),
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my_data.get('xformers', xformers),
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my_data.get('save_model_as', save_model_as)
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my_data.get('save_model_as', save_model_as),
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my_data.get('shuffle_caption', shuffle_caption),
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my_data.get('save_state', save_state),
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my_data.get('resume', resume),
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my_data.get('prior_loss_weight', prior_loss_weight),
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)
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@ -236,7 +246,11 @@ def train_model(
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stop_text_encoder_training_pct,
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use_8bit_adam,
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xformers,
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save_model_as
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save_model_as,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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):
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def save_inference_file(output_dir, v2, v_parameterization):
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# Copy inference model for v2 if required
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@ -360,6 +374,10 @@ def train_model(
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run_cmd += ' --use_8bit_adam'
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if xformers:
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run_cmd += ' --xformers'
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if shuffle_caption:
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run_cmd += ' --shuffle_caption'
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if save_state:
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run_cmd += ' --save_state'
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run_cmd += (
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f' --pretrained_model_name_or_path={pretrained_model_name_or_path}'
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)
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@ -382,9 +400,15 @@ def train_model(
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run_cmd += f' --logging_dir={logging_dir}'
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run_cmd += f' --caption_extention={caption_extention}'
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if not stop_text_encoder_training == 0:
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run_cmd += f' --stop_text_encoder_training={stop_text_encoder_training}'
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run_cmd += (
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f' --stop_text_encoder_training={stop_text_encoder_training}'
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)
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if not save_model_as == 'same as source model':
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run_cmd += f' --save_model_as={save_model_as}'
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if not resume == '':
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run_cmd += f' --resume={resume}'
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if not float(prior_loss_weight) == 1.0:
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run_cmd += f' --prior_loss_weight={prior_loss_weight}'
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print(run_cmd)
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# Run the command
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@ -392,7 +416,7 @@ def train_model(
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# check if output_dir/last is a folder... therefore it is a diffuser model
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last_dir = pathlib.Path(f'{output_dir}/last')
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if not last_dir.is_dir():
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# Copy inference model for v2 if required
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save_inference_file(output_dir, v2, v_parameterization)
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@ -472,8 +496,8 @@ with interface:
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)
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config_file_name = gr.Textbox(
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label='',
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# placeholder="type the configuration file path or use the 'Open' button above to select it...",
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interactive=False
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placeholder="type the configuration file path or use the 'Open' button above to select it...",
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interactive=True,
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)
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# config_file_name.change(
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# remove_doublequote,
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@ -491,13 +515,16 @@ with interface:
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document_symbol, elem_id='open_folder_small'
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)
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pretrained_model_name_or_path_fille.click(
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get_file_path, inputs=[pretrained_model_name_or_path_input], outputs=pretrained_model_name_or_path_input
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get_file_path,
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inputs=[pretrained_model_name_or_path_input],
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outputs=pretrained_model_name_or_path_input,
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)
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pretrained_model_name_or_path_folder = gr.Button(
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folder_symbol, elem_id='open_folder_small'
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)
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pretrained_model_name_or_path_folder.click(
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get_folder_path, outputs=pretrained_model_name_or_path_input
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get_folder_path,
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outputs=pretrained_model_name_or_path_input,
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)
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model_list = gr.Dropdown(
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label='(Optional) Model Quick Pick',
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@ -517,10 +544,10 @@ with interface:
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'same as source model',
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'ckpt',
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'diffusers',
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"diffusers_safetensors",
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'diffusers_safetensors',
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'safetensors',
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],
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value='same as source model'
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value='same as source model',
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)
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with gr.Row():
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v2_input = gr.Checkbox(label='v2', value=True)
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@ -607,7 +634,9 @@ with interface:
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)
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with gr.Tab('Training parameters'):
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with gr.Row():
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learning_rate_input = gr.Textbox(label='Learning rate', value=1e-6)
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learning_rate_input = gr.Textbox(
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label='Learning rate', value=1e-6
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)
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lr_scheduler_input = gr.Dropdown(
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label='LR Scheduler',
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choices=[
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@ -662,7 +691,9 @@ with interface:
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with gr.Row():
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seed_input = gr.Textbox(label='Seed', value=1234)
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max_resolution_input = gr.Textbox(
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label='Max resolution', value='512,512', placeholder='512,512'
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label='Max resolution',
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value='512,512',
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placeholder='512,512',
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)
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with gr.Row():
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caption_extention_input = gr.Textbox(
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@ -676,27 +707,45 @@ with interface:
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step=1,
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label='Stop text encoder training',
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)
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with gr.Row():
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full_fp16_input = gr.Checkbox(
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label='Full fp16 training (experimental)', value=False
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)
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no_token_padding_input = gr.Checkbox(
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label='No token padding', value=False
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)
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gradient_checkpointing_input = gr.Checkbox(
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label='Gradient checkpointing', value=False
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)
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with gr.Row():
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enable_bucket_input = gr.Checkbox(
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label='Enable buckets', value=True
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)
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cache_latent_input = gr.Checkbox(label='Cache latent', value=True)
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cache_latent_input = gr.Checkbox(
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label='Cache latent', value=True
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)
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use_8bit_adam_input = gr.Checkbox(
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label='Use 8bit adam', value=True
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)
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xformers_input = gr.Checkbox(label='Use xformers', value=True)
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with gr.Accordion('Advanced Configuration', open=False):
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with gr.Row():
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full_fp16_input = gr.Checkbox(
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label='Full fp16 training (experimental)', value=False
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)
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no_token_padding_input = gr.Checkbox(
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label='No token padding', value=False
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)
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gradient_checkpointing_input = gr.Checkbox(
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label='Gradient checkpointing', value=False
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)
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shuffle_caption = gr.Checkbox(
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label='Shuffle caption', value=False
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)
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save_state = gr.Checkbox(label='Save state', value=False)
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with gr.Row():
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resume = gr.Textbox(
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label='Resume',
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placeholder='path to "last-state" state folder to resume from',
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)
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resume_button = gr.Button('📂', elem_id='open_folder_small')
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resume_button.click(get_folder_path, outputs=resume)
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prior_loss_weight = gr.Number(
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label='Prior loss weight', value=1.0
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)
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button_run = gr.Button('Train model')
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with gr.Tab('Utilities'):
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@ -713,8 +762,6 @@ with interface:
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gradio_dataset_balancing_tab()
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gradio_convert_model_tab()
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button_open_config.click(
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open_configuration,
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inputs=[
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@ -746,7 +793,11 @@ with interface:
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stop_text_encoder_training_input,
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use_8bit_adam_input,
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xformers_input,
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save_model_as_dropdown
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save_model_as_dropdown,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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],
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outputs=[
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config_file_name,
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@ -777,7 +828,11 @@ with interface:
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stop_text_encoder_training_input,
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use_8bit_adam_input,
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xformers_input,
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save_model_as_dropdown
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save_model_as_dropdown,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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],
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)
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@ -815,7 +870,11 @@ with interface:
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stop_text_encoder_training_input,
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use_8bit_adam_input,
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xformers_input,
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save_model_as_dropdown
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save_model_as_dropdown,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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],
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outputs=[config_file_name],
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)
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@ -852,7 +911,11 @@ with interface:
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stop_text_encoder_training_input,
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use_8bit_adam_input,
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xformers_input,
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save_model_as_dropdown
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save_model_as_dropdown,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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],
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outputs=[config_file_name],
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)
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@ -887,7 +950,11 @@ with interface:
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stop_text_encoder_training_input,
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use_8bit_adam_input,
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xformers_input,
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save_model_as_dropdown
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save_model_as_dropdown,
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shuffle_caption,
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save_state,
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resume,
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prior_loss_weight,
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],
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)
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@ -5,7 +5,12 @@ from .common_gui import get_folder_path, add_pre_postfix
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def caption_images(
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caption_text_input, images_dir_input, overwrite_input, caption_file_ext, prefix, postfix
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caption_text_input,
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images_dir_input,
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overwrite_input,
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caption_file_ext,
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prefix,
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postfix,
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):
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# Check for images_dir_input
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if images_dir_input == '':
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@ -28,13 +33,20 @@ def caption_images(
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# Run the command
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subprocess.run(run_cmd)
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if overwrite_input:
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# Add prefix and postfix
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add_pre_postfix(folder=images_dir_input, caption_file_ext=caption_file_ext, prefix=prefix, postfix=postfix)
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add_pre_postfix(
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folder=images_dir_input,
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caption_file_ext=caption_file_ext,
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prefix=prefix,
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postfix=postfix,
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)
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else:
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if not prefix == '' or not postfix == '':
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msgbox('Could not modify caption files with requested change because the "Overwrite existing captions in folder" option is not selected...')
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msgbox(
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'Could not modify caption files with requested change because the "Overwrite existing captions in folder" option is not selected...'
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)
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print('...captioning done')
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@ -97,6 +109,7 @@ def gradio_basic_caption_gui_tab():
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images_dir_input,
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overwrite_input,
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caption_file_ext,
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prefix, postfix
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prefix,
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postfix,
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],
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)
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@ -4,6 +4,7 @@ import subprocess
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import os
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from .common_gui import get_folder_path, add_pre_postfix
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def caption_images(
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train_data_dir,
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caption_file_ext,
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@ -14,7 +15,7 @@ def caption_images(
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min_length,
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beam_search,
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prefix,
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postfix
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postfix,
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):
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# Check for caption_text_input
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# if caption_text_input == "":
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@ -44,9 +45,14 @@ def caption_images(
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# Run the command
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subprocess.run(run_cmd)
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# Add prefix and postfix
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add_pre_postfix(folder=train_data_dir, caption_file_ext=caption_file_ext, prefix=prefix, postfix=postfix)
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add_pre_postfix(
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folder=train_data_dir,
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caption_file_ext=caption_file_ext,
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prefix=prefix,
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postfix=postfix,
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)
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print('...captioning done')
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@ -79,13 +85,13 @@ def gradio_blip_caption_gui_tab():
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placeholder='(Optional) Default: .caption',
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interactive=True,
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)
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prefix = gr.Textbox(
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label='Prefix to add to BLIP caption',
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placeholder='(Optional)',
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interactive=True,
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)
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postfix = gr.Textbox(
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label='Postfix to add to BLIP caption',
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placeholder='(Optional)',
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@ -125,6 +131,6 @@ def gradio_blip_caption_gui_tab():
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min_length,
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beam_search,
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prefix,
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postfix
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postfix,
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],
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)
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@ -1,16 +1,20 @@
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from tkinter import filedialog, Tk
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import os
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def get_file_path(file_path='', defaultextension='.json'):
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current_file_path = file_path
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# print(f'current file path: {current_file_path}')
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root = Tk()
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root.wm_attributes('-topmost', 1)
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root.withdraw()
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file_path = filedialog.askopenfilename(filetypes = (("Config files", "*.json"), ("All files", "*")), defaultextension=defaultextension)
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file_path = filedialog.askopenfilename(
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filetypes=(('Config files', '*.json'), ('All files', '*')),
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||||
defaultextension=defaultextension,
|
||||
)
|
||||
root.destroy()
|
||||
|
||||
|
||||
if file_path == '':
|
||||
file_path = current_file_path
|
||||
|
||||
@ -26,50 +30,58 @@ def remove_doublequote(file_path):
|
||||
|
||||
def get_folder_path(folder_path=''):
|
||||
current_folder_path = folder_path
|
||||
|
||||
|
||||
root = Tk()
|
||||
root.wm_attributes('-topmost', 1)
|
||||
root.withdraw()
|
||||
folder_path = filedialog.askdirectory()
|
||||
root.destroy()
|
||||
|
||||
|
||||
if folder_path == '':
|
||||
folder_path = current_folder_path
|
||||
|
||||
return folder_path
|
||||
|
||||
|
||||
def get_saveasfile_path(file_path='', defaultextension='.json'):
|
||||
current_file_path = file_path
|
||||
# print(f'current file path: {current_file_path}')
|
||||
|
||||
|
||||
root = Tk()
|
||||
root.wm_attributes('-topmost', 1)
|
||||
root.withdraw()
|
||||
save_file_path = filedialog.asksaveasfile(filetypes = (("Config files", "*.json"), ("All files", "*")), defaultextension=defaultextension)
|
||||
save_file_path = filedialog.asksaveasfile(
|
||||
filetypes=(('Config files', '*.json'), ('All files', '*')),
|
||||
defaultextension=defaultextension,
|
||||
)
|
||||
root.destroy()
|
||||
|
||||
# file_path = file_path.name
|
||||
if file_path == '':
|
||||
|
||||
# print(save_file_path)
|
||||
|
||||
if save_file_path == None:
|
||||
file_path = current_file_path
|
||||
else:
|
||||
print(save_file_path.name)
|
||||
file_path = save_file_path.name
|
||||
|
||||
print(file_path)
|
||||
# print(file_path)
|
||||
|
||||
return file_path
|
||||
|
||||
def add_pre_postfix(folder='', prefix='', postfix='', caption_file_ext='.caption'):
|
||||
files = [f for f in os.listdir(folder) if f.endswith(caption_file_ext)]
|
||||
|
||||
def add_pre_postfix(
|
||||
folder='', prefix='', postfix='', caption_file_ext='.caption'
|
||||
):
|
||||
files = [f for f in os.listdir(folder) if f.endswith(caption_file_ext)]
|
||||
if not prefix == '':
|
||||
prefix = f'{prefix} '
|
||||
if not postfix == '':
|
||||
postfix = f' {postfix}'
|
||||
|
||||
|
||||
for file in files:
|
||||
with open(os.path.join(folder, file), 'r+') as f:
|
||||
content = f.read()
|
||||
content = content.rstrip()
|
||||
f.seek(0,0)
|
||||
f.seek(0, 0)
|
||||
f.write(f'{prefix}{content}{postfix}')
|
||||
f.close()
|
||||
f.close()
|
||||
|
||||
@ -8,37 +8,45 @@ from .common_gui import get_folder_path, get_file_path
|
||||
folder_symbol = '\U0001f4c2' # 📂
|
||||
refresh_symbol = '\U0001f504' # 🔄
|
||||
save_style_symbol = '\U0001f4be' # 💾
|
||||
document_symbol = '\U0001F4C4' # 📄
|
||||
document_symbol = '\U0001F4C4' # 📄
|
||||
|
||||
def convert_model(source_model_input, source_model_type, target_model_folder_input, target_model_name_input, target_model_type, target_save_precision_type):
|
||||
|
||||
def convert_model(
|
||||
source_model_input,
|
||||
source_model_type,
|
||||
target_model_folder_input,
|
||||
target_model_name_input,
|
||||
target_model_type,
|
||||
target_save_precision_type,
|
||||
):
|
||||
# Check for caption_text_input
|
||||
if source_model_type == "":
|
||||
msgbox("Invalid source model type")
|
||||
if source_model_type == '':
|
||||
msgbox('Invalid source model type')
|
||||
return
|
||||
|
||||
|
||||
# Check if source model exist
|
||||
if os.path.isfile(source_model_input):
|
||||
print('The provided source model is a file')
|
||||
elif os.path.isdir(source_model_input):
|
||||
print('The provided model is a folder')
|
||||
else:
|
||||
msgbox("The provided source model is neither a file nor a folder")
|
||||
msgbox('The provided source model is neither a file nor a folder')
|
||||
return
|
||||
|
||||
|
||||
# Check if source model exist
|
||||
if os.path.isdir(target_model_folder_input):
|
||||
print('The provided model folder exist')
|
||||
else:
|
||||
msgbox("The provided target folder does not exist")
|
||||
msgbox('The provided target folder does not exist')
|
||||
return
|
||||
|
||||
|
||||
run_cmd = f'.\\venv\Scripts\python.exe "tools/convert_diffusers20_original_sd.py"'
|
||||
|
||||
|
||||
v1_models = [
|
||||
'runwayml/stable-diffusion-v1-5',
|
||||
'CompVis/stable-diffusion-v1-4',
|
||||
'runwayml/stable-diffusion-v1-5',
|
||||
'CompVis/stable-diffusion-v1-4',
|
||||
]
|
||||
|
||||
|
||||
# check if v1 models
|
||||
if str(source_model_type) in v1_models:
|
||||
print('SD v1 model specified. Setting --v1 parameter')
|
||||
@ -46,54 +54,76 @@ def convert_model(source_model_input, source_model_type, target_model_folder_inp
|
||||
else:
|
||||
print('SD v2 model specified. Setting --v2 parameter')
|
||||
run_cmd += ' --v2'
|
||||
|
||||
|
||||
if not target_save_precision_type == 'unspecified':
|
||||
run_cmd += f' --{target_save_precision_type}'
|
||||
|
||||
if target_model_type == "diffuser" or target_model_type == "diffuser_safetensors":
|
||||
|
||||
if (
|
||||
target_model_type == 'diffuser'
|
||||
or target_model_type == 'diffuser_safetensors'
|
||||
):
|
||||
run_cmd += f' --reference_model="{source_model_type}"'
|
||||
|
||||
|
||||
if target_model_type == 'diffuser_safetensors':
|
||||
run_cmd += ' --use_safetensors'
|
||||
|
||||
|
||||
run_cmd += f' "{source_model_input}"'
|
||||
|
||||
if target_model_type == "diffuser" or target_model_type == "diffuser_safetensors":
|
||||
target_model_path = os.path.join(target_model_folder_input, target_model_name_input)
|
||||
|
||||
if (
|
||||
target_model_type == 'diffuser'
|
||||
or target_model_type == 'diffuser_safetensors'
|
||||
):
|
||||
target_model_path = os.path.join(
|
||||
target_model_folder_input, target_model_name_input
|
||||
)
|
||||
run_cmd += f' "{target_model_path}"'
|
||||
else:
|
||||
target_model_path = os.path.join(target_model_folder_input, f'{target_model_name_input}.{target_model_type}')
|
||||
target_model_path = os.path.join(
|
||||
target_model_folder_input,
|
||||
f'{target_model_name_input}.{target_model_type}',
|
||||
)
|
||||
run_cmd += f' "{target_model_path}"'
|
||||
|
||||
|
||||
print(run_cmd)
|
||||
|
||||
|
||||
# Run the command
|
||||
subprocess.run(run_cmd)
|
||||
|
||||
if not target_model_type == "diffuser" or target_model_type == "diffuser_safetensors":
|
||||
|
||||
v2_models = ['stabilityai/stable-diffusion-2-1-base',
|
||||
'stabilityai/stable-diffusion-2-base',]
|
||||
v_parameterization =[
|
||||
'stabilityai/stable-diffusion-2-1',
|
||||
'stabilityai/stable-diffusion-2',]
|
||||
|
||||
|
||||
if (
|
||||
not target_model_type == 'diffuser'
|
||||
or target_model_type == 'diffuser_safetensors'
|
||||
):
|
||||
|
||||
v2_models = [
|
||||
'stabilityai/stable-diffusion-2-1-base',
|
||||
'stabilityai/stable-diffusion-2-base',
|
||||
]
|
||||
v_parameterization = [
|
||||
'stabilityai/stable-diffusion-2-1',
|
||||
'stabilityai/stable-diffusion-2',
|
||||
]
|
||||
|
||||
if str(source_model_type) in v2_models:
|
||||
inference_file = os.path.join(target_model_folder_input, f'{target_model_name_input}.yaml')
|
||||
inference_file = os.path.join(
|
||||
target_model_folder_input, f'{target_model_name_input}.yaml'
|
||||
)
|
||||
print(f'Saving v2-inference.yaml as {inference_file}')
|
||||
shutil.copy(
|
||||
f'./v2_inference/v2-inference.yaml',
|
||||
f'{inference_file}',
|
||||
)
|
||||
|
||||
|
||||
if str(source_model_type) in v_parameterization:
|
||||
inference_file = os.path.join(target_model_folder_input, f'{target_model_name_input}.yaml')
|
||||
inference_file = os.path.join(
|
||||
target_model_folder_input, f'{target_model_name_input}.yaml'
|
||||
)
|
||||
print(f'Saving v2-inference-v.yaml as {inference_file}')
|
||||
shutil.copy(
|
||||
f'./v2_inference/v2-inference-v.yaml',
|
||||
f'{inference_file}',
|
||||
)
|
||||
|
||||
|
||||
# parser = argparse.ArgumentParser()
|
||||
# parser.add_argument("--v1", action='store_true',
|
||||
# help='load v1.x model (v1 or v2 is required to load checkpoint) / 1.xのモデルを読み込む')
|
||||
@ -138,22 +168,27 @@ def gradio_convert_model_tab():
|
||||
button_source_model_dir.click(
|
||||
get_folder_path, outputs=source_model_input
|
||||
)
|
||||
|
||||
|
||||
button_source_model_file = gr.Button(
|
||||
document_symbol, elem_id='open_folder_small'
|
||||
)
|
||||
button_source_model_file.click(
|
||||
get_file_path, inputs=[source_model_input], outputs=source_model_input
|
||||
get_file_path,
|
||||
inputs=[source_model_input],
|
||||
outputs=source_model_input,
|
||||
)
|
||||
|
||||
source_model_type = gr.Dropdown(label="Source model type", choices=[
|
||||
|
||||
source_model_type = gr.Dropdown(
|
||||
label='Source model type',
|
||||
choices=[
|
||||
'stabilityai/stable-diffusion-2-1-base',
|
||||
'stabilityai/stable-diffusion-2-base',
|
||||
'stabilityai/stable-diffusion-2-1',
|
||||
'stabilityai/stable-diffusion-2',
|
||||
'runwayml/stable-diffusion-v1-5',
|
||||
'CompVis/stable-diffusion-v1-4',
|
||||
],)
|
||||
],
|
||||
)
|
||||
with gr.Row():
|
||||
target_model_folder_input = gr.Textbox(
|
||||
label='Target model folder',
|
||||
@ -166,30 +201,37 @@ def gradio_convert_model_tab():
|
||||
button_target_model_folder.click(
|
||||
get_folder_path, outputs=target_model_folder_input
|
||||
)
|
||||
|
||||
|
||||
target_model_name_input = gr.Textbox(
|
||||
label='Target model name',
|
||||
placeholder='target model name...',
|
||||
interactive=True,
|
||||
)
|
||||
target_model_type = gr.Dropdown(label="Target model type", choices=[
|
||||
target_model_type = gr.Dropdown(
|
||||
label='Target model type',
|
||||
choices=[
|
||||
'diffuser',
|
||||
'diffuser_safetensors',
|
||||
'ckpt',
|
||||
'safetensors',
|
||||
],)
|
||||
target_save_precision_type = gr.Dropdown(label="Target model precison", choices=[
|
||||
'unspecified',
|
||||
'fp16',
|
||||
'bf16',
|
||||
'float'
|
||||
], value='unspecified')
|
||||
|
||||
|
||||
],
|
||||
)
|
||||
target_save_precision_type = gr.Dropdown(
|
||||
label='Target model precison',
|
||||
choices=['unspecified', 'fp16', 'bf16', 'float'],
|
||||
value='unspecified',
|
||||
)
|
||||
|
||||
convert_button = gr.Button('Convert model')
|
||||
|
||||
convert_button.click(
|
||||
convert_model,
|
||||
inputs=[source_model_input, source_model_type, target_model_folder_input, target_model_name_input, target_model_type, target_save_precision_type
|
||||
inputs=[
|
||||
source_model_input,
|
||||
source_model_type,
|
||||
target_model_folder_input,
|
||||
target_model_name_input,
|
||||
target_model_type,
|
||||
target_save_precision_type,
|
||||
],
|
||||
)
|
||||
|
||||
@ -13,7 +13,7 @@ from .common_gui import get_folder_path
|
||||
|
||||
|
||||
def dataset_balancing(concept_repeats, folder, insecure):
|
||||
|
||||
|
||||
if not concept_repeats > 0:
|
||||
# Display an error message if the total number of repeats is not a valid integer
|
||||
msgbox('Please enter a valid integer for the total number of repeats.')
|
||||
@ -72,23 +72,35 @@ def dataset_balancing(concept_repeats, folder, insecure):
|
||||
|
||||
os.rename(old_name, new_name)
|
||||
else:
|
||||
print(f"Skipping folder {subdir} because it does not match kohya_ss expected syntax...")
|
||||
print(
|
||||
f'Skipping folder {subdir} because it does not match kohya_ss expected syntax...'
|
||||
)
|
||||
|
||||
msgbox('Dataset balancing completed...')
|
||||
|
||||
|
||||
def warning(insecure):
|
||||
if insecure:
|
||||
if boolbox(f'WARNING!!! You have asked to rename non kohya_ss <num>_<text> folders...\n\nAre you sure you want to do that?', choices=("Yes, I like danger", "No, get me out of here")):
|
||||
if boolbox(
|
||||
f'WARNING!!! You have asked to rename non kohya_ss <num>_<text> folders...\n\nAre you sure you want to do that?',
|
||||
choices=('Yes, I like danger', 'No, get me out of here'),
|
||||
):
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
def gradio_dataset_balancing_tab():
|
||||
with gr.Tab('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.')
|
||||
gr.Markdown('WARNING! The use of this utility on the wrong folder can lead to unexpected folder renaming!!!')
|
||||
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.'
|
||||
)
|
||||
gr.Markdown(
|
||||
'WARNING! The use of this utility on the wrong folder can lead to unexpected folder renaming!!!'
|
||||
)
|
||||
with gr.Row():
|
||||
select_dataset_folder_input = gr.Textbox(label="Dataset folder",
|
||||
select_dataset_folder_input = gr.Textbox(
|
||||
label='Dataset folder',
|
||||
placeholder='Folder containing the concepts folders to balance...',
|
||||
interactive=True,
|
||||
)
|
||||
@ -106,10 +118,17 @@ def gradio_dataset_balancing_tab():
|
||||
label='Training steps per concept per epoch',
|
||||
)
|
||||
with gr.Accordion('Advanced options', open=False):
|
||||
insecure = gr.Checkbox(value=False, label="DANGER!!! -- Insecure folder renaming -- DANGER!!!")
|
||||
insecure = gr.Checkbox(
|
||||
value=False,
|
||||
label='DANGER!!! -- Insecure folder renaming -- DANGER!!!',
|
||||
)
|
||||
insecure.change(warning, inputs=insecure, outputs=insecure)
|
||||
balance_button = gr.Button('Balance dataset')
|
||||
balance_button.click(
|
||||
dataset_balancing,
|
||||
inputs=[total_repeats_number, select_dataset_folder_input, insecure],
|
||||
inputs=[
|
||||
total_repeats_number,
|
||||
select_dataset_folder_input,
|
||||
insecure,
|
||||
],
|
||||
)
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
Loading…
Reference in New Issue
Block a user