code: def getRegressionModel(X, Y):
      m = gpflow.models.GPR(X, Y, kern=getKernel())
      m.likelihood.variance = 1.0
      m.kern.lengthscales = 1.0
      m.kern.variance = 1.0
      return m
  
file_path: GPflow/doc/sphinx/notebooks/theory/FITCvsVFE.py
imports: import numpy
  import tensorflow
  import gpflow
  from gpflow.ci_utils import reduce_in_tests
label_desc: Use image node_id 5 for calling a global function with example usage: getRegressionModel(X, Y) and returns: m