format

README.md

@@ -52,4 +52,4 @@ DeepSpeech is provided under the [Apache-2.0 License](./LICENSE).
 
 ## Acknowledgement
 
-We depends on many open source repos. See [References](doc/src/reference.md) for more information.
+We depends on many open source repos. See [References](doc/src/reference.md) for more information.

README_cn.md

@@ -50,4 +50,4 @@ DeepSpeech遵循[Apache-2.0开源协议](./LICENSE)。
 
 ## 感谢
 
-开发中参考一些优秀的仓库，详情参见 [References](doc/src/reference.md)。
+开发中参考一些优秀的仓库，详情参见 [References](doc/src/reference.md)。

examples/ngram_lm/local/kenlm_score_test.py

@@ -1,9 +1,22 @@
-import kenlm
-import jieba
-import time
-
+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 import os
 import sys
+import time
+
+import jieba
+import kenlm
 
 language_model_path = sys.argv[1]
 assert os.path.exists(language_model_path)
@@ -33,7 +46,8 @@ def test_score():
     for i, v in enumerate(model.full_scores(sentence_char_split)):
         print(i, v)
         split_size += 1
-    assert split_size == len(sentence_char_split.split()) + 1, "error split size."
+    assert split_size == len(
+        sentence_char_split.split()) + 1, "error split size."
 
     print(sentence_word_split)
     print(model.score(sentence_word_split))
@@ -47,8 +61,10 @@ def test_full_scores_chars():
     print(sentence_char_split)
     # Show scores and n-gram matches
     words = ['<s>'] + list(sentence) + ['</s>']
-    for i, (prob, length, oov) in enumerate(model.full_scores(sentence_char_split)):
-        print('{0} {1}: {2}'.format(prob, length, ' '.join(words[i + 2 - length:i + 2])))
+    for i, (prob, length,
+            oov) in enumerate(model.full_scores(sentence_char_split)):
+        print('{0} {1}: {2}'.format(prob, length, ' '.join(words[i + 2 - length:
+                                                                 i + 2])))
         if oov:
             print('\t"{0}" is an OOV'.format(words[i + 1]))
 
@@ -67,8 +83,10 @@ def test_full_scores_words():
     print(sentence_word_split)
     # Show scores and n-gram matches
     words = ['<s>'] + sentence_word_split.split() + ['</s>']
-    for i, (prob, length, oov) in enumerate(model.full_scores(sentence_word_split)):
-        print('{0} {1}: {2}'.format(prob, length, ' '.join(words[i + 2 - length:i + 2])))
+    for i, (prob, length,
+            oov) in enumerate(model.full_scores(sentence_word_split)):
+        print('{0} {1}: {2}'.format(prob, length, ' '.join(words[i + 2 - length:
+                                                                 i + 2])))
         if oov:
             print('\t"{0}" is an OOV'.format(words[i + 1]))
 
@@ -80,7 +98,8 @@ def test_full_scores_words():
             print('"{0}" is an OOV'.format(w))
             oov.append(w)
     # zh_giga.no_cna_cmn.prune01244.klm is chinese charactor LM 
-    assert oov == ["盘点", "不怕", "网站", "❗", "️", "海淘", "向来", "便宜", "保真", "！"], 'error oov'
+    assert oov == ["盘点", "不怕", "网站", "❗", "️", "海淘", "向来", "便宜", "保真", "！"
+                   ], 'error oov'
 
 
 def test_full_scores_chars_length():
@@ -159,9 +178,10 @@ def test_ppl_sentence():
     n2 = model.perplexity(part_char_split2)
     print(n2)
 
+
 if __name__ == '__main__':
     test_score()
     test_full_scores_chars()
     test_full_scores_words()
     test_full_scores_chars_length()
-    test_ppl_sentence()
+    test_ppl_sentence()

examples/ngram_lm/local/zh_preprocess.py

@@ -1,31 +1,36 @@
 #!/usr/bin/env python3
-
-from typing import List, Text
+import re
+import string
 import sys
+from typing import List
+from typing import Text
+
 import jieba
-import string
-import re
 from zhon import hanzi
 
+
 def char_token(s: Text) -> List[Text]:
     return list(s)
 
+
 def word_token(s: Text) -> List[Text]:
     return jieba.lcut(s)
 
+
 def tn(s: Text) -> Text:
     s = s.strip()
     s = s.replace('*', '')
     # rm english punctuations
-    s = re.sub(f'[re.escape(string.punctuation)]' , "", s)
+    s = re.sub(f'[re.escape(string.punctuation)]', "", s)
     # rm chinese punctuations
     s = re.sub(f'[{hanzi.punctuation}]', "", s)
     # text normalization
-    
+
     # rm english
     s = ''.join(re.findall(hanzi.sent, s))
     return s
 
+
 def main(infile, outfile, tokenizer=None):
     with open(infile, 'rt') as fin, open(outfile, 'wt') as fout:
         lines = fin.readlines()
@@ -36,6 +41,7 @@ def main(infile, outfile, tokenizer=None):
             fout.write(l)
             fout.write('\n')
 
+
 if __name__ == '__main__':
     if len(sys.argv) != 4:
         print(f"sys.arv[0] [char|word] text text_out ")
@@ -52,4 +58,4 @@ if __name__ == '__main__':
     else:
         tokenizer = None
 
-    main(text, text_out, tokenizer)
+    main(text, text_out, tokenizer)