Implement open and save config for LoRA

library/common_gui.py

@@ -20,6 +20,21 @@ def get_file_path(file_path='', defaultextension='.json'):
 
     return file_path
 
+def get_any_file_path(file_path=''):
+    current_file_path = file_path
+    # print(f'current file path: {current_file_path}')
+
+    root = Tk()
+    root.wm_attributes('-topmost', 1)
+    root.withdraw()
+    file_path = filedialog.askopenfilename()
+    root.destroy()
+
+    if file_path == '':
+        file_path = current_file_path
+
+    return file_path
+
 
 def remove_doublequote(file_path):
     if file_path != None:

lora_gui.py

@@ -15,6 +15,7 @@ from library.common_gui import (
     get_folder_path,
     remove_doublequote,
     get_file_path,
+    get_any_file_path,
     get_saveasfile_path,
 )
 from library.dreambooth_folder_creation_gui import (
@@ -64,7 +65,7 @@ def save_configuration(
     shuffle_caption,
     save_state,
     resume,
-    prior_loss_weight,
+    prior_loss_weight, text_encoder_lr, unet_lr, network_train, network_dim
 ):
     original_file_path = file_path
 
@@ -117,6 +118,10 @@ def save_configuration(
         'save_state': save_state,
         'resume': resume,
         'prior_loss_weight': prior_loss_weight,
+        'text_encoder_lr': text_encoder_lr,
+        'unet_lr': unet_lr,
+        'network_train': network_train,
+        'network_dim': network_dim
     }
 
     # Save the data to the selected file
@@ -159,7 +164,7 @@ def open_configuration(
     shuffle_caption,
     save_state,
     resume,
-    prior_loss_weight,
+    prior_loss_weight, text_encoder_lr, unet_lr, network_train, network_dim
 ):
 
     original_file_path = file_path
@@ -213,6 +218,10 @@ def open_configuration(
         my_data.get('save_state', save_state),
         my_data.get('resume', resume),
         my_data.get('prior_loss_weight', prior_loss_weight),
+        my_data.get('text_encoder_lr', text_encoder_lr),
+        my_data.get('unet_lr', unet_lr),
+        my_data.get('network_train', network_train),
+        my_data.get('network_dim', network_dim),
     )
 
 
@@ -548,10 +557,10 @@ def lora_tab(
                 label='Pretrained model name or path',
                 placeholder='enter the path to custom model or name of pretrained model',
             )
-            pretrained_model_name_or_path_fille = gr.Button(
+            pretrained_model_name_or_path_file = gr.Button(
                 document_symbol, elem_id='open_folder_small'
             )
-            pretrained_model_name_or_path_fille.click(
+            pretrained_model_name_or_path_file.click(
                 get_file_path,
                 inputs=[pretrained_model_name_or_path_input],
                 outputs=pretrained_model_name_or_path_input,
@@ -586,6 +595,19 @@ def lora_tab(
                 ],
                 value='same as source model',
             )
+        with gr.Row():
+            lora_network_weights = gr.Textbox(
+                label='LoRA network weights',
+                placeholder='{Optional) Path to existing LoRA network weights to resume training}',
+            )
+            lora_network_weights_file = gr.Button(
+                document_symbol, elem_id='open_folder_small'
+            )
+            lora_network_weights_file.click(
+                get_any_file_path,
+                inputs=[lora_network_weights],
+                outputs=lora_network_weights,
+            )
         with gr.Row():
             v2_input = gr.Checkbox(label='v2', value=True)
             v_parameterization_input = gr.Checkbox(
@@ -812,200 +834,63 @@ def lora_tab(
         gradio_dataset_balancing_tab()
 
     button_run = gr.Button('Train model')
+    
+    settings_list = [
+        pretrained_model_name_or_path_input,
+        v2_input,
+        v_parameterization_input,
+        logging_dir_input,
+        train_data_dir_input,
+        reg_data_dir_input,
+        output_dir_input,
+        max_resolution_input,
+        learning_rate_input,
+        lr_scheduler_input,
+        lr_warmup_input,
+        train_batch_size_input,
+        epoch_input,
+        save_every_n_epochs_input,
+        mixed_precision_input,
+        save_precision_input,
+        seed_input,
+        num_cpu_threads_per_process_input,
+        cache_latent_input,
+        caption_extention_input,
+        enable_bucket_input,
+        gradient_checkpointing_input,
+        full_fp16_input,
+        no_token_padding_input,
+        stop_text_encoder_training_input,
+        use_8bit_adam_input,
+        xformers_input,
+        save_model_as_dropdown,
+        shuffle_caption,
+        save_state,
+        resume,
+        prior_loss_weight, text_encoder_lr, unet_lr, network_train, network_dim
+    ]
 
     button_open_config.click(
         open_configuration,
-        inputs=[
+        inputs=[config_file_name] + settings_list,
-            config_file_name,
+        outputs=[config_file_name] + settings_list,
-            pretrained_model_name_or_path_input,
-            v2_input,
-            v_parameterization_input,
-            logging_dir_input,
-            train_data_dir_input,
-            reg_data_dir_input,
-            output_dir_input,
-            max_resolution_input,
-            learning_rate_input,
-            lr_scheduler_input,
-            lr_warmup_input,
-            train_batch_size_input,
-            epoch_input,
-            save_every_n_epochs_input,
-            mixed_precision_input,
-            save_precision_input,
-            seed_input,
-            num_cpu_threads_per_process_input,
-            cache_latent_input,
-            caption_extention_input,
-            enable_bucket_input,
-            gradient_checkpointing_input,
-            full_fp16_input,
-            no_token_padding_input,
-            stop_text_encoder_training_input,
-            use_8bit_adam_input,
-            xformers_input,
-            save_model_as_dropdown,
-            shuffle_caption,
-            save_state,
-            resume,
-            prior_loss_weight,
-        ],
-        outputs=[
-            config_file_name,
-            pretrained_model_name_or_path_input,
-            v2_input,
-            v_parameterization_input,
-            logging_dir_input,
-            train_data_dir_input,
-            reg_data_dir_input,
-            output_dir_input,
-            max_resolution_input,
-            learning_rate_input,
-            lr_scheduler_input,
-            lr_warmup_input,
-            train_batch_size_input,
-            epoch_input,
-            save_every_n_epochs_input,
-            mixed_precision_input,
-            save_precision_input,
-            seed_input,
-            num_cpu_threads_per_process_input,
-            cache_latent_input,
-            caption_extention_input,
-            enable_bucket_input,
-            gradient_checkpointing_input,
-            full_fp16_input,
-            no_token_padding_input,
-            stop_text_encoder_training_input,
-            use_8bit_adam_input,
-            xformers_input,
-            save_model_as_dropdown,
-            shuffle_caption,
-            save_state,
-            resume,
-            prior_loss_weight,
-        ],
     )
 
     button_save_config.click(
         save_configuration,
-        inputs=[
+        inputs=[dummy_db_false, config_file_name] + settings_list,
-            dummy_db_false,
-            config_file_name,
-            pretrained_model_name_or_path_input,
-            v2_input,
-            v_parameterization_input,
-            logging_dir_input,
-            train_data_dir_input,
-            reg_data_dir_input,
-            output_dir_input,
-            max_resolution_input,
-            learning_rate_input,
-            lr_scheduler_input,
-            lr_warmup_input,
-            train_batch_size_input,
-            epoch_input,
-            save_every_n_epochs_input,
-            mixed_precision_input,
-            save_precision_input,
-            seed_input,
-            num_cpu_threads_per_process_input,
-            cache_latent_input,
-            caption_extention_input,
-            enable_bucket_input,
-            gradient_checkpointing_input,
-            full_fp16_input,
-            no_token_padding_input,
-            stop_text_encoder_training_input,
-            use_8bit_adam_input,
-            xformers_input,
-            save_model_as_dropdown,
-            shuffle_caption,
-            save_state,
-            resume,
-            prior_loss_weight,
-        ],
         outputs=[config_file_name],
     )
 
     button_save_as_config.click(
         save_configuration,
-        inputs=[
+        inputs=[dummy_db_true, config_file_name] + settings_list,
-            dummy_db_true,
-            config_file_name,
-            pretrained_model_name_or_path_input,
-            v2_input,
-            v_parameterization_input,
-            logging_dir_input,
-            train_data_dir_input,
-            reg_data_dir_input,
-            output_dir_input,
-            max_resolution_input,
-            learning_rate_input,
-            lr_scheduler_input,
-            lr_warmup_input,
-            train_batch_size_input,
-            epoch_input,
-            save_every_n_epochs_input,
-            mixed_precision_input,
-            save_precision_input,
-            seed_input,
-            num_cpu_threads_per_process_input,
-            cache_latent_input,
-            caption_extention_input,
-            enable_bucket_input,
-            gradient_checkpointing_input,
-            full_fp16_input,
-            no_token_padding_input,
-            stop_text_encoder_training_input,
-            use_8bit_adam_input,
-            xformers_input,
-            save_model_as_dropdown,
-            shuffle_caption,
-            save_state,
-            resume,
-            prior_loss_weight,
-        ],
         outputs=[config_file_name],
     )
 
     button_run.click(
         train_model,
-        inputs=[
+        inputs=settings_list, 
-            pretrained_model_name_or_path_input,
-            v2_input,
-            v_parameterization_input,
-            logging_dir_input,
-            train_data_dir_input,
-            reg_data_dir_input,
-            output_dir_input,
-            max_resolution_input,
-            learning_rate_input,
-            lr_scheduler_input,
-            lr_warmup_input,
-            train_batch_size_input,
-            epoch_input,
-            save_every_n_epochs_input,
-            mixed_precision_input,
-            save_precision_input,
-            seed_input,
-            num_cpu_threads_per_process_input,
-            cache_latent_input,
-            caption_extention_input,
-            enable_bucket_input,
-            gradient_checkpointing_input,
-            full_fp16_input,
-            no_token_padding_input,
-            stop_text_encoder_training_input,
-            use_8bit_adam_input,
-            xformers_input,
-            save_model_as_dropdown,
-            shuffle_caption,
-            save_state,
-            resume,
-            prior_loss_weight,
-            text_encoder_lr, unet_lr, network_train, network_dim
-        ],
     )
 
     return (

setup.py

@@ -1,3 +1,3 @@
 from setuptools import setup, find_packages
  
-setup(name = "library", version="1.0.0", packages = find_packages())
+setup(name = "library", version="1.0.1", packages = find_packages())