Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! about proda

[yuheyuan]

    def feat_prototype_distance(self, feat):
        print("enterehre!")
        N, C, H, W = feat.shape
        feat_proto_distance = -torch.ones((N, self.class_numbers, H, W)).to(feat.device)
        for i in range(self.class_numbers):
            #feat_proto_distance[:, i, :, :] = torch.norm(torch.Tensor(self.objective_vectors[i]).reshape(-1,1,1).expand(-1, H, W).to(feat.device) - feat, 2, dim=1,)
            print(feat)
            print(self.objective_vectors[i].to(feat.device))
            # print(self.objective_vectors[i])
            feat_proto_distance[:, i, :, :] = torch.norm(self.objective_vectors[i].reshape(-1,1,1).expand(-1, H, W) - feat, 2, dim=1,)  # here feat.toGPU, but self.objective_vecotrs belong to cpu
        
        return feat_proto_distance

I find it may be occur torch.norm here,one belong to GPU, one belong to CPU