


'''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       UpperCAmelCase__ (     UpperCAmelCase_   :    int=10							)					->		Union[str, Any]:
     for _ in tqdm(range(0				,   args.n_examples				,   UpperCAmelCase_							)							):
          yield [next(UpperCAmelCase_							)[args.text_column] for _ in range(UpperCAmelCase_							)]


# Configuration
A__		: List[str]												=  HfArgumentParser(TokenizerTrainingArguments)
A__		: Dict												=  parser.parse_args()

# Base tokenizer
A__		: Optional[int]												=  AutoTokenizer.from_pretrained(args.base_tokenizer)
A__		: Optional[int]												=  list(bytes_to_unicode().values())

# Load dataset
A__		: Dict												=  load_dataset(args.dataset_name, split="""train""", streaming=True)
A__		: Optional[int]												=  iter(dataset)


# Training and saving
A__		: str												=  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)










'''simple docstring'''



from typing import Literal

A__		: Tuple												=  """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""



def       UpperCAmelCase__ (     UpperCAmelCase_   :    str				,   UpperCAmelCase_   :    str				,   UpperCAmelCase_   :    Literal["encrypt", "decrypt"]							)					->		str:
     __lowerCamelCase       :     Dict        =		LETTERS if mode == 'decrypt' else key
     __lowerCamelCase       :     Tuple        =		key if mode == 'decrypt' else LETTERS
     __lowerCamelCase       :     Optional[int]        =		''
     # loop through each symbol in the message
     for symbol in message:
          if symbol.upper() in chars_a:
               # encrypt/decrypt the symbol
               __lowerCamelCase       :     Optional[int]        =		chars_a.find(symbol.upper()							)
               if symbol.isupper():
                    translated += chars_b[sym_index].upper()
               else:
                    translated += chars_b[sym_index].lower()
          else:
               # symbol is not in LETTERS, just add it
               translated += symbol
     return translated



def       UpperCAmelCase__ (     UpperCAmelCase_   :    str				,   UpperCAmelCase_   :    str							)					->		str:
     return translate_message(UpperCAmelCase_				,   UpperCAmelCase_				,   'encrypt'							)



def       UpperCAmelCase__ (     UpperCAmelCase_   :    str				,   UpperCAmelCase_   :    str							)					->		str:
     return translate_message(UpperCAmelCase_				,   UpperCAmelCase_				,   'decrypt'							)



def       UpperCAmelCase__ (     )					->		None:
     __lowerCamelCase       :     Dict        =		'Hello World'
     __lowerCamelCase       :     str        =		'QWERTYUIOPASDFGHJKLZXCVBNM'
     __lowerCamelCase       :     Any        =		'decrypt'  # set to 'encrypt' or 'decrypt'

     if mode == "encrypt":
          __lowerCamelCase       :     Optional[int]        =		encrypt_message(UpperCAmelCase_				,   UpperCAmelCase_							)
     elif mode == "decrypt":
          __lowerCamelCase       :     List[str]        =		decrypt_message(UpperCAmelCase_				,   UpperCAmelCase_							)
     print(F'Using the key {key}, the {mode}ed message is: {translated}'							)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()






