code: def test_random_under_sampling_datetime():
      """Check that we don't convert input data and only sample from it."""
      pd = pytest.importorskip("pandas")
      X = pd.DataFrame(
          {"label": [0, 0, 0, 1], "td": [datetime.now()] * 4}
      )
      y = X["label"]
      rus = RandomUnderSampler(random_state=0)
      X_res, y_res = rus.fit_resample(X, y)
  
      pd.testing.assert_series_equal(X_res.dtypes, X.dtypes)
      pd.testing.assert_index_equal(X_res.index, y_res.index)
      assert_array_equal(y_res.to_numpy(), np.array([0, 1]))
  
file_path: imbalanced-learn/imblearn/under_sampling/_prototype_selection/tests/test_random_under_sampler.py
imports: from collections import Counter
  from datetime import datetime
  import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.utils._testing import assert_array_equal
  from imblearn.under_sampling import RandomUnderSampler
label_desc: Use image node_id 7 for calling a global function with example usage: test_random_under_sampling_datetime() without return types