@ -34,7 +34,7 @@ from datetime import timedelta
from tortoise . api import TextToSpeech , MODELS , get_model_path , pad_or_truncate
from tortoise . utils . audio import load_audio , load_voice , load_voices , get_voice_dir
from tortoise . utils . text import split_and_recombine_text
from tortoise . utils . device import get_device_name , set_device_name , get_device_count
from tortoise . utils . device import get_device_name , set_device_name , get_device_count , get_device_vram
MODELS [ ' dvae.pth ' ] = " https://huggingface.co/jbetker/tortoise-tts-v2/resolve/3704aea61678e7e468a06d8eea121dba368a798e/.models/dvae.pth "
@ -1278,6 +1278,8 @@ def optimize_training_settings( **kwargs ):
messages . append ( f " Batch size is not evenly divisible by the gradient accumulation size, adjusting gradient accumulation size to: { settings [ ' gradient_accumulation_size ' ] } " )
print ( " VRAM " , get_device_vram ( ) )
iterations = calc_iterations ( epochs = settings [ ' epochs ' ] , lines = lines , batch_size = settings [ ' batch_size ' ] )
if settings [ ' epochs ' ] < settings [ ' print_rate ' ] :
@ -1828,10 +1830,12 @@ def import_generate_settings(file="./config/generate.json"):
res = [ ]
if GENERATE_SETTINGS_ARGS is not None :
for k in GENERATE_SETTINGS_ARGS :
res . append ( defaults [ k ] if not settings or settings [ k ] is None else settings [ k ] )
if k not in defaults :
continue
res . append ( defaults [ k ] if not settings or k not in settings or not settings [ k ] is None else settings [ k ] )
else :
for k in defaults :
res . append ( defaults [ k ] if not settings or settings[ k ] is None else settings [ k ] )
res . append ( defaults [ k ] if not settings or k not in settings or not settings[ k ] is None else settings [ k ] )
return tuple ( res )