a5eb8d66cf4d433cb5fd0a2cb5cd229077ea54f4,test/lazy/test_cached_cg_lazy_tensor.py,TestCachedCGLazyTensor,create_lazy_tensor,#TestCachedCGLazyTensor#,14

Before Change

        mat = mat.matmul(mat.transpose(-1, -2))
        mat.requires_grad_(True)

        eager_rhss = [torch.randn(5, 10), torch.randn(5, 1)]
        return CachedCGLazyTensor(NonLazyTensor(mat), eager_rhss)

    def evaluate_lazy_tensor(self, lazy_tensor):
        return lazy_tensor.base_lazy_tensor.tensor

After Change

        mat.requires_grad_(True)

        lazy_tensor = NonLazyTensor(mat)
        eager_rhs = torch.randn(5, 10).detach()
        with gpytorch.settings.num_trace_samples(1000):  // For inv_quad_log_det tests
            solve, probe_vecs, probe_vec_norms, probe_vec_solves, tmats = CachedCGLazyTensor.precompute_terms(
                lazy_tensor, eager_rhs.detach()
            )
            eager_rhss = [eager_rhs.detach(), eager_rhs[..., -2:-1].detach()]
            solves = [solve.detach(), solve[..., -2:-1].detach()]

        return CachedCGLazyTensor(

Instances