code: def test_table_to_pandas(dtype, dummy_value):
      features = datasets.Features(
          {"foo": datasets.Array2D(dtype=dtype, shape=(2, 2))}
      )
      dataset = datasets.Dataset.from_dict(
          {"foo": [[[dummy_value] * 2] * 2]}, features=features
      )
      df = dataset._data.to_pandas()
      assert type(df.foo.dtype) == PandasArrayExtensionDtype
      arr = df.foo.to_numpy()
      np.testing.assert_equal(
          arr,
          np.array([[[dummy_value] * 2] * 2], dtype=np.dtype(dtype)),
      )
  
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 3 for calling a global function with example usage: test_table_to_pandas(dtype, dummy_value) without return types