code: def test_linear_regression_model_default_generalized(dataset):
      X_train, X_test, y_train, _ = dataset
  
      # Filter datasets based on required assumptions
      assume(sklearn_compatible_dataset(X_train, X_test, y_train))
      assume(cuml_compatible_dataset(X_train, X_test, y_train))
  
      # Initialization of cuML's linear regression model
      cuols = cuLinearRegression()
  
      # fit and predict cuml linear regression model
      cuols.fit(X_train, y_train)
      cuols_predict = cuols.predict(X_test)
  
      # sklearn linear regression model initialization and fit
      skols = skLinearRegression()
      skols.fit(X_train, y_train)
  
      skols_predict = skols.predict(X_test)
  
      target(float(array_difference(skols_predict, cuols_predict)))
      assert array_equal(
          skols_predict, cuols_predict, 1e-1, with_sign=True
      )
  
imports: from contextlib import nullcontext
  from distutils.version import LooseVersion
  from functools import lru_cache
  import pytest
  import sklearn
  from cuml.internals.array import elements_in_representable_range
  from cuml.internals.safe_imports import cpu_only_import, cpu_only_import_from, gpu_only_import
  from cuml.testing.strategies import regression_datasets, split_datasets, standard_classification_datasets, standard_regression_datasets
  from cuml.testing.utils import array_difference, array_equal, quality_param, small_classification_dataset, small_regression_dataset, stress_param, unit_param
  from hypothesis import assume, example, given, note
  from hypothesis import strategies
  from hypothesis import target
  from hypothesis.extra.numpy import floating_dtypes
  from sklearn.datasets import load_breast_cancer, load_digits, make_classification, make_regression
  from sklearn.linear_model import LinearRegression
  from sklearn.linear_model import LogisticRegression
  from sklearn.linear_model import Ridge
  from sklearn.model_selection import train_test_split
  from cuml import ElasticNet
  from cuml import LinearRegression
  from cuml import LogisticRegression
  from cuml import Ridge
label_desc: Use image node_id 11 for calling a global function with example usage: test_linear_regression_model_default_generalized(dataset) without return types