code: def linear(x):
      """
      First order polynomial (linear, p = n+1) regression model.
  
      x --> f(x) = [ 1, x_1, ..., x_n ].T
  
      Parameters
      ----------
      x : array_like
          An array with shape (n_eval, n_features) giving the locations x at
          which the regression model should be evaluated.
  
      Returns
      -------
      f : array_like
          An array with shape (n_eval, p) with the values of the regression
          model.
      """
      x = np.asarray(x, dtype=np.float64)
      n_eval = x.shape[0]
      f = np.hstack([np.ones([n_eval, 1]), x])
      return f
  
label_desc: Use image node_id 2 for calling a global function with example usage: linear(x) and returns: f