| import os | |
| from trainer import Trainer, TrainerArgs | |
| from TTS.config.shared_configs import BaseDatasetConfig | |
| from TTS.tts.configs.delightful_tts_config import DelightfulTtsAudioConfig, DelightfulTTSConfig | |
| from TTS.tts.datasets import load_tts_samples | |
| from TTS.tts.models.delightful_tts import DelightfulTTS, DelightfulTtsArgs, VocoderConfig | |
| from TTS.tts.utils.text.tokenizer import TTSTokenizer | |
| from TTS.utils.audio.processor import AudioProcessor | |
| data_path = "" | |
| output_path = os.path.dirname(os.path.abspath(__file__)) | |
| dataset_config = BaseDatasetConfig( | |
| dataset_name="ljspeech", formatter="ljspeech", meta_file_train="metadata.csv", path=data_path | |
| ) | |
| audio_config = DelightfulTtsAudioConfig() | |
| model_args = DelightfulTtsArgs() | |
| vocoder_config = VocoderConfig() | |
| delightful_tts_config = DelightfulTTSConfig( | |
| run_name="delightful_tts_ljspeech", | |
| run_description="Train like in delightful tts paper.", | |
| model_args=model_args, | |
| audio=audio_config, | |
| vocoder=vocoder_config, | |
| batch_size=32, | |
| eval_batch_size=16, | |
| num_loader_workers=10, | |
| num_eval_loader_workers=10, | |
| precompute_num_workers=10, | |
| batch_group_size=2, | |
| compute_input_seq_cache=True, | |
| compute_f0=True, | |
| f0_cache_path=os.path.join(output_path, "f0_cache"), | |
| run_eval=True, | |
| test_delay_epochs=-1, | |
| epochs=1000, | |
| text_cleaner="english_cleaners", | |
| use_phonemes=True, | |
| phoneme_language="en-us", | |
| phoneme_cache_path=os.path.join(output_path, "phoneme_cache"), | |
| print_step=50, | |
| print_eval=False, | |
| mixed_precision=True, | |
| output_path=output_path, | |
| datasets=[dataset_config], | |
| start_by_longest=False, | |
| eval_split_size=0.1, | |
| binary_align_loss_alpha=0.0, | |
| use_attn_priors=False, | |
| lr_gen=4e-1, | |
| lr=4e-1, | |
| lr_disc=4e-1, | |
| max_text_len=130, | |
| ) | |
| tokenizer, config = TTSTokenizer.init_from_config(delightful_tts_config) | |
| ap = AudioProcessor.init_from_config(config) | |
| train_samples, eval_samples = load_tts_samples( | |
| dataset_config, | |
| eval_split=True, | |
| eval_split_max_size=config.eval_split_max_size, | |
| eval_split_size=config.eval_split_size, | |
| ) | |
| model = DelightfulTTS(ap=ap, config=config, tokenizer=tokenizer, speaker_manager=None) | |
| trainer = Trainer( | |
| TrainerArgs(), | |
| config, | |
| output_path, | |
| model=model, | |
| train_samples=train_samples, | |
| eval_samples=eval_samples, | |
| ) | |
| trainer.fit() | |