init (not checked bat script yet)

style_gen.py

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+import argparse
+import concurrent.futures
+import sys
+import warnings
+
+import numpy as np
+import torch
+from tqdm import tqdm
+
+import utils
+from config import config
+
+warnings.filterwarnings("ignore", category=UserWarning)
+from pyannote.audio import Inference, Model
+
+model = Model.from_pretrained("pyannote/wespeaker-voxceleb-resnet34-LM")
+inference = Inference(model, window="whole")
+device = torch.device(config.style_gen_config.device)
+inference.to(device)
+
+
+def extract_style_vector(wav_path):
+    return inference(wav_path)
+
+
+def save_style_vector(wav_path):
+    style_vec = extract_style_vector(wav_path)
+    # `test.wav` -> `test.wav.npy`
+    np.save(f"{wav_path}.npy", style_vec)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "-c", "--config", type=str, default=config.style_gen_config.config_path
+    )
+    parser.add_argument(
+        "--num_processes", type=int, default=config.style_gen_config.num_processes
+    )
+    args, _ = parser.parse_known_args()
+    config_path = args.config
+    num_processes = args.num_processes
+
+    hps = utils.get_hparams_from_file(config_path)
+
+    device = config.style_gen_config.device
+
+    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())
+
+    wavnames = [line.split("|")[0] for line in lines]
+
+    with concurrent.futures.ThreadPoolExecutor(max_workers=num_processes) as executor:
+        list(
+            tqdm(
+                executor.map(save_style_vector, wavnames),
+                total=len(wavnames),
+                file=sys.stdout,
+            )
+        )
+
+    print(f"Finished generating style vectors! total: {len(wavnames)} npy files.")