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import argparse |
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from multiprocessing import Pool, cpu_count |
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import torch |
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import torch.multiprocessing as mp |
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from tqdm import tqdm |
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import utils |
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from config import config |
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from clap_wrapper import get_clap_audio_feature |
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import librosa |
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import os |
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os.environ["OMP_NUM_THREADS"] = "1" |
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os.environ["MKL_NUM_THREADS"] = "1" |
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def process_line(line): |
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device = config.emo_gen_config.device |
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if config.emo_gen_config.use_multi_device: |
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rank = mp.current_process()._identity |
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rank = rank[0] if len(rank) > 0 else 0 |
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if torch.cuda.is_available(): |
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gpu_id = rank % torch.cuda.device_count() |
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device = torch.device(f"cuda:{gpu_id}") |
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else: |
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device = torch.device("cpu") |
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wav_path, _, language_str, text, phones, tone, word2ph = line.strip().split("|") |
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clap_path = wav_path.replace(".WAV", ".wav").replace(".wav", ".emo.pt") |
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if os.path.isfile(clap_path): |
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return |
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audio = librosa.load(wav_path, 48000)[0] |
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clap = get_clap_audio_feature(audio, device) |
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torch.save(clap, clap_path) |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser() |
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parser.add_argument( |
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"-c", "--config", type=str, default=config.emo_gen_config.config_path |
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) |
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parser.add_argument( |
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"--num_processes", type=int, default=config.emo_gen_config.num_processes |
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) |
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args, _ = parser.parse_known_args() |
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config_path = args.config |
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hps = utils.get_hparams_from_file(config_path) |
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lines = [] |
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with open(hps.data.training_files, encoding="utf-8") as f: |
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lines.extend(f.readlines()) |
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with open(hps.data.validation_files, encoding="utf-8") as f: |
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lines.extend(f.readlines()) |
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if len(lines) != 0: |
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num_processes = min(args.num_processes, cpu_count()) |
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with Pool(processes=num_processes) as pool: |
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for _ in tqdm(pool.imap_unordered(process_line, lines), total=len(lines)): |
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pass |
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print(f"clap生成完毕!, 共有{len(lines)}个emo.pt生成!") |
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