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


A						=			logging.get_logger(__name__)

A						=			{
    'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}





class     lowerCAmelCase__     (				__snake_case			):


		'''simple docstring'''






		lowerCAmelCase_     =   """mra"""
		def __init__(       self     :     List[str]     ,  snake_case__     :     Any=5_0_2_6_5     ,  snake_case__     :     int=7_6_8     ,  snake_case__     :     Union[str, Any]=1_2     ,  snake_case__     :     Any=1_2     ,  snake_case__     :     List[str]=3_0_7_2     ,  snake_case__     :     Dict="gelu"     ,  snake_case__     :     Dict=0.1     ,  snake_case__     :     List[str]=0.1     ,  snake_case__     :     Optional[int]=5_1_2     ,  snake_case__     :     Dict=1     ,  snake_case__     :     List[str]=0.02     ,  snake_case__     :     Union[str, Any]=1e-5     ,  snake_case__     :     Optional[Any]="absolute"     ,  snake_case__     :     int=4     ,  snake_case__     :     Union[str, Any]="full"     ,  snake_case__     :     Tuple=0     ,  snake_case__     :     Optional[Any]=0     ,  snake_case__     :     List[Any]=1     ,  snake_case__     :     List[Any]=0     ,  snake_case__     :     Tuple=2     ,  **snake_case__     :     List[Any]     ,  )      ->	Any:
				super().__init__(pad_token_id=snake_case__     ,  bos_token_id=snake_case__     ,  eos_token_id=snake_case__     ,  **snake_case__		)

				_lowerCamelCase				   =  vocab_size
				_lowerCamelCase				   =  max_position_embeddings
				_lowerCamelCase				   =  hidden_size
				_lowerCamelCase				   =  num_hidden_layers
				_lowerCamelCase				   =  num_attention_heads
				_lowerCamelCase				   =  intermediate_size
				_lowerCamelCase				   =  hidden_act
				_lowerCamelCase				   =  hidden_dropout_prob
				_lowerCamelCase				   =  attention_probs_dropout_prob
				_lowerCamelCase				   =  initializer_range
				_lowerCamelCase				   =  type_vocab_size
				_lowerCamelCase				   =  layer_norm_eps
				_lowerCamelCase				   =  position_embedding_type
				_lowerCamelCase				   =  block_per_row
				_lowerCamelCase				   =  approx_mode
				_lowerCamelCase				   =  initial_prior_first_n_blocks
				_lowerCamelCase				   =  initial_prior_diagonal_n_blocks







"""simple docstring"""







def      UpperCamelCase       ( _A  ,				_A )     ->       int:
				lowercase    :      int       = 1  # To kept the Calculated Value
				# Since C(n, k) = C(n, n-k)
				if k > (n - k):
								lowercase    :      List[Any]       = n - k
				# Calculate C(n,k)
				for i in range(_A ):
								result *= n - i
								result //= i + 1
				return result


def      UpperCamelCase       ( _A )     ->       int:
				return binomial_coefficient(2 * node_count  ,				_A ) // (node_count + 1)


def      UpperCamelCase       ( _A )     ->       int:
				if n < 0:
								raise ValueError("""factorial() not defined for negative values""" )
				lowercase    :      Union[str, Any]       = 1
				for i in range(1  ,				n + 1 ):
								result *= i
				return result


def      UpperCamelCase       ( _A )     ->       int:
				return catalan_number(_A ) * factorial(_A )


if __name__ == "__main__":
				_lowerCAmelCase            =	int(input('Enter the number of nodes: ').strip() or 0)
				if node_count <= 0:
								raise ValueError('We need some nodes to work with.')
				print(
				    F'Given {node_count} nodes, there are {binary_tree_count(node_count)} '
				    F'binary trees and {catalan_number(node_count)} binary search trees.'
				)
