code: def optimize_model_with_scipy(model):
      optimizer = gpf.optimizers.Scipy()
      optimizer.minimize(
          model.training_loss_closure(data),
          variables=model.trainable_variables,
          method="l-bfgs-b",
          options={"disp": 50, "maxiter": MAXITER},
      )
  
file_path: GPflow/notebooks/advanced/multioutput.pct.py
imports: import matplotlib.pyplot
  import numpy
  import gpflow
  from gpflow.ci_utils import reduce_in_tests
  from gpflow.utilities import print_summary
label_desc: Use image node_id 3 for calling a global function with example usage: optimize_model_with_scipy(model) without return types