code: def test_pd_as_tensor_variable_multiindex() -> None:
      tuples = [("L", "Q"), ("L", "I"), ("O", "L"), ("O", "I")]
  
      index = pd.MultiIndex.from_tuples(tuples, names=["Id1", "Id2"])
  
      df = pd.DataFrame(
          {
              "A": [12.0, 80.0, 30.0, 20.0],
              "B": [120.0, 700.0, 30.0, 20.0],
          },
          index=index,
      )
      np_array = np.array(
          [[12.0, 80.0, 30.0, 20.0], [120.0, 700.0, 30.0, 20.0]]
      ).T
      assert isinstance(df.index, pd.MultiIndex)
      np.testing.assert_array_equal(
          x=pt.as_tensor_variable(x=df).eval(), y=np_array
      )
  
imports: import warnings
  import numpy
  import numpy.ma
  import numpy.testing
  import pandas
  import pytensor
  import pytensor.tensor
  import pytest
  import scipy.sparse
  from pytensor import scan, shared
  from pytensor.compile import UnusedInputError
  from pytensor.compile.builders import OpFromGraph
  from pytensor.graph.basic import Variable
  from pytensor.tensor.random.basic import normal, uniform
  from pytensor.tensor.random.var import RandomStateSharedVariable
  from pytensor.tensor.subtensor import AdvancedIncSubtensor, AdvancedIncSubtensor1
  from pytensor.tensor.variable import TensorVariable
  import pymc
  from pymc.distributions.dist_math import check_parameters
  from pymc.distributions.distribution import SymbolicRandomVariable
  from pymc.exceptions import NotConstantValueError
  from pymc.logprob.utils import ParameterValueError
  from pymc.pytensorf import collect_default_updates, compile_pymc, constant_fold, convert_observed_data, extract_obs_data, replace_rng_nodes, replace_vars_in_graphs, reseed_rngs, walk_model
  from pymc.vartypes import int_types
label_desc: Use image node_id 3 for calling a global function with example usage: test_pd_as_tensor_variable_multiindex() without return types