"""simple docstring"""




import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class 						__A							( SCREAMING_SNAKE_CASE_    ,	unittest.TestCase		):
     _UpperCamelCase							:			str							=		TransfoXLTokenizer
     _UpperCamelCase							:			List[str]							=		False
     _UpperCamelCase							:			int							=		False






     def     __A  (		self  ):
       super().setUp()

       _lowerCAmelCase						:       int  			=     [
           """<unk>""",
           """[CLS]""",
           """[SEP]""",
           """want""",
           """unwanted""",
           """wa""",
           """un""",
           """running""",
           """,""",
           """low""",
           """l""",
       ]
       _lowerCAmelCase						:       Union[str, Any]  			=     os.path.join(self.tmpdirname				,     VOCAB_FILES_NAMES["""vocab_file"""]  )
       with open(self.vocab_file				,     """w"""				,     encoding="""utf-8"""  ) as vocab_writer:
         vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]  )  )






     def     __A  (		self				,     **a__  ):
       _lowerCAmelCase						:       Dict  			=     True
       return TransfoXLTokenizer.from_pretrained(self.tmpdirname				,     **a__  )






     def     __A  (		self				,     a__  ):
       _lowerCAmelCase						:       Dict  			=     """<unk> UNwanted , running"""
       _lowerCAmelCase						:       List[str]  			=     """<unk> unwanted, running"""
       return input_text, output_text






     def     __A  (		self  ):
       _lowerCAmelCase						:       List[str]  			=     TransfoXLTokenizer(vocab_file=self.vocab_file				,     lower_case=a__  )

       _lowerCAmelCase						:       Union[str, Any]  			=     tokenizer.tokenize("""<unk> UNwanted , running"""  )
       self.assertListEqual(a__				,     ["""<unk>""", """unwanted""", """,""", """running"""]  )

       self.assertListEqual(tokenizer.convert_tokens_to_ids(a__  )				,     [0, 4, 8, 7]  )






     def     __A  (		self  ):
       _lowerCAmelCase						:       Dict  			=     TransfoXLTokenizer(lower_case=a__  )

       self.assertListEqual(
           tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """  )				,     ["""hello""", """!""", """how""", """are""", """you""", """?"""]  )






     def     __A  (		self  ):
       _lowerCAmelCase						:       Any  			=     TransfoXLTokenizer(lower_case=a__  )

       self.assertListEqual(
           tokenizer.tokenize(""" \tHeLLo ! how  \n Are yoU ?  """  )				,     ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]  )






     def     __A  (		self  ):
       _lowerCAmelCase						:       Optional[int]  			=     TransfoXLTokenizer(lower_case=a__  )
       _lowerCAmelCase						:       Dict  			=     """Hello (bracket) and side-scrolled [and] Henry's $5,000 with 3.34 m. What's up!?"""
       _lowerCAmelCase						:       Tuple  			=     [
           """Hello""",
           """(""",
           """bracket""",
           """)""",
           """and""",
           """side""",
           """@-@""",
           """scrolled""",
           """[""",
           """and""",
           """]""",
           """Henry""",
           """'s""",
           """$""",
           """5""",
           """@,@""",
           """000""",
           """with""",
           """3""",
           """@.@""",
           """34""",
           """m""",
           """.""",
           """What""",
           """'s""",
           """up""",
           """!""",
           """?""",
       ]

       self.assertListEqual(tokenizer.tokenize(a__  )				,     a__  )

       self.assertEqual(tokenizer.convert_tokens_to_string(a__  )				,     a__  )






     def     __A  (		self  ):
       _lowerCAmelCase						:       str  			=     self.get_tokenizer()
       _lowerCAmelCase						:       Optional[int]  			=     len(a__  )

       tokenizer.add_tokens(["""new1""", """new2"""]  )
       tokenizer.move_added_token("""new1"""				,     1  )

       # Check that moved token is not copied (duplicate)
       self.assertEqual(len(a__  )				,     original_len + 2  )
       # Check that token is moved to specified id
       self.assertEqual(tokenizer.encode("""new1"""  )				,     [1]  )
       self.assertEqual(tokenizer.decode([1]  )				,     """new1"""  )








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_snake_case             =     {
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     ['''SqueezeBertTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     [
       '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''SqueezeBertForMaskedLM''',
       '''SqueezeBertForMultipleChoice''',
       '''SqueezeBertForQuestionAnswering''',
       '''SqueezeBertForSequenceClassification''',
       '''SqueezeBertForTokenClassification''',
       '''SqueezeBertModel''',
       '''SqueezeBertModule''',
       '''SqueezeBertPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_squeezebert import (
       SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       SqueezeBertConfig,
       SqueezeBertOnnxConfig,
   )
   from .tokenization_squeezebert import SqueezeBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_squeezebert import (
          SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          SqueezeBertForMaskedLM,
          SqueezeBertForMultipleChoice,
          SqueezeBertForQuestionAnswering,
          SqueezeBertForSequenceClassification,
          SqueezeBertForTokenClassification,
          SqueezeBertModel,
          SqueezeBertModule,
          SqueezeBertPreTrainedModel,
      )

else:
   import sys

   _snake_case             =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



