The other is `step`, it can be called with `pruner.step()` after each minibatch. Note that not all algorithms need these two APIs, for those that do not need them, calling them is allowed but has no effect.
__[TODO]__ The last API is for users to export the compressed model. You will get a compressed model when you finish the training using this API. It also exports another file storing the values of masks.
You can easily export the compressed model using the following API if you are pruning your model, ```state_dict``` of the sparse model weights will be stored in ```model.pth```, which can be loaded by ```torch.load('model.pth')```
```
pruner.export_model(model_path='model.pth')
```
```mask_dict ``` and pruned model in ```onnx``` format(```input_shape``` need to be specified) can also be exported like this:
