code: def test_get_learners(mock_get_model_fcn):
      """
      Test if it is receiving a list of treatments and is returning a dict
      of learners.
      """
      unique_treatments = ["treatment_a", "treatment_b", "treatment_c"]
  
      mock_get_model_fcn.side_effect = [
          ("mocked_control_fcn", None, None),
          ("mocked_treatment_fcn_filtering_treatment_a", None, None),
          ("mocked_treatment_fcn_filtering_treatment_b", None, None),
          ("mocked_treatment_fcn_filtering_treatment_c", None, None),
      ]
  
      learners, logs = _get_learners(
          df="mocked_df",
          unique_treatments=unique_treatments,
          treatment_col="treatment",
          control_name="control",
          control_learner="mocked_control_fcn",
          treatment_learner="mocked_treatment_fcn",
      )
  
      assert learners["control"] == "mocked_control_fcn"
      assert (
          learners["treatment_a"]
          == "mocked_treatment_fcn_filtering_treatment_a"
      )
      assert (
          learners["treatment_b"]
          == "mocked_treatment_fcn_filtering_treatment_b"
      )
      assert (
          learners["treatment_c"]
          == "mocked_treatment_fcn_filtering_treatment_c"
      )
      assert isinstance(learners, dict)
      assert isinstance(logs, dict)
  
      calls = [
          call(
              "mocked_df", "treatment", "control", "mocked_control_fcn"
          ),
          call(
              "mocked_df",
              "treatment",
              "treatment_a",
              "mocked_treatment_fcn",
          ),
          call(
              "mocked_df",
              "treatment",
              "treatment_b",
              "mocked_treatment_fcn",
          ),
          call(
              "mocked_df",
              "treatment",
              "treatment_c",
              "mocked_treatment_fcn",
          ),
      ]
  
      mock_get_model_fcn.assert_has_calls(calls)
  
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 18 for calling a global function with example usage: test_get_learners(mock_get_model_fcn) without return types