diff --git a/finetune_gui.py b/finetune_gui.py index 914905b..1b938f7 100644 --- a/finetune_gui.py +++ b/finetune_gui.py @@ -41,7 +41,6 @@ def save_variables( "pretrained_model_name_or_path": pretrained_model_name_or_path, "v2": v2, "v_model": v_model, - # "model_list": model_list, "logging_dir": logging_dir, "train_data_dir": train_data_dir, "reg_data_dir": reg_data_dir, @@ -280,29 +279,25 @@ def set_pretrained_model_name_or_path_input(value, v2, v_model): return value, v2, v_model - -# Define the output element -output = gr.outputs.Textbox(label="Values of variables") - interface = gr.Blocks() with interface: gr.Markdown("Enter kohya finetuner parameter using this interface.") with gr.Accordion("Configuration File Load/Save", open=False): with gr.Row(): - config_file_name = gr.inputs.Textbox( - label="Config file name", default="") + config_file_name = gr.Textbox( + label="Config file name") b1 = gr.Button("Load config") b2 = gr.Button("Save config") with gr.Tab("Source model"): # Define the input elements with gr.Row(): - pretrained_model_name_or_path_input = gr.inputs.Textbox( + pretrained_model_name_or_path_input = gr.Textbox( label="Pretrained model name or path", placeholder="enter the path to custom model or name of pretrained model", ) model_list = gr.Dropdown( - label="Model Quick Pick", + label="(Optional) Model Quick Pick", choices=[ "custom", "stabilityai/stable-diffusion-2-1-base", @@ -312,11 +307,10 @@ with interface: "runwayml/stable-diffusion-v1-5", "CompVis/stable-diffusion-v1-4" ], - value="custom", ) with gr.Row(): - v2_input = gr.inputs.Checkbox(label="v2", default=True) - v_model_input = gr.inputs.Checkbox(label="v_model", default=False) + v2_input = gr.Checkbox(label="v2", value=True) + v_model_input = gr.Checkbox(label="v_model", value=False) model_list.change( set_pretrained_model_name_or_path_input, inputs=[model_list, v2_input, v_model_input], @@ -325,25 +319,25 @@ with interface: ) with gr.Tab("Directories"): with gr.Row(): - train_data_dir_input = gr.inputs.Textbox( + train_data_dir_input = gr.Textbox( label="Image folder", placeholder="directory where the training folders containing the images are located" ) - reg_data_dir_input = gr.inputs.Textbox( + reg_data_dir_input = gr.Textbox( label="Regularisation folder", placeholder="directory where where the regularization folders containing the images are located" ) with gr.Row(): - output_dir_input = gr.inputs.Textbox( + output_dir_input = gr.Textbox( label="Output directory", placeholder="directory to output trained model", ) - logging_dir_input = gr.inputs.Textbox( + logging_dir_input = gr.Textbox( label="Logging directory", placeholder="Optional: enable logging and output TensorBoard log to this directory" ) with gr.Tab("Training parameters"): with gr.Row(): - learning_rate_input = gr.inputs.Textbox( - label="Learning rate", default=1e-6) + learning_rate_input = gr.Textbox( + label="Learning rate", value=1e-6) lr_scheduler_input = gr.Dropdown( label="LR Scheduler", choices=[ @@ -356,14 +350,14 @@ with interface: ], value="constant", ) - lr_warmup_input = gr.inputs.Textbox(label="LR warmup", default=0) + lr_warmup_input = gr.Textbox(label="LR warmup", value=0) with gr.Row(): - train_batch_size_input = gr.inputs.Textbox( - label="Train batch size", default=1 + train_batch_size_input = gr.Textbox( + label="Train batch size", value=1 ) - epoch_input = gr.inputs.Textbox(label="Epoch", default=1) - save_every_n_epochs_input = gr.inputs.Textbox( - label="Save every N epochs", default=1 + epoch_input = gr.Textbox(label="Epoch", value=1) + save_every_n_epochs_input = gr.Textbox( + label="Save every N epochs", value=1 ) with gr.Row(): mixed_precision_input = gr.Dropdown( @@ -384,34 +378,34 @@ with interface: ], value="fp16", ) - num_cpu_threads_per_process_input = gr.inputs.Textbox( - label="Number of CPU threads per process", default=4 + num_cpu_threads_per_process_input = gr.Textbox( + label="Number of CPU threads per process", value=4 ) with gr.Row(): - seed_input = gr.inputs.Textbox(label="Seed", default=1234) - max_resolution_input = gr.inputs.Textbox( - label="Max resolution", default="512,512" + seed_input = gr.Textbox(label="Seed", value=1234) + max_resolution_input = gr.Textbox( + label="Max resolution", value="512,512" ) - caption_extention_input = gr.inputs.Textbox( + caption_extention_input = gr.Textbox( label="Caption Extension", placeholder="(Optional) Extension for caption files. default: .caption") with gr.Row(): - use_safetensors_input = gr.inputs.Checkbox( - label="Use safetensor when saving checkpoint", default=False + use_safetensors_input = gr.Checkbox( + label="Use safetensor when saving checkpoint", value=False ) - enable_bucket_input = gr.inputs.Checkbox( - label="Enable buckets", default=False + enable_bucket_input = gr.Checkbox( + label="Enable buckets", value=False ) - cache_latent_input = gr.inputs.Checkbox( - label="Cache latent", default=True + cache_latent_input = gr.Checkbox( + label="Cache latent", value=True ) with gr.Tab("Model conversion"): - convert_to_safetensors_input = gr.inputs.Checkbox( - label="Convert to SafeTensors", default=False + convert_to_safetensors_input = gr.Checkbox( + label="Convert to SafeTensors", value=False ) - convert_to_ckpt_input = gr.inputs.Checkbox( - label="Convert to CKPT", default=False + convert_to_ckpt_input = gr.Checkbox( + label="Convert to CKPT", value=False ) b3 = gr.Button("Run")