cleaning the ui

modules/tabs/server.py

@@ -16,19 +16,19 @@
 
 
 def server_options_ui(show_out_dir=True):
- with gr.Row().style(equal_height=False):
+ with gr.Row():
  with gr.Row():
  host = gr.Textbox(value="127.0.0.1", label="host")
  port = gr.Textbox(value="5001", label="port")
- with gr.Row().style(equal_height=False):
+ with gr.Row():
  with gr.Row():
  rvc_model_file = gr.Textbox(
  label="RVC model file path",
  value=os.path.join(
  MODELS_DIR, "pretrained", "beta", "voras_sample_japanese.pth"
  ),
  )
- with gr.Row().style(equal_height=False):
+ with gr.Row():
  with gr.Row():
  input_voice_file = gr.Textbox(value="", label="input voice file path")
  speaker_id = gr.Number(
@@ -79,25 +79,24 @@ def convert(host, port, input_voice_file, speaker_id):
  yield "convert succeed", (sr, audio)
 
  with gr.Group():
- with gr.Box():
- with gr.Column():
- (
- host,
- port,
- rvc_model_file,
- input_voice_file,
- speaker_id,
- ) = server_options_ui()
-
- with gr.Row().style(equal_height=False):
- with gr.Column():
- status = gr.Textbox(value="", label="Status")
- output = gr.Audio(label="Output", interactive=False)
-
- with gr.Row():
- start_button = gr.Button("Start server", variant="primary")
- upload_button = gr.Button("Upload Model")
- convert_button = gr.Button("Convert Voice")
+ with gr.Column():
+ (
+ host,
+ port,
+ rvc_model_file,
+ input_voice_file,
+ speaker_id,
+ ) = server_options_ui()
+
+ with gr.Row():
+ with gr.Column():
+ status = gr.Textbox(value="", label="Status")
+ output = gr.Audio(label="Output", interactive=False)
+
+ with gr.Row():
+ start_button = gr.Button("Start server", variant="primary")
+ upload_button = gr.Button("Upload Model")
+ convert_button = gr.Button("Convert Voice")
 
  start_button.click(
  start,

modules/tabs/training.py

@@ -113,9 +113,9 @@ def train_all(
  yield "Training index..."
 
  with gr.Group():
- with gr.Box():
+ with gr.Accordion("Model Information"):
  with gr.Column():
- with gr.Row().style():
+ with gr.Row():
  with gr.Column():
  model_name = gr.Textbox(label="Model Name")
  ignore_cache = gr.Checkbox(label="Ignore cache")
@@ -127,98 +127,102 @@ def train_all(
  multiple_speakers = gr.Checkbox(
  label="Multiple speakers", value=False
  )
- with gr.Row().style(equal_height=False):
- version = gr.Radio(
- choices=["voras"],
- value="voras",
- label="Model version",
- )
- target_sr = gr.Radio(
- choices=["24k"],
- value="24k",
- label="Target sampling rate",
- )
- f0 = gr.Radio(
- choices=["No"],
- value="No",
- label="f0 Model",
- )
- with gr.Row().style(equal_height=False):
- embedding_name = gr.Radio(
- choices=list(models.EMBEDDINGS_LIST.keys()),
- value="hubert-base-japanese",
- label="Using phone embedder",
- )
- embedding_channels = gr.Radio(
- choices=["768"],
- value="768",
- label="Embedding channels",
- )
- embedding_output_layer = gr.Radio(
- choices=["12"],
- value="12",
- label="Embedding output layer",
- )
- with gr.Row().style(equal_height=False):
- gpu_id = gr.Textbox(
- label="GPU ID",
- value=", ".join([f"{x.index}" for x in utils.get_gpus()]),
- )
- num_cpu_process = gr.Slider(
- minimum=0,
- maximum=cpu_count(),
- step=1,
- value=math.ceil(cpu_count() / 2),
- label="Number of CPU processes",
- )
- with gr.Row().style(equal_height=False):
- batch_size = gr.Number(value=4, label="Batch size")
- num_epochs = gr.Number(
- value=30,
- label="Number of epochs",
- )
- save_every_epoch = gr.Slider(
- minimum=0,
- maximum=100,
- value=10,
- step=1,
- label="Save every epoch",
- )
- fp16 = gr.Checkbox(
- label="BFP16", value=half_support, disabled=not half_support
- )
- with gr.Row().style(equal_height=False):
- augment = gr.Checkbox(label="Augment", value=True)
- augment_from_pretrain = gr.Checkbox(
- label="Augment From Pretrain", value=True
- )
- augment_path = gr.Textbox(
- label="Pre trained checkpoint path (pth)",
- value=os.path.join(
- MODELS_DIR,
- "pretrained",
- "beta",
- "voras_pretrain_libritts_r.pth",
- ),
- )
- with gr.Row().style(equal_height=False):
- finetuning = gr.Checkbox(label="finetuning", value=True)
- pre_trained_generator = gr.Textbox(
- label="Pre trained generator path",
- value=os.path.join(
- MODELS_DIR, "pretrained", "beta", "G24k.pth"
- ),
- )
- pre_trained_discriminator = gr.Textbox(
- label="Pre trained discriminator path",
- value=os.path.join(
- MODELS_DIR, "pretrained", "beta", "D24k.pth"
- ),
- )
- with gr.Row().style(equal_height=False):
- status = gr.Textbox(value="", label="Status")
- with gr.Row().style(equal_height=False):
- train_all_button = gr.Button("Train", variant="primary")
+ with gr.Group():
+ with gr.Accordion("VoRAS Settings"):
+ with gr.Row():
+ version = gr.Radio(
+ choices=["voras"],
+ value="voras",
+ label="Model version",
+ )
+ target_sr = gr.Radio(
+ choices=["24k"],
+ value="24k",
+ label="Target sampling rate",
+ )
+ f0 = gr.Radio(
+ choices=["No"],
+ value="No",
+ label="f0 Model",
+ )
+ with gr.Row():
+ embedding_name = gr.Radio(
+ choices=list(models.EMBEDDINGS_LIST.keys()),
+ value="hubert-base-japanese",
+ label="Using phone embedder",
+ )
+ embedding_channels = gr.Radio(
+ choices=["768"],
+ value="768",
+ label="Embedding channels",
+ )
+ embedding_output_layer = gr.Radio(
+ choices=["12"],
+ value="12",
+ label="Embedding output layer",
+ )
+ with gr.Group():
+ with gr.Accordion("Training Configuration"):
+ with gr.Row():
+ gpu_id = gr.Textbox(
+ label="GPU ID",
+ value=", ".join([f"{x.index}" for x in utils.get_gpus()]),
+ )
+ num_cpu_process = gr.Slider(
+ minimum=0,
+ maximum=cpu_count(),
+ step=1,
+ value=math.ceil(cpu_count() / 2),
+ label="Number of CPU processes",
+ )
+ batch_size = gr.Slider(
+ value=4, minimum=1, maximum=100, step=1, label="Batch size"
+ )
+ num_epochs = gr.Slider(
+ value=100,
+ minimum=1,
+ step=1,
+ maximum=1000,
+ label="Epochs",
+ )
+ save_every_epoch = gr.Slider(
+ minimum=1,
+ maximum=100,
+ value=10,
+ step=1,
+ label="Save every epoch",
+ )
+
+ with gr.Row():
+ augment = gr.Checkbox(label="Augment", value=True)
+ augment_from_pretrain = gr.Checkbox(
+ label="Augment From Pretrain", value=True
+ )
+ finetuning = gr.Checkbox(label="finetuning", value=True)
+ fp16 = gr.Checkbox(label="BFP16", value=half_support)
+ with gr.Row():
+ pre_trained_generator = gr.Textbox(
+ label="Pre trained generator path",
+ value=os.path.join(MODELS_DIR, "pretrained", "beta", "G24k.pth"),
+ )
+ pre_trained_discriminator = gr.Textbox(
+ label="Pre trained discriminator path",
+ value=os.path.join(MODELS_DIR, "pretrained", "beta", "D24k.pth"),
+ )
+ augment_path = gr.Textbox(
+ label="Pre trained checkpoint path (pth)",
+ value=os.path.join(
+ MODELS_DIR,
+ "pretrained",
+ "beta",
+ "voras_pretrain_libritts_r.pth",
+ ),
+ )
+
+ with gr.Group():
+ with gr.Column():
+ train_all_button = gr.Button("Train", variant="primary")
+ status = gr.Textbox(value="", label="Status")
 
  train_all_button.click(
  train_all,

modules/ui.py

@@ -10,6 +10,8 @@
 from .core import preload
 from .shared import ROOT_DIR
 
+import logging
+logging.getLogger("httpx").setLevel(logging.CRITICAL)
 
 class Tab:
  TABS_DIR = os.path.join(ROOT_DIR, "modules", "tabs")
@@ -96,34 +98,9 @@ def webpath(fn):
  return f"file={web_path}?{os.path.getmtime(fn)}"
 
 
-def javascript_html():
- script_js = os.path.join(ROOT_DIR, "script.js")
- head = f'<script type="text/javascript" src="{webpath(script_js)}"></script>\n'
-
- return head
-
-
-def css_html():
- return f'<link rel="stylesheet" property="stylesheet" href="{webpath(os.path.join(ROOT_DIR, "styles.css"))}">'
-
-
-def create_head():
- head = ""
- head += css_html()
- head += javascript_html()
-
- def template_response(*args, **kwargs):
- res = shared.gradio_template_response_original(*args, **kwargs)
- res.body = res.body.replace(b"</head>", f"{head}</head>".encode("utf8"))
- res.init_headers()
- return res
-
- gradio.routes.templates.TemplateResponse = template_response
-
-
 def create_ui():
  preload()
- block = gr.Blocks()
+ block = gr.Blocks(theme="remilia/Ghostly")
 
  with block:
  with gr.Tabs():
@@ -132,8 +109,6 @@ def create_ui():
  with gr.Tab(tab.title()):
  tab()
 
- create_head()
-
  return block
 
 

requirements.txt

@@ -1,4 +1,4 @@
-gradio==3.28.3
+gradio
 tqdm==4.65.0
 numpy==1.23.5
 faiss-cpu==1.7.3

webui.py

@@ -2,25 +2,26 @@
 
 from modules import cmd_opts, ui
 
-# なんか知らんが湧いて出てくる ".DS_Store"　を無視する。
-# ここにこんなコードを置くべきかはわからないけど…
 _list_dir = os.listdir
 
+
 def listdir4mac(path):
  return [file for file in _list_dir(path) if not file.startswith(".")]
 
+
 os.listdir = listdir4mac
 
 
 def webui():
  app = ui.create_ui()
  app.queue(64)
- app, local_url, share_url = app.launch(
+ app = app.launch(
  server_name=cmd_opts.opts.host,
  server_port=cmd_opts.opts.port,
  share=cmd_opts.opts.share,
+ inbrowser=True,
  )
 
 
 if __name__ == "__main__":
- webui()
+ webui()