code: def test_switched_likelihood_regression_valid_num_latent_gps(
      num_latent_gps: int,
  ) -> None:
      """
      A Regression test when using Switched likelihood: the number of latent
      functions in a GP model must be equal to the number of columns in Y minus
      one. The final column of Y is used to index the switch. If the number of
      latent functions does not match, an exception will be raised.
      """
      x = np.random.randn(100, 1)
      y: AnyNDArray = np.hstack(
          (np.random.randn(100, 1), np.random.randint(0, 3, (100, 1)))
      )
      data = x, y
  
      Z = InducingPoints(np.random.randn(num_latent_gps, 1))
      likelihoods = [StudentT()] * 3
      switched_likelihood = SwitchedLikelihood(likelihoods)
      m = gpflow.models.SVGP(
          kernel=gpflow.kernels.Matern12(),
          inducing_variable=Z,
          likelihood=switched_likelihood,
          num_latent_gps=num_latent_gps,
      )
      m.training_loss(data)
  
file_path: GPflow/tests/gpflow/likelihoods/test_switched_likelihood.py
imports: from typing import Sequence
  import numpy
  import pytest
  import tensorflow
  from numpy.testing import assert_allclose
  import gpflow
  from gpflow.base import AnyNDArray, Parameter, TensorType
  from gpflow.inducing_variables import InducingPoints
  from gpflow.likelihoods import Gaussian, StudentT, SwitchedLikelihood
label_desc: Use image node_id 5 for calling a global function with example usage: test_switched_likelihood_regression_valid_num_latent_gps(num_latent_gps) without return types