code: def test_Cov3FactorKron(seeded_rng):
      assert m % 4 == 0
      dim1 = int(m / 4)
      dim2 = 2
      dim3 = 2
      cov = CovKroneckerFactored(sizes=[dim1, dim2, dim3])
  
      L1 = (cov.L[0]).numpy()
      L2 = (cov.L[1]).numpy()
      L3 = (cov.L[2]).numpy()
      cov_np = np.kron(
          np.kron(
              np.dot(L1, L1.transpose()), np.dot(L2, L2.transpose())
          ),
          np.dot(L3, L3.transpose()),
      )
      logdet_np, sinv_np, sinvx_np = logdet_sinv_np(X, cov_np)
  
      assert_allclose(logdet_np, cov.logdet, rtol=rtol)
      assert_allclose(sinv_np, cov.solve(eye), rtol=rtol)
      assert_allclose(sinvx_np, cov.solve(X_tf), rtol=rtol)
  
imports: import pytest
  import numpy
  from numpy.testing import assert_allclose
  from scipy.stats import norm, wishart, invgamma, invwishart
  import tensorflow
  from brainiak.matnormal.covs import CovIdentity, CovAR1, CovIsotropic, CovDiagonal, CovDiagonalGammaPrior, CovUnconstrainedCholesky, CovUnconstrainedCholeskyWishartReg, CovUnconstrainedInvCholesky, CovKroneckerFactored
label_desc: Use image node_id 13 for calling a global function with example usage: test_Cov3FactorKron(seeded_rng) without return types