code: def test_tensor_array_ops():
      outer_dim = 3
      inner_shape = (2, 2, 2)
      shape = (outer_dim,) + inner_shape
      num_items = np.prod(np.array(shape))
      arr = np.arange(num_items).reshape(shape)
  
      df = pd.DataFrame({"one": [1, 2, 3], "two": TensorArray(arr)})
  
      def apply_arithmetic_ops(arr):
          return 2 * (arr + 1) / 3
  
      def apply_comparison_ops(arr):
          return arr % 2 == 0
  
      def apply_logical_ops(arr):
          return arr & (3 * arr) | (5 * arr)
  
      # Op tests, using NumPy as the groundtruth.
      np.testing.assert_equal(
          apply_arithmetic_ops(arr), apply_arithmetic_ops(df["two"])
      )
  
      np.testing.assert_equal(
          apply_comparison_ops(arr), apply_comparison_ops(df["two"])
      )
  
      np.testing.assert_equal(
          apply_logical_ops(arr), apply_logical_ops(df["two"])
      )
  
imports: import itertools
  import numpy
  import pandas
  from packaging.version import parse
  import pyarrow
  import pytest
  from ray.air.util.tensor_extensions.arrow import ArrowTensorArray, ArrowTensorType, ArrowVariableShapedTensorArray, ArrowVariableShapedTensorType
  from ray.air.util.tensor_extensions.pandas import TensorArray, TensorDtype
  from ray.air.util.tensor_extensions.utils import create_ragged_ndarray
  from ray._private.utils import _get_pyarrow_version
label_desc: Use image node_id 15 for calling a global function with example usage: test_tensor_array_ops() and returns: unknown, unknown, unknown