mirror of https://github.com/bmaltais/kohya_ss
Relocate config file accordion
parent
9493d6eeb7
commit
97d3102312
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@ -42,6 +42,7 @@ The GUI allows you to set the training parameters and generate and run the requi
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- [SDXL training](#sdxl-training)
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- [Masked loss](#masked-loss)
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- [Change History](#change-history)
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- [2024/04/08 (v23.1.4)](#20240408-v2314)
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- [2024/04/08 (v23.1.3)](#20240408-v2313)
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- [2024/04/08 (v23.1.2)](#20240408-v2312)
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- [2024/04/07 (v23.1.1)](#20240407-v2311)
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@ -406,6 +407,10 @@ ControlNet dataset is used to specify the mask. The mask images should be the RG
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## Change History
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### 2024/04/08 (v23.1.4)
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- Relocate config accordion to the top of the GUI.
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### 2024/04/08 (v23.1.3)
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- Fix dataset preparation bug.
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@ -747,6 +747,10 @@ def dreambooth_tab(
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with gr.Tab("Training"), gr.Column(variant="compact"):
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gr.Markdown("Train a custom model using kohya dreambooth python code...")
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# Setup Configuration Files Gradio
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with gr.Accordion("Configuration", open=False):
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configuration = ConfigurationFile(headless=headless, config=config)
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with gr.Accordion("Accelerate launch", open=False), gr.Column():
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accelerate_launch = AccelerateLaunch(config=config)
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@ -793,10 +797,6 @@ def dreambooth_tab(
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)
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gradio_dataset_balancing_tab(headless=headless)
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# Setup Configuration Files Gradio
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with gr.Accordion("Configuration", open=False):
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configuration = ConfigurationFile(headless=headless, config=config)
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with gr.Column(), gr.Group():
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with gr.Row():
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button_run = gr.Button("Start training", variant="primary")
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@ -770,6 +770,10 @@ def finetune_tab(headless=False, config: dict = {}):
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with gr.Tab("Training"), gr.Column(variant="compact"):
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gr.Markdown("Train a custom model using kohya finetune python code...")
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# Setup Configuration Files Gradio
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with gr.Accordion("Configuration", open=False):
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configuration = ConfigurationFile(headless=headless, config=config)
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with gr.Accordion("Accelerate launch", open=False), gr.Column():
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accelerate_launch = AccelerateLaunch(config=config)
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@ -893,10 +897,6 @@ def finetune_tab(headless=False, config: dict = {}):
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label="Weighted captions", value=False
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)
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# Setup Configuration Files Gradio
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with gr.Accordion("Configuration", open=False):
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configuration = ConfigurationFile(headless=headless, config=config)
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with gr.Column(), gr.Group():
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with gr.Row():
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button_run = gr.Button("Start training", variant="primary")
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@ -1100,6 +1100,10 @@ def lora_tab(
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"Train a custom model using kohya train network LoRA python code..."
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)
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# Setup Configuration Files Gradio
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with gr.Accordion("Configuration", open=False):
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configuration = ConfigurationFile(headless=headless, config=config)
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with gr.Accordion("Accelerate launch", open=False), gr.Column():
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accelerate_launch = AccelerateLaunch(config=config)
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@ -1919,10 +1923,6 @@ def lora_tab(
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)
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gradio_dataset_balancing_tab(headless=headless)
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# Setup Configuration Files Gradio
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with gr.Accordion("Configuration", open=False):
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configuration = ConfigurationFile(headless=headless, config=config)
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with gr.Column(), gr.Group():
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with gr.Row():
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button_run = gr.Button("Start training", variant="primary")
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@ -723,6 +723,10 @@ def ti_tab(headless=False, default_output_dir=None, config: dict = {}):
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with gr.Tab("Training"), gr.Column(variant="compact"):
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gr.Markdown("Train a TI using kohya textual inversion python code...")
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# Setup Configuration Files Gradio
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with gr.Accordion("Configuration", open=False):
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configuration = ConfigurationFile(headless=headless)
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with gr.Accordion("Accelerate launch", open=False), gr.Column():
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accelerate_launch = AccelerateLaunch(config=config)
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