commit
f6b261de52
@ -163,7 +163,12 @@ This will store your a backup file with your current locally installed pip packa
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## Change History
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* 2023/02/24 (v20.8.2):
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* 2023/03/01 (v21.0.1):
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- Add warning to tensorboard start if the log information is missing
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- Fix issue with 8bitadam on older config file load
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* 2023/02/27 (v21.0.0):
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- Add tensorboard start and stop support to the GUI
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* 2023/02/26 (v20.8.2):
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- Fix issue https://github.com/bmaltais/kohya_ss/issues/231
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- Change default for seed to random
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- Add support for --share argument to `kohya_gui.py` and `gui.ps1`
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@ -25,6 +25,12 @@ from library.common_gui import (
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gradio_config,
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gradio_source_model,
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set_legacy_8bitadam,
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update_optimizer,
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)
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from library.tensorboard_gui import (
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gradio_tensorboard,
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start_tensorboard,
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stop_tensorboard,
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)
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from library.dreambooth_folder_creation_gui import (
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gradio_dreambooth_folder_creation_tab,
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@ -203,6 +209,8 @@ def open_configuration(
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with open(file_path, 'r') as f:
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my_data_db = json.load(f)
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print('Loading config...')
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# Update values to fix deprecated use_8bit_adam checkbox and set appropriate optimizer if it is set to True
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my_data = update_optimizer(my_data)
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else:
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file_path = original_file_path # In case a file_path was provided and the user decide to cancel the open action
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my_data_db = {}
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@ -639,7 +647,19 @@ def dreambooth_tab(
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logging_dir_input=logging_dir,
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)
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button_run = gr.Button('Train model')
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button_run = gr.Button('Train model', variant='primary')
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# Setup gradio tensorboard buttons
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button_start_tensorboard, button_stop_tensorboard = gradio_tensorboard()
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button_start_tensorboard.click(
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start_tensorboard,
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inputs=logging_dir,
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)
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button_stop_tensorboard.click(
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stop_tensorboard,
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)
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settings_list = [
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pretrained_model_name_or_path,
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@ -19,6 +19,12 @@ from library.common_gui import (
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color_aug_changed,
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run_cmd_training,
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set_legacy_8bitadam,
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update_optimizer,
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)
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from library.tensorboard_gui import (
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gradio_tensorboard,
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start_tensorboard,
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stop_tensorboard,
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)
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from library.utilities import utilities_tab
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@ -198,21 +204,22 @@ def open_config_file(
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original_file_path = file_path
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file_path = get_file_path(file_path)
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if file_path != '' and file_path != None:
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print(f'Loading config file {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_ft = json.load(f)
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my_data_db = json.load(f)
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print('Loading config...')
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# Update values to fix deprecated use_8bit_adam checkbox and set appropriate optimizer if it is set to True
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my_data = update_optimizer(my_data)
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else:
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file_path = original_file_path # In case a file_path was provided and the user decide to cancel the open action
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my_data_ft = {}
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file_path = original_file_path # In case a file_path was provided and the user decide to cancel the open action
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my_data_db = {}
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values = [file_path]
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for key, value in parameters:
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# Set the value in the dictionary to the corresponding value in `my_data_ft`, or the default value if not found
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# Set the value in the dictionary to the corresponding value in `my_data`, or the default value if not found
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if not key in ['file_path']:
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values.append(my_data_ft.get(key, value))
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# print(values)
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values.append(my_data_db.get(key, value))
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return tuple(values)
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@ -623,7 +630,19 @@ def finetune_tab():
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outputs=[optimizer, use_8bit_adam],
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)
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button_run = gr.Button('Train model')
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button_run = gr.Button('Train model', variant='primary')
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# Setup gradio tensorboard buttons
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button_start_tensorboard, button_stop_tensorboard = gradio_tensorboard()
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button_start_tensorboard.click(
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start_tensorboard,
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inputs=logging_dir,
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)
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button_stop_tensorboard.click(
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stop_tensorboard,
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)
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settings_list = [
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pretrained_model_name_or_path,
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@ -9,6 +9,12 @@ refresh_symbol = '\U0001f504' # 🔄
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save_style_symbol = '\U0001f4be' # 💾
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document_symbol = '\U0001F4C4' # 📄
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def update_optimizer(my_data):
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if my_data.get('use_8bit_adam', False):
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my_data['optimizer'] = 'AdamW8bit'
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my_data['use_8bit_adam'] = False
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return my_data
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def get_dir_and_file(file_path):
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dir_path, file_name = os.path.split(file_path)
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@ -604,7 +610,8 @@ def gradio_advanced_training():
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label='Memory efficient attention', value=False
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)
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with gr.Row():
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use_8bit_adam = gr.Checkbox(label='Use 8bit adam', value=True)
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# This use_8bit_adam element should be removed in a future release as it is no longer used
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use_8bit_adam = gr.Checkbox(label='Use 8bit adam', value=False, visible=False)
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xformers = gr.Checkbox(label='Use xformers', value=True)
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color_aug = gr.Checkbox(label='Color augmentation', value=False)
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flip_aug = gr.Checkbox(label='Flip augmentation', value=False)
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46
library/tensorboard_gui.py
Normal file
46
library/tensorboard_gui.py
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@ -0,0 +1,46 @@
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import os
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import gradio as gr
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from easygui import msgbox
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import subprocess
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import time
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tensorboard_proc = None # I know... bad but heh
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def start_tensorboard(logging_dir):
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global tensorboard_proc
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if not os.listdir(logging_dir):
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print("Error: log folder is empty")
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msgbox(msg="Error: log folder is empty")
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return
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run_cmd = f'tensorboard.exe --logdir "{logging_dir}"'
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print(run_cmd)
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if tensorboard_proc is not None:
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print("Tensorboard is already running. Terminating existing process before starting new one...")
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stop_tensorboard()
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# Start background process
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print('Starting tensorboard...')
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tensorboard_proc = subprocess.Popen(run_cmd)
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# Wait for some time to allow TensorBoard to start up
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time.sleep(5)
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# Open the TensorBoard URL in the default browser
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print('Opening tensorboard url in browser...')
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import webbrowser
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webbrowser.open('http://localhost:6006')
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def stop_tensorboard():
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print('Stopping tensorboard process...')
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tensorboard_proc.kill()
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print('...process stopped')
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def gradio_tensorboard():
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with gr.Row():
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button_start_tensorboard = gr.Button('Start tensorboard')
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button_stop_tensorboard = gr.Button('Stop tensorboard')
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return(button_start_tensorboard, button_stop_tensorboard)
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25
lora_gui.py
25
lora_gui.py
@ -25,10 +25,16 @@ from library.common_gui import (
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gradio_source_model,
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run_cmd_training,
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set_legacy_8bitadam,
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update_optimizer,
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)
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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.tensorboard_gui import (
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gradio_tensorboard,
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start_tensorboard,
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stop_tensorboard,
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)
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from library.dataset_balancing_gui import gradio_dataset_balancing_tab
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from library.utilities import utilities_tab
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from library.merge_lora_gui import gradio_merge_lora_tab
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@ -41,7 +47,6 @@ refresh_symbol = '\U0001f504' # 🔄
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save_style_symbol = '\U0001f4be' # 💾
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document_symbol = '\U0001F4C4' # 📄
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def save_configuration(
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save_as,
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file_path,
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@ -221,6 +226,8 @@ def open_configuration(
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with open(file_path, 'r') as f:
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my_data = json.load(f)
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print('Loading config...')
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# Update values to fix deprecated use_8bit_adam checkbox and set appropriate optimizer if it is set to True
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my_data = update_optimizer(my_data)
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else:
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file_path = original_file_path # In case a file_path was provided and the user decide to cancel the open action
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my_data = {}
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@ -745,7 +752,19 @@ def lora_tab(
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gradio_resize_lora_tab()
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gradio_verify_lora_tab()
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button_run = gr.Button('Train model')
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button_run = gr.Button('Train model', variant='primary')
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# Setup gradio tensorboard buttons
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button_start_tensorboard, button_stop_tensorboard = gradio_tensorboard()
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button_start_tensorboard.click(
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start_tensorboard,
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inputs=logging_dir,
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)
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button_stop_tensorboard.click(
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stop_tensorboard,
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)
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settings_list = [
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pretrained_model_name_or_path,
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@ -894,4 +913,4 @@ if __name__ == '__main__':
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args = parser.parse_args()
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UI(username=args.username, password=args.password, inbrowser=args.inbrowser, server_port=args.server_port)
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UI(username=args.username, password=args.password, inbrowser=args.inbrowser, server_port=args.server_port)
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@ -25,6 +25,12 @@ from library.common_gui import (
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gradio_config,
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gradio_source_model,
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set_legacy_8bitadam,
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update_optimizer,
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)
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from library.tensorboard_gui import (
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gradio_tensorboard,
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start_tensorboard,
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stop_tensorboard,
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)
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from library.dreambooth_folder_creation_gui import (
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gradio_dreambooth_folder_creation_tab,
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@ -213,6 +219,8 @@ def open_configuration(
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with open(file_path, 'r') as f:
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my_data_db = json.load(f)
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print('Loading config...')
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# Update values to fix deprecated use_8bit_adam checkbox and set appropriate optimizer if it is set to True
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my_data = update_optimizer(my_data)
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else:
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file_path = original_file_path # In case a file_path was provided and the user decide to cancel the open action
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my_data_db = {}
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@ -714,7 +722,19 @@ def ti_tab(
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logging_dir_input=logging_dir,
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)
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button_run = gr.Button('Train TI')
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button_run = gr.Button('Train model', variant='primary')
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# Setup gradio tensorboard buttons
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button_start_tensorboard, button_stop_tensorboard = gradio_tensorboard()
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button_start_tensorboard.click(
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start_tensorboard,
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inputs=logging_dir,
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)
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button_stop_tensorboard.click(
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stop_tensorboard,
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)
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settings_list = [
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pretrained_model_name_or_path,
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21
tools/rename_depth_mask.py
Normal file
21
tools/rename_depth_mask.py
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@ -0,0 +1,21 @@
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import os
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import argparse
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# Define the command line arguments
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parser = argparse.ArgumentParser(description='Rename files in a folder')
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parser.add_argument('folder', metavar='folder', type=str, help='the folder containing the files to rename')
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# Parse the arguments
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args = parser.parse_args()
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# Get the list of files in the folder
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files = os.listdir(args.folder)
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# Loop through each file in the folder
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for file in files:
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# Check if the file has the expected format
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if file.endswith('-0000.png'):
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# Get the new file name
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new_file_name = file[:-9] + '.mask'
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# Rename the file
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os.rename(os.path.join(args.folder, file), os.path.join(args.folder, new_file_name))
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Block a user