


def 							UpperCamelCase_( lowerCamelCase_					)       ->		int:
    _lowercase			:				list[list[int]] 						=						[[0 for _ in range(lowerCamelCase_					)] for _ in range(m + 1					)]
    for i in range(m + 1					):
        _lowercase			:				Dict 						=						1

    for n in range(m + 1					):
        for k in range(1				,					lowerCamelCase_					):
            memo[n][k] += memo[n][k - 1]
            if n - k > 0:
                memo[n][k] += memo[n - k - 1][k]

    return memo[m][m - 1]


if __name__ == "__main__":
 import sys

 if len(sys.argv) == 1:
  try:
   SCREAMING_SNAKE_CASE			: Optional[Any]				   =					int(input("Enter a number: ").strip())
   print(partition(n))
  except ValueError:
   print("Please enter a number.")
 else:
  try:
   SCREAMING_SNAKE_CASE			: Union[str, Any]				   =					int(sys.argv[1])
   print(partition(n))
  except ValueError:
   print("Please pass a number.")






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


SCREAMING_SNAKE_CASE			: List[Any]				   =					{
    "configuration_poolformer": [
        "POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "PoolFormerConfig",
        "PoolFormerOnnxConfig",
    ]
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE			: List[str]				   =					["PoolFormerFeatureExtractor"]
 SCREAMING_SNAKE_CASE			: List[Any]				   =					["PoolFormerImageProcessor"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE			: List[Any]				   =					[
     "POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
     "PoolFormerForImageClassification",
     "PoolFormerModel",
     "PoolFormerPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_poolformer import (
     POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
     PoolFormerConfig,
     PoolFormerOnnxConfig,
 )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_poolformer import PoolFormerFeatureExtractor
  from .image_processing_poolformer import PoolFormerImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_poolformer import (
      POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      PoolFormerForImageClassification,
      PoolFormerModel,
      PoolFormerPreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE			: str				   =					_LazyModule(__name__, globals()["__file__"], _import_structure)


