code: def create_model() -> gpflow.models.GPModel:
      kernel = create_kernel()
      model = gpflow.models.SVGP(
          kernel=kernel,
          likelihood=gpflow.likelihoods.Gaussian(
              variance_lower_bound=0.0
          ),
          inducing_variable=Data.Z,
          q_diag=True,
      )
      set_trainable(model.q_mu, False)
      return model
  
imports: from typing import Any, Callable, Mapping, Optional, Type
  import numpy
  import pytest
  import tensorflow
  from _pytest.fixtures import SubRequest
  from packaging.version import Version
  import gpflow
  from gpflow.base import AnyNDArray
  from gpflow.config import Config, as_context
  from gpflow.utilities import set_trainable
  from gpflow.utilities.traversal import _merge_leaf_components, leaf_components, tabulate_module_summary
label_desc: Use image node_id 3 for calling a global function with example usage: create_model() and returns: model