4c6458b841bb49610b5cf6b9fbab94df5cad85ee,gpytorch/lazy/mul_lazy_tensor.py,MulLazyTensor,_matmul,#MulLazyTensor#Any#,108

Before Change

        if rhs.ndimension() == 1:
            rhs = rhs.unsqueeze(1)
            is_vector = True
        batch_size = max(rhs.size(0), self.size(0)) if rhs.ndimension() == 3 else None

        // Here we have a root decomposition
        if isinstance(self.left_lazy_tensor, RootLazyTensor):
            left_root = self.left_lazy_tensor.root.evaluate()

After Change

        pass

    def _matmul(self, rhs):
        output_shape = _matmul_broadcast_shape(self.shape, rhs.shape)
        output_batch_shape = torch.Size(output_shape[:-2])

        if self.non_lazy_self is not None:
            return self.non_lazy_self._matmul(rhs)

Instances