code: def test_non_parametric_double_ml_learner_curry():
      df_train = pd.DataFrame(
          dict(
              # TE = 1       TE = 2      TE = 3
              x1=[1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3],
              x2=[1, 2, 3, 1, 3, 1, 4, 1, 4, 1, 4, 1],
              t=[
                  1 + 1,
                  1 + 1,
                  2 + 1,
                  3 + 1,
                  1 + 2,
                  1 + 2,
                  2 + 2,
                  3 + 2,
                  1 + 3,
                  1 + 3,
                  2 + 3,
                  3 + 3,
              ],
              y=[
                  1 - 1,
                  1 - 1,
                  2 - 1,
                  3 - 1,
                  1 - 2,
                  1 - 2,
                  3 - 2,
                  5 - 2,
                  1 - 3,
                  1 - 3,
                  4 - 3,
                  7 - 3,
              ],
          )
      )
  
      np.random.seed(123)
  
      fit_fn = non_parametric_double_ml_learner(
          df=df_train,
          treatment_column="t",
          outcome_column="y",
          debias_model=RandomForestRegressor(),
          denoise_model=RandomForestRegressor(),
          final_model=RandomForestRegressor(),
          prediction_column="test_prediction",
      )
  
      m1, m1_df, _ = fit_fn(feature_columns=["x1"])
      m2, m2_df, _ = fit_fn(feature_columns=["x1", "x2"])
  
      pd.testing.assert_frame_equal(m1_df, m1(df_train))
      pd.testing.assert_frame_equal(m2_df, m2(df_train))
  
file_path: fklearn/tests/causal/cate_learning/test_double_machine_learning.py
imports: from collections import Counter
  import pandas
  import numpy
  from sklearn.ensemble import RandomForestRegressor
  from fklearn.causal.cate_learning.double_machine_learning import non_parametric_double_ml_learner, _cv_estimate
  from sklearn.linear_model import LinearRegression
label_desc: Use image node_id 3 for calling a global function with example usage: test_non_parametric_double_ml_learner_curry() without return types