refine the code

deepspeech/utils/bleu_score.py

@@ -35,6 +35,7 @@ def bleu(hypothesis, reference):
 
     return sacrebleu.corpus_bleu(hypothesis, reference)
 
+
 def char_bleu(hypothesis, reference):
     """Calculate BLEU. BLEU compares reference text and
     hypothesis text in char-level using scarebleu.
@@ -48,6 +49,7 @@ def char_bleu(hypothesis, reference):
     :raises ValueError: If the reference number is zero.
     """
     hypothesis = [' '.join(list(hyp.replace(' ', ''))) for hyp in hypothesis]
-    reference = [[' '.join(list(ref_i.replace(' ', ''))) for ref_i in ref ]for ref in reference ]
+    reference = [[' '.join(list(ref_i.replace(' ', ''))) for ref_i in ref]
+                 for ref in reference]
 
     return sacrebleu.corpus_bleu(hypothesis, reference)

examples/dataset/ted_en_zh/ted_en_zh.py

@@ -44,9 +44,11 @@ def create_manifest(data_dir, manifest_path_prefix):
     print("Creating manifest %s ..." % manifest_path_prefix)
     json_lines = []
 
-    data_types_infos = [('train', 'train-split/train-segment', 'En-Zh/train.en-zh'), 
+    data_types_infos = [
+        ('train', 'train-split/train-segment', 'En-Zh/train.en-zh'),
         ('dev', 'test-segment/tst2010', 'En-Zh/tst2010.en-zh'),
-                ('test', 'test-segment/tst2015', 'En-Zh/tst2015.en-zh')]
+        ('test', 'test-segment/tst2015', 'En-Zh/tst2015.en-zh')
+    ]
     for data_info in data_types_infos:
         dtype, audio_relative_dir, text_relative_path = data_info
         del json_lines[:]