code: def test_where_dt64_2d():
      dti = date_range("2016-01-01", periods=6)
      dta = dti._data.reshape(3, 2)
      other = dta - dta[0, 0]
  
      df = DataFrame(dta, columns=["A", "B"])
  
      mask = np.asarray(df.isna()).copy()
      mask[:, 1] = True
  
      # setting all of one column, none of the other
      expected = DataFrame({"A": other[:, 0], "B": dta[:, 1]})
      with tm.assert_produces_warning(
          FutureWarning, match="Setting an item of incompatible dtype"
      ):
          _check_where_equivalences(df, mask, other, expected)
  
      # setting part of one column, none of the other
      mask[1, 0] = True
      expected = DataFrame(
          {
              "A": np.array(
                  [other[0, 0], dta[1, 0], other[2, 0]], dtype=object
              ),
              "B": dta[:, 1],
          }
      )
      with tm.assert_produces_warning(
          FutureWarning, match="Setting an item of incompatible dtype"
      ):
          _check_where_equivalences(df, mask, other, expected)
  
      # setting nothing in either column
      mask[:] = True
      expected = df
      _check_where_equivalences(df, mask, other, expected)
  
imports: from datetime import datetime
  from hypothesis import given
  import numpy
  import pytest
  from pandas.core.dtypes.common import is_scalar
  import pandas
  from pandas import DataFrame, DatetimeIndex, Index, Series, StringDtype, Timestamp, date_range, isna
  import pandas._testing
  from pandas._testing._hypothesis import OPTIONAL_ONE_OF_ALL
label_desc: Use image node_id 15 for calling a global function with example usage: test_where_dt64_2d() without return types