code: def trainSparseModel(
      Xtrain, Ytrain, exact_model, isFITC, Xtest, Ytest
  ):
      sparse_model = getSparseModel(Xtrain, Ytrain, isFITC)
      sparse_model.likelihood.variance = (
          exact_model.likelihood.variance.numpy()
      )
      sparse_model.kern.lengthscales = (
          exact_model.kern.lengthscales.numpy()
      )
      sparse_model.kern.variance = exact_model.kern.variance.numpy()
      return sparse_model, repeatMinimization(
          sparse_model, Xtest, Ytest
      )
  
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 10 for calling a global function with example usage: trainSparseModel(Xtrain, Ytrain, exact_model, isFITC, Xtest, Ytest) and returns: sparse_model,  repeatMinimization