class_docstr: Represents an invertible structural graphical causal model, as required e.g. by
  :func:`~dowhy.gcm.whatif.counterfactual_samples`. This is a subclass of
  :class:`~dowhy.gcm.cms.StructuralCausalModel` and has further restrictions on the class of causal mechanisms.
  Here, the mechanisms of non-root nodes need to be invertible with respect to the noise,
  such as :class:`~dowhy.gcm.causal_mechanisms.PostNonlinearModel`.
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code: def causal_mechanism(
      self, node: Any
  ) -> Union[StochasticModel, InvertibleFunctionalCausalModel]:
      return super().causal_mechanism(node)
  
imports: from typing import Any, Callable, Optional, Union
  import networkx
  from dowhy.gcm.causal_mechanisms import ConditionalStochasticModel, FunctionalCausalModel, InvertibleFunctionalCausalModel, StochasticModel
  from dowhy.graph import DirectedGraph, HasNodes, get_ordered_predecessors, is_root_node, validate_acyclic, validate_node_in_graph
label_desc: Use image node_id 2 for calling the InvertibleStructuralCausalModel obj's underlying member method code with example usage: obj.causal_mechanism(node) and returns: super