code: def svgp(data: RegressionData) -> GPModel:
      return SVGP(
          kernel=create_kernel(),
          likelihood=create_linear_noise(),
          inducing_variable=create_inducing(),
      )
  
imports: from typing import Callable
  import numpy
  import pytest
  from check_shapes import ShapeChecker
  import gpflow
  from gpflow import default_float
  from gpflow.base import AnyNDArray, RegressionData
  from gpflow.functions import Linear
  from gpflow.kernels import Kernel
  from gpflow.likelihoods import Gaussian
  from gpflow.models import GPR, GPRFITC, SGPR, SVGP, VGP, GPModel, training_loss_closure
  from gpflow.models.util import InducingPointsLike
label_desc: Use image node_id 8 for calling a global function with example usage: svgp(data) and returns: SVGP