(Stable) Freezing API
Module Freezing is the process of inlining module parameters and attributes values as constants into the TorchScript internal representation. This allows further optimization and specialization of your program, both for TorchScript optimizations and lowering to other backends. It is used by optimize_for_mobile API, ONNX, and others.   
Freezing is recommended for model deployment. It helps TorchScript JIT optimizations optimize away overhead and bookkeeping that is necessary for training, tuning, or debugging PyTorch models. It enables graph fusions that are not semantically valid on non-frozen graphs - such as fusing Conv-BN. For more details, refer to the documentation.
(Beta) PyTorch Profiler


