code: def test__create_treatment_flag_multiple_treatments():
      with pytest.raises(Exception) as e:
          df = pd.DataFrame(
              {
                  "feature": [1.0, 4.0, 1.0, 5.0, 3.0],
                  "treatment": [
                      "treatment_A",
                      "treatment_C",
                      "treatment_B",
                      "treatment_A",
                      "control",
                  ],
                  "target": [1, 1, 0, 0, 1],
              }
          )
  
          _create_treatment_flag(
              df,
              treatment_col="treatment",
              treatment_name="treatment_A",
              control_name="control",
          )
  
      assert e.type == MultipleTreatmentsError
      assert e.value.args[0] == "Data contains multiple treatments."
  
imports: from typing import Callable
  from unittest.mock import MagicMock, call, create_autospec, patch
  import numpy
  import pandas
  import pytest
  from pandas import DataFrame
  from pandas.testing import assert_frame_equal
  from fklearn.causal.cate_learning.meta_learners import TREATMENT_FEATURE, _append_treatment_feature, _create_treatment_flag, _filter_by_treatment, _fit_by_treatment, _get_learners, _get_model_fcn, _get_unique_treatments, _predict_by_treatment_flag, _simulate_t_learner_treatment_effect, _simulate_treatment_effect, causal_s_classification_learner, causal_t_classification_learner
  from fklearn.exceptions.exceptions import MissingControlError, MissingTreatmentError, MultipleTreatmentsError
  from fklearn.training.classification import logistic_classification_learner
  from fklearn.types import LearnerFnType
label_desc: Use image node_id 7 for calling a global function with example usage: test__create_treatment_flag_multiple_treatments() without return types