code: def test_te_model_does_nothing_if_there_is_no_categorical_column_to_encode():
      ds = load_dataset()
      non_cat = {
          n for n, t in ds.train.types.items() if t in ["int", "real"]
      }
      to_encode = non_cat
      assert len(to_encode) > 0
      te = H2OTargetEncoderEstimator()
  
      te.train(x=to_encode, y=ds.target, training_frame=ds.train)
      transformed = te.transform(ds.train)
      assert transformed.names == ds.train.names
      assert transformed.key == ds.train.key
  
      encoded = te.predict(ds.train)
      assert encoded.names == ds.train.names
      assert encoded.key != ds.train.key
  
file_path: h2o-3/h2o-py/tests/testdir_algos/targetencoder/pyunit_targetencoder_training.py
imports: import os
  import sys
  import h2o
  from h2o.estimators import H2OTargetEncoderEstimator
  from h2o.exceptions import H2OResponseError
  from tests import pyunit_utils
label_desc: Use image node_id 5 for calling a global function with example usage: test_te_model_does_nothing_if_there_is_no_categorical_column_to_encode() without return types