code: def test_predict_pass():
      X = np.array([[1], [2], [3]])
      y = np.array([1.0, 2.0, 3.0])
      est = BlankRegressor()
      est.fit(X, y)
      est.predict(X)
  
file_path: mlxtend/mlxtend/_base/tests/test_regressor.py
imports: import numpy
  from mlxtend._base import _BaseModel, _Regressor
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 4 for calling a global function with example usage: test_predict_pass() without return types