

"""simple docstring"""


from __future__ import annotations

from functools import lru_cache
from math import ceil

__A						       =      100

__A						       =      set(range(3, NUM_PRIMES, 2))
primes.add(2)
__A						       =      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=1_0_0			)
def    a__   (   __SCREAMING_SNAKE_CASE			)     ->     set[int]:
  if number_to_partition < 0:
    return set()
  elif number_to_partition == 0:
    return {1}

  __lowerCAmelCase:	set[int]   				=      set()
  __lowerCAmelCase:	int
  __lowerCAmelCase:	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    a__   (   __SCREAMING_SNAKE_CASE = 5_0_0_0			)     ->     int | None:
  for number_to_partition in range(1 ,			__SCREAMING_SNAKE_CASE			):
    if len(partition(__SCREAMING_SNAKE_CASE			)			) > number_unique_partitions:
      return number_to_partition
  return None


if __name__ == "__main__":
   print(F'''{solution() = }''')





"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A						       =      {
    "configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A						       =      [
			    "SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "Swinv2ForImageClassification",
			    "Swinv2ForMaskedImageModeling",
			    "Swinv2Model",
			    "Swinv2PreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swinva import (
						    SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwinvaForImageClassification,
						    SwinvaForMaskedImageModeling,
						    SwinvaModel,
						    SwinvaPreTrainedModel,
						)


else:
			import sys

			__A						       =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


