code: def test_date_object_to_list(date_obj, date_obj_vec, fill_value):
      """Test support for datetime.date object conversion.
  
      Args:
          date_obj: Date object to convert into a vector
          date_obj_vector: Expected vector version of `date_obj`
      """
      computed_date_vec = date_feature.DateInputFeature.date_to_list(
          date_obj,
          None,
          preprocessing_parameters={
              MISSING_VALUE_STRATEGY: FILL_WITH_CONST,
              "fill_value": fill_value,
          },
      )
      assert computed_date_vec == date_obj_vec
  
imports: from copy import deepcopy
  from datetime import date, datetime
  from typing import Any, List
  import pytest
  import torch
  from dateutil.parser import parse
  from ludwig.constants import ENCODER_OUTPUT, FILL_WITH_CONST, MISSING_VALUE_STRATEGY
  from ludwig.features import date_feature
  from ludwig.features.date_feature import DateInputFeature
  from ludwig.schema.features.date_feature import DateInputFeatureConfig
  from ludwig.schema.utils import load_config_with_kwargs
  from ludwig.types import FeatureConfigDict
  from ludwig.utils.date_utils import create_vector_from_datetime_obj
  from ludwig.utils.misc_utils import merge_dict
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 12 for calling a global function with example usage: test_date_object_to_list(date_obj, date_obj_vec, fill_value) without return types