code: def sgpr_model(
      dummy_data: Tuple[InputData, InputData, OutputData]
  ) -> SGPR:
      X, _, Y = dummy_data
      return SGPR(
          data=(X, Y),
          kernel=KERNEL,
          inducing_variable=InducingPoints(Z),
          mean_function=MEAN_FUNCTION,
      )
  
file_path: GPflow/tests/gpflow/models/test_sgpr_posterior.py
imports: from typing import Tuple
  import numpy
  import pytest
  import tensorflow
  from check_shapes import check_shapes
  import gpflow
  from gpflow.base import InputData, OutputData
  from gpflow.inducing_variables import InducingPoints
  from gpflow.models.sgpr import SGPR, SGPR_deprecated
  from gpflow.posteriors import PrecomputeCacheType
label_desc: Use image node_id 3 for calling a global function with example usage: sgpr_model(dummy_data) and returns: SGPR