update ui with extra training options

1 files changed, 9 insertions, 2 deletions

diff --git a/modules/ui.py b/modules/ui.py
index 93c0767c..cdb9d335 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1206,6 +1206,7 @@ def create_ui(wrap_gradio_gpu_call):
                     new_embedding_name = gr.Textbox(label="Name")

                     initialization_text = gr.Textbox(label="Initialization text", value="*")

                     nvpt = gr.Slider(label="Number of vectors per token", minimum=1, maximum=75, step=1, value=1)

+                    overwrite_old_embedding = gr.Checkbox(value=False, label="Overwrite Old Embedding")

 

                     with gr.Row():

                         with gr.Column(scale=3):

@@ -1219,6 +1220,7 @@ def create_ui(wrap_gradio_gpu_call):
                     new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])

                     new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'")

                     new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization")

+                    overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork")

 

                     with gr.Row():

                         with gr.Column(scale=3):

@@ -1247,14 +1249,17 @@ def create_ui(wrap_gradio_gpu_call):
                             run_preprocess = gr.Button(value="Preprocess", variant='primary')

 

                 with gr.Tab(label="Train"):

-                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images<br/>Initial learning rates: 0.005 for an Embedding, 0.00001 for Hypernetwork <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")

+                    gr.HTML(value="<p style='margin-bottom: 0.7em'>Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images <a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\" style=\"font-weight:bold;\">[wiki]</a></p>")

                     with gr.Row():

                         train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))

                         create_refresh_button(train_embedding_name, sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings, lambda: {"choices": sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())}, "refresh_train_embedding_name")

                     with gr.Row():

                         train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', elem_id="train_hypernetwork", choices=[x for x in shared.hypernetworks.keys()])

                         create_refresh_button(train_hypernetwork_name, shared.reload_hypernetworks, lambda: {"choices": sorted([x for x in shared.hypernetworks.keys()])}, "refresh_train_hypernetwork_name")

-                    learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value="0.005")

+                    with gr.Row():

+                        embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005")

+                        hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001")

+                    

                     batch_size = gr.Number(label='Batch size', value=1, precision=0)

                     dataset_directory = gr.Textbox(label='Dataset directory', placeholder="Path to directory with input images")

                     log_directory = gr.Textbox(label='Log directory', placeholder="Path to directory where to write outputs", value="textual_inversion")

@@ -1288,6 +1293,7 @@ def create_ui(wrap_gradio_gpu_call):
                 new_embedding_name,

                 initialization_text,

                 nvpt,

+                overwrite_old_embedding,

             ],

             outputs=[

                 train_embedding_name,

@@ -1303,6 +1309,7 @@ def create_ui(wrap_gradio_gpu_call):
                 new_hypernetwork_sizes,

                 new_hypernetwork_layer_structure,

                 new_hypernetwork_add_layer_norm,

+                overwrite_old_hypernetwork,

             ],

             outputs=[

                 train_hypernetwork_name,