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Merge branch 'learning_rate-scheduling' into learnschedule

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AUTOMATIC1111
2022-10-11 21:50:19 +03:00
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parent 2536ecbb17 d7474a5185
commit 419e539fe3
33 changed files with 1955 additions and 271 deletions
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112
modules/ui.py
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@@ -39,6 +39,7 @@ import modules.generation_parameters_copypaste
from modules import prompt_parser
from modules.images import save_image
import modules.textual_inversion.ui
import modules.hypernetworks.ui
# this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
mimetypes.init()
@@ -50,6 +51,11 @@ if not cmd_opts.share and not cmd_opts.listen:
gradio.utils.version_check = lambda: None
gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
if cmd_opts.ngrok != None:
import modules.ngrok as ngrok
print('ngrok authtoken detected, trying to connect...')
ngrok.connect(cmd_opts.ngrok, cmd_opts.port if cmd_opts.port != None else 7860)
def gr_show(visible=True):
return {"visible": visible, "__type__": "update"}
@@ -311,7 +317,7 @@ def interrogate(image):
def interrogate_deepbooru(image):
prompt = get_deepbooru_tags(image)
prompt = get_deepbooru_tags(image, opts.interrogate_deepbooru_score_threshold)
return gr_show(True) if prompt is None else prompt
@@ -428,7 +434,10 @@ def create_toprow(is_img2img):
with gr.Row():
with gr.Column(scale=8):
negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
with gr.Row():
negative_prompt = gr.Textbox(label="Negative prompt", elem_id="negative_prompt", show_label=False, placeholder="Negative prompt", lines=2)
with gr.Column(scale=1, elem_id="roll_col"):
sh = gr.Button(elem_id="sh", visible=True)
with gr.Column(scale=1, elem_id="style_neg_col"):
prompt_style2 = gr.Dropdown(label="Style 2", elem_id=f"{id_part}_style2_index", choices=[k for k, v in shared.prompt_styles.styles.items()], value=next(iter(shared.prompt_styles.styles.keys())), visible=len(shared.prompt_styles.styles) > 1)
@@ -524,7 +533,7 @@ def create_ui(wrap_gradio_gpu_call):
denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7)
with gr.Row():
batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
@@ -549,15 +558,15 @@ def create_ui(wrap_gradio_gpu_call):
button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
open_txt2img_folder = gr.Button(folder_symbol, elem_id=button_id)
with gr.Row():
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
with gr.Row():
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
with gr.Row():
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
with gr.Row():
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
@@ -710,7 +719,7 @@ def create_ui(wrap_gradio_gpu_call):
tiling = gr.Checkbox(label='Tiling', value=False)
with gr.Row():
batch_count = gr.Slider(minimum=1, maximum=cmd_opts.max_batch_count, step=1, label='Batch count', value=1)
batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1)
batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1)
with gr.Group():
@@ -737,15 +746,15 @@ def create_ui(wrap_gradio_gpu_call):
button_id = "hidden_element" if shared.cmd_opts.hide_ui_dir_config else 'open_folder'
open_img2img_folder = gr.Button(folder_symbol, elem_id=button_id)
with gr.Row():
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
with gr.Row():
do_make_zip = gr.Checkbox(label="Make Zip when Save?", value=False)
with gr.Row():
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
with gr.Row():
download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False)
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
with gr.Group():
html_info = gr.HTML()
generation_info = gr.Textbox(visible=False)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
@@ -961,7 +970,7 @@ def create_ui(wrap_gradio_gpu_call):
extras_send_to_inpaint.click(
fn=lambda x: image_from_url_text(x),
_js="extract_image_from_gallery_img2img",
_js="extract_image_from_gallery_inpaint",
inputs=[result_images],
outputs=[init_img_with_mask],
)
@@ -1022,7 +1031,20 @@ def create_ui(wrap_gradio_gpu_call):
gr.HTML(value="")
with gr.Column():
create_embedding = gr.Button(value="Create", variant='primary')
create_embedding = gr.Button(value="Create embedding", variant='primary')
with gr.Group():
gr.HTML(value="<p style='margin-bottom: 0.7em'>Create a new hypernetwork</p>")
new_hypernetwork_name = gr.Textbox(label="Name")
new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])
with gr.Row():
with gr.Column(scale=3):
gr.HTML(value="")
with gr.Column():
create_hypernetwork = gr.Button(value="Create hypernetwork", variant='primary')
with gr.Group():
gr.HTML(value="<p style='margin-bottom: 0.7em'>Preprocess images</p>")
@@ -1047,6 +1069,7 @@ def create_ui(wrap_gradio_gpu_call):
with gr.Group():
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>")
train_embedding_name = gr.Dropdown(label='Embedding', choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys()))
train_hypernetwork_name = gr.Dropdown(label='Hypernetwork', choices=[x for x in shared.hypernetworks.keys()])
learn_rate = gr.Textbox(label='Learning rate', placeholder="Learning rate", value = "5.0e-03")
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")
@@ -1057,15 +1080,12 @@ def create_ui(wrap_gradio_gpu_call):
num_repeats = gr.Number(label='Number of repeats for a single input image per epoch', value=100, precision=0)
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)
preview_image_prompt = gr.Textbox(label='Preview prompt', value="")
with gr.Row():
with gr.Column(scale=2):
gr.HTML(value="")
with gr.Column():
with gr.Row():
interrupt_training = gr.Button(value="Interrupt")
train_embedding = gr.Button(value="Train", variant='primary')
interrupt_training = gr.Button(value="Interrupt")
train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary')
train_embedding = gr.Button(value="Train Embedding", variant='primary')
with gr.Column():
progressbar = gr.HTML(elem_id="ti_progressbar")
@@ -1091,6 +1111,19 @@ def create_ui(wrap_gradio_gpu_call):
]
)
create_hypernetwork.click(
fn=modules.hypernetworks.ui.create_hypernetwork,
inputs=[
new_hypernetwork_name,
new_hypernetwork_sizes,
],
outputs=[
train_hypernetwork_name,
ti_output,
ti_outcome,
]
)
run_preprocess.click(
fn=wrap_gradio_gpu_call(modules.textual_inversion.ui.preprocess, extra_outputs=[gr.update()]),
_js="start_training_textual_inversion",
@@ -1124,6 +1157,27 @@ def create_ui(wrap_gradio_gpu_call):
create_image_every,
save_embedding_every,
template_file,
preview_image_prompt,
],
outputs=[
ti_output,
ti_outcome,
]
)
train_hypernetwork.click(
fn=wrap_gradio_gpu_call(modules.hypernetworks.ui.train_hypernetwork, extra_outputs=[gr.update()]),
_js="start_training_textual_inversion",
inputs=[
train_hypernetwork_name,
learn_rate,
dataset_directory,
log_directory,
steps,
create_image_every,
save_embedding_every,
template_file,
preview_image_prompt,
],
outputs=[
ti_output,
@@ -1137,6 +1191,7 @@ def create_ui(wrap_gradio_gpu_call):
outputs=[],
)
def create_setting_component(key):
def fun():
return opts.data[key] if key in opts.data else opts.data_labels[key].default
@@ -1290,6 +1345,7 @@ Requested path was: {f}
shared.state.interrupt()
settings_interface.gradio_ref.do_restart = True
restart_gradio.click(
fn=request_restart,
inputs=[],
@@ -1331,7 +1387,7 @@ Requested path was: {f}
with gr.Tabs() as tabs:
for interface, label, ifid in interfaces:
with gr.TabItem(label, id=ifid):
with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid):
interface.render()
if os.path.exists(os.path.join(script_path, "notification.mp3")):