code: def test_causal_t_classification_learner(
      mock_get_unique_treatments,
      mock_get_learners,
      mock_simulate_t_learner_treatment_effect,
      base_input_df,
  ):
      mock_get_learners.side_effect = [([], dict())]
      mock_model = create_autospec(logistic_classification_learner)
  
      causal_t_classification_learner(
          df=base_input_df,
          treatment_col="treatment",
          control_name="control",
          prediction_column="prediction",
          learner=mock_model,
      )
  
      mock_get_unique_treatments.assert_called()
      mock_get_learners.assert_called()
      mock_simulate_t_learner_treatment_effect.assert_called()
  
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 19 for calling a global function with example usage: test_causal_t_classification_learner(mock_get_unique_treatments, mock_get_learners, mock_simulate_t_learner_treatment_effect, base_input_df) without return types