code: def create_model() -> gpflow.models.GPModel:
      return gpflow.models.GPR(
          Datum.data,
          gpflow.kernels.SquaredExponential(),
          noise_variance=Datum.noise_scale**2,
      )
  
file_path: GPflow/tests/gpflow/utilities/test_training_loop.py
imports: from typing import Any
  import numpy
  import tensorflow
  from check_shapes import ShapeChecker
  import gpflow
  from gpflow.utilities import training_loop
label_desc: Use image node_id 1 for calling a global function with example usage: create_model() and returns: gpflow