code: def test_covariances_kwds(estimator, kwds, rndstate):
      n_matrices, n_channels, n_times = 3, 3, 100
      x = rndstate.randn(n_matrices, n_channels, n_times) + 1
      covs_none = Covariances(estimator=estimator).fit_transform(x)
      covs_kwds = Covariances(
          estimator=estimator, **kwds
      ).fit_transform(x)
      assert_raises(
          AssertionError, assert_array_equal, covs_none, covs_kwds
      )
  
imports: import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal, assert_raises
  import pytest
  from pyriemann.estimation import Covariances, ERPCovariances, XdawnCovariances, CospCovariances, HankelCovariances, Coherences, Shrinkage, BlockCovariances, Kernels
  from pyriemann.utils.test import is_sym_pos_def, is_sym_pos_semi_def
label_desc: Use image node_id 2 for calling a global function with example usage: test_covariances_kwds(estimator, kwds, rndstate) without return types