





def    __UpperCAmelCase(      lowercase_      ):
       _lowerCamelCase							:     list[list[int]]	=		[[0 for _ in range(lowercase_      )] for _ in range(m + 1      )]
       for i in range(m + 1      ):
              _lowerCamelCase							:     List[Any]	=		1

       for n in range(m + 1      ):
              for k in range(1 ,    lowercase_      ):
                     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:
                     _lowerCamelCase			       =      int(input('Enter a number: ').strip())
                     print(partition(n))
              except ValueError:
                     print('Please enter a number.')
       else:
              try:
                     _lowerCamelCase			       =      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_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCamelCase			       =      {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      [
           'OPT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'OPTForCausalLM',
           'OPTModel',
           'OPTPreTrainedModel',
           'OPTForSequenceClassification',
           'OPTForQuestionAnswering',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      ['TFOPTForCausalLM', 'TFOPTModel', 'TFOPTPreTrainedModel']

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _lowerCamelCase			       =      [
           'FlaxOPTForCausalLM',
           'FlaxOPTModel',
           'FlaxOPTPreTrainedModel',
       ]


if TYPE_CHECKING:
       from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_opt import (
                  OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  OPTForCausalLM,
                  OPTForQuestionAnswering,
                  OPTForSequenceClassification,
                  OPTModel,
                  OPTPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
       import sys

       _lowerCamelCase			       =      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

