code: def create_vgp(data: RegressionData) -> VGP:
      return VGP(
          data=data,
          kernel=create_kernel(),
          likelihood=create_likelihood(),
      )
  
imports: from typing import Any, Callable, DefaultDict, Generic, Iterator, List, Set, Tuple, Type, TypeVar, cast
  import numpy
  import pytest
  import tensorflow
  from _pytest.fixtures import SubRequest
  from check_shapes import check_shapes
  import gpflow
  from gpflow.base import RegressionData
  from gpflow.config import default_float
  from gpflow.inducing_variables import InducingPoints, InducingVariables
  from gpflow.kernels import Kernel, Matern52
  from gpflow.likelihoods import Exponential, Likelihood
  from gpflow.models import GPR, SGPR, SVGP, VGP, GPModel, training_loss_closure
  from gpflow.models.vgp import update_vgp_data
  from gpflow.posteriors import AbstractPosterior, PrecomputeCacheType
label_desc: Use image node_id 9 for calling a global function with example usage: create_vgp(data) and returns: VGP