




def 					SCREAMING_SNAKE_CASE							(   __UpperCamelCase)			->     str:
     a      =      word.upper()
     a      =      0
     a      =      {}
     a      =      []

     for letter in word:
          if letter not in letter_nums:
               a      =      str(__UpperCamelCase)
               next_num += 1
          word_pattern.append(letter_nums[letter])
     return ".".join(__UpperCamelCase)


if __name__ == "__main__":
   import pprint
   import time

   lowercase__      :			str           =					time.time()
   with open("dictionary.txt") as in_file:
      lowercase__      :			Optional[int]           =					in_file.read().splitlines()

   lowercase__      :			dict           =					{}
   for word in word_list:
      lowercase__      :			Any           =					get_word_pattern(word)
      if pattern in all_patterns:
         all_patterns[pattern].append(word)
      else:
         lowercase__      :			Optional[int]           =					[word]

   with open("word_patterns.txt", "w") as out_file:
      out_file.write(pprint.pformat(all_patterns))

   lowercase__      :			Dict           =					round(time.time() - start_time, 2)
   print(F'Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.')
   # Done!  9,581 word patterns found in 0.58 seconds.







import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 			a__       (					UpperCamelCase__   ,					unittest.TestCase      ):
     a		:			Dict							=	MPNetTokenizer
     a		:			Dict							=	MPNetTokenizerFast
     a		:			Optional[int]							=	True
     a		:			Any							=	True







     def 			lowerCAmelCase_				(	self )  ->    Any:



          '''simple docstring'''



          super().setUp()

          a      =      [
              "[UNK]",
              "[CLS]",
              "[SEP]",
              "[PAD]",
              "[MASK]",
              "want",
              "##want",
              "##ed",
              "wa",
              "un",
              "runn",
              "##ing",
              ",",
              "low",
              "lowest",
          ]
          a      =      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 			lowerCAmelCase_				(	self  ,		A )  ->    Any:



          '''simple docstring'''



          a      =      "UNwant\u00E9d,running"
          a      =      "unwanted, running"
          return input_text, output_text







     def 			lowerCAmelCase_				(	self )  ->    List[Any]:



          '''simple docstring'''



          a      =      self.tokenizer_class(self.vocab_file )

          a      =      tokenizer.tokenize("UNwant\u00E9d,running" )
          self.assertListEqual(A  ,		["un", "##want", "##ed", ",", "runn", "##ing"] )
          self.assertListEqual(tokenizer.convert_tokens_to_ids(A )  ,		[9, 6, 7, 12, 10, 11] )







     @slow
     def 			lowerCAmelCase_				(	self )  ->    Dict:



          '''simple docstring'''



          a      =      self.tokenizer_class.from_pretrained("microsoft/mpnet-base" )

          a      =      tokenizer.encode("sequence builders"  ,		add_special_tokens=A )
          a      =      tokenizer.encode("multi-sequence build"  ,		add_special_tokens=A )

          a      =      tokenizer.build_inputs_with_special_tokens(A )
          a      =      tokenizer.build_inputs_with_special_tokens(A  ,		A )

          assert encoded_sentence == [0] + text + [2]
          assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]

