code: 
  
  
  
  
  
  '''simple docstring'''
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowercase_			       =				logging.get_logger(__name__)
  
  lowercase_			       =				{
      """tau/splinter-base""": """https://huggingface.co/tau/splinter-base/resolve/main/config.json""",
      """tau/splinter-base-qass""": """https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json""",
      """tau/splinter-large""": """https://huggingface.co/tau/splinter-large/resolve/main/config.json""",
      """tau/splinter-large-qass""": """https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json""",
      # See all Splinter models at https://huggingface.co/models?filter=splinter
  }
  
  
  class       a_  (       snake_case_ ):
  
      '''simple docstring'''
      UpperCamelCase									=				'''splinter'''
  
  
      def __init__(	self				,	A=3_0522				,	A=768				,	A=12				,	A=12				,	A=3072				,	A="gelu"				,	A=0.1				,	A=0.1				,	A=512				,	A=2				,	A=0.02				,	A=1e-12				,	A=True				,	A=0				,	A=104				,	**A				,	)	->     Dict:
          super().__init__(pad_token_id=A				,	**A )
  
          _SCREAMING_SNAKE_CASE             =    vocab_size
          _SCREAMING_SNAKE_CASE             =    max_position_embeddings
          _SCREAMING_SNAKE_CASE             =    hidden_size
          _SCREAMING_SNAKE_CASE             =    num_hidden_layers
          _SCREAMING_SNAKE_CASE             =    num_attention_heads
          _SCREAMING_SNAKE_CASE             =    intermediate_size
          _SCREAMING_SNAKE_CASE             =    hidden_act
          _SCREAMING_SNAKE_CASE             =    hidden_dropout_prob
          _SCREAMING_SNAKE_CASE             =    attention_probs_dropout_prob
          _SCREAMING_SNAKE_CASE             =    initializer_range
          _SCREAMING_SNAKE_CASE             =    type_vocab_size
          _SCREAMING_SNAKE_CASE             =    layer_norm_eps
          _SCREAMING_SNAKE_CASE             =    use_cache
          _SCREAMING_SNAKE_CASE             =    question_token_id
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  def lowerCamelCase		(  __lowerCamelCase				:					str					)		->str:
      _SCREAMING_SNAKE_CASE             =    word.upper()
      _SCREAMING_SNAKE_CASE             =    0
      _SCREAMING_SNAKE_CASE             =    {}
      _SCREAMING_SNAKE_CASE             =    []
  
      for letter in word:
          if letter not in letter_nums:
              _SCREAMING_SNAKE_CASE             =    str(__lowerCamelCase					)
              next_num += 1
          word_pattern.append(letter_nums[letter]					)
      return ".".join(__lowerCamelCase					)
  
  
  if __name__ == "__main__":
        import pprint
        import time
  
        lowercase_			       =				time.time()
        with open("""dictionary.txt""") as in_file:
              lowercase_			       =				in_file.read().splitlines()
  
        lowercase_			       =				{}
        for word in word_list:
              lowercase_			       =				get_word_pattern(word)
              if pattern in all_patterns:
                    all_patterns[pattern].append(word)
              else:
                    lowercase_			       =				[word]
  
        with open("""word_patterns.txt""", """w""") as out_file:
              out_file.write(pprint.pformat(all_patterns))
  
        lowercase_			       =				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.
  
  
  
  