code: def test_gplvm_with_kernels(
      kernel: Optional[gpflow.kernels.Kernel],
  ) -> None:
      m = gpflow.models.GPLVM(Data.Y, Data.Q, kernel=kernel)
      lml_initial = m.log_marginal_likelihood()
      opt = gpflow.optimizers.Scipy()
      opt.minimize(
          m.training_loss,
          m.trainable_variables,
          options=dict(maxiter=2),
      )
      assert m.log_marginal_likelihood() > lml_initial
  
file_path: GPflow/tests/gpflow/models/test_gplvm.py
imports: from typing import Optional
  import numpy
  import pytest
  import gpflow
  from gpflow.utilities.ops import pca_reduce
label_desc: Use image node_id 1 for calling a global function with example usage: test_gplvm_with_kernels(kernel) without return types