change textual inversion tab to train
remake train interface to use tabs
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2fffd4bddc
commit
ee015a1af6
2 changed files with 10 additions and 14 deletions
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@ -175,7 +175,7 @@ def attention_CrossAttention_forward(self, x, context=None, mask=None):
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def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory, steps, create_image_every, save_hypernetwork_every, template_file, preview_image_prompt):
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assert hypernetwork_name, 'embedding not selected'
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assert hypernetwork_name, 'hypernetwork not selected'
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path = shared.hypernetworks.get(hypernetwork_name, None)
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shared.loaded_hypernetwork = Hypernetwork()
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@ -1035,14 +1035,14 @@ def create_ui(wrap_gradio_gpu_call):
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sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
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with gr.Blocks() as textual_inversion_interface:
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with gr.Blocks() as train_interface:
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with gr.Row().style(equal_height=False):
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with gr.Column():
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with gr.Group():
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gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")
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gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new embedding</p>")
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with gr.Row().style(equal_height=False):
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with gr.Tabs(elem_id="train_tabs"):
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with gr.Tab(label="Create embedding"):
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new_embedding_name = gr.Textbox(label="Name")
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initialization_text = gr.Textbox(label="Initialization text", value="*")
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nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)
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@ -1054,9 +1054,7 @@ def create_ui(wrap_gradio_gpu_call):
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with gr.Column():
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create_embedding = gr.Button(value="Create embedding", variant='primary')
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with gr.Group():
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gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
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with gr.Tab(label="Create hypernetwork"):
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new_hypernetwork_name = gr.Textbox(label="Name")
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new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])
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@ -1067,9 +1065,7 @@ def create_ui(wrap_gradio_gpu_call):
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with gr.Column():
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create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary')
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with gr.Group():
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gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
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with gr.Tab(label="Preprocess images"):
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process_src = gr.Textbox(label='Source directory')
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process_dst = gr.Textbox(label='Destination directory')
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process_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
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@ -1091,7 +1087,7 @@ def create_ui(wrap_gradio_gpu_call):
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with gr.Column():
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run_preprocess = gr.Button(value="Preprocess", variant='primary')
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with gr.Group():
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with gr.Tab(label="Train"):
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gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding; must specify a directory with a set of 1:1 ratio images</p>")
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train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
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train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
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@ -1388,7 +1384,7 @@ Requested path was: {f}
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(extras_interface, "Extras", "extras"),
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(pnginfo_interface, "PNG Info", "pnginfo"),
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(modelmerger_interface, "Checkpoint Merger", "modelmerger"),
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(textual_inversion_interface, "Textual inversion", "ti"),
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(train_interface, "Train", "ti"),
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(settings_interface, "Settings", "settings"),
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]
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