@ -55,7 +55,7 @@ def setup_args():
' sample-batch-size ' : None ,
' embed-output-metadata ' : True ,
' latents-lean-and-mean ' : True ,
' voice-fixer ' : True,
' voice-fixer ' : False, # getting tired of long initialization times in a Colab for downloading a large dataset for it
' voice-fixer-use-cuda ' : True ,
' force-cpu-for-conditioning-latents ' : False ,
' device-override ' : None ,
@ -167,7 +167,7 @@ def generate(
progress ( 0 , desc = " Loading voice... " )
voice_samples , conditioning_latents = load_voice ( voice )
if voice_samples is not None :
if voice_samples is not None and len ( voice_samples ) > 0 :
sample_voice = torch . cat ( voice_samples , dim = - 1 ) . squeeze ( ) . cpu ( )
conditioning_latents = tts . get_conditioning_latents ( voice_samples , return_mels = not args . latents_lean_and_mean , progress = progress , slices = voice_latents_chunks , force_cpu = args . force_cpu_for_conditioning_latents )
@ -374,7 +374,7 @@ def generate(
with open ( f ' { outdir } / { voice } _ { name } .json ' , ' w ' , encoding = " utf-8 " ) as f :
f . write ( json . dumps ( info , indent = ' \t ' ) )
if args . voice_fixer and voicefixer :
if args . voice_fixer and voicefixer is not None :
fixed_output_voices = [ ]
for path in progress . tqdm ( output_voices , desc = " Running voicefix... " ) :
fixed = path . replace ( " .wav " , " _fixed.wav " )
@ -409,6 +409,7 @@ def generate(
if ' latents ' in info :
del info [ ' latents ' ]
os . makedirs ( ' ./config/ ' , exist_ok = True )
with open ( f ' ./config/generate.json ' , ' w ' , encoding = " utf-8 " ) as f :
f . write ( json . dumps ( info , indent = ' \t ' ) )
@ -422,13 +423,18 @@ def generate(
stats ,
)
import subprocess
def run_training ( config_path ) :
print ( " Unloading TTS to save VRAM. " )
global tts
del tts
tts = None
import subprocess
subprocess . run ( [ " python " , " ./src/train.py " , " -opt " , config_path ] , env = os . environ . copy ( ) , shell = True , stdout = subprocess . PIPE )
cmd = [ " python " , " ./src/train.py " , " -opt " , config_path ]
print ( " Spawning process: " , " " . join ( cmd ) )
subprocess . run ( cmd , env = os . environ . copy ( ) , shell = True , stdout = subprocess . STDOUT , stderr = subprocess . STDOUT )
"""
from train import train
train ( config )
@ -501,7 +507,7 @@ def prepare_dataset( files, outdir, language=None ):
for file in files :
print ( f " Transcribing file: { file } " )
result = whisper_model . transcribe ( file , language = language )
result = whisper_model . transcribe ( file , language = language if language else " English " )
results [ os . path . basename ( file ) ] = result
print ( f " Transcribed file: { file } , { len ( result [ ' segments ' ] ) } found. " )
@ -557,7 +563,7 @@ def import_voice(file, saveAs = None):
path = f " { outdir } / { os . path . basename ( filename ) } "
waveform , sampling_rate = torchaudio . load ( filename )
if args . voice_fixer :
if args . voice_fixer and voicefixer is not None :
# resample to best bandwidth since voicefixer will do it anyways through librosa
if sampling_rate != 44100 :
print ( f " Resampling imported voice sample: { path } " )
@ -714,6 +720,7 @@ def export_exec_settings( listen, share, check_for_updates, models_from_local_on
' output-volume ' : args . output_volume ,
}
os . makedirs ( ' ./config/ ' , exist_ok = True )
with open ( f ' ./config/exec.json ' , ' w ' , encoding = " utf-8 " ) as f :
f . write ( json . dumps ( settings , indent = ' \t ' ) )
