Medix-AI/coqui-tts
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coqui-tts
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Update train_tts for the new API

This commit is contained in:
Eren Gölge 2022-01-07 15:38:57 +00:00
parent 001da8afc8
commit 8e248913d6
1 changed files with 1 additions and 36 deletions
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37
TTS/bin/train_tts.py
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@ -44,43 +44,8 @@ def main():
# load training samples # load training samples
train_samples, eval_samples = load_tts_samples(config.datasets, eval_split=True, eval_split_max_size=config.eval_split_max_size, eval_split_size=config.eval_split_size) train_samples, eval_samples = load_tts_samples(config.datasets, eval_split=True, eval_split_max_size=config.eval_split_max_size, eval_split_size=config.eval_split_size)
# setup audio processor
ap = AudioProcessor(**config.audio)
# init speaker manager
if check_config_and_model_args(config, "use_speaker_embedding", True):
speaker_manager = SpeakerManager(data_items=train_samples + eval_samples)
if hasattr(config, "model_args"):
config.model_args.num_speakers = speaker_manager.num_speakers
else:
config.num_speakers = speaker_manager.num_speakers
elif check_config_and_model_args(config, "use_d_vector_file", True):
if check_config_and_model_args(config, "use_speaker_encoder_as_loss", True):
speaker_manager = SpeakerManager(
d_vectors_file_path=config.model_args.d_vector_file,
encoder_model_path=config.model_args.speaker_encoder_model_path,
encoder_config_path=config.model_args.speaker_encoder_config_path,
use_cuda=torch.cuda.is_available(),
)
else:
speaker_manager = SpeakerManager(d_vectors_file_path=get_from_config_or_model_args(config, "d_vector_file"))
config.num_speakers = speaker_manager.num_speakers
if hasattr(config, "model_args"):
config.model_args.num_speakers = speaker_manager.num_speakers
else:
speaker_manager = None
if check_config_and_model_args(config, "use_language_embedding", True):
language_manager = LanguageManager(config=config)
if hasattr(config, "model_args"):
config.model_args.num_languages = language_manager.num_languages
else:
config.num_languages = language_manager.num_languages
else:
language_manager = None
# init the model from config # init the model from config
model = setup_model(config, speaker_manager, language_manager) model = setup_model(config, train_samples + eval_samples)
# init the trainer and 🚀 # init the trainer and 🚀
trainer = Trainer( trainer = Trainer(