code: def test_small_q_sqrt_handeled_correctly(
      gpr_and_vgp: Tuple[GPR, VGP], data: Tuple[tf.Tensor, tf.Tensor]
  ) -> None:
      """
      This is an extra test to make sure things still work when q_sqrt is small.
      This was breaking (#767)
      """
      gpr, vgp = gpr_and_vgp
      vgp.q_mu.assign(np.random.randn(data[0].shape[0], 1))
      vgp.q_sqrt.assign(np.eye(data[0].shape[0])[None, :, :] * 1e-3)
      assert_gpr_vs_vgp(gpr, vgp)
  
imports: from typing import Any, Optional, Tuple
  import numpy
  import pytest
  import tensorflow
  from check_shapes import check_shapes
  import gpflow
  from gpflow import set_trainable
  from gpflow.config import default_float
  from gpflow.kernels import Kernel, SquaredExponential
  from gpflow.likelihoods import Gaussian, Likelihood
  from gpflow.models import GPR, SGPR, SVGP, VGP, BayesianModel
  from gpflow.optimizers import NaturalGradient
label_desc: Use image node_id 11 for calling a global function with example usage: test_small_q_sqrt_handeled_correctly(gpr_and_vgp, data) without return types