c63cc933782e2de32c9fe74c18b337b2bbe0f242,test/examples/test_kissgp_variational_regression.py,TestKissGPVariationalRegression,test_kissgp_gp_mean_abs_error,#TestKissGPVariationalRegression#,61

Before Change

                    optimizer.step()

            for name, param in gp_model.named_parameters():
                print(name, param.grad.norm())
                self.assertTrue(param.grad is not None)
                self.assertGreater(param.grad.norm().item(), 0)
            for param in likelihood.parameters():
                self.assertTrue(param.grad is not None)

After Change

        // Our loss object
        // We"re using the VariationalMarginalLogLikelihood object
        mll = gpytorch.mlls.VariationalMarginalLogLikelihood(likelihood, model, n_data=train_y.size(0))

        // The training loop
        def train():
            for i in range(n_iter):

Instances