code: def test_elastic_net_default(datatype, nrows, column_info):
      ncols, n_info = column_info
      X, y = make_regression(
          n_samples=nrows,
          n_features=ncols,
          n_informative=n_info,
          random_state=0,
      )
      X = X.astype(datatype)
      y = y.astype(datatype)
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, train_size=0.8, random_state=0
      )
  
      elastic_cu = cuElasticNet()
      elastic_cu.fit(X_train, y_train)
      cu_predict = elastic_cu.predict(X_test)
      cu_r2 = r2_score(y_test, cu_predict)
  
      elastic_sk = ElasticNet()
      elastic_sk.fit(X_train, y_train)
      sk_predict = elastic_sk.predict(X_test)
      sk_r2 = r2_score(y_test, sk_predict)
      assert cu_r2 >= sk_r2 - 0.07
  
file_path: cuml/python/cuml/tests/test_coordinate_descent.py
imports: from sklearn.model_selection import train_test_split
  from sklearn.datasets import make_regression
  from sklearn.linear_model import Lasso, ElasticNet
  from cuml.testing.utils import unit_param, quality_param, stress_param
  from cuml.metrics import r2_score
  from cuml.linear_model import ElasticNet
  from cuml import Lasso
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 5 for calling a global function with example usage: test_elastic_net_default(datatype, nrows, column_info) without return types