Disable multiprocessing when dumping features in hubert preprocessing (#2311)

Summary:
The multi-processing works well on MFCC features. However, it sometimes makes the script hang when dumping HuBERT features. Change it to for-loop resolves the issue.

Pull Request resolved: https://github.com/pytorch/audio/pull/2311

Reviewed By: mthrok

Differential Revision: D35393813

Pulled By: nateanl

fbshipit-source-id: afdc14557a1102b20ecd5fafba0964a913250a11

examples/hubert/preprocess.py

@@ -8,7 +8,6 @@ The script includes:
 """
 import logging
 from argparse import ArgumentParser, RawTextHelpFormatter
-from multiprocessing import Pool
 from pathlib import Path
 
 import torch
@@ -99,9 +98,8 @@ def main(args):
         feat_dir.mkdir()
 
     for split in ["train", "valid"]:
-        p = Pool(args.num_rank)
-        inputs = [
-            (
+        for rank in range(1, args.num_rank + 1):
+            dump_features(
                 tsv_dir / f"{args.dataset}_{split}.tsv",
                 feat_dir,
                 split,
@@ -113,11 +111,6 @@ def main(args):
                 args.checkpoint_path,
                 16_000,
             )
-            for rank in range(1, args.num_rank + 1)
-        ]
-        _ = p.starmap(dump_features, inputs)
-        p.close()
-        p.join()
 
     # Fit KMeans clustering model
     learn_kmeans(