code: def test_simple_datatype_converter(
      field, feature_type, int_dtype, float_dtype
  ):
      actual_feature = croissant_builder.datatype_converter(
          field,
          int_dtype=int_dtype if int_dtype else np.int64,
          float_dtype=float_dtype if float_dtype else np.float32,
      )
      assert actual_feature == feature_type
  
file_path: datasets/tensorflow_datasets/core/dataset_builders/croissant_builder_test.py
imports: import json
  import tempfile
  from etils import epath
  import numpy
  import pytest
  from tensorflow_datasets import testing
  from tensorflow_datasets.core import FileFormat
  from tensorflow_datasets.core.dataset_builders import croissant_builder
  from tensorflow_datasets.core.features import image_feature
  from tensorflow_datasets.core.features import text_feature
  from tensorflow_datasets.core.utils.lazy_imports_utils import mlcroissant
label_desc: Use image node_id 2 for calling a global function with example usage: test_simple_datatype_converter(field, feature_type, int_dtype, float_dtype) without return types