fix style

egs/audioset/AT/local/generate_audioset_manifest.py

@@ -1,72 +1,70 @@
 import argparse
 import csv
+import glob
+import logging
 
 import torch
-import torchaudio
-import logging
-import glob
-from lhotse import load_manifest, CutSet, Fbank, FbankConfig, LilcomChunkyWriter
-from lhotse.cut import MonoCut
+from lhotse import CutSet, Fbank, FbankConfig, LilcomChunkyWriter
 from lhotse.audio import Recording
+from lhotse.cut import MonoCut
 from lhotse.supervision import SupervisionSegment
-from argparse import ArgumentParser
 
-from icefall.utils import get_executor, str2bool
+from icefall.utils import get_executor
 
 torch.set_num_threads(1)
 torch.set_num_interop_threads(1)
 
+
 def parse_csv(csv_file="downloads/audioset/full_train_asedata_with_duration.csv"):
 
     mapping = {}
-    with open(csv_file, 'r') as fin:
+    with open(csv_file, "r") as fin:
         reader = csv.reader(fin, delimiter="\t")
         for i, row in enumerate(reader):
             if i == 0:
                 continue
-            key = "/".join(row[0].split('/')[-2:])
+            key = "/".join(row[0].split("/")[-2:])
             mapping[key] = row[1]
     return mapping
-            
+
 
 def get_parser():
     parser = argparse.ArgumentParser(
         formatter_class=argparse.ArgumentDefaultsHelpFormatter
     )
-    
-    parser.add_argument(
-        "--dataset-dir",
-        type=str,
-        default="downloads/audioset"
-    )
-    
+
+    parser.add_argument("--dataset-dir", type=str, default="downloads/audioset")
+
     parser.add_argument(
         "--split",
         type=str,
         default="balanced",
-        choices=["balanced", "unbalanced", "eval", "eval_all"]
+        choices=["balanced", "unbalanced", "eval", "eval_all"],
     )
-    
+
     parser.add_argument(
         "--feat-output-dir",
         type=str,
         default="data/fbank_audioset",
     )
-    
+
     return parser
 
+
 def main():
     parser = get_parser()
     args = parser.parse_args()
-    
+
     dataset_dir = args.dataset_dir
     split = args.split
     feat_output_dir = args.feat_output_dir
-    
+
     num_jobs = 15
     num_mel_bins = 80
 
-    import pdb; pdb.set_trace()
+    import pdb
+
+    pdb.set_trace()
     if split in ["balanced", "unbalanced"]:
         csv_file = "downloads/audioset/full_train_asedata_with_duration.csv"
     elif split == "eval":
@@ -79,10 +77,10 @@ def main():
     labels = parse_csv(csv_file)
 
     audio_files = glob.glob(f"{dataset_dir}/eval/wav_all/*.wav")
-    
+
     new_cuts = []
     for i, audio in enumerate(audio_files):
-        cut_id = "/".join(audio.split('/')[-2:])
+        cut_id = "/".join(audio.split("/")[-2:])
         recording = Recording.from_file(audio, cut_id)
         cut = MonoCut(
             id=cut_id,
@@ -105,7 +103,7 @@ def main():
             supervision.audio_event = ""
         cut.supervisions = [supervision]
         new_cuts.append(cut)
-        
+
         if i % 100 == 0 and i:
             logging.info(f"Processed {i} cuts until now.")
 
@@ -122,14 +120,15 @@ def main():
             executor=ex,
             storage_type=LilcomChunkyWriter,
         )
-    
+
     manifest_output_dir = feat_output_dir + "/" + f"cuts_audioset_{split}.jsonl.gz"
 
     logging.info(f"Storing the manifest to {manifest_output_dir}")
     cuts.to_jsonl(manifest_output_dir)
 
-if __name__=="__main__":
+
+if __name__ == "__main__":
     formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
 
     logging.basicConfig(format=formatter, level=logging.INFO)
-    main()
+    main()