code: def base_input_df():
      return pd.DataFrame(
          {
              "x1": [1.3, 1.0, 1.8, -0.1, 0.0, 1.0, 2.2, 0.4, -5.0],
              "x2": [10, 4, 15, 6, 5, 12, 14, 5, 12],
              "treatment": [
                  "A",
                  "B",
                  "A",
                  "A",
                  "B",
                  "control",
                  "control",
                  "B",
                  "control",
              ],
              "target": [1, 1, 1, 0, 0, 1, 0, 0, 1],
          }
      )
  
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 1 for calling a global function with example usage: base_input_df() and returns: pd