

import json
import os
import tempfile

import transformers

import datasets
from utils import generate_example_dataset, get_duration


lowercase_     :   Optional[int] 				=				5_0_0_0_0_0

lowercase_     :   int 				=				os.path.split(__file__)
lowercase_     :   Any 				=				os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))







@get_duration
def 			A__      (	snake_case_ :		datasets.Dataset       ,				**snake_case_ :		Dict      ):
 SCREAMING_SNAKE_CASE__:   Optional[Any]=      dataset.map(**UpperCamelCase__      )







@get_duration
def 			A__      (	snake_case_ :		datasets.Dataset       ,				**snake_case_ :		Union[str, Any]      ):
 SCREAMING_SNAKE_CASE__:   Optional[int]=      dataset.filter(**UpperCamelCase__      )







def 			A__      (	):
 SCREAMING_SNAKE_CASE__:   Tuple=      {"""num examples""": SPEED_TEST_N_EXAMPLES}
 with tempfile.TemporaryDirectory() as tmp_dir:
  SCREAMING_SNAKE_CASE__:   str=      datasets.Features({'''text''': datasets.Value('''string'''      ), '''numbers''': datasets.Value('''float32'''      )}      )
  SCREAMING_SNAKE_CASE__:   Tuple=      generate_example_dataset(
      os.path.join(UpperCamelCase__       ,				'''dataset.arrow'''      )       ,				UpperCamelCase__       ,				num_examples=UpperCamelCase__      )

  SCREAMING_SNAKE_CASE__:   Tuple=      transformers.AutoTokenizer.from_pretrained('''bert-base-cased'''       ,				use_fast=UpperCamelCase__      )

  def tokenize(snake_case_ :		Dict      ):
   return tokenizer(examples['''text''']      )

  SCREAMING_SNAKE_CASE__:   Any=      map(UpperCamelCase__      )

  SCREAMING_SNAKE_CASE__:   Union[str, Any]=      map(UpperCamelCase__       ,				batched=UpperCamelCase__      )

  SCREAMING_SNAKE_CASE__:   List[str]=      map(UpperCamelCase__       ,				function=lambda snake_case_      : None       ,				batched=UpperCamelCase__      )

  with dataset.formatted_as(type='''numpy'''      ):
   SCREAMING_SNAKE_CASE__:   Dict=      map(UpperCamelCase__       ,				function=lambda snake_case_      : None       ,				batched=UpperCamelCase__      )

  with dataset.formatted_as(type='''pandas'''      ):
   SCREAMING_SNAKE_CASE__:   List[Any]=      map(UpperCamelCase__       ,				function=lambda snake_case_      : None       ,				batched=UpperCamelCase__      )

  with dataset.formatted_as(type='''torch'''       ,				columns='''numbers'''      ):
   SCREAMING_SNAKE_CASE__:   str=      map(UpperCamelCase__       ,				function=lambda snake_case_      : None       ,				batched=UpperCamelCase__      )

  with dataset.formatted_as(type='''tensorflow'''       ,				columns='''numbers'''      ):
   SCREAMING_SNAKE_CASE__:   Tuple=      map(UpperCamelCase__       ,				function=lambda snake_case_      : None       ,				batched=UpperCamelCase__      )

  SCREAMING_SNAKE_CASE__:   Tuple=      map(UpperCamelCase__       ,				function=UpperCamelCase__       ,				batched=UpperCamelCase__      )

  SCREAMING_SNAKE_CASE__:   List[str]=      filter(UpperCamelCase__      )

  # 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(UpperCamelCase__       ,				'''wb'''      ) as f:
  f.write(json.dumps(UpperCamelCase__      ).encode('''utf-8'''      )      )


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


def 			A__      (	snake_case_ :		list      ):

 if len(snake_case_      ) < 2:
  return collection

 def circle_sort_util(snake_case_ :		list       ,				snake_case_ :		int       ,				snake_case_ :		int      ) -> bool:
  SCREAMING_SNAKE_CASE__:   Dict=      False

  if low == high:
   return swapped

  SCREAMING_SNAKE_CASE__:   str=      low
  SCREAMING_SNAKE_CASE__:   Optional[int]=      high

  while left < right:
   if collection[left] > collection[right]:
    SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__:   Optional[int]=      (
        collection[right],
        collection[left],
    )
    SCREAMING_SNAKE_CASE__:   List[Any]=      True

   left += 1
   right -= 1

  if left == right and collection[left] > collection[right + 1]:
   SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__:   List[str]=      (
       collection[right + 1],
       collection[left],
   )

   SCREAMING_SNAKE_CASE__:   List[str]=      True

  SCREAMING_SNAKE_CASE__:   Dict=      low + int((high - low) / 2      )
  SCREAMING_SNAKE_CASE__:   str=      circle_sort_util(snake_case_       ,				snake_case_       ,				snake_case_      )
  SCREAMING_SNAKE_CASE__:   List[Any]=      circle_sort_util(snake_case_       ,				mid + 1       ,				snake_case_      )

  return swapped or left_swap or right_swap

 SCREAMING_SNAKE_CASE__:   Optional[int]=      True

 while is_not_sorted is True:
  SCREAMING_SNAKE_CASE__:   Tuple=      circle_sort_util(snake_case_       ,				0       ,				len(snake_case_      ) - 1      )

 return collection


if __name__ == "__main__":
      lowercase_     :   Tuple 				=				input('Enter numbers separated by a comma:\n').strip()
      lowercase_     :   str 				=				[int(item) for item in user_input.split(',')]
      print(circle_sort(unsorted))

