I want to know how can I parallelize my modulelist in torchscript C++ codes.
I have read that the modulelist is completely unrolled from this blog: https://pytorch.org/docs/master/jit_language_reference_v2.html
- Code that iterates over
torch.nn.ModuleDictis completely unrolled so that elements of
torch.nn.ModuleListor keys of
torch.nn.ModuleDictcan be of different subclasses of
Does it mean we don’t need to modify the C++ code to enabel parallelism of Modulelist
because the modulelist is unrolled automatically?
On the other hand, I also read from this blog Dynamic Parallelism in TorchScript — PyTorch Tutorials 1.12.0+cu102 documentation
that we can use torch.jit.fork and torch.jit.wait to manually parallelize the modulelist calculations. I want to know will the fork &wait also affects C++ torchscript code so that modulelist can be calculated in parallel automatically ?
Finally, if above two methods cannot automatically enable C++ parallel calculation of modulelist, could we implemented a new torchscript custom class that accept some torch.nn.Modules as parameters and parallel these modules manually by ourselves?
Thanks very much for any advices.