code: def test_predict_y() -> None:
      vgp0, vgp1, cvgp = _prepare_models()
      mu1, var1 = vgp0.predict_y(Datum.Xtest)
      c_mu1, c_var1 = cvgp.predict_y(
          np.hstack([Datum.Xtest, np.zeros((Datum.Xtest.shape[0], 1))])
      )
  
      # predict_y returns results for all the likelihoods in multi_likelihood
      assert_allclose(mu1, c_mu1[:, :1], atol=1.0e-4)
      assert_allclose(var1, c_var1[:, :1], atol=1.0e-4)
  
      mu2, var2 = vgp1.predict_y(Datum.Xtest)
      c_mu2, c_var2 = cvgp.predict_y(
          np.hstack([Datum.Xtest, np.ones((Datum.Xtest.shape[0], 1))])
      )
  
      # predict_y returns results for all the likelihoods in multi_likelihood
      assert_allclose(mu2, c_mu2[:, 1:2], atol=1.0e-4)
      assert_allclose(var2, c_var2[:, 1:2], atol=1.0e-4)
  
file_path: GPflow/tests/gpflow/kernels/test_coregion.py
imports: from typing import Sequence, Tuple
  import numpy
  from check_shapes import ShapeChecker
  from numpy.testing import assert_allclose
  import gpflow
  from gpflow import set_trainable
  from gpflow.base import AnyNDArray
  from gpflow.mean_functions import Constant
  from gpflow.models import VGP
label_desc: Use image node_id 6 for calling a global function with example usage: test_predict_y() without return types