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PyTorch Mobile is a start and is available for iOS and Android. Given folks like PFN and Microsoft are (or will be heavy contributors) i would expect support fo

PyTorch Mobile is a start and is available for iOS and Android. Given folks like PFN and Microsoft are (or will be heavy contributors) i would expect support for more devices to broaden. Have you tried it out yet? No need for a separate set of op semantics or framework.. :) https://pytorch.org/mobile/home/ https://pytorch.org/mobile/home/

m0zg 7y ago
Anything that can't use mobile GPU (or DSP/TPU for quantized inference) is pretty useless IMO, because it's just not energy efficient enough to be practical in a battery powered device, even if it's fast enough.
- Nimitz14 7y ago
  Once pytorch is updated to use XNNPACK (being worked on right now) I think it should be fine to use. That plus QNNPACK makes inference quite low on power usage in my (admittedly limited, just integrated XNNPACK) experience.
  - m0zg 7y ago
    As a rule, CPU burns at least 5x the energy per FLOP. So no, CPU is not a viable option on mobile if you need to do inference constantly. For "every now and then" cases, sure.
    - Nimitz14 7y ago
      Interesting, thanks.