code: def test_FromMultipleDataMismatchedTypes(self) -> None:
      # create two custom data types
      CustomDataA = custom_data_class(
          column_data_types={
              "metadata": str,
              "created_time": pd.Timestamp,
          },
          required_columns={"metadata"},
      )
  
      CustomDataB = custom_data_class(
          column_data_types={"year": pd.Timestamp}
      )
  
      # Test data of multiple empty custom types raises a value error
      with self.assertRaises(ValueError):
          Data.from_multiple_data([CustomDataA(), CustomDataB()])
  
      # Test data of multiple non-empty types raises a value error
      with self.assertRaises(ValueError):
          data_elt_A = CustomDataA(
              df=pd.DataFrame(
                  [
                      {
                          "arm_name": "0_1",
                          "mean": 3.7,
                          "sem": 0.5,
                          "metric_name": "b",
                          "metadata": "42",
                          "created_time": "2018-09-20",
                      }
                  ]
              )
          )
          data_elt_B = CustomDataB(
              df=pd.DataFrame(
                  [
                      {
                          "arm_name": "0_1",
                          "mean": 3.7,
                          "sem": 0.5,
                          "metric_name": "b",
                          "year": "2018-09-20",
                      }
                  ]
              )
          )
          Data.from_multiple_data([data_elt_A, data_elt_B])
  
imports: import random
  import pandas
  from ax.core.data import clone_without_metrics, custom_data_class, Data, set_single_trial
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.timeutils import current_timestamp_in_millis
label_desc: Use image node_id 11 for calling the DataTest obj's underlying member method code with example usage: obj.test_FromMultipleDataMismatchedTypes() without return types