b0eecef1c8acdfe6e65f1e96ff6e26d2bc43e7db,gpytorch/lazy/diag_lazy_tensor.py,DiagLazyTensor,zero_mean_mvn_samples,#DiagLazyTensor#Any#,153

Before Change

    def zero_mean_mvn_samples(self, num_samples):
        if self.ndimension() == 3:
            base_samples = torch.randn(
                num_samples, self._diag.size(0), self._diag.size(1), dtype=self.dtype, device=self.device
            )
        else:
            base_samples = torch.randn(num_samples, self._diag.size(0), dtype=self.dtype, device=self.device)
        samples = self._diag.unsqueeze(0).sqrt() * base_samples
        return samples

After Change

    def zero_mean_mvn_samples(self, num_samples):
        base_samples = torch.randn(num_samples, *self._diag.shape, dtype=self.dtype, device=self.device)
        return base_samples * self._diag.sqrt()

Instances