code: def sample_approx(approx, draws=100, include_transformed=True):
      """Draw samples from variational posterior.
  
      Parameters
      ----------
      approx: :class:`Approximation`
          Approximation to sample from
      draws: `int`
          Number of random samples.
      include_transformed: `bool`
          If True, transformed variables are also sampled. Default is True.
  
      Returns
      -------
      trace: class:`pymc.backends.base.MultiTrace`
          Samples drawn from variational posterior.
      """
      return approx.sample(
          draws=draws, include_transformed=include_transformed
      )
  
imports: from typing import Optional
  import numpy
  import pytensor
  from arviz import InferenceData
  from pytensor import tensor
  from pytensor.graph.basic import Variable
  from pytensor.graph.replace import graph_replace
  from pytensor.tensor.variable import TensorVariable
  import pymc
  from pymc.blocking import DictToArrayBijection
  from pymc.distributions.dist_math import rho2sigma
  from pymc.util import makeiter
  from pymc.variational import opvi
  from pymc.variational.opvi import Approximation, Group, NotImplementedInference, _known_scan_ignored_inputs, node_property
label_desc: Use image node_id 1 for calling a global function with example usage: sample_approx(approx, draws, include_transformed) and returns: approx