


'''simple docstring'''


import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class 	__lowerCAmelCase		(							__SCREAMING_SNAKE_CASE  , unittest.TestCase    ):


  '''simple docstring'''







  a_  					=							BioGptTokenizer
  a_  					=							False






  def        _a							(							self :       Tuple ):

        '''simple docstring'''




        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        A_						:  int          =				[
            """l""",
            """o""",
            """w""",
            """e""",
            """r""",
            """s""",
            """t""",
            """i""",
            """d""",
            """n""",
            """w</w>""",
            """r</w>""",
            """t</w>""",
            """lo""",
            """low""",
            """er</w>""",
            """low</w>""",
            """lowest</w>""",
            """newer</w>""",
            """wider</w>""",
            """<unk>""",
        ]
        A_						:  Any          =				dict(zip(_a	,range(len(_a ) ) ) )
        A_						:  List[Any]          =				["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

        A_						:  Dict          =				os.path.join(self.tmpdirname	,VOCAB_FILES_NAMES["""vocab_file"""] )
        A_						:  Dict          =				os.path.join(self.tmpdirname	,VOCAB_FILES_NAMES["""merges_file"""] )
        with open(self.vocab_file	,"""w""" ) as fp:
              fp.write(json.dumps(_a ) )
        with open(self.merges_file	,"""w""" ) as fp:
              fp.write("""\n""".join(_a ) )






  def        _a							(							self :       Optional[int]	,_a :       Union[str, Any] ):

        '''simple docstring'''




        A_						:  int          =				"""lower newer"""
        A_						:  Any          =				"""lower newer"""
        return input_text, output_text






  def        _a							(							self :       int ):

        '''simple docstring'''




        A_						:  Optional[Any]          =				BioGptTokenizer(self.vocab_file	,self.merges_file )

        A_						:  Optional[Any]          =				"""lower"""
        A_						:  Union[str, Any]          =				["""low""", """er</w>"""]
        A_						:  Union[str, Any]          =				tokenizer.tokenize(_a )
        self.assertListEqual(_a	,_a )

        A_						:  List[str]          =				tokens + ["""<unk>"""]
        A_						:  Optional[int]          =				[14, 15, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(_a )	,_a )






  @slow
  def        _a							(							self :       Dict ):

        '''simple docstring'''




        A_						:  List[str]          =				BioGptTokenizer.from_pretrained("""microsoft/biogpt""" )

        A_						:  List[str]          =				tokenizer.encode("""sequence builders"""	,add_special_tokens=_a )
        A_						:  Tuple          =				tokenizer.encode("""multi-sequence build"""	,add_special_tokens=_a )

        A_						:  str          =				tokenizer.build_inputs_with_special_tokens(_a )
        A_						:  Tuple          =				tokenizer.build_inputs_with_special_tokens(_a	,_a )

        self.assertTrue(encoded_sentence == [2] + text )
        self.assertTrue(encoded_pair == [2] + text + [2] + text_a )




'''simple docstring'''


import baseaa




def      lowerCamelCase					(      lowerCamelCase  :      str):
      return baseaa.aaaencode(string.encode("""utf-8"""))




def      lowerCamelCase					(      lowerCamelCase  :      bytes):
      return baseaa.aaadecode(lowerCamelCase).decode("""utf-8""")


if __name__ == "__main__":
     import doctest

     doctest.testmod()
