@ -135,6 +135,21 @@ def get_training_configs():
def update_training_configs ( ) :
return gr . update ( choices = get_training_configs ( ) )
history_headers = {
" Name " : " " ,
" Samples " : " num_autoregressive_samples " ,
" Iterations " : " diffusion_iterations " ,
" Temp. " : " temperature " ,
" Sampler " : " diffusion_sampler " ,
" CVVP " : " cvvp_weight " ,
" Top P " : " top_p " ,
" Diff. Temp. " : " diffusion_temperature " ,
" Len Pen " : " length_penalty " ,
" Rep Pen " : " repetition_penalty " ,
" Cond-Free K " : " cond_free_k " ,
" Time " : " time " ,
}
def history_view_results ( voice ) :
results = [ ]
files = [ ]
@ -148,7 +163,7 @@ def history_view_results( voice ):
continue
values = [ ]
for k in h eaders:
for k in h istory_h eaders:
v = file
if k != " Name " :
v = metadata [ headers [ k ] ]
@ -163,6 +178,10 @@ def history_view_results( voice ):
gr . Dropdown . update ( choices = sorted ( files ) )
)
def import_voices_proxy ( files , name , progress = gr . Progress ( track_tqdm = True ) ) :
import_voices ( files , name , progress )
return gr . update ( )
def read_generate_settings_proxy ( file , saveAs = ' .temp ' ) :
j , latents = read_generate_settings ( file )
@ -175,13 +194,14 @@ def read_generate_settings_proxy(file, saveAs='.temp'):
latents = f ' { outdir } /cond_latents.pth '
return (
j ,
gr . update ( value = j , visible = j is not None ) ,
gr . update ( visible = j is not None ) ,
gr . update ( value = latents , visible = latents is not None ) ,
None if j is None else j [ ' voice ' ]
)
def prepare_dataset_proxy ( voice , language ) :
return prepare_dataset ( get_voices ( load_latents = False ) [ voice ] , outdir = f " ./training/ { voice } / " , language = language )
def prepare_dataset_proxy ( voice , language , progress = gr . Progress ( track_tqdm = True ) ) :
return prepare_dataset ( get_voices ( load_latents = False ) [ voice ] , outdir = f " ./training/ { voice } / " , language = language , progress = progress )
def update_voices ( ) :
return (
@ -222,52 +242,18 @@ def setup_gradio():
with gr . Column ( ) :
delimiter = gr . Textbox ( lines = 1 , label = " Line Delimiter " , placeholder = " \\ n " )
emotion = gr . Radio (
[ " Happy " , " Sad " , " Angry " , " Disgusted " , " Arrogant " , " Custom " ] ,
value = " Custom " ,
label = " Emotion " ,
type = " value " ,
interactive = True
)
emotion = gr . Radio ( [ " Happy " , " Sad " , " Angry " , " Disgusted " , " Arrogant " , " Custom " ] , value = " Custom " , label = " Emotion " , type = " value " , interactive = True )
prompt = gr . Textbox ( lines = 1 , label = " Custom Emotion + Prompt (if selected) " )
voice = gr . Dropdown (
get_voice_list ( ) ,
label = " Voice " ,
type = " value " ,
)
mic_audio = gr . Audio (
label = " Microphone Source " ,
source = " microphone " ,
type = " filepath " ,
)
voice = gr . Dropdown ( get_voice_list ( ) , label = " Voice " , type = " value " )
mic_audio = gr . Audio ( label = " Microphone Source " , source = " microphone " , type = " filepath " )
refresh_voices = gr . Button ( value = " Refresh Voice List " )
voice_latents_chunks = gr . Slider ( label = " Voice Chunks " , minimum = 1 , maximum = 64 , value = 1 , step = 1 )
recompute_voice_latents = gr . Button ( value = " (Re)Compute Voice Latents " )
recompute_voice_latents . click ( compute_latents ,
inputs = [
voice ,
voice_latents_chunks ,
] ,
outputs = voice ,
)
prompt . change ( fn = lambda value : gr . update ( value = " Custom " ) ,
inputs = prompt ,
outputs = emotion
)
mic_audio . change ( fn = lambda value : gr . update ( value = " microphone " ) ,
inputs = mic_audio ,
outputs = voice
)
with gr . Column ( ) :
candidates = gr . Slider ( value = 1 , minimum = 1 , maximum = 6 , step = 1 , label = " Candidates " )
seed = gr . Number ( value = 0 , precision = 0 , label = " Seed " )
preset = gr . Radio (
[ " Ultra Fast " , " Fast " , " Standard " , " High Quality " ] ,
label = " Preset " ,
type = " value " ,
)
preset = gr . Radio ( [ " Ultra Fast " , " Fast " , " Standard " , " High Quality " ] , label = " Preset " , type = " value " )
num_autoregressive_samples = gr . Slider ( value = 128 , minimum = 0 , maximum = 512 , step = 1 , label = " Samples " )
diffusion_iterations = gr . Slider ( value = 128 , minimum = 0 , maximum = 512 , step = 1 , label = " Iterations " )
@ -275,19 +261,7 @@ def setup_gradio():
breathing_room = gr . Slider ( value = 8 , minimum = 1 , maximum = 32 , step = 1 , label = " Pause Size " )
diffusion_sampler = gr . Radio (
[ " P " , " DDIM " ] , # + ["K_Euler_A", "DPM++2M"],
value = " P " ,
label = " Diffusion Samplers " ,
type = " value " ,
)
preset . change ( fn = update_presets ,
inputs = preset ,
outputs = [
num_autoregressive_samples ,
diffusion_iterations ,
] ,
)
value = " P " , label = " Diffusion Samplers " , type = " value " )
show_experimental_settings = gr . Checkbox ( label = " Show Experimental Settings " )
reset_generation_settings_button = gr . Button ( value = " Reset to Default " )
with gr . Column ( visible = False ) as col :
@ -300,12 +274,6 @@ def setup_gradio():
length_penalty = gr . Slider ( value = 1.0 , minimum = 0 , maximum = 8 , label = " Length Penalty " )
repetition_penalty = gr . Slider ( value = 2.0 , minimum = 0 , maximum = 8 , label = " Repetition Penalty " )
cond_free_k = gr . Slider ( value = 2.0 , minimum = 0 , maximum = 4 , label = " Conditioning-Free K " )
show_experimental_settings . change (
fn = lambda x : gr . update ( visible = x ) ,
inputs = show_experimental_settings ,
outputs = experimental_column
)
with gr . Column ( ) :
submit = gr . Button ( value = " Generate " )
stop = gr . Button ( value = " Stop " )
@ -315,33 +283,13 @@ def setup_gradio():
output_audio = gr . Audio ( label = " Output " )
candidates_list = gr . Dropdown ( label = " Candidates " , type = " value " , visible = False )
output_pick = gr . Button ( value = " Select Candidate " , visible = False )
with gr . Tab ( " History " ) :
with gr . Row ( ) :
with gr . Column ( ) :
headers = {
" Name " : " " ,
" Samples " : " num_autoregressive_samples " ,
" Iterations " : " diffusion_iterations " ,
" Temp. " : " temperature " ,
" Sampler " : " diffusion_sampler " ,
" CVVP " : " cvvp_weight " ,
" Top P " : " top_p " ,
" Diff. Temp. " : " diffusion_temperature " ,
" Len Pen " : " length_penalty " ,
" Rep Pen " : " repetition_penalty " ,
" Cond-Free K " : " cond_free_k " ,
" Time " : " time " ,
}
history_info = gr . Dataframe ( label = " Results " , headers = list ( headers . keys ( ) ) )
history_info = gr . Dataframe ( label = " Results " , headers = list ( history_headers . keys ( ) ) )
with gr . Row ( ) :
with gr . Column ( ) :
history_voices = gr . Dropdown (
get_voice_list ( " ./results/ " ) ,
label = " Voice " ,
type = " value " ,
)
history_voices = gr . Dropdown ( choices = get_voice_list ( " ./results/ " ) , label = " Voice " , type = " value " )
history_view_results_button = gr . Button ( value = " View Files " )
with gr . Column ( ) :
history_results_list = gr . Dropdown ( label = " Results " , type = " value " , interactive = True )
@ -349,51 +297,16 @@ def setup_gradio():
with gr . Column ( ) :
history_audio = gr . Audio ( )
history_copy_settings_button = gr . Button ( value = " Copy Settings " )
history_view_results_button . click (
fn = history_view_results ,
inputs = history_voices ,
outputs = [
history_info ,
history_results_list ,
]
)
history_view_result_button . click (
fn = lambda voice , file : f " ./results/ { voice } / { file } " ,
inputs = [
history_voices ,
history_results_list ,
] ,
outputs = history_audio
)
with gr . Tab ( " Utilities " ) :
with gr . Row ( ) :
with gr . Column ( ) :
audio_in = gr . File ( type = " file " , label = " Audio Input " , file_types = [ " audio " ] )
copy_button = gr . Button ( value = " Copy Settings " )
audio_in = gr . Files ( type = " file " , label = " Audio Input " , file_types = [ " audio " ] )
import_voice_name = gr . Textbox ( label = " Voice Name " )
import_voice_button = gr . Button ( value = " Import Voice " )
with gr . Column ( ) :
metadata_out = gr . JSON ( label = " Audio Metadata " )
latents_out = gr . File ( type = " binary " , label = " Voice Latents " )
audio_in . upload (
fn = read_generate_settings_proxy ,
inputs = audio_in ,
outputs = [
metadata_out ,
latents_out ,
import_voice_name
]
)
import_voice_button . click (
fn = import_voice ,
inputs = [
audio_in ,
import_voice_name ,
]
)
metadata_out = gr . JSON ( label = " Audio Metadata " , visible = False )
copy_button = gr . Button ( value = " Copy Settings " , visible = False )
latents_out = gr . File ( type = " binary " , label = " Voice Latents " , visible = False )
with gr . Tab ( " Training " ) :
with gr . Tab ( " Prepare Dataset " ) :
with gr . Row ( ) :
@ -402,16 +315,9 @@ def setup_gradio():
gr . Dropdown ( get_voice_list ( ) , label = " Dataset Source " , type = " value " ) ,
gr . Textbox ( label = " Language " , placeholder = " English " )
]
dataset_voices = dataset_settings [ 0 ]
with gr . Column ( ) :
prepare_dataset_button = gr . Button ( value = " Prepare " )
prepare_dataset_button . click (
prepare_dataset_proxy ,
inputs = dataset_settings ,
outputs = None
)
with gr . Column ( ) :
prepare_dataset_output = gr . TextArea ( label = " Console Output " , interactive = False , max_lines = 8 )
with gr . Tab ( " Generate Configuration " ) :
with gr . Row ( ) :
with gr . Column ( ) :
@ -421,8 +327,6 @@ def setup_gradio():
gr . Number ( label = " Print Frequency " , value = 50 ) ,
gr . Number ( label = " Save Frequency " , value = 50 ) ,
]
save_yaml_button = gr . Button ( value = " Save Training Configuration " )
with gr . Column ( ) :
training_settings = training_settings + [
gr . Textbox ( label = " Training Name " , placeholder = " finetune " ) ,
gr . Textbox ( label = " Dataset Name " , placeholder = " finetune " ) ,
@ -430,24 +334,18 @@ def setup_gradio():
gr . Textbox ( label = " Validation Name " , placeholder = " finetune " ) ,
gr . Textbox ( label = " Validation Path " , placeholder = " ./training/finetune/train.txt " ) ,
]
save_yaml_button . click ( save_training_settings ,
inputs = training_settings ,
outputs = None
)
with gr . Tab ( " Train " ) :
with gr . Column ( ) :
save_yaml_output = gr . TextArea ( label = " Console Output " , interactive = False , max_lines = 8 )
save_yaml_button = gr . Button ( value = " Save Training Configuration " )
with gr . Tab ( " Run Training " ) :
with gr . Row ( ) :
with gr . Column ( ) :
training_configs = gr . Dropdown ( label = " Training Configuration " , choices = get_training_configs ( ) )
refresh_configs = gr . Button ( value = " Refresh Configurations " )
train = gr . Button ( value = " Train " )
refresh_configs . click ( update_training_configs , inputs = None , outputs = training_configs )
train . click ( run_training ,
inputs = training_configs ,
outputs = None
)
start_training_button = gr . Button ( value = " Train " )
stop_training_button = gr . Button ( value = " Stop " )
with gr . Column ( ) :
training_output = gr . TextArea ( label = " Console Output " , interactive = False , max_lines = 8 )
with gr . Tab ( " Settings " ) :
with gr . Row ( ) :
exec_inputs = [ ]
@ -465,23 +363,22 @@ def setup_gradio():
gr . Checkbox ( label = " Force CPU for Conditioning Latents " , value = args . force_cpu_for_conditioning_latents ) ,
gr . Checkbox ( label = " Defer TTS Load " , value = args . defer_tts_load ) ,
gr . Textbox ( label = " Device Override " , value = args . device_override ) ,
gr . Dropdown ( label = " Whisper Model " , value = args . whisper_model , choices = [ " tiny " , " tiny.en " , " base " , " base.en " , " small " , " small.en " , " medium " , " medium.en " , " large " ] ) ,
]
gr . Button ( value = " Check for Updates " ) . click ( check_for_updates )
gr . Button ( value = " Reload TTS " ) . click ( reload_tts )
with gr . Column ( ) :
exec_inputs = exec_inputs + [
gr . Number ( label = " Sample Batch Size " , precision = 0 , value = args . sample_batch_size ) ,
gr . Number ( label = " Concurrency Count " , precision = 0 , value = args . concurrency_count ) ,
gr . Number ( label = " Ouptut Sample Rate " , precision = 0 , value = args . output_sample_rate ) ,
gr . Slider ( label = " Ouptut Volume " , minimum = 0 , maximum = 2 , value = args . output_volume ) ,
gr . Dropdown ( label = " Whisper Model " , value = args . whisper_model , choices = [ " tiny " , " tiny.en " , " base " , " base.en " , " small " , " small.en " , " medium " , " medium.en " , " large " ] ) ,
]
gr . Button ( value = " Check for Updates " ) . click ( check_for_updates )
gr . Button ( value = " Reload TTS " ) . click ( reload_tts )
for i in exec_inputs :
i . change (
fn = export_exec_settings ,
inputs = exec_inputs
)
i . change ( fn = export_exec_settings , inputs = exec_inputs )
# console_output = gr.TextArea(label="Console Output", interactive=False, max_lines=8)
input_settings = [
text ,
@ -507,11 +404,76 @@ def setup_gradio():
experimental_checkboxes ,
]
history_view_results_button . click (
fn = history_view_results ,
inputs = history_voices ,
outputs = [
history_info ,
history_results_list ,
]
)
history_view_result_button . click (
fn = lambda voice , file : f " ./results/ { voice } / { file } " ,
inputs = [
history_voices ,
history_results_list ,
] ,
outputs = history_audio
)
audio_in . upload (
fn = read_generate_settings_proxy ,
inputs = audio_in ,
outputs = [
metadata_out ,
copy_button ,
latents_out ,
import_voice_name
]
)
import_voice_button . click (
fn = import_voices_proxy ,
inputs = [
audio_in ,
import_voice_name ,
] ,
outputs = import_voice_name #console_output
)
show_experimental_settings . change (
fn = lambda x : gr . update ( visible = x ) ,
inputs = show_experimental_settings ,
outputs = experimental_column
)
preset . change ( fn = update_presets ,
inputs = preset ,
outputs = [
num_autoregressive_samples ,
diffusion_iterations ,
] ,
)
recompute_voice_latents . click ( compute_latents ,
inputs = [
voice ,
voice_latents_chunks ,
] ,
outputs = voice ,
)
prompt . change ( fn = lambda value : gr . update ( value = " Custom " ) ,
inputs = prompt ,
outputs = emotion
)
mic_audio . change ( fn = lambda value : gr . update ( value = " microphone " ) ,
inputs = mic_audio ,
outputs = voice
)
refresh_voices . click ( update_voices ,
inputs = None ,
outputs = [
voice ,
dataset_voices ,
dataset_ settings[ 0 ] ,
history_voices
]
)
@ -552,6 +514,25 @@ def setup_gradio():
outputs = input_settings
)
refresh_configs . click ( update_training_configs , inputs = None , outputs = training_configs )
start_training_button . click ( run_training ,
inputs = training_configs ,
outputs = training_output #console_output
)
stop_training_button . click ( stop_training ,
inputs = None ,
outputs = training_output #console_output
)
prepare_dataset_button . click (
prepare_dataset_proxy ,
inputs = dataset_settings ,
outputs = prepare_dataset_output #console_output
)
save_yaml_button . click ( save_training_settings ,
inputs = training_settings ,
outputs = save_yaml_output #console_output
)
if os . path . isfile ( ' ./config/generate.json ' ) :
ui . load ( import_generate_settings , inputs = None , outputs = input_settings )
