Roadmap for torch and pytorch

hi pierre,

Torch is not going anywhere. PyTorch and Torch use the same C libraries that contain all the performance: TH, THC, THNN, THCUNN and they will continue to be shared.
We still and will have continued engineering on Torch itself, and we have no immediate plan to remove that.

We have also mentioned this to the folks developing the OpenNMT project: GitHub - OpenNMT/OpenNMT: Open Source Neural Machine Translation in Torch (deprecated)

Continue to develop things in whichever frontend you want (Torch or PyTorch) and you can be assured that the Lua side of things will be maintained.

Coming to " all those slides stating that lua is more efficient and easier to learn than python, "

we have done some thorough benchmarks and found this to be not the case, especially for the Torch ecosystem where we cross the C boundaries all the time (LuaJIT traces stop everytime you cross the C boundary).

gain as a torch user, would you see some big pros to move from torch to pytorch, without sacrifying performance for example ?

recurrent nets, weight sharing and memory usage will be big positives with PyTorch compared to Torch, while retaining the flexibility of interfacing with C and the current speed of Torch.

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