code: def model() -> GPModel:
      data = (
          cs(np.random.randn(Data.num_data, 2), "[N, 2]"),
          cs(np.random.randn(Data.num_data, 2), "[N, 2]"),
      )
      kernel = gpflow.kernels.SquaredExponential(
          lengthscales=[1.0, 2.0]
      )
      return GPR(data, kernel, noise_variance=0.01)
  
imports: from pathlib import Path
  from typing import Any, List, Optional, Sequence, Union
  import numpy
  import pytest
  import tensorflow
  from _pytest.capture import CaptureFixture
  from check_shapes import check_shape
  from check_shapes import check_shapes
  from matplotlib.axes import Axes
  from matplotlib.figure import Figure
  import gpflow
  from gpflow.base import AnyNDArray
  from gpflow.models import GPR, GPModel
  from gpflow.monitor import ExecuteCallback, ImageToTensorBoard, ModelToTensorBoard, Monitor, MonitorTask, MonitorTaskGroup, ScalarToTensorBoard
label_desc: Use image node_id 1 for calling a global function with example usage: model() and returns: GPR