6bca4eed74e22ee369c166649f15db56f8565e35,test/lazy/_lazy_tensor_test_case.py,LazyTensorTestCase,test_inv_quad_logdet,#LazyTensorTestCase#,563

Before Change

            ).view(lazy_tensor.batch_shape)

            diff_invq = (res_inv_quad - actual_inv_quad).abs() / actual_inv_quad.abs().clamp(1, math.inf)
            diff_logdet = (res_logdet - actual_logdet).abs() / actual_logdet.abs().clamp(1, math.inf)
            self.assertLess(diff_invq.max().item(), 0.01)
            self.assertLess(diff_logdet.max().item(), 0.3)

    def test_inv_quad_logdet_no_reduce(self):

After Change

            vecs = torch.randn(*lazy_tensor.batch_shape, lazy_tensor.size(-1), 3, requires_grad=True)
            vecs_copy = vecs.clone().detach_().requires_grad_(True)

            with gpytorch.settings.num_trace_samples(128):
                with gpytorch.settings.max_cholesky_numel(0), gpytorch.settings.cg_tolerance(1e-5):
                    res_inv_quad, res_logdet = lazy_tensor.inv_quad_logdet(inv_quad_rhs=vecs, logdet=True)

            actual_inv_quad = evaluated.inverse().matmul(vecs_copy).mul(vecs_copy).sum(-2).sum(-1)
            actual_logdet = torch.cat(
                [torch.logdet(flattened_evaluated[i]).unsqueeze(0) for i in range(lazy_tensor.batch_shape.numel())]
            ).view(lazy_tensor.batch_shape)

Instances