code: def dataset():
      np.random.seed(42)
      n = 100
      inputs = np.concatenate(
          [np.ones((n, 1)), np.random.normal(0, 1, (n, 1))], axis=1
      )
      targets = 3.1 * inputs[:, 0] + 2.0 * inputs[:, 1]
      return inputs, targets
  
file_path: scikit-lego/tests/test_estimators/test_deadzone.py
imports: import numpy
  import pytest
  from sklego.linear_model import DeadZoneRegressor
  from sklego.testing import check_shape_remains_same_regressor
label_desc: Use image node_id 1 for calling a global function with example usage: dataset() and returns: inputs,  targets