mirror of https://github.com/coqui-ai/TTS.git
61 lines
1.5 KiB
Python
61 lines
1.5 KiB
Python
import os
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from coqpit import Coqpit
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from trainer import Trainer, TrainerArgs
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from TTS.tts.configs.shared_configs import BaseAudioConfig
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from TTS.utils.audio import AudioProcessor
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from TTS.vocoder.configs.hifigan_config import *
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from TTS.vocoder.datasets.preprocess import load_wav_data
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from TTS.vocoder.models.gan import GAN
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output_path = "/storage/output-hifigan/"
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audio_config = BaseAudioConfig(
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mel_fmin=50,
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mel_fmax=8000,
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hop_length=256,
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stats_path="/storage/TTS/scale_stats.npy",
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)
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config = HifiganConfig(
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batch_size=74,
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eval_batch_size=16,
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num_loader_workers=8,
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num_eval_loader_workers=8,
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lr_disc=0.0002,
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lr_gen=0.0002,
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run_eval=True,
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test_delay_epochs=5,
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epochs=1000,
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use_noise_augment=True,
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seq_len=8192,
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pad_short=2000,
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save_step=5000,
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print_step=50,
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print_eval=True,
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mixed_precision=False,
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eval_split_size=30,
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save_n_checkpoints=2,
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save_best_after=5000,
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data_path="/storage/filtered_dataset",
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output_path=output_path,
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audio=audio_config,
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)
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# init audio processor
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ap = AudioProcessor.init_from_config(config)
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# load training samples
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print("config.eval_split_size = ", config.eval_split_size)
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eval_samples, train_samples = load_wav_data(config.data_path, config.eval_split_size)
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# init model
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model = GAN(config, ap)
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# init the trainer and 🚀
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trainer = Trainer(
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TrainerArgs(), config, output_path, model=model, train_samples=train_samples, eval_samples=eval_samples
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)
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trainer.fit()
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