• Erosis@alien.topB
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    10 months ago

    I get access to some awesome data loading and preprocessing tools with the pytorch backend then I swap to tensorflow for quantization for tflite model with almost no fuss.

    It was somewhat annoying going from torch to onnx to tflite previously. There’s a bunch of small roadbumps that you have to deal with.

    • Relevant-Yak-9657@alien.topB
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      10 months ago

      Yeah, unifying these tools feels like the best way to go for me too. I also like JAX for a similar reason because there are 50 different libraries with different use cases and it is easy to mix parts of them together, due to the common infrastructure. Like Keras losses + flax models + optax training + my custom libraries super classes. It’s great tbh.