def __init__(self):
gpus = tf.config.experimental.list_physical_devices(device_type='GPU')
tf.config.experimental.set_visible_devices(devices=gpus[0:2],
device_type='GPU')
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
self.__init_model()
self.tts_pause = TTSSegPause()
self.tts_py = TTSPinYin()
class TTSModel():
def __init__(self):
gpus = tf.config.experimental.list_physical_devices(device_type='GPU')
tf.config.experimental.set_visible_devices(devices=gpus[0:2],
device_type='GPU')
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
self.__init_model()
self.tts_pause = TTSSegPause()
self.tts_py = TTSPinYin()
def __init_model(self):
tacotron2_config = AutoConfig.from_pretrained(config.tacotron2_baker)
self.tacotron2 = TFAutoModel.from_pretrained(
config=tacotron2_config,
pretrained_path=config.tacotron2_pretrained_path,
training=False,
name="tacotron2")
self.tacotron2.setup_window(win_front=5, win_back=5)
mb_melgan_config = AutoConfig.from_pretrained(
config.multiband_melgan_baker)
self.mb_melgan = TFAutoModel.from_pretrained(
config=mb_melgan_config,
pretrained_path=config.multiband_melgan_pretrained_path,
name="mb_melgan")
self.processor = AutoProcessor.from_pretrained(
pretrained_path=config.baker_mapper_pretrained_path)
def text_to_pinyin_sequence(self, text):
# pinyin = self.processor.pinyin_parser(text, style=Style.TONE3, errors="ignore")
pinyin, text = self.tts_py.get_pyin(text)
new_pinyin = []
for x in str(pinyin).split(" "):
if "#" not in x:
new_pinyin.append(x)
phonemes = self.processor.get_phoneme_from_char_and_pinyin(
text, new_pinyin)
text = " ".join(phonemes)
print("phoneme seq: {}".format(text))
logging.info(
"[TTSModel] [text_to_pinyin_sequence] phoneme seq:{}".format(text))
input_ids = self.processor.text_to_sequence(text, inference=False)
return input_ids
def do_synthesis(self, input_text):
input_text = self.tts_pause.add_pause(input_text)
print("input_text>>>>", input_text)
logging.info(
"[TTSModel] [do_synthesis] input_text:{}".format(input_text))
input_ids = self.processor.text_to_sequence(input_text, inference=True)
_, mel_outputs, stop_token_prediction, alignment_history = self.tacotron2.inference(
tf.expand_dims(tf.convert_to_tensor(input_ids, dtype=tf.int32), 0),
tf.convert_to_tensor([len(input_ids)], tf.int32),
tf.convert_to_tensor([0], dtype=tf.int32))
remove_end = 1024
audio = self.mb_melgan.inference(mel_outputs)[0, :-remove_end, 0]
return mel_outputs.numpy(), alignment_history.numpy(), audio.numpy()
'''