| |
| Serialization semantics |
| ======================= |
| |
| Best practices |
| -------------- |
| |
| .. _recommend-saving-models: |
| |
| Recommended approach for saving a model |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| |
| There are two main approaches for serializing and restoring a model. |
| |
| The first (recommended) saves and loads only the model parameters:: |
| |
| torch.save(the_model.state_dict(), PATH) |
| |
| Then later:: |
| |
| the_model = TheModelClass(*args, **kwargs) |
| the_model.load_state_dict(torch.load(PATH)) |
| |
| The second saves and loads the entire model:: |
| |
| torch.save(the_model, PATH) |
| |
| Then later:: |
| |
| the_model = torch.load(PATH) |
| |
| However in this case, the serialized data is bound to the specific classes |
| and the exact directory structure used, so it can break in various ways when |
| used in other projects, or after some serious refactors. |
| |
| .. note:: |
| The 1.6 release of PyTorch switched ``torch.save`` to use a new |
| zipfile-based file format. ``torch.load`` still retains the ability to |
| load files in the old format. If for any reason you want ``torch.save`` |
| to use the old format, pass the kwarg ``_use_new_zipfile_serialization=False``. |
