text: Title: prune pointpillar with mmdetection3d
  Body: I want to prune pointpillar on mmdetection3d framework, but the model has more than one input`def forward(self, img, img_metas, return_loss=True, **kwargs):`, which makes it not suitable for speedup: `ModelSpeedup(model, dummy_input=torch.rand([10, 3, 32, 32]).to(device), masks_file=masks).speedup_model()`
  so I just prune and speedup the backbone: `model.backbone` follow steps:
  step1 : load origin model
  step2:  prune model, speedup model, save the speeduped model
  step3 :   load speeduped model and finetune it
  the reason I save model in step2 is I can not finetune it in mmdetection3d immediately if I prune the model in mmdetection3d.
  the sparse ratio is 0.9(cut 10% weight with L1Norm), accuracy drops about 2%
  **question is, am I right?**  
  ps: finetune loss
  ![image-20221027120605758](https://user-images.githubusercontent.com/14066190/198223557-ca223120-d213-424f-9df3-9cd53d5cc277.png)
  
  