class_docstr: Init method for the base class of Elimination Orders.
  
  Parameters
  ----------
  model: BayesianNetwork instance
      The model on which we want to compute the elimination orders.
docstr: The cost function to compute the cost of elimination of each node.
  This method is just a dummy and returns 0 for all the nodes. Actual cost functions
  are implemented in the classes inheriting BaseEliminationOrder.
  
  Parameters
  ----------
  node: string, any hashable python object.
      The node whose cost is to be computed.
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code: def cost(self, node):
      """
      The cost function to compute the cost of elimination of each node.
      This method is just a dummy and returns 0 for all the nodes. Actual cost functions
      are implemented in the classes inheriting BaseEliminationOrder.
  
      Parameters
      ----------
      node: string, any hashable python object.
          The node whose cost is to be computed.
      """
      return 0
  
imports: from abc import abstractmethod
  from itertools import combinations
  import numpy
  from tqdm.auto import tqdm
  from pgmpy import config
  from pgmpy.models import BayesianNetwork
label_desc: Use image node_id 2 for calling the BaseEliminationOrder obj's underlying member method code with example usage: obj.cost(node) and returns: int