code: def _eval_iter(self, model, cuda=False):
      inducing_batch_shape = (
          model.variational_strategy.inducing_points.shape[:-2]
      )
      test_x = torch.randn(*inducing_batch_shape, 32, 2).clamp(
          -2.5, 2.5
      )
      if cuda:
          test_x = test_x.cuda()
          model = model.cuda()
  
      # Single optimization iteration
      model.eval()
      with torch.no_grad():
          output = model(test_x)
  
      return output
  
imports: import unittest
  import torch
  import gpytorch
  from gpytorch.test.variational_test_case import VariationalTestCase
label_desc: Use image node_id 9 for calling the TestVNNGP obj's underlying member method code with example usage: obj._eval_iter(model, cuda) and returns: output