






"""simple docstring"""



import math




def      _lowerCAmelCase		(							)		->None:
						A__						:  Any		  =  input("""Enter message: """      )
						A__						:  Optional[int]		  =  int(input(f'Enter key [2-{len(UpperCAmelCase__      ) - 1}]: '      )      )
						A__						:  Optional[int]		  =  input("""Encryption/Decryption [e/d]: """      )

						if mode.lower().startswith("""e"""      ):
												A__						:  int		  =  encrypt_message(UpperCAmelCase__,						UpperCAmelCase__      )
						elif mode.lower().startswith("""d"""      ):
												A__						:  List[Any]		  =  decrypt_message(UpperCAmelCase__,						UpperCAmelCase__      )

						# Append pipe symbol (vertical bar) to identify spaces at the end.
						print(f'Output:\n{text + "|"}'      )




def      _lowerCAmelCase		(							UpperCAmelCase__       :					int,						UpperCAmelCase__       :					str      )		->str:
						A__						:  str		  =  [""""""] * key
						for col in range(UpperCAmelCase__      ):
												A__						:  str		  =  col
												while pointer < len(UpperCAmelCase__      ):
																		cipher_text[col] += message[pointer]
																		pointer += key
						return "".join(UpperCAmelCase__      )




def      _lowerCAmelCase		(							UpperCAmelCase__       :					int,						UpperCAmelCase__       :					str      )		->str:
						A__						:  Any		  =  math.ceil(len(UpperCAmelCase__      ) / key      )
						A__						:  Optional[int]		  =  key
						A__						:  Tuple		  =  (num_cols * num_rows) - len(UpperCAmelCase__      )
						A__						:  Optional[Any]		  =  [""""""] * num_cols
						A__						:  Optional[int]		  =  0
						A__						:  List[str]		  =  0

						for symbol in message:
												plain_text[col] += symbol
												col += 1

												if (
												    (col == num_cols)
												    or (col == num_cols - 1)
												    and (row >= num_rows - num_shaded_boxes)
												):
																		A__						:  List[str]		  =  0
																		row += 1

						return "".join(UpperCAmelCase__      )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()














"""simple docstring"""



import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser




def      _lowerCAmelCase		(							UpperCAmelCase__       :					List[str]      )		->str:
						A__						:  Tuple		  =  {}
						A__						:  Union[str, Any]		  =  tokenizer(example["""content"""],						truncation=UpperCAmelCase__      )["""input_ids"""]
						A__						:  Any		  =  len(example["""content"""]      ) / len(output["""input_ids"""]      )
						return output


A_    =							HfArgumentParser(PretokenizationArguments)
A_    =							parser.parse_args()
if args.num_workers is None:
						A_    =							multiprocessing.cpu_count()
A_    =							AutoTokenizer.from_pretrained(args.tokenizer_dir)

A_    =							time.time()
A_    =							load_dataset(args.dataset_name, split='''train''')
print(F'Dataset loaded in {time.time()-t_start:.2f}s')

A_    =							time.time()
A_    =							ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        '''repo_name''',
        '''path''',
        '''copies''',
        '''size''',
        '''content''',
        '''license''',
        '''hash''',
        '''line_mean''',
        '''line_max''',
        '''alpha_frac''',
        '''autogenerated''',
    ],
)
print(F'Dataset tokenized in {time.time()-t_start:.2f}s')

A_    =							time.time()
ds.push_to_hub(args.tokenized_data_repo)

print(F'Data pushed to the hub in {time.time()-t_start:.2f}s')






