"""simple docstring"""





def   lowerCamelCase_(__SCREAMING_SNAKE_CASE = 50	)->     int:
							_SCREAMING_SNAKE_CASE		:    Optional[int]      	=     [[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() = }")




"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_            =    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_            =    {
    '''tiiuae/falcon-40b''': '''https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json''',
    '''tiiuae/falcon-7b''': '''https://huggingface.co/tiiuae/falcon-7b/resolve/main/config.json''',
}
class   _UpperCAmelCase				(		SCREAMING_SNAKE_CASE_				):
      __SCREAMING_SNAKE_CASE :				Optional[Any]				   =						"falcon"
      __SCREAMING_SNAKE_CASE :				List[Any]				   =						["past_key_values"]




      def __init__(				self ,							lowercase_=6_5_0_2_4 ,							lowercase_=4_5_4_4 ,							lowercase_=3_2 ,							lowercase_=7_1 ,							lowercase_=1E-5 ,							lowercase_=0.0_2 ,							lowercase_=True ,							lowercase_=0.0 ,							lowercase_=0.0 ,							lowercase_=None ,							lowercase_=False ,							lowercase_=False ,							lowercase_=True ,							lowercase_=True ,							lowercase_=False ,							lowercase_=1_1 ,							lowercase_=1_1 ,							**lowercase_ ,							)    ->       Any:
          UpperCAmelCase          =       vocab_size
          # Backward compatibility with n_embed kwarg
          UpperCAmelCase          =       kwargs.pop('n_embed' ,							lowercase_				)
          UpperCAmelCase          =       hidden_size if n_embed is None else n_embed
          UpperCAmelCase          =       num_hidden_layers
          UpperCAmelCase          =       num_attention_heads
          UpperCAmelCase          =       layer_norm_epsilon
          UpperCAmelCase          =       initializer_range
          UpperCAmelCase          =       use_cache
          UpperCAmelCase          =       hidden_dropout
          UpperCAmelCase          =       attention_dropout

          UpperCAmelCase          =       bos_token_id
          UpperCAmelCase          =       eos_token_id
          UpperCAmelCase          =       num_attention_heads if num_kv_heads is None else num_kv_heads
          UpperCAmelCase          =       alibi
          UpperCAmelCase          =       new_decoder_architecture
          UpperCAmelCase          =       multi_query  # Ignored when new_decoder_architecture is True
          UpperCAmelCase          =       parallel_attn
          UpperCAmelCase          =       bias

          super().__init__(bos_token_id=lowercase_ ,							eos_token_id=lowercase_ ,							**lowercase_				)




      @property
      def      a_   (				self				)    ->       List[Any]:
          return self.hidden_size // self.num_attention_heads




      @property
      def      a_   (				self				)    ->       List[str]:
          return not self.alibi



