


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__magic_name__   :   List[Any]  							={
    """configuration_sam""": [
        """SAM_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SamConfig""",
        """SamMaskDecoderConfig""",
        """SamPromptEncoderConfig""",
        """SamVisionConfig""",
    ],
    """processing_sam""": ["""SamProcessor"""],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__magic_name__   :   Tuple  							=[
						    """SAM_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """SamModel""",
						    """SamPreTrainedModel""",
						]
try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__magic_name__   :   Optional[Any]  							=[
						    """TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TFSamModel""",
						    """TFSamPreTrainedModel""",
						]
try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__magic_name__   :   int  							=["""SamImageProcessor"""]


if TYPE_CHECKING:
						from .configuration_sam import (
						    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SamConfig,
						    SamMaskDecoderConfig,
						    SamPromptEncoderConfig,
						    SamVisionConfig,
						)
						from .processing_sam import SamProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_sam import SamImageProcessor

else:
						import sys

						__magic_name__   :   int  							=_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







'''simple docstring'''
def      __snake_case       (       lowerCamelCase_ :				int = 100						):
				'''simple docstring'''




				__magic_name__	  = [[0 for _ in range(lowerCamelCase_						)] for _ in range(m + 1						)]
				for i in range(m + 1						):
								__magic_name__	  = 1

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

				return memo[m][m - 1] - 1


if __name__ == "__main__":
						print(solution(int(input('Enter a number: ').strip())))



