code: def _good_gradients(preds, _):
      return np.random.randn(*preds.shape), np.random.rand(*preds.shape)
  
imports: import filecmp
  import numbers
  import re
  from copy import deepcopy
  from os import getenv
  from pathlib import Path
  import numpy
  import pytest
  from scipy import sparse
  from sklearn.datasets import dump_svmlight_file, load_svmlight_file
  from sklearn.model_selection import train_test_split
  import lightgbm
  from lightgbm.compat import PANDAS_INSTALLED, pd_DataFrame, pd_Series
  from .utils import dummy_obj, load_breast_cancer, mse_obj, np_assert_array_equal
label_desc: Use image node_id 27 for calling a global function with example usage: _good_gradients(preds, _) and returns: np,  np