from synthesizer.preprocess import create_embeddings

from utils.argutils import print_args

from pathlib import Path

import argparse

if __name__ == "__main__":

parser = argparse.ArgumentParser(

description="Creates embeddings for the synthesizer from the LibriSpeech utterances.",

formatter_class=argparse.ArgumentDefaultsHelpFormatter

)

parser.add_argument("--synthesizer_root",default="d/SV2TTS/synthesizer/", type=Path, help=\

"Path to the synthesizer training data that contains the audios and the train.txt file. "

"If you let everything as default, it should be <datasets_root>/SV2TTS/synthesizer/.")

parser.add_argument("-e", "--encoder_model_fpath", type=Path,

default="encoder/saved_models/pretrained.pt", help=\

"Path your trained encoder model.")

parser.add_argument("-n", "--n_processes", type=int, default=4, help= \

"Number of parallel processes. An encoder is created for each, so you may need to lower "

"this value on GPUs with low memory. Set it to 1 if CUDA is unhappy.")

args = parser.parse_args()

# Preprocess the dataset

print_args(args, parser)

create_embeddings(**vars(args))