@ -92,7 +92,7 @@ def generate_proxy(
unload_tts ( )
raise e
return (
outputs [ 0 ] ,
gr . update ( value = sample , visible = sample is not None ) ,
@ -131,7 +131,7 @@ def history_view_results( voice ):
metadata , _ = read_generate_settings ( f " { outdir } / { file } " , read_latents = False )
if metadata is None :
continue
values = [ ]
for k in HISTORY_HEADERS :
v = file
@ -185,7 +185,7 @@ def read_generate_settings_proxy(file, saveAs='.temp'):
os . makedirs ( outdir , exist_ok = True )
with open ( f ' { outdir } /cond_latents.pth ' , ' wb ' ) as f :
f . write ( latents )
latents = f ' { outdir } /cond_latents.pth '
return (
@ -229,7 +229,7 @@ def prepare_all_datasets( language, validation_text_length, validation_audio_len
print ( " Processing: " , voice )
message = slice_dataset ( voice , trim_silence = trim_silence , start_offset = slice_start_offset , end_offset = slice_end_offset , results = None , progress = progress )
messages . append ( message )
for voice in voices :
print ( " Processing: " , voice )
message = prepare_dataset ( voice , use_segments = slice_audio , text_length = validation_text_length , audio_length = validation_audio_length , progress = progress )
@ -239,7 +239,7 @@ def prepare_all_datasets( language, validation_text_length, validation_audio_len
def prepare_dataset_proxy ( voice , language , validation_text_length , validation_audio_length , skip_existings , slice_audio , trim_silence , slice_start_offset , slice_end_offset , progress = gr . Progress ( track_tqdm = True ) ) :
messages = [ ]
message = transcribe_dataset ( voice = voice , language = language , skip_existings = skip_existings , progress = progress )
messages . append ( message )
@ -355,7 +355,7 @@ def setup_gradio():
voice_list_with_defaults = get_voice_list ( append_defaults = True )
voice_list = get_voice_list ( )
result_voices = get_voice_list ( args . results_folder )
valle_models = get_valle_models ( )
autoregressive_models = get_autoregressive_models ( )
@ -371,7 +371,9 @@ def setup_gradio():
arg = GENERATE_SETTINGS_ARGS [ i ]
GENERATE_SETTINGS [ arg ] = None
with gr . Blocks ( ) as ui :
with gr . Blocks ( theme = " freddyaboulton/dracula_revamped " , css = " footer { display: none!important} " , title = " Voice Clonning WebUI " ) as ui :
gr . Markdown ( " ## 🤗🎙️ Voice clonning " )
gr . Markdown ( " Ai Voice clonning <a href= ' https://git.ecker.tech/terminator/ai-voice-cloning-terminator ' >based on Tortoise</a> " )
with gr . Tab ( " Generate " ) :
with gr . Row ( ) :
with gr . Column ( ) :
@ -402,7 +404,7 @@ def setup_gradio():
outputs = GENERATE_SETTINGS [ " mic_audio " ] ,
)
with gr . Column ( ) :
preset = None
preset = None
GENERATE_SETTINGS [ " candidates " ] = gr . Slider ( value = 1 , minimum = 1 , maximum = 6 , step = 1 , label = " Candidates " , visible = args . tts_backend == " tortoise " )
GENERATE_SETTINGS [ " seed " ] = gr . Number ( value = 0 , precision = 0 , label = " Seed " , visible = args . tts_backend == " tortoise " )
@ -412,7 +414,7 @@ def setup_gradio():
GENERATE_SETTINGS [ " diffusion_iterations " ] = gr . Slider ( value = 30 , minimum = 0 , maximum = 512 , step = 1 , label = " Iterations " , visible = args . tts_backend == " tortoise " )
GENERATE_SETTINGS [ " temperature " ] = gr . Slider ( value = 0.95 if args . tts_backend == " vall-e " else 0.2 , minimum = 0 , maximum = 1 , step = 0.05 , label = " Temperature " )
show_experimental_settings = gr . Checkbox ( label = " Show Experimental Settings " , visible = args . tts_backend == " tortoise " )
reset_generate_settings_button = gr . Button ( value = " Reset to Default " )
with gr . Column ( visible = False ) as col :
@ -514,7 +516,7 @@ def setup_gradio():
transcribe_button = gr . Button ( value = " Transcribe and Process " )
transcribe_all_button = gr . Button ( value = " Transcribe All " )
diarize_button = gr . Button ( value = " Diarize " , visible = False )
with gr . Row ( ) :
slice_dataset_button = gr . Button ( value = " (Re)Slice Audio " )
prepare_dataset_button = gr . Button ( value = " (Re)Create Dataset " )
@ -534,7 +536,7 @@ def setup_gradio():
TRAINING_SETTINGS [ " learning_rate " ] = gr . Slider ( label = " Learning Rate " , value = 1e-5 , minimum = 0 , maximum = 1e-4 , step = 1e-6 )
TRAINING_SETTINGS [ " mel_lr_weight " ] = gr . Slider ( label = " Mel LR Ratio " , value = 1.00 , minimum = 0 , maximum = 1 )
TRAINING_SETTINGS [ " text_lr_weight " ] = gr . Slider ( label = " Text LR Ratio " , value = 0.01 , minimum = 0 , maximum = 1 )
with gr . Row ( visible = args . tts_backend == " tortoise " ) :
lr_schemes = list ( LEARNING_RATE_SCHEMES . keys ( ) )
TRAINING_SETTINGS [ " learning_rate_scheme " ] = gr . Radio ( lr_schemes , label = " Learning Rate Scheme " , value = lr_schemes [ 0 ] , type = " value " )
@ -567,7 +569,7 @@ def setup_gradio():
TRAINING_SETTINGS [ " source_model " ] = gr . Dropdown ( choices = autoregressive_models , label = " Source Model " , type = " value " , value = autoregressive_models [ 0 ] , visible = args . tts_backend == " tortoise " )
TRAINING_SETTINGS [ " resume_state " ] = gr . Textbox ( label = " Resume State Path " , placeholder = " ./training/$ {voice} /finetune/training_state/$ {last_state} .state " , visible = args . tts_backend == " tortoise " )
TRAINING_SETTINGS [ " voice " ] = gr . Dropdown ( choices = dataset_list , label = " Dataset " , type = " value " , value = dataset_list [ 0 ] if len ( dataset_list ) else " " )
with gr . Row ( ) :
@ -585,9 +587,9 @@ def setup_gradio():
refresh_configs = gr . Button ( value = " Refresh Configurations " )
training_output = gr . TextArea ( label = " Console Output " , interactive = False , max_lines = 8 )
verbose_training = gr . Checkbox ( label = " Verbose Console Output " , value = True )
keep_x_past_checkpoints = gr . Slider ( label = " Keep X Previous States " , minimum = 0 , maximum = 8 , value = 0 , step = 1 )
with gr . Row ( ) :
training_graph_x_min = gr . Number ( label = " X Min " , precision = 0 , value = 0 )
training_graph_x_max = gr . Number ( label = " X Max " , precision = 0 , value = 0 )
@ -598,8 +600,8 @@ def setup_gradio():
start_training_button = gr . Button ( value = " Train " )
stop_training_button = gr . Button ( value = " Stop " )
reconnect_training_button = gr . Button ( value = " Reconnect " )
with gr . Column ( ) :
training_loss_graph = gr . LinePlot ( label = " Training Metrics " ,
x = " it " , # x="epoch",
@ -658,7 +660,7 @@ def setup_gradio():
EXEC_SETTINGS [ ' results_folder ' ] = gr . Textbox ( label = " Results Folder " , value = args . results_folder )
# EXEC_SETTINGS['tts_backend'] = gr.Dropdown(TTSES, label="TTS Backend", value=args.tts_backend if args.tts_backend else TTSES[0])
if args . tts_backend == " vall-e " :
with gr . Column ( ) :
EXEC_SETTINGS [ ' valle_model ' ] = gr . Dropdown ( choices = valle_models , label = " VALL-E Model Config " , value = args . valle_model if args . valle_model else valle_models [ 0 ] )
@ -668,7 +670,7 @@ def setup_gradio():
EXEC_SETTINGS [ ' diffusion_model ' ] = gr . Dropdown ( choices = diffusion_models , label = " Diffusion Model " , value = args . diffusion_model if args . diffusion_model else diffusion_models [ 0 ] )
EXEC_SETTINGS [ ' vocoder_model ' ] = gr . Dropdown ( VOCODERS , label = " Vocoder " , value = args . vocoder_model if args . vocoder_model else VOCODERS [ - 1 ] )
EXEC_SETTINGS [ ' tokenizer_json ' ] = gr . Dropdown ( tokenizer_jsons , label = " Tokenizer JSON Path " , value = args . tokenizer_json if args . tokenizer_json else tokenizer_jsons [ 0 ] )
EXEC_SETTINGS [ ' training_default_halfp ' ] = TRAINING_SETTINGS [ ' half_p ' ]
EXEC_SETTINGS [ ' training_default_bnb ' ] = TRAINING_SETTINGS [ ' bitsandbytes ' ]
@ -718,7 +720,7 @@ def setup_gradio():
exec_inputs = list ( EXEC_SETTINGS . values ( ) )
for k in EXEC_SETTINGS :
EXEC_SETTINGS [ k ] . change ( fn = update_args_proxy , inputs = exec_inputs )
EXEC_SETTINGS [ ' autoregressive_model ' ] . change (
fn = update_autoregressive_model ,
inputs = EXEC_SETTINGS [ ' autoregressive_model ' ] ,
@ -790,7 +792,7 @@ def setup_gradio():
] ,
outputs = GENERATE_SETTINGS [ ' voice ' ] ,
)
GENERATE_SETTINGS [ ' emotion ' ] . change (
fn = lambda value : gr . update ( visible = value == " Custom " ) ,
inputs = GENERATE_SETTINGS [ ' emotion ' ] ,
@ -944,7 +946,7 @@ def setup_gradio():
] ,
outputs = prepare_dataset_output
)
training_refresh_dataset . click (
lambda : gr . update ( choices = get_dataset_list ( ) ) ,
inputs = None ,
@ -966,7 +968,7 @@ def setup_gradio():
if os . path . isfile ( ' ./config/generate.json ' ) :
ui . load ( import_generate_settings_proxy , inputs = None , outputs = generate_settings )
if args . check_for_updates :
ui . load ( check_for_updates )
Terminator
mrq