class_docstr: A Block serves as the foundation class for all graph-based optimization techniques.
class_docstr_tok: ["A","Block","serves","as","the","foundation","class","for","all","graph-based","optimization","techniques","."]
docstr: Initialization method.
  
  Args:
      type: Type of the block.
      pointer: Any type of callable to be applied when block is called.
      n_input: Number of input arguments.
      n_output: Number of output arguments.
docstr_tok: ["Initialization","method",".","Args",":","type",":","Type","of","the","block",".","pointer",":","Any","type","of","callable","to","be","applied","when","block","is","called",".","n_input",":","Number","of","input","arguments",".","n_output",":","Number","of","output","arguments","."]
code: def __init__(
      self, type: str, pointer: callable, n_input: int, n_output: int
  ) -> None:
      """Initialization method.
  
      Args:
          type: Type of the block.
          pointer: Any type of callable to be applied when block is called.
          n_input: Number of input arguments.
          n_output: Number of output arguments.
  
      """
  
      self.type = type
      self.pointer = pointer
  
      self.n_input = n_input
      self.n_output = n_output
  
imports: import opytimizer.utils.exception
label_desc: Use image node_id 1 to create a new Block object  with example: obj = Block(type, pointer, n_input, n_output)