






import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


UpperCAmelCase__				   =		pytest.mark.integration
@pytest.mark.parametrize('''path'''	,							['''paws''', '''csv'''] )
def 						_a    (      a :Dict	,							a :Optional[int] )							->			List[str]:
 inspect_dataset(a	,							a )
 a		  =      path + '''.py'''
 assert script_name in os.listdir(a )
 assert "__pycache__" not in os.listdir(a )
@pytest.mark.filterwarnings('''ignore:inspect_metric is deprecated:FutureWarning''' )
@pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning''' )
@pytest.mark.parametrize('''path'''	,							['''accuracy'''] )
def 						_a    (      a :Any	,							a :Optional[Any] )							->			Union[str, Any]:
 inspect_metric(a	,							a )
 a		  =      path + '''.py'''
 assert script_name in os.listdir(a )
 assert "__pycache__" not in os.listdir(a )
@pytest.mark.parametrize(
    '''path, config_name, expected_splits'''	,							[
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]	,							)
def 						_a    (      a :Union[str, Any]	,							a :List[Any]	,							a :Optional[Any] )							->			List[str]:
 a		  =      get_dataset_config_info(a	,							config_name=a )
 assert info.config_name == config_name
 assert list(info.splits.keys() ) == expected_splits
@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''	,							[
        ('''paws''', None, ValueError),
    ]	,							)
def 						_a    (      a :str	,							a :Tuple	,							a :Any )							->			Tuple:
 with pytest.raises(a ):
  get_dataset_config_info(a	,							config_name=a )
@pytest.mark.parametrize(
    '''path, expected'''	,							[
        ('''squad''', '''plain_text'''),
        ('''acronym_identification''', '''default'''),
        ('''lhoestq/squad''', '''plain_text'''),
        ('''lhoestq/test''', '''default'''),
        ('''lhoestq/demo1''', '''lhoestq--demo1'''),
        ('''dalle-mini/wit''', '''dalle-mini--wit'''),
    ]	,							)
def 						_a    (      a :Any	,							a :Union[str, Any] )							->			Optional[Any]:
 a		  =      get_dataset_config_names(a )
 assert expected in config_names
@pytest.mark.parametrize(
    '''path, expected_configs, expected_splits_in_first_config'''	,							[
        ('''squad''', ['''plain_text'''], ['''train''', '''validation''']),
        ('''dalle-mini/wit''', ['''dalle-mini--wit'''], ['''train''']),
        ('''paws''', ['''labeled_final''', '''labeled_swap''', '''unlabeled_final'''], ['''train''', '''test''', '''validation''']),
    ]	,							)
def 						_a    (      a :Optional[int]	,							a :Optional[Any]	,							a :Optional[Any] )							->			List[Any]:
 a		  =      get_dataset_infos(a )
 assert list(infos.keys() ) == expected_configs
 a		  =      expected_configs[0]
 assert expected_config in infos
 a		  =      infos[expected_config]
 assert info.config_name == expected_config
 assert list(info.splits.keys() ) == expected_splits_in_first_config
@pytest.mark.parametrize(
    '''path, expected_config, expected_splits'''	,							[
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]	,							)
def 						_a    (      a :str	,							a :Union[str, Any]	,							a :Union[str, Any] )							->			Any:
 a		  =      get_dataset_infos(a )
 assert expected_config in infos
 a		  =      infos[expected_config]
 assert info.config_name == expected_config
 assert list(info.splits.keys() ) == expected_splits

@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''	,							[
        ('''paws''', None, ValueError),
    ]	,							)
def 						_a    (      a :Dict	,							a :Any	,							a :Optional[int] )							->			Tuple:
 with pytest.raises(a ):
  get_dataset_split_names(a	,							config_name=a )










import math
def 						_a    (      a :int )							->			list:
 a		  =      [True] * n
 a		  =      False
 a		  =      False
 a		  =      True

 for i in range(3	,							int(n**0.5 + 1 )	,							2 ):
  a		  =      i * 2
  while index < n:
   a		  =      False
   a		  =      index + i

 a		  =      [2]

 for i in range(3	,							a	,							2 ):
  if is_prime[i]:
   primes.append(a )

 return primes
def 						_a    (      a :int = 999_966_663_333 )							->			int:
 a		  =      math.floor(math.sqrt(a ) ) + 100
 a		  =      prime_sieve(a )

 a		  =      0
 a		  =      0
 a		  =      primes[prime_index]

 while (last_prime**2) <= limit:
  a		  =      primes[prime_index + 1]

  a		  =      last_prime**2
  a		  =      next_prime**2

  # Get numbers divisible by lps(current)
  a		  =      lower_bound + last_prime
  while upper_bound > current <= limit:
   matches_sum += current
   current += last_prime

  # Reset the upper_bound
  while (upper_bound - next_prime) > limit:
   upper_bound -= next_prime

  # Add the numbers divisible by ups(current)
  a		  =      upper_bound - next_prime
  while current > lower_bound:
   matches_sum += current
   current -= next_prime

  # Remove the numbers divisible by both ups and lps
  a		  =      0
  while upper_bound > current <= limit:
   if current <= lower_bound:
    # Increment the current number
    current += last_prime * next_prime
    continue

   if current > limit:
    break

   # Remove twice since it was added by both ups and lps
   matches_sum -= current * 2

   # Increment the current number
   current += last_prime * next_prime

  # Setup for next pair
  a		  =      next_prime
  prime_index += 1

 return matches_sum


if __name__ == "__main__":
     print(solution())


