Fix CI failure due to linter warnings

This resolves coding-style warnings emitted by linters:

 * Quote the `test_sets` variable to resolve a shellcheck worning.
 * Apply isort and black to reformat `local/data.py`.

Signed-off-by: Fujimoto Seiji <fujimoto@ceptord.net>

egs2/reazonspeech/asr1/local/data.py

@@ -1,14 +1,17 @@
 import os
 import sys
+
 from datasets import load_dataset
 from reazonspeech.text import normalize
 
+
 def save_kaldi_format(outdir, ds):
     os.makedirs(outdir, exist_ok=True)
-    with open(os.path.join(outdir, 'text'), 'w') as fp_text, \
-         open(os.path.join(outdir, 'wav.scp'), 'w') as fp_wav, \
-         open(os.path.join(outdir, 'utt2spk'), 'w') as fp_utt2spk, \
-         open(os.path.join(outdir, 'spk2utt'), 'w') as fp_spk2utt:
+    with open(os.path.join(outdir, "text"), "w") as fp_text, open(
+        os.path.join(outdir, "wav.scp"), "w"
+    ) as fp_wav, open(os.path.join(outdir, "utt2spk"), "w") as fp_utt2spk, open(
+        os.path.join(outdir, "spk2utt"), "w"
+    ) as fp_spk2utt:
 
         for item in ds.sort("name"):
             path = item["audio"]["path"]
@@ -17,23 +20,27 @@ def save_kaldi_format(outdir, ds):
             text = normalize(item["transcription"])
 
             # '000/e7fb3323c280c.flac' -> '000e7fb3323c280c'
-            name = os.path.splitext(item["name"].replace('/', ''))[0]
-            uttid = 'uttid%s' % name
-            spkid = 'spkid%s' % name
+            name = os.path.splitext(item["name"].replace("/", ""))[0]
+            uttid = "uttid%s" % name
+            spkid = "spkid%s" % name
             print(uttid, text, file=fp_text)
             print(uttid, path, file=fp_wav)
             print(uttid, spkid, file=fp_utt2spk)
             print(spkid, uttid, file=fp_spk2utt)
 
+
 def main():
     if len(sys.argv) != 2:
         print("Usage: %s <download_dir>" % sys.argv[0], file=sys.stderr)
         return 1
     download_dir = sys.argv[1]
-    ds = load_dataset("reazon-research/reazonspeech", "all", cache_dir=download_dir)["train"]
-    save_kaldi_format('data/dev', ds.select(range(1000)))
-    save_kaldi_format('data/test', ds.select(range(1000, 2000)))
-    save_kaldi_format('data/train', ds.select(range(2000, ds.num_rows)))
+    ds = load_dataset("reazon-research/reazonspeech", "all", cache_dir=download_dir)[
+        "train"
+    ]
+    save_kaldi_format("data/dev", ds.select(range(1000)))
+    save_kaldi_format("data/test", ds.select(range(1000, 2000)))
+    save_kaldi_format("data/train", ds.select(range(2000, ds.num_rows)))
+
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()

egs2/reazonspeech/asr1/run.sh

@@ -7,7 +7,7 @@ set -o pipefail
 
 train_set=train
 valid_set=dev
-test_sets=test
+test_sets="test"
 
 asr_config=conf/train_asr_conformer.yaml
 inference_config=conf/decode_asr.yaml