bca150def5e45d0b55d5d20860e3e1b6b6d1ed42,gpytorch/distributions/multivariate_normal.py,MultivariateNormal,rsample,#MultivariateNormal#Any#Any#,146

Before Change

            if covar_root.shape[-1] < base_samples.shape[-2]:
                base_samples = base_samples[..., : covar_root.shape[-1], :]
            elif covar_root.shape[-1] > base_samples.shape[-2]:
                raise RuntimeError("Incompatible dimension of `base_samples`")
            res = covar_root.matmul(base_samples) + self.loc.unsqueeze(-1)

            // Permute and reshape new samples to be original size
            res = res.permute(-1, *range(self.loc.dim())).contiguous()

After Change

                base_samples = base_samples[..., : covar_root.shape[-1], :]
            elif covar_root.shape[-1] > base_samples.shape[-2]:
                // raise RuntimeError("Incompatible dimension of `base_samples`")
                covar_root = covar_root.transpose(-2, -1)
            res = covar_root.matmul(base_samples) + self.loc.unsqueeze(-1)

            // Permute and reshape new samples to be original size
            res = res.permute(-1, *range(self.loc.dim())).contiguous()

Instances