code: def iternumpy(key1, value1, value2):
      if value1.dtype != value2.dtype:  # check only for dtype
          raise AssertionError(
              f"dtype of '{key1}' key for casted object: {value1.dtype} and expected object: {value2.dtype} not matching"
          )
  
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 9 for calling a global function with example usage: iternumpy(key1, value1, value2) without return types