
'''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  __A				( __A    ,						unittest.TestCase			):
 lowerCamelCase				       =BioGptTokenizer
 lowerCamelCase				       =False
 def 		lowercase_(   self			:    Optional[int]       ):



   """simple docstring"""





   super().setUp()

   # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
   __A		:     Tuple												=		[
       '''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		:     List[Any]												=		dict(zip(lowerCamelCase				,   range(len(lowerCamelCase       )       )       )       )
   __A		:     int												=		['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

   __A		:     Union[str, Any]												=		os.path.join(self.tmpdirname				,   VOCAB_FILES_NAMES["""vocab_file"""]       )
   __A		:     Tuple												=		os.path.join(self.tmpdirname				,   VOCAB_FILES_NAMES["""merges_file"""]       )
   with open(self.vocab_file				,   """w"""       ) as fp:
     fp.write(json.dumps(lowerCamelCase       )       )
   with open(self.merges_file				,   """w"""       ) as fp:
     fp.write("""\n""".join(lowerCamelCase       )       )
 def 		lowercase_(   self			:    str				,   lowerCamelCase			:    Tuple       ):



   """simple docstring"""





   __A		:     Dict												=		'''lower newer'''
   __A		:     Optional[int]												=		'''lower newer'''
   return input_text, output_text
 def 		lowercase_(   self			:    str       ):



   """simple docstring"""





   __A		:     Any												=		BioGptTokenizer(self.vocab_file				,   self.merges_file       )

   __A		:     str												=		'''lower'''
   __A		:     str												=		['''low''', '''er</w>''']
   __A		:     List[str]												=		tokenizer.tokenize(lowerCamelCase       )
   self.assertListEqual(lowerCamelCase				,   lowerCamelCase       )

   __A		:     Optional[Any]												=		tokens + ['''<unk>''']
   __A		:     Dict												=		[14, 15, 20]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase       )				,   lowerCamelCase       )






 @slow
 def 		lowercase_(   self			:    Tuple       ):



   """simple docstring"""





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

   __A		:     int												=		tokenizer.encode("""sequence builders"""				,   add_special_tokens=lowerCamelCase       )
   __A		:     List[Any]												=		tokenizer.encode("""multi-sequence build"""				,   add_special_tokens=lowerCamelCase       )

   __A		:     str												=		tokenizer.build_inputs_with_special_tokens(lowerCamelCase       )
   __A		:     List[str]												=		tokenizer.build_inputs_with_special_tokens(lowerCamelCase				,   lowerCamelCase       )

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





'''simple docstring'''
from __future__ import annotations







def        A_     (						__SCREAMING_SNAKE_CASE						:  list[int] )				->       int:





  """simple docstring"""

  if not nums:
    return 0
  __A		:     List[Any]												=		nums[0]
  __A		:     Union[str, Any]												=		0
  for num in nums[1:]:
    __A							,					__A		:     Union[str, Any]												=		(
        max_excluding + num,
        max(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE ),
    )
  return max(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
     import doctest

     doctest.testmod()



