"""simple docstring"""
def 		__a  (      _SCREAMING_SNAKE_CASE = 100  )      ->int:
  a__:	Tuple     				=      [[0 for _ in range(_SCREAMING_SNAKE_CASE  )] for _ in range(m + 1  )]
  for i in range(m + 1  ):
    a__:	Union[str, Any]     				=      1

  for n in range(m + 1  ):
    for k in range(1						,	_SCREAMING_SNAKE_CASE  ):
      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())))





from typing import TYPE_CHECKING

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


lowerCAmelCase__             =		{
    """configuration_markuplm""": ["""MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarkupLMConfig"""],
    """feature_extraction_markuplm""": ["""MarkupLMFeatureExtractor"""],
    """processing_markuplm""": ["""MarkupLMProcessor"""],
    """tokenization_markuplm""": ["""MarkupLMTokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__             =		["""MarkupLMTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__             =		[
							    """MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """MarkupLMForQuestionAnswering""",
							    """MarkupLMForSequenceClassification""",
							    """MarkupLMForTokenClassification""",
							    """MarkupLMModel""",
							    """MarkupLMPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
							from .feature_extraction_markuplm import MarkupLMFeatureExtractor
							from .processing_markuplm import MarkupLMProcessor
							from .tokenization_markuplm import MarkupLMTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_markuplm_fast import MarkupLMTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_markuplm import (
														    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MarkupLMForQuestionAnswering,
														    MarkupLMForSequenceClassification,
														    MarkupLMForTokenClassification,
														    MarkupLMModel,
														    MarkupLMPreTrainedModel,
														)


else:
							import sys

							lowerCAmelCase__             =		_LazyModule(__name__, globals()["""__file__"""], _import_structure)




