code: def _create_full_gp_model() -> gpflow.models.GPR:
      """
      GP Regression
      """
      full_gp_model = gpflow.models.GPR(
          (Datum.X, Datum.Y),
          kernel=gpflow.kernels.SquaredExponential(),
          mean_function=gpflow.mean_functions.Constant(),
      )
      return full_gp_model
  
imports: from typing import Optional, Tuple
  import numpy
  import pytest
  from check_shapes import ShapeChecker
  from numpy.testing import assert_allclose
  import gpflow
  from gpflow.base import AnyNDArray, TensorType
  from gpflow.config import default_jitter
  from gpflow.kernels import Kernel
  from gpflow.likelihoods import Likelihood
  from gpflow.mean_functions import Constant
  from gpflow.models import GPModel, maximum_log_likelihood_objective, training_loss_closure
label_desc: Use image node_id 1 for calling a global function with example usage: _create_full_gp_model() and returns: full_gp_model