class_docstr: A no-op that pairs the original value with its transformed version.
  
  This is introduced by the `TransformValuesRewrite`
class_docstr_tok: ["A","no-op","that","pairs","the","original","value","with","its","transformed","version",".","This","is","introduced","by","the","`","TransformValuesRewrite","`"]
code: def make_node(
      self, tran_value: TensorVariable, value: TensorVariable
  ):
      return Apply(self, [tran_value, value], [tran_value.type()])
  
imports: from typing import Dict, Optional, Sequence, Union
  import numpy
  from pytensor.gradient import DisconnectedType
  from pytensor.graph import Apply, Op
  from pytensor.graph.features import AlreadyThere, Feature
  from pytensor.graph.fg import FunctionGraph
  from pytensor.graph.replace import clone_replace
  from pytensor.graph.rewriting.basic import GraphRewriter, in2out, node_rewriter
  from pytensor.scan.op import Scan
  from pytensor.tensor.variable import TensorVariable
  from pymc.logprob.abstract import MeasurableVariable, _logprob
  from pymc.logprob.rewriting import PreserveRVMappings, cleanup_ir_rewrites_db
  from pymc.logprob.transforms import Transform
label_desc: Use image node_id 1 for calling the TransformedValue obj's underlying member method code with example usage: obj.make_node(tran_value, value) and returns: Apply