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| author | flamelaw <flamelaw.com3d2@gmail.com> | 2022-11-20 03:35:26 +0000 |
|---|---|---|
| committer | flamelaw <flamelaw.com3d2@gmail.com> | 2022-11-20 03:35:26 +0000 |
| commit | bd68e35de3b7cf7547ed97d8bdf60147402133cc (patch) | |
| tree | 248d3810f1f06530f19c9db7e8b0b6d2e22f7225 /modules/ui.py | |
| parent | 47a44c7e421b98ca07e92dbf88769b04c9e28f86 (diff) | |
| download | stable-diffusion-webui-gfx803-bd68e35de3b7cf7547ed97d8bdf60147402133cc.tar.gz stable-diffusion-webui-gfx803-bd68e35de3b7cf7547ed97d8bdf60147402133cc.tar.bz2 stable-diffusion-webui-gfx803-bd68e35de3b7cf7547ed97d8bdf60147402133cc.zip | |
Gradient accumulation, autocast fix, new latent sampling method, etc
Diffstat (limited to 'modules/ui.py')
| -rw-r--r-- | modules/ui.py | 16 |
1 files changed, 15 insertions, 1 deletions
diff --git a/modules/ui.py b/modules/ui.py index a5953fce..9d2a1cbf 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1262,7 +1262,7 @@ def create_ui(wrap_gradio_gpu_call): with gr.Column():
with gr.Row():
interrupt_preprocessing = gr.Button("Interrupt")
- run_preprocess = gr.Button(value="Preprocess", variant='primary')
+ run_preprocess = gr.Button(value="Preprocess", variant='primary')
process_split.change(
fn=lambda show: gr_show(show),
@@ -1289,6 +1289,7 @@ def create_ui(wrap_gradio_gpu_call): 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)
+ gradient_step = gr.Number(label='Gradient accumulation steps', 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")
template_file = gr.Textbox(label='Prompt template file', value=os.path.join(script_path, "textual_inversion_templates", "style_filewords.txt"))
@@ -1299,6 +1300,11 @@ def create_ui(wrap_gradio_gpu_call): 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)
preview_from_txt2img = gr.Checkbox(label='Read parameters (prompt, etc...) from txt2img tab when making previews', value=False)
+ with gr.Row():
+ shuffle_tags = gr.Checkbox(label="Shuffle tags by ',' when creating prompts.", value=False)
+ tag_drop_out = gr.Slider(minimum=0, maximum=1, step=0.1, label="Drop out tags when creating prompts.", value=0)
+ with gr.Row():
+ latent_sampling_method = gr.Radio(label='Choose latent sampling method', value="once", choices=['once', 'deterministic', 'random'])
with gr.Row():
interrupt_training = gr.Button(value="Interrupt")
@@ -1387,11 +1393,15 @@ def create_ui(wrap_gradio_gpu_call): train_embedding_name,
embedding_learn_rate,
batch_size,
+ gradient_step,
dataset_directory,
log_directory,
training_width,
training_height,
steps,
+ shuffle_tags,
+ tag_drop_out,
+ latent_sampling_method,
create_image_every,
save_embedding_every,
template_file,
@@ -1412,11 +1422,15 @@ def create_ui(wrap_gradio_gpu_call): train_hypernetwork_name,
hypernetwork_learn_rate,
batch_size,
+ gradient_step,
dataset_directory,
log_directory,
training_width,
training_height,
steps,
+ shuffle_tags,
+ tag_drop_out,
+ latent_sampling_method,
create_image_every,
save_embedding_every,
template_file,
|