Fix: support infer 2.2 models (#244)

* Fix: support infer 2.2 models

* Fix imports

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

clap_gen.py

@@ -1,64 +0,0 @@
-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]
-    # audio = librosa.resample(audio, 44100, 48000)
-
-    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!")