code: def multiout_measurable_op():
      # Create a dummy Op that just returns the two inputs
      mu1, mu2 = pt.scalars("mu1", "mu2")
  
      class TestOpFromGraph(OpFromGraph):
          def do_constant_folding(self, fgraph, node):
              False
  
      multiout_op = TestOpFromGraph([mu1, mu2], [mu1 + 0.0, mu2 + 0.0])
  
      MeasurableVariable.register(TestOpFromGraph)
  
      @_logprob.register(TestOpFromGraph)
      def logp_multiout(op, values, mu1, mu2):
          value1, value2 = values
          return value1 + mu1, value2 + mu2
  
      return multiout_op
  
imports: import gc
  import operator
  import numpy
  import pytensor
  import pytest
  import scipy
  from numdifftools import Jacobian
  from pytensor import scan
  from pytensor import tensor
  from pytensor.compile.builders import OpFromGraph
  from pytensor.graph import FunctionGraph
  from pytensor.graph.basic import equal_computations
  import pymc
  from pymc.distributions.transforms import _default_transform, log, logodds
  from pymc.logprob import conditional_logp
  from pymc.logprob.abstract import MeasurableVariable, _logprob
  from pymc.logprob.transform_value import TransformValuesMapping, TransformValuesRewrite
  from pymc.logprob.transforms import ExpTransform, LogOddsTransform, LogTransform
  from pymc.testing import assert_no_rvs
  from tests.logprob.test_transforms import DirichletScipyDist
label_desc: Use image node_id 1 for calling a global function with example usage: multiout_measurable_op() and returns: multiout_op, unknown,  unknown