import os

from TTS.config.shared_configs import BaseAudioConfig
from TTS.trainer import Trainer, TrainingArgs
from TTS.tts.configs.glow_tts_config import GlowTTSConfig
from TTS.tts.configs.shared_configs import BaseDatasetConfig
from TTS.tts.datasets import load_tts_samples
from TTS.tts.models.glow_tts import GlowTTS
from TTS.tts.utils.speakers import SpeakerManager
from TTS.utils.audio import AudioProcessor

# set experiment paths
output_path = os.path.dirname(os.path.abspath(__file__))
dataset_path = os.path.join(output_path, "../VCTK/")

# download the dataset if not downloaded
if not os.path.exists(dataset_path):
    from TTS.utils.downloaders import download_vctk

    download_vctk(dataset_path)

# define dataset config
dataset_config = BaseDatasetConfig(name="vctk", meta_file_train="", path=dataset_path)

# define audio config
# ❗ resample the dataset externally using `TTS/bin/resample.py` and set `resample=False` for faster training
audio_config = BaseAudioConfig(sample_rate=22050, resample=True, do_trim_silence=True, trim_db=23.0)

# define model config
config = GlowTTSConfig(
    batch_size=64,
    eval_batch_size=16,
    num_loader_workers=4,
    num_eval_loader_workers=4,
    run_eval=True,
    test_delay_epochs=-1,
    epochs=1000,
    text_cleaner="phoneme_cleaners",
    use_phonemes=True,
    phoneme_language="en-us",
    phoneme_cache_path=os.path.join(output_path, "phoneme_cache"),
    print_step=25,
    print_eval=False,
    mixed_precision=True,
    output_path=output_path,
    datasets=[dataset_config],
    use_speaker_embedding=True,
)

# init audio processor
ap = AudioProcessor(**config.audio.to_dict())

# load training samples
train_samples, eval_samples = load_tts_samples(dataset_config, eval_split=True)

# init speaker manager for multi-speaker training
# it maps speaker-id to speaker-name in the model and data-loader
speaker_manager = SpeakerManager()
speaker_manager.set_speaker_ids_from_data(train_samples + eval_samples)
config.num_speakers = speaker_manager.num_speakers

# init model
model = GlowTTS(config, speaker_manager)

# init the trainer and 🚀
trainer = Trainer(
    TrainingArgs(),
    config,
    output_path,
    model=model,
    train_samples=train_samples,
    eval_samples=eval_samples,
    training_assets={"audio_processor": ap},
)
trainer.fit()