




'''simple docstring'''


import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser






def 		_lowerCAmelCase							(   lowercase							: Any    )			->Optional[int]:
   """simple docstring"""




   lowercase__       							=							{}
   lowercase__       							=							tokenizer(example['''content''']					,  truncation=__UpperCAmelCase    )['''input_ids''']
   lowercase__       							=							len(example['''content''']    ) / len(output['''input_ids''']    )
   return output


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

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

_lowerCAmelCase  		=      time.time()
_lowerCAmelCase  		=      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''')

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





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










import operator as op

def    UpperCAmelCase_				( __UpperCAmelCase		:      str				)   ->					Any:
      SCREAMING_SNAKE_CASE_      		=     []
      SCREAMING_SNAKE_CASE_      		=     lambda __UpperCAmelCase     ,     __UpperCAmelCase				: int(x / y				)  # noqa: E731 integer division operation
      SCREAMING_SNAKE_CASE_      		=     {
          '^': op.pow,
          '*': op.mul,
          '/': div,
          '+': op.add,
          '-': op.sub,
      }  # operators & their respective operation

      # print table header
      print('Symbol'.center(8				)     ,     'Action'.center(12				)     ,     'Stack'     ,     sep=' | '				)
      print('-' * (30 + len(__UpperCAmelCase				))				)

      for x in post_fix:
            if x.isdigit():  # if x in digit
                  stack.append(__UpperCAmelCase				)  # append x to stack
                  # output in tabular format
                  print(x.rjust(8				)     ,     ('push(' + x + ')').ljust(12				)     ,     ','.join(__UpperCAmelCase				)     ,     sep=' | '				)
            else:
                  SCREAMING_SNAKE_CASE_      		=     stack.pop()  # pop stack
                  # output in tabular format
                  print(''.rjust(8				)     ,     ('pop(' + b + ')').ljust(12				)     ,     ','.join(__UpperCAmelCase				)     ,     sep=' | '				)

                  SCREAMING_SNAKE_CASE_      		=     stack.pop()  # pop stack
                  # output in tabular format
                  print(''.rjust(8				)     ,     ('pop(' + a + ')').ljust(12				)     ,     ','.join(__UpperCAmelCase				)     ,     sep=' | '				)

                  stack.append(
                      str(opr[x](int(__UpperCAmelCase				)     ,     int(__UpperCAmelCase				)				)				)				)  # evaluate the 2 values popped from stack & push result to stack
                  # output in tabular format
                  print(
                      x.rjust(8				)     ,     ('push(' + a + x + b + ')').ljust(12				)     ,     ','.join(__UpperCAmelCase				)     ,     sep=' | '     ,     )

      return int(stack[0]				)


if __name__ == "__main__":
   lowerCamelCase__					:  Tuple      							=				input('\n\nEnter a Postfix Equation (space separated) = ').split(' ')
   print('\n\tResult = ', solve(Postfix))