(Beta) torch.package
torch.package is a new way to package PyTorch models in a self-contained, stable format. A package will include both the model’s data (e.g. parameters, buffers) and its code (model architecture). Packaging a model with its full set of Python dependencies, combined with a description of a conda environment with pinned versions, can be used to easily reproduce training. Representing a model in a self-contained artifact will also allow it to be published and transferred throughout a production ML pipeline while retaining the flexibility of a pure-Python representation. For more details, refer to the documentation.
(Prototype) prepare_for_inference