| import argparse |
| from multiprocessing import Pool, cpu_count |
|
|
| import torch |
| import torch.multiprocessing as mp |
| from tqdm import tqdm |
|
|
| import utils |
| from config import config |
| from clap_wrapper import get_clap_audio_feature |
| import librosa |
| import os |
|
|
| os.environ["OMP_NUM_THREADS"] = "1" |
| os.environ["MKL_NUM_THREADS"] = "1" |
|
|
|
|
| def process_line(line): |
| device = config.emo_gen_config.device |
| if config.emo_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("|") |
|
|
| clap_path = wav_path.replace(".WAV", ".wav").replace(".wav", ".emo.pt") |
| if os.path.isfile(clap_path): |
| return |
|
|
| audio = librosa.load(wav_path, 48000)[0] |
| |
|
|
| clap = get_clap_audio_feature(audio, device) |
| torch.save(clap, clap_path) |
|
|
|
|
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser() |
| parser.add_argument( |
| "-c", "--config", type=str, default=config.emo_gen_config.config_path |
| ) |
| parser.add_argument( |
| "--num_processes", type=int, default=config.emo_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 = min(args.num_processes, cpu_count()) |
| with Pool(processes=num_processes) as pool: |
| for _ in tqdm(pool.imap_unordered(process_line, lines), total=len(lines)): |
| pass |
|
|
| print(f"clap生成完毕!, 共有{len(lines)}个emo.pt生成!") |
|
|
