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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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Merge remote-tracking branch 'flamelaw/master'
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@@ -1240,7 +1240,7 @@ def create_ui(wrap_gradio_gpu_call):
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with gr.Column():
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with gr.Row():
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interrupt_preprocessing = gr.Button("Interrupt")
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run_preprocess = gr.Button(value="Preprocess", variant='primary')
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run_preprocess = gr.Button(value="Preprocess", variant='primary')
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process_split.change(
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fn=lambda show: gr_show(show),
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@@ -1267,6 +1267,7 @@ def create_ui(wrap_gradio_gpu_call):
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hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001")
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batch_size = gr.Number(label='Batch size', value=1, precision=0)
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gradient_step = gr.Number(label='Gradient accumulation steps', value=1, precision=0)
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dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")
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log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")
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template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
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@@ -1277,6 +1278,11 @@ def create_ui(wrap_gradio_gpu_call):
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save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
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save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
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preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)
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with gr.Row():
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shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False)
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tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0)
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with gr.Row():
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latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'])
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with gr.Row():
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interrupt_training = gr.Button(value="Interrupt")
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@@ -1365,11 +1371,15 @@ def create_ui(wrap_gradio_gpu_call):
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train_embedding_name,
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embedding_learn_rate,
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batch_size,
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gradient_step,
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dataset_directory,
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log_directory,
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training_width,
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training_height,
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steps,
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shuffle_tags,
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tag_drop_out,
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latent_sampling_method,
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create_image_every,
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save_embedding_every,
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template_file,
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@@ -1390,11 +1400,15 @@ def create_ui(wrap_gradio_gpu_call):
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train_hypernetwork_name,
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hypernetwork_learn_rate,
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batch_size,
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gradient_step,
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dataset_directory,
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log_directory,
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training_width,
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training_height,
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steps,
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shuffle_tags,
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tag_drop_out,
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latent_sampling_method,
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create_image_every,
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save_embedding_every,
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template_file,
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