code: def test_zero_covariance_x():
      """Tests zero covariance variables are zero in corresponding CP_PLSR
      factor
      """
      x, y, _, _ = _get_standard_synthetic()
      x = np.copy(
          tl.to_numpy(x)
      )  # workaround to make this work for all backends
      x[:, 0, :] = 1
      x = tl.tensor(x, **tl.context(y))
      pls = CP_PLSR(N_LATENT)
      pls.fit(x, y)
  
      assert_allclose(pls.X_factors[1][0, :], 0, atol=1e-6)
  
imports: import numpy
  import pytest
  import tensorly
  from ...testing import assert_allclose
  from ...cp_tensor import CPTensor, cp_normalize, cp_to_tensor
  from ...metrics.factors import congruence_coefficient
  from ...random import random_cp
  from ..cp_plsr import CP_PLSR
label_desc: Use image node_id 8 for calling a global function with example usage: test_zero_covariance_x() without return types