from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType





class     lowerCAmelCase__     (				__snake_case			):


		'''simple docstring'''






		lowerCAmelCase_     =   ["""image_processor""", """tokenizer"""]
		lowerCAmelCase_     =   """BridgeTowerImageProcessor"""
		lowerCAmelCase_     =   ("""RobertaTokenizer""", """RobertaTokenizerFast""")
		def __init__(       self     :     List[str]     ,  snake_case__     :     Any     ,  snake_case__     :     Union[str, Any]		)      ->	str:
				super().__init__(snake_case__     ,  snake_case__		)
		def __call__(       self     :     Union[str, Any]     ,  snake_case__     :     Optional[int]     ,  snake_case__     :     Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None     ,  snake_case__     :     bool = True     ,  snake_case__     :     Union[bool, str, PaddingStrategy] = False     ,  snake_case__     :     Union[bool, str, TruncationStrategy] = None     ,  snake_case__     :     Optional[int] = None     ,  snake_case__     :     int = 0     ,  snake_case__     :     Optional[int] = None     ,  snake_case__     :     Optional[bool] = None     ,  snake_case__     :     Optional[bool] = None     ,  snake_case__     :     bool = False     ,  snake_case__     :     bool = False     ,  snake_case__     :     bool = False     ,  snake_case__     :     bool = False     ,  snake_case__     :     bool = True     ,  snake_case__     :     Optional[Union[str, TensorType]] = None     ,  **snake_case__     :     Optional[Any]     ,  )      ->	BatchEncoding:
				_lowerCamelCase				   =  self.tokenizer(
				    text=snake_case__     ,  add_special_tokens=snake_case__     ,  padding=snake_case__     ,  truncation=snake_case__     ,  max_length=snake_case__     ,  stride=snake_case__     ,  pad_to_multiple_of=snake_case__     ,  return_token_type_ids=snake_case__     ,  return_attention_mask=snake_case__     ,  return_overflowing_tokens=snake_case__     ,  return_special_tokens_mask=snake_case__     ,  return_offsets_mapping=snake_case__     ,  return_length=snake_case__     ,  verbose=snake_case__     ,  return_tensors=snake_case__     ,  **snake_case__     ,  )
				# add pixel_values + pixel_mask
				_lowerCamelCase				   =  self.image_processor(
				    snake_case__     ,  return_tensors=snake_case__     ,  do_normalize=snake_case__     ,  do_center_crop=snake_case__     ,  **snake_case__		)
				encoding.update(snake_case__		)

				return encoding
		def   _snake_case       (       self     :     Tuple     ,  *snake_case__     :     Dict     ,  **snake_case__     :     Tuple		)      ->	int:
				return self.tokenizer.batch_decode(*snake_case__     ,  **snake_case__		)
		def   _snake_case       (       self     :     Any     ,  *snake_case__     :     Union[str, Any]     ,  **snake_case__     :     Optional[Any]		)      ->	Dict:
				return self.tokenizer.decode(*snake_case__     ,  **snake_case__		)



		@property
		def   _snake_case       (       self     :     Optional[Any]		)      ->	Any:
				_lowerCamelCase				   =  self.tokenizer.model_input_names
				_lowerCamelCase				   =  self.image_processor.model_input_names
				return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)







"""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.'
				)
