code: def test_cast_to_python_or_numpy(self):
      obj = {
          "col_1": [{"vec": np.arange(1, 4), "txt": "foo"}] * 3,
          "col_2": np.arange(1, 7).reshape(3, 2),
      }
      expected_obj = {
          "col_1": [{"vec": np.array([1, 2, 3]), "txt": "foo"}] * 3,
          "col_2": np.array([[1, 2], [3, 4], [5, 6]]),
      }
      casted_obj = cast_to_python_objects(obj)
      dict_diff(casted_obj, expected_obj)
  
imports: import datetime
  from unittest import TestCase
  from unittest.mock import patch
  import numpy
  import pandas
  import pyarrow
  import pytest
  from datasets import Array2D
  from datasets.arrow_dataset import Dataset
  from datasets.features import Audio, ClassLabel, Features, Image, Sequence, Value
  from datasets.features.features import _arrow_to_datasets_dtype, _cast_to_python_objects, cast_to_python_objects, encode_nested_example, generate_from_dict, string_to_arrow
  from datasets.features.translation import Translation, TranslationVariableLanguages
  from datasets.info import DatasetInfo
  from datasets.utils.py_utils import asdict
  from ..utils import require_jax, require_tf, require_torch
label_desc: Use image node_id 3 for calling the CastToPythonObjectsTest obj's underlying member method code with example usage: obj.test_cast_to_python_or_numpy() without return types