class_docstr: A dummy Op that describes the purpose of a Model variable and contains
  meta-information as additional inputs (value and dims).
class_docstr_tok: ["A","dummy","Op","that","describes","the","purpose","of","a","Model","variable","and","contains","meta-information","as","additional","inputs","(","value","and","dims",")","."]
code: def do_constant_folding(self, fgraph, node):
      return False
  
imports: from copy import copy
  from typing import Dict, Optional, Tuple
  import pytensor
  from pytensor import Variable, shared
  from pytensor.compile import SharedVariable
  from pytensor.graph import Apply, FunctionGraph, Op, node_rewriter
  from pytensor.graph.rewriting.basic import out2in
  from pytensor.scalar import Identity
  from pytensor.tensor.elemwise import Elemwise
  from pytensor.tensor.sharedvar import ScalarSharedVariable
  from pymc.logprob.transforms import Transform
  from pymc.model.core import Model
  from pymc.pytensorf import StringType, find_rng_nodes, toposort_replace
label_desc: Use image node_id 4 for calling the ModelVar obj's underlying member method code with example usage: obj.do_constant_folding(fgraph, node) and returns: False