| import torch | |
| from multiprocessing import Pool | |
| import commons | |
| import utils | |
| from tqdm import tqdm | |
| from text import cleaned_text_to_sequence, get_bert | |
| import argparse | |
| import torch.multiprocessing as mp | |
| from config import config | |
| def process_line(line): | |
| device = config.bert_gen_config.device | |
| if config.bert_gen_config.use_multi_device: | |
| rank = mp.current_process()._identity | |
| rank = rank[0] if len(rank) > 0 else 0 | |
| if torch.cuda.is_available(): | |
| gpu_id = rank % torch.cuda.device_count() | |
| device = torch.device(f"cuda:{gpu_id}") | |
| else: | |
| device = torch.device("cpu") | |
| wav_path, _, language_str, text, phones, tone, word2ph = line.strip().split("|") | |
| phone = phones.split(" ") | |
| tone = [int(i) for i in tone.split(" ")] | |
| word2ph = [int(i) for i in word2ph.split(" ")] | |
| word2ph = [i for i in word2ph] | |
| phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str) | |
| phone = commons.intersperse(phone, 0) | |
| tone = commons.intersperse(tone, 0) | |
| language = commons.intersperse(language, 0) | |
| for i in range(len(word2ph)): | |
| word2ph[i] = word2ph[i] * 2 | |
| word2ph[0] += 1 | |
| bert_path = wav_path.replace(".WAV", ".wav").replace(".wav", ".bert.pt") | |
| try: | |
| bert = torch.load(bert_path) | |
| assert bert.shape[-1] == len(phone) | |
| except Exception: | |
| bert = get_bert(text, word2ph, language_str, device) | |
| assert bert.shape[-1] == len(phone) | |
| torch.save(bert, bert_path) | |
| preprocess_text_config = config.preprocess_text_config | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "-c", "--config", type=str, default=config.bert_gen_config.config_path | |
| ) | |
| parser.add_argument( | |
| "--num_processes", type=int, default=config.bert_gen_config.num_processes | |
| ) | |
| args, _ = parser.parse_known_args() | |
| config_path = args.config | |
| hps = utils.get_hparams_from_file(config_path) | |
| lines = [] | |
| with open(hps.data.training_files, encoding="utf-8") as f: | |
| lines.extend(f.readlines()) | |
| with open(hps.data.validation_files, encoding="utf-8") as f: | |
| lines.extend(f.readlines()) | |
| if len(lines) != 0: | |
| num_processes = args.num_processes | |
| with Pool(processes=num_processes) as pool: | |
| for _ in tqdm(pool.imap_unordered(process_line, lines), total=len(lines)): | |
| pass | |
| print(f"bert生成完毕!, 共有{len(lines)}个bert.pt生成!") | |