from __future__ import annotations

from functools import lru_cache
from math import ceil

UpperCAmelCase_			    =							1_0_0

UpperCAmelCase_			    =							set(range(3, NUM_PRIMES, 2))
primes.add(2)
UpperCAmelCase_			    =							42

for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
  if prime not in primes:
    continue
  primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))




@lru_cache(maxsize=100		)
def       lowerCAmelCase_     (		lowercase:							int		)    ->				set[int]:







 '''simple docstring'''
 if number_to_partition < 0:
  return set()
 elif number_to_partition == 0:
  return {1}

 _UpperCamelCase:     set[int]							= set()
 _UpperCamelCase:     int
 _UpperCamelCase:     int

 for prime in primes:
  if prime > number_to_partition:
   continue
  for sub in partition(number_to_partition - prime		):
   ret.add(sub * prime		)

 return ret




def       lowerCAmelCase_     (		lowercase:							int = 5_000		)    ->				int | None:







 '''simple docstring'''
 for number_to_partition in range(1  ,					lowercase		):
  if len(partition(lowercase		)		) > number_unique_partitions:
   return number_to_partition
 return None


if __name__ == "__main__":
  print(f"""{solution() = }""")
import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


UpperCAmelCase_			    =							logging.get_logger(__name__)




class  __magic_name__  (		__a    ):





   """simple docstring"""




   def __init__(	self					:  str		,  *_lowercase					:  str		,  **_lowercase					:  int							):



    """simple docstring"""



    warnings.warn(
        '''The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
        ''' Please use PerceiverImageProcessor instead.'''		,  _lowercase		,  )
    super().__init__(*_lowercase		,  **_lowercase							)