






import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin




class 							_lowerCAmelCase(			UpperCAmelCase_				,      unittest.TestCase   ):





       """simple docstring"""







       a							:						Optional[int]										=XLMTokenizer
       a							:						int										=False





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

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

         UpperCamelCase_:   int        =							os.path.join(self.tmpdirname    ,     VOCAB_FILES_NAMES['vocab_file']				)
         UpperCamelCase_:   Union[str, Any]        =							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      _a       (   self    ,     _lowerCamelCase				):
         UpperCamelCase_:   Optional[Any]        =							'lower newer'
         UpperCamelCase_:   str        =							'lower newer'
         return input_text, output_text





       def      _a       (   self				):
         UpperCamelCase_:   str        =							XLMTokenizer(self.vocab_file    ,     self.merges_file				)

         UpperCamelCase_:   List[Any]        =							'lower'
         UpperCamelCase_:   Any        =							['low', 'er</w>']
         UpperCamelCase_:   Optional[int]        =							tokenizer.tokenize(_lowerCamelCase				)
         self.assertListEqual(_lowerCamelCase    ,     _lowerCamelCase				)

         UpperCamelCase_:   int        =							tokens + ['<unk>']
         UpperCamelCase_:   Tuple        =							[1_4, 1_5, 2_0]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase				)    ,     _lowerCamelCase				)





       @slow
       def      _a       (   self				):
         UpperCamelCase_:   Union[str, Any]        =							XLMTokenizer.from_pretrained('xlm-mlm-en-2048'				)

         UpperCamelCase_:   Optional[int]        =							tokenizer.encode('sequence builders'    ,     add_special_tokens=_lowerCamelCase				)
         UpperCamelCase_:   List[str]        =							tokenizer.encode('multi-sequence build'    ,     add_special_tokens=_lowerCamelCase				)

         UpperCamelCase_:   Optional[Any]        =							tokenizer.build_inputs_with_special_tokens(_lowerCamelCase				)
         UpperCamelCase_:   Dict        =							tokenizer.build_inputs_with_special_tokens(_lowerCamelCase    ,     _lowerCamelCase				)

         assert encoded_sentence == [0] + text + [1]
         assert encoded_pair == [0] + text + [1] + text_a + [1]







"""simple docstring"""



import os


def 	SCREAMING_SNAKE_CASE__       (  )->		Optional[Any]:






     '''simple docstring'''



     with open(os.path.dirname(snake_case				) + "/p022_names.txt"				) as file:
          UpperCAmelCase__						:    Tuple							=							str(file.readlines()[0]				)
          UpperCAmelCase__						:    str							=							names.replace("\""			,					""				).split(","				)

     names.sort()

     UpperCAmelCase__						:    Optional[int]							=							0
     UpperCAmelCase__						:    List[str]							=							0

     for i, name in enumerate(snake_case				):
          for letter in name:
               name_score += ord(snake_case				) - 64

          total_score += (i + 1) * name_score
          UpperCAmelCase__						:    Optional[int]							=							0
     return total_score


if __name__ == "__main__":
 print(solution())


