
'''simple docstring'''

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        SCREAMING_SNAKE_CASE_  (	snake_case_				:	str=10							)       ->	Optional[Any]:



 for _ in tqdm(range(0   ,     args.n_examples   ,     snake_case_							)							):
  yield [next(snake_case_							)[args.text_column] for _ in range(snake_case_							)]


# Configuration
__UpperCAmelCase												=   HfArgumentParser(TokenizerTrainingArguments)
__UpperCAmelCase												=   parser.parse_args()

# Base tokenizer
__UpperCAmelCase												=   AutoTokenizer.from_pretrained(args.base_tokenizer)
__UpperCAmelCase												=   list(bytes_to_unicode().values())

# Load dataset
__UpperCAmelCase												=   load_dataset(args.dataset_name, split='train', streaming=True)
__UpperCAmelCase												=   iter(dataset)


# Training and saving
__UpperCAmelCase												=   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)






from hashlib import mda, shaaaa

__UpperCamelCase							:							Dict    							=					(shaaaa, mda)

class    __magic_name__						:


     def __init__(   self				:  Optional[Any]				,						lowerCamelCase__				:  int = 8      )	->   None:





      '''simple docstring'''






      UpperCamelCase__       :     int 							= 0b0
      UpperCamelCase__       :     Optional[int] 							= size


     def   UpperCAmelCase__						(   self				:  Tuple				,						lowerCamelCase__				:  str      )	->   None:





      '''simple docstring'''






      UpperCamelCase__       :     Union[str, Any] 							= self.hash_(lowerCamelCase__      )
      self.bitarray |= h


     def   UpperCAmelCase__						(   self				:  Any				,						lowerCamelCase__				:  str      )	->   bool:





      '''simple docstring'''






      UpperCamelCase__       :     Any 							= self.hash_(lowerCamelCase__      )
      return (h & self.bitarray) == h


     def __contains__(   self				:  Any				,						lowerCamelCase__				:  str      )	->   bool:





      '''simple docstring'''






      return self.exists(lowerCamelCase__      )


     def   UpperCAmelCase__						(   self				:  Union[str, Any]				,						lowerCamelCase__				:  int      )	->   str:





      '''simple docstring'''






      UpperCamelCase__       :     Optional[int] 							= bin(lowerCamelCase__      )[2:]
      return res.zfill(self.size      )


     @property
     def   UpperCAmelCase__						(   self				:  Tuple      )	->   str:





      '''simple docstring'''






      return self.format_bin(self.bitarray      )


     def   UpperCAmelCase__						(   self				:  int				,						lowerCamelCase__				:  str      )	->   int:





      '''simple docstring'''






      UpperCamelCase__       :     Union[str, Any] 							= 0b0
      for func in HASH_FUNCTIONS:
       UpperCamelCase__       :     Optional[Any] 							= (
           int.from_bytes(func(value.encode()      ).digest()				,						'''little'''      ) % self.size
       )
       res |= 2**position
      return res


     def   UpperCAmelCase__						(   self				:  Union[str, Any]				,						lowerCamelCase__				:  str      )	->   str:





      '''simple docstring'''






      return self.format_bin(self.hash_(lowerCamelCase__      )      )


     @property
     def   UpperCAmelCase__						(   self				:  str      )	->   float:





      '''simple docstring'''






      UpperCamelCase__       :     Tuple 							= bin(self.bitarray      ).count('''1'''      )
      return (n_ones / self.size) ** len(lowerCamelCase__      )


