code: def RMSE(y_true, y_pred, axis=None):
      """Returns the regularised mean squared error between the two predictions
      (the square-root is applied to the mean_squared_error)
  
      Parameters
      ----------
      y_true : array of shape (n_samples, )
          Ground truth (correct) target values.
      y_pred : array of shape (n_samples, )
          Estimated target values.
  
      Returns
      -------
      float
      """
      return T.sqrt(MSE(y_true, y_pred, axis=axis))
  
file_path: tensorly/tensorly/metrics/regression.py
imports: from ..None import backend
label_desc: Use image node_id 2 for calling a global function with example usage: RMSE(y_true, y_pred, axis) and returns: T