code: 
  
  
  from arguments import TokenizerTrainingArguments
  from datasets import load_dataset
  from tqdm import tqdm
  
  from transformers import AutoTokenizer, HfArgumentParser
  from transformers.models.gpta.tokenization_gpta import bytes_to_unicode
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase=10     )    ->Optional[int]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        for _ in tqdm(range(0,    args.n_examples,    _UpperCamelCase     )     ):
              yield [next(_UpperCamelCase     )[args.text_column] for _ in range(_UpperCamelCase     )]
  
  
  # Configuration
  __a   				=      HfArgumentParser(TokenizerTrainingArguments)
  __a   				=      parser.parse_args()
  
  # Base tokenizer
  __a   				=      AutoTokenizer.from_pretrained(args.base_tokenizer)
  __a   				=      list(bytes_to_unicode().values())
  
  # Load dataset
  __a   				=      load_dataset(args.dataset_name, split='''train''', streaming=True)
  __a   				=      iter(dataset)
  
  
  # Training and saving
  __a   				=      tokenizer.train_new_from_iterator(
      batch_iterator(), vocab_size=args.vocab_size, initial_alphabet=base_vocab
  )
  
  
  
  new_tokenizer.save_pretrained(args.tokenizer_name, push_to_hub=args.push_to_hub)
  
  
style_context: 
  
  
  import math
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase     )    ->Union[str, Any]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   List[Any]					   =		0
        if n % 2 == 0:
              count += 1
              while n % 2 == 0:
                    lowercase			:   Any					   =		int(n / 2     )
      # the n input value must be odd so that
      # we can skip one element (ie i += 2)
  
        lowercase			:   Optional[int]					   =		3
  
        while i <= int(math.sqrt(_UpperCamelCase     )     ):
              if n % i == 0:
                    count += 1
                    while n % i == 0:
                          lowercase			:   Optional[Any]					   =		int(n / i     )
              lowercase			:   str					   =		i + 2
  
        # this condition checks the prime
        # number n is greater than 2
  
        if n > 2:
              count += 1
        return count
  
  
  if __name__ == "__main__":
    __a   				=      51_24_21_83
    print(F'''The number of distinct prime factors is/are {exact_prime_factor_count(n)}''')
    print(F'''The value of log(log(n)) is {math.log(math.log(n)):.4f}''')
  
  