4 ms·

Exactly, especially in the age of ridiculously rapid development that we have found ourselves in over the past few years. This is exactly why TensorFlow is dyin

Exactly, especially in the age of ridiculously rapid development that we have found ourselves in over the past few years. This is exactly why TensorFlow is dying

amitport 4y ago
I do not believe TensorFlow is anywhere close to dying.
la_fayette 4y ago
:) it still is impossible to bring a cnn rnn network in pytorch to mobile, which works fine with tflite...
- antixk 4y ago
  Not sure if you have heard of Pytorch Mobile but it is very possible[0] [0] https://pytorch.org/tutorials/beginner/deeplabv3_on_ios.html https://pytorch.org/tutorials/beginner/deeplabv3_on_ios.html
  - perturbation 4y ago
    The big thing that PyTorch Mobile is lacking compared to TF Lite is on-device accelerator support (GPU/DSP/etc.) (there's experimental support for NNAPI https://pytorch.org/tutorials/prototype/nnapi_mobilenetv2.html https://pytorch.org/tutorials/prototype/nnapi_mobilenetv2.ht..., but this is a hack).
- levesque 4y ago
  I don't think that's a problem for the vast majority of pytorch users