修改了CNXNLI的_load()，可以处理特殊的instance格式如下：

“XXX\t"XXX\tXXX

fastNLP/io/pipe/matching.py

@@ -352,8 +352,7 @@ class MNLIPipe(MatchingPipe):
 
 class LCQMCPipe(MatchingPipe):
     def __init__(self):
-        super().__init__()
-        self.tokenizer = 'cn-char'
+        super().__init__(tokenizer='cn-char')
 
     def process_from_file(self, paths=None):
         data_bundle = LCQMCLoader().load(paths)
@@ -365,8 +364,7 @@ class LCQMCPipe(MatchingPipe):
 
 class CNXNLIPipe(MatchingPipe):
     def __init__(self):
-        super().__init__()
-        self.tokenizer = 'cn-char'
+        super().__init__(tokenizer='cn-char')
 
     def process_from_file(self, paths=None):
         data_bundle = CNXNLILoader().load(paths)
@@ -379,8 +377,7 @@ class CNXNLIPipe(MatchingPipe):
 
 class BQCorpusPipe(MatchingPipe):
     def __init__(self):
-        super().__init__()
-        self.tokenizer = 'cn-char'
+        super().__init__(tokenizer='cn-char')
 
     def process_from_file(self, paths=None):
         data_bundle = BQCorpusLoader().load(paths)
@@ -475,8 +472,7 @@ class MachingTruncatePipe(Pipe):  # truncate sentence for bert, modify seq_len
 
 class LCQMCBertPipe(MatchingBertPipe):
     def __init__(self):
-        super().__init__()
-        self.tokenizer = 'cn-char'
+        super().__init__(tokenizer='cn-char')
 
     def process_from_file(self, paths=None):
         data_bundle = LCQMCLoader().load(paths)
@@ -489,8 +485,7 @@ class LCQMCBertPipe(MatchingBertPipe):
 
 class BQCorpusBertPipe(MatchingBertPipe):
     def __init__(self):
-        super().__init__()
-        self.tokenizer = 'cn-char'
+        super().__init__(tokenizer='cn-char')
 
     def process_from_file(self, paths=None):
         data_bundle = BQCorpusLoader().load(paths)
@@ -503,8 +498,7 @@ class BQCorpusBertPipe(MatchingBertPipe):
 
 class CNXNLIBertPipe(MatchingBertPipe):
     def __init__(self):
-        super().__init__()
-        self.tokenizer = 'cn-char'
+        super().__init__(tokenizer='cn-char')
 
     def process_from_file(self, paths=None):
         data_bundle = CNXNLILoader().load(paths)