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import os
from trainer import Trainer, TrainerArgs
from TTS.config.shared_configs import BaseAudioConfig
from TTS.tts.configs.shared_configs import BaseDatasetConfig, CapacitronVAEConfig
from TTS.tts.configs.tacotron_config import TacotronConfig
from TTS.tts.datasets import load_tts_samples
from TTS.tts.models.tacotron import Tacotron
from TTS.tts.utils.text.tokenizer import TTSTokenizer
from TTS.utils.audio import AudioProcessor
output_path = os.path.dirname(os.path.abspath(__file__))
data_path = "/srv/data/"
# Using LJSpeech like dataset processing for the blizzard dataset
dataset_config = BaseDatasetConfig(formatter="ljspeech", meta_file_train="metadata.csv", path=data_path)
audio_config = BaseAudioConfig(
sample_rate=24000,
do_trim_silence=True,
trim_db=60.0,
signal_norm=True,
mel_fmin=80.0,
mel_fmax=12000,
spec_gain=20.0,
log_func="np.log10",
ref_level_db=20,
preemphasis=0.0,
min_level_db=-100,
)
# Using the standard Capacitron config
capacitron_config = CapacitronVAEConfig(capacitron_VAE_loss_alpha=1.0)
config = TacotronConfig(
run_name="Blizzard-Capacitron-T1",
audio=audio_config,
capacitron_vae=capacitron_config,
use_capacitron_vae=True,
batch_size=128, # Tune this to your gpu
max_audio_len=6 * 24000, # Tune this to your gpu
min_audio_len=0.5 * 24000,
eval_batch_size=16,
num_loader_workers=12,
num_eval_loader_workers=8,
precompute_num_workers=24,
run_eval=True,
test_delay_epochs=5,
r=2,
optimizer="CapacitronOptimizer",
optimizer_params={"RAdam": {"betas": [0.9, 0.998], "weight_decay": 1e-6}, "SGD": {"lr": 1e-5, "momentum": 0.9}},
attention_type="graves",
attention_heads=5,
epochs=1000,
text_cleaner="phoneme_cleaners",
use_phonemes=True,
phoneme_language="en-us",
phonemizer="espeak",
phoneme_cache_path=os.path.join(data_path, "phoneme_cache"),
stopnet_pos_weight=15,
print_step=50,
print_eval=True,
mixed_precision=False,
output_path=output_path,
datasets=[dataset_config],
lr=1e-3,
lr_scheduler="StepwiseGradualLR",
lr_scheduler_params={"gradual_learning_rates": [[0, 1e-3], [2e4, 5e-4], [4e4, 3e-4], [6e4, 1e-4], [8e4, 5e-5]]},
scheduler_after_epoch=False, # scheduler doesn't work without this flag
loss_masking=False,
decoder_loss_alpha=1.0,
postnet_loss_alpha=1.0,
postnet_diff_spec_alpha=1.0,
decoder_diff_spec_alpha=1.0,
decoder_ssim_alpha=1.0,
postnet_ssim_alpha=1.0,
)
ap = AudioProcessor(**config.audio.to_dict())
tokenizer, config = TTSTokenizer.init_from_config(config)
train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)
model = Tacotron(config, ap, tokenizer, speaker_manager=None)
trainer = Trainer(
TrainerArgs(),
config,
output_path,
model=model,
train_samples=train_samples,
eval_samples=eval_samples,
)
# 🚀
trainer.fit()
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