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import argparse
from pathlib import Path
from utils.argutils import print_args
from vocoder.train import train
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Trains the vocoder from the synthesizer audios and the GTA synthesized mels, "
"or ground truth mels.",
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument("run_id", type=str, help= \
"Name for this model. By default, training outputs will be stored to saved_models/<run_id>/. If a model state "
"from the same run ID was previously saved, the training will restart from there. Pass -f to overwrite saved "
"states and restart from scratch.")
parser.add_argument("datasets_root", type=Path, help= \
"Path to the directory containing your SV2TTS directory. Specifying --syn_dir or --voc_dir "
"will take priority over this argument.")
parser.add_argument("--syn_dir", type=Path, default=argparse.SUPPRESS, help= \
"Path to the synthesizer directory that contains the ground truth mel spectrograms, "
"the wavs and the embeds. Defaults to <datasets_root>/SV2TTS/synthesizer/.")
parser.add_argument("--voc_dir", type=Path, default=argparse.SUPPRESS, help= \
"Path to the vocoder directory that contains the GTA synthesized mel spectrograms. "
"Defaults to <datasets_root>/SV2TTS/vocoder/. Unused if --ground_truth is passed.")
parser.add_argument("-m", "--models_dir", type=Path, default="saved_models", help=\
"Path to the directory that will contain the saved model weights, as well as backups "
"of those weights and wavs generated during training.")
parser.add_argument("-g", "--ground_truth", action="store_true", help= \
"Train on ground truth spectrograms (<datasets_root>/SV2TTS/synthesizer/mels).")
parser.add_argument("-s", "--save_every", type=int, default=1000, help= \
"Number of steps between updates of the model on the disk. Set to 0 to never save the "
"model.")
parser.add_argument("-b", "--backup_every", type=int, default=25000, help= \
"Number of steps between backups of the model. Set to 0 to never make backups of the "
"model.")
parser.add_argument("-f", "--force_restart", action="store_true", help= \
"Do not load any saved model and restart from scratch.")
args = parser.parse_args()
# Process the arguments
if not hasattr(args, "syn_dir"):
args.syn_dir = args.datasets_root / "SV2TTS" / "synthesizer"
if not hasattr(args, "voc_dir"):
args.voc_dir = args.datasets_root / "SV2TTS" / "vocoder"
del args.datasets_root
args.models_dir.mkdir(exist_ok=True)
# Run the training
print_args(args, parser)
train(**vars(args))
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