code: def model_with_imputations():
      """The example from https://github.com/pymc-devs/pymc/issues/4043"""
      x = np.random.randn(10) + 10.0
      x = np.concatenate([x, [np.nan], [np.nan]])
      x = np.ma.masked_array(x, np.isnan(x))
  
      with pm.Model() as model:
          a = pm.Normal("a")
          with pytest.warns(ImputationWarning):
              pm.Normal("L", a, 1.0, observed=x)
  
      compute_graph = {
          "a": set(),
          "L_unobserved": {"a"},
          "L_observed": {"a"},
          "L": {"L_unobserved", "L_observed"},
      }
      plates = {
          "": {"a"},
          "2": {"L_unobserved"},
          "10": {"L_observed"},
          "12": {"L"},
      }
      return model, compute_graph, plates
  
imports: import warnings
  import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  from pytensor.compile.sharedvalue import SharedVariable
  from pytensor.tensor.variable import TensorConstant
  import pymc
  from pymc.exceptions import ImputationWarning
  from pymc.model_graph import ModelGraph, model_to_graphviz, model_to_networkx
label_desc: Use image node_id 3 for calling a global function with example usage: model_with_imputations() and returns: model,  compute_graph,  plates