code: def get_array_feature_types():
      shape_1 = [3] * 5
      shape_2 = [3, 4, 5, 6, 7]
      return [
          {
              "testcase_name": f"{d}d",
              "array_feature": array_feature,
              "shape_1": tuple(shape_1[:d]),
              "shape_2": tuple(shape_2[:d]),
          }
          for d, array_feature in zip(
              range(2, 6), [Array2D, Array3D, Array4D, Array5D]
          )
      ]
  
imports: import os
  import random
  import tempfile
  import unittest
  import numpy
  import pandas
  import pyarrow
  import pytest
  from absl.testing import parameterized
  import datasets
  from datasets.arrow_writer import ArrowWriter
  from datasets.features import Array2D, Array3D, Array4D, Array5D, Value
  from datasets.features.features import Array3DExtensionType, PandasArrayExtensionDtype, _ArrayXD
  from datasets.formatting.formatting import NumpyArrowExtractor, SimpleArrowExtractor
label_desc: Use image node_id 2 for calling a global function with example usage: get_array_feature_types() and returns: unknown