c517e0b8b34a85b8142b4669c152b6e62c02d8e2,gpytorch/lazy/lazy_tensor.py,LazyTensor,zero_mean_mvn_samples,#LazyTensor#Any#,1260

Before Change

        else:
            covar_root = self.root_decomposition().root

        if self.ndimension() == 3:
            base_samples = torch.randn(
                self.size(0), covar_root.size(-1), num_samples, dtype=self.dtype, device=self.device
            )
            samples = covar_root.matmul(base_samples).permute(2, 0, 1).contiguous()
        else:
            base_samples = torch.randn(covar_root.size(-1), num_samples, dtype=self.dtype, device=self.device)
            samples = covar_root.matmul(base_samples).permute(1, 0).contiguous()

        return samples

    def __add__(self, other):
        

After Change

        base_samples = torch.randn(
            *self.batch_shape, covar_root.size(-1), num_samples, dtype=self.dtype, device=self.device
        )
        samples = covar_root.matmul(base_samples).permute(-1, *range(self.dim() - 1)).contiguous()

        return samples

Instances