

import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


UpperCAmelCase__ :     List[Any]				    =    500_000

UpperCAmelCase__ :     Union[str, Any]				    =    os.path.split(__file__)
UpperCAmelCase__ :     List[str]				    =    os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))






@get_duration
def 					__lowercase      (     _A						,    **_A			)     ->						Optional[int]:
      SCREAMING_SNAKE_CASE :      List[str]       =   dataset.map(**_A			)






@get_duration
def 					__lowercase      (     _A						,    **_A			)     ->						List[Any]:
      SCREAMING_SNAKE_CASE :      Union[str, Any]       =   dataset.filter(**_A			)






def 					__lowercase      (     )     ->						Tuple:
      SCREAMING_SNAKE_CASE :      List[str]       =   {"""num examples""": SPEED_TEST_N_EXAMPLES}
      with tempfile.TemporaryDirectory() as tmp_dir:
            SCREAMING_SNAKE_CASE :      Union[str, Any]       =   datasets.Features({"""text""": datasets.Value("""string"""			), """numbers""": datasets.Value("""float32"""			)}			)
            SCREAMING_SNAKE_CASE :      List[Any]       =   generate_example_dataset(
                os.path.join(_A						,    """dataset.arrow"""			)						,    _A						,    num_examples=_A			)

            SCREAMING_SNAKE_CASE :      List[str]       =   transformers.AutoTokenizer.from_pretrained("""bert-base-cased"""						,    use_fast=_A			)

            def tokenize(_A			):
                  return tokenizer(examples["""text"""]			)

            SCREAMING_SNAKE_CASE :      List[Any]       =   map(_A			)

            SCREAMING_SNAKE_CASE :      List[Any]       =   map(_A						,    batched=_A			)

            SCREAMING_SNAKE_CASE :      Optional[int]       =   map(_A						,    function=lambda _A			: None						,    batched=_A			)

            with dataset.formatted_as(type="""numpy"""			):
                  SCREAMING_SNAKE_CASE :      Tuple       =   map(_A						,    function=lambda _A			: None						,    batched=_A			)

            with dataset.formatted_as(type="""pandas"""			):
                  SCREAMING_SNAKE_CASE :      Optional[int]       =   map(_A						,    function=lambda _A			: None						,    batched=_A			)

            with dataset.formatted_as(type="""torch"""						,    columns="""numbers"""			):
                  SCREAMING_SNAKE_CASE :      Any       =   map(_A						,    function=lambda _A			: None						,    batched=_A			)

            with dataset.formatted_as(type="""tensorflow"""						,    columns="""numbers"""			):
                  SCREAMING_SNAKE_CASE :      Tuple       =   map(_A						,    function=lambda _A			: None						,    batched=_A			)

            SCREAMING_SNAKE_CASE :      Tuple       =   map(_A						,    function=_A						,    batched=_A			)

            SCREAMING_SNAKE_CASE :      Optional[Any]       =   filter(_A			)

            # Activate later when tokenizer support batched inputs
            # with dataset.formatted_as(type='numpy'):
            #     times[func.__name__ + " fast-tokenizer batched numpy"] = func(dataset, function=tokenize, batched=True)

      with open(_A						,    """wb"""			) as f:
            f.write(json.dumps(_A			).encode("""utf-8"""			)			)


if __name__ == "__main__":  # useful to run the profiler
   benchmark_map_filter()







from math import ceil






def 					__lowercase      (     _A = 1001			)     ->						int:
      SCREAMING_SNAKE_CASE :      Union[str, Any]       =   1

      for i in range(1						,    int(ceil(n / 2.0			)			)			):
            SCREAMING_SNAKE_CASE :      Dict       =   2 * i + 1
            SCREAMING_SNAKE_CASE :      Optional[int]       =   2 * i
            SCREAMING_SNAKE_CASE :      str       =   total + 4 * odd**2 - 6 * even

      return total


if __name__ == "__main__":
  import sys

  if len(sys.argv) == 1:
    print(solution())
  else:
    try:
      UpperCAmelCase__ :     str				    =    int(sys.argv[1])
      print(solution(n))
    except ValueError:
      print("""Invalid entry - please enter a number""")




