fix some importing bugs

fastNLP/io/pipe/cws.py

@@ -1,10 +1,13 @@
+import re
+from itertools import chain
+
 from .pipe import Pipe
+from .utils import _indexize
 from .. import DataBundle
 from ..loader import CWSLoader
-from ... import Const
-from itertools import chain
-from .utils import _indexize
-import re
+from ...core.const import Const
+
+
 def _word_lens_to_bmes(word_lens):
     """
 
@@ -13,11 +16,11 @@ def _word_lens_to_bmes(word_lens):
     """
     tags = []
     for word_len in word_lens:
-        if word_len==1:
+        if word_len == 1:
             tags.append('S')
         else:
             tags.append('B')
-            tags.extend(['M']*(word_len-2))
+            tags.extend(['M'] * (word_len - 2))
             tags.append('E')
     return tags
 
@@ -30,10 +33,10 @@ def _word_lens_to_segapp(word_lens):
     """
     tags = []
     for word_len in word_lens:
-        if word_len==1:
+        if word_len == 1:
             tags.append('SEG')
         else:
-            tags.extend(['APP']*(word_len-1))
+            tags.extend(['APP'] * (word_len - 1))
             tags.append('SEG')
     return tags
 
@@ -97,13 +100,21 @@ def _digit_span_to_special_tag(span):
     else:
         return '<NUM>'
 
+
 def _find_and_replace_digit_spans(line):
-    # only consider words start with number, contains '.', characters.
-    #	If ends with space, will be processed
-    #	If ends with Chinese character, will be processed
-    #	If ends with or contains english char, not handled.
-    # floats are replaced by <DEC>
-    # otherwise unkdgt
+    """
+    only consider words start with number, contains '.', characters.
+    
+        If ends with space, will be processed
+        
+        If ends with Chinese character, will be processed
+        
+        If ends with or contains english char, not handled.
+    
+    floats are replaced by <DEC>
+    
+    otherwise unkdgt
+    """
     new_line = ''
     pattern = '\d[\d\\.﹒·]*(?=[\u4e00-\u9fff  ，％,。！<－“])'
     prev_end = 0
@@ -136,17 +147,18 @@ class CWSPipe(Pipe):
     :param bool bigrams: 是否增加一列bigram. bigram的构成是['复', '旦', '大', '学', ...]->["复旦", "旦大", ...]
     :param bool trigrams: 是否增加一列trigram. trigram的构成是 ['复', '旦', '大', '学', ...]->["复旦大", "旦大学", ...]
     """
+    
     def __init__(self, dataset_name=None, encoding_type='bmes', replace_num_alpha=True, bigrams=False, trigrams=False):
-        if encoding_type=='bmes':
+        if encoding_type == 'bmes':
             self.word_lens_to_tags = _word_lens_to_bmes
         else:
             self.word_lens_to_tags = _word_lens_to_segapp
-
+        
         self.dataset_name = dataset_name
         self.bigrams = bigrams
         self.trigrams = trigrams
         self.replace_num_alpha = replace_num_alpha
-
+    
     def _tokenize(self, data_bundle):
         """
         将data_bundle中的'chars'列切分成一个一个的word.
@@ -162,10 +174,10 @@ class CWSPipe(Pipe):
                 char = []
                 subchar = []
                 for c in word:
-                    if c=='<':
+                    if c == '<':
                         subchar.append(c)
                         continue
-                    if c=='>' and subchar[0]=='<':
+                    if c == '>' and subchar[0] == '<':
                         char.append(''.join(subchar))
                         subchar = []
                     if subchar:
@@ -175,12 +187,12 @@ class CWSPipe(Pipe):
                 char.extend(subchar)
                 chars.append(char)
             return chars
-
+        
         for name, dataset in data_bundle.datasets.items():
             dataset.apply_field(split_word_into_chars, field_name=Const.CHAR_INPUT,
                                 new_field_name=Const.CHAR_INPUT)
         return data_bundle
-
+    
     def process(self, data_bundle: DataBundle) -> DataBundle:
         """
         可以处理的DataSet需要包含raw_words列
@@ -196,42 +208,43 @@ class CWSPipe(Pipe):
         :return:
         """
         data_bundle.copy_field(Const.RAW_WORD, Const.CHAR_INPUT)
-
+        
         if self.replace_num_alpha:
             data_bundle.apply_field(_find_and_replace_alpha_spans, Const.CHAR_INPUT, Const.CHAR_INPUT)
             data_bundle.apply_field(_find_and_replace_digit_spans, Const.CHAR_INPUT, Const.CHAR_INPUT)
-
+        
         self._tokenize(data_bundle)
-
+        
         for name, dataset in data_bundle.datasets.items():
-            dataset.apply_field(lambda chars:self.word_lens_to_tags(map(len, chars)), field_name=Const.CHAR_INPUT,
+            dataset.apply_field(lambda chars: self.word_lens_to_tags(map(len, chars)), field_name=Const.CHAR_INPUT,
                                 new_field_name=Const.TARGET)
-            dataset.apply_field(lambda chars:list(chain(*chars)), field_name=Const.CHAR_INPUT,
+            dataset.apply_field(lambda chars: list(chain(*chars)), field_name=Const.CHAR_INPUT,
                                 new_field_name=Const.CHAR_INPUT)
         input_field_names = [Const.CHAR_INPUT]
         if self.bigrams:
             for name, dataset in data_bundle.datasets.items():
-                dataset.apply_field(lambda chars: [c1+c2 for c1, c2 in zip(chars, chars[1:]+['<eos>'])],
+                dataset.apply_field(lambda chars: [c1 + c2 for c1, c2 in zip(chars, chars[1:] + ['<eos>'])],
                                     field_name=Const.CHAR_INPUT, new_field_name='bigrams')
             input_field_names.append('bigrams')
         if self.trigrams:
             for name, dataset in data_bundle.datasets.items():
-                dataset.apply_field(lambda chars: [c1+c2+c3 for c1, c2, c3 in zip(chars, chars[1:]+['<eos>'], chars[2:]+['<eos>']*2)],
+                dataset.apply_field(lambda chars: [c1 + c2 + c3 for c1, c2, c3 in
+                                                   zip(chars, chars[1:] + ['<eos>'], chars[2:] + ['<eos>'] * 2)],
                                     field_name=Const.CHAR_INPUT, new_field_name='trigrams')
             input_field_names.append('trigrams')
-
+        
         _indexize(data_bundle, input_field_names, Const.TARGET)
-
+        
         input_fields = [Const.TARGET, Const.INPUT_LEN] + input_field_names
         target_fields = [Const.TARGET, Const.INPUT_LEN]
         for name, dataset in data_bundle.datasets.items():
             dataset.add_seq_len(Const.CHAR_INPUT)
-
+        
         data_bundle.set_input(*input_fields)
         data_bundle.set_target(*target_fields)
-
+        
         return data_bundle
-
+    
     def process_from_file(self, paths=None) -> DataBundle:
         """
 
@@ -239,8 +252,9 @@ class CWSPipe(Pipe):
         :return:
         """
         if self.dataset_name is None and paths is None:
-            raise RuntimeError("You have to set `paths` when calling process_from_file() or `dataset_name `when initialization.")
+            raise RuntimeError(
+                "You have to set `paths` when calling process_from_file() or `dataset_name `when initialization.")
         if self.dataset_name is not None and paths is not None:
             raise RuntimeError("You cannot specify `paths` and `dataset_name` simultaneously")
         data_bundle = CWSLoader(self.dataset_name).load(paths)
-        return self.process(data_bundle)
+        return self.process(data_bundle)