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Doesn't CoreML abstract 90% of the actual model format/training source away? Last time I played with it in Xcode, it was painless to pull a pretrained TF model

Doesn't CoreML abstract 90% of the actual model format/training source away? Last time I played with it in Xcode, it was painless to pull a pretrained TF model and use as-is.

Q6T46nT668w6i3m 7y ago
The number of operations supported by CoreML or Onyx is limited.
- akhilcacharya 7y ago
  What's an example of a missing operator?
- ghop02 7y ago
  Core ML 3 adds a ton of new operations, including control flow support. https://heartbeat.fritz.ai/whats-new-in-core-ml-3-d108d352e50a https://heartbeat.fritz.ai/whats-new-in-core-ml-3-d108d352e5...
  - throwawaybbqed 7y ago
    What about Android?
    - pjmlp 7y ago
      Android has its own incompatible world with NN and NDK fun. https://developer.android.com/ndk/reference/group/neural-networks https://developer.android.com/ndk/reference/group/neural-net... Or you get to use Tensorflow Lite and target both platforms, also with a smaller feature set than its big brother. https://www.tensorflow.org/lite/guide/get_started https://www.tensorflow.org/lite/guide/get_started
      - m0zg 7y ago
        But, crucially, larger feature set than the likes of CoreML etc. You don't get access to the NPU that way though, at least not on iOS. The only acceleration option there seems to be Metal. Which isn't bad, but also not the most power efficient thing the hardware supports. Still though, it's the only game in town if you don't want to have insane un-debuggable headaches everywhere you deploy to device. Plus it also supports embedded Linux boards, and pretty much all current TPU-like things available there.