


'''simple docstring'''

def _SCREAMING_SNAKE_CASE      (A = 50       )       ->       int:






       """simple docstring"""







       lowercase__      			= [[0] * 3 for _ in range(length + 1       )]

       for row_length in range(length + 1       ):
              for tile_length in range(2  , 5       ):
                     for tile_start in range(row_length - tile_length + 1       ):
                            different_colour_ways_number[row_length][tile_length - 2] += (
                                different_colour_ways_number[row_length - tile_start - tile_length][
                                    tile_length - 2
                                ]
                                + 1
                            )

       return sum(different_colour_ways_number[length]       )


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








from typing import TYPE_CHECKING

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


__lowerCAmelCase		       =							{
    '''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
    '''tokenization_canine''': ['''CanineTokenizer'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase		       =							[
     '''CANINE_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''CanineForMultipleChoice''',
     '''CanineForQuestionAnswering''',
     '''CanineForSequenceClassification''',
     '''CanineForTokenClassification''',
     '''CanineLayer''',
     '''CanineModel''',
     '''CaninePreTrainedModel''',
     '''load_tf_weights_in_canine''',
 ]


if TYPE_CHECKING:
 from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
 from .tokenization_canine import CanineTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_canine import (
      CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
      CanineForMultipleChoice,
      CanineForQuestionAnswering,
      CanineForSequenceClassification,
      CanineForTokenClassification,
      CanineLayer,
      CanineModel,
      CaninePreTrainedModel,
      load_tf_weights_in_canine,
  )


else:
 import sys

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


