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| author | Muhammad Rizqi Nur <rizqinur2010@gmail.com> | 2022-10-28 10:16:23 +0000 |
|---|---|---|
| committer | Muhammad Rizqi Nur <rizqinur2010@gmail.com> | 2022-10-28 10:16:23 +0000 |
| commit | 16451ca573220e49f2eaaab97580b6b91287c8c4 (patch) | |
| tree | 5f80fa2082fbbc6469c5807020273af75b5f1a21 /modules/ui.py | |
| parent | 1618df41bad092e068c61bf510b1e20856821ad5 (diff) | |
| download | stable-diffusion-webui-gfx803-16451ca573220e49f2eaaab97580b6b91287c8c4.tar.gz stable-diffusion-webui-gfx803-16451ca573220e49f2eaaab97580b6b91287c8c4.tar.bz2 stable-diffusion-webui-gfx803-16451ca573220e49f2eaaab97580b6b91287c8c4.zip | |
Learning rate sched syntax support for grad clipping
Diffstat (limited to 'modules/ui.py')
| -rw-r--r-- | modules/ui.py | 7 |
1 files changed, 3 insertions, 4 deletions
diff --git a/modules/ui.py b/modules/ui.py index 97de7da2..47d16429 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1305,7 +1305,9 @@ def create_ui(wrap_gradio_gpu_call): 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")
-
+ with gr.Row():
+ clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
+ clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="1.0", show_label=False)
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")
@@ -1313,9 +1315,6 @@ def create_ui(wrap_gradio_gpu_call): training_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
training_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512)
steps = gr.Number(label='Max steps', value=100000, precision=0)
- with gr.Row():
- clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"])
- clip_grad_value = gr.Number(value=1.0, show_label=False)
create_image_every = gr.Number(label='Save an image to log directory every N steps, 0 to disable', value=500, precision=0)
save_embedding_every = gr.Number(label='Save a copy of embedding to log directory every N steps, 0 to disable', value=500, precision=0)
save_image_with_stored_embedding = gr.Checkbox(label='Save images with embedding in PNG chunks', value=True)
|