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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.speakers import SpeakerManager
from TTS.tts.utils.text.tokenizer import TTSTokenizer
from TTS.utils.audio.processor import AudioProcessor
data_path = "/raid/datasets/vctk_v092_48khz_removed_silence_silero_vad"
output_path = os.path.dirname(os.path.abspath(__file__))
dataset_config = BaseDatasetConfig(
dataset_name="vctk", formatter="vctk", meta_file_train="", path=data_path, language="en-us"
)
audio_config = DelightfulTtsAudioConfig()
model_args = DelightfulTtsArgs()
vocoder_config = VocoderConfig()
something_tts_config = DelightfulTTSConfig(
run_name="delightful_tts_vctk",
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=40,
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=True,
binary_align_loss_alpha=0.0,
use_attn_priors=False,
max_text_len=60,
steps_to_start_discriminator=10000,
)
tokenizer, config = TTSTokenizer.init_from_config(something_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,
)
speaker_manager = SpeakerManager()
speaker_manager.set_ids_from_data(train_samples + eval_samples, parse_key="speaker_name")
config.model_args.num_speakers = speaker_manager.num_speakers
model = DelightfulTTS(ap=ap, config=config, tokenizer=tokenizer, speaker_manager=speaker_manager, emotion_manager=None)
trainer = Trainer(
TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
)
trainer.fit()
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