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From GitBox <...@apache.org>
Subject [GitHub] [incubator-tvm] FrozenGene opened a new issue #5823: [TFLite] TFLite FP16 Post Quantization Support
Date Tue, 16 Jun 2020 11:06:52 GMT

FrozenGene opened a new issue #5823:
URL: https://github.com/apache/incubator-tvm/issues/5823


   TensorFlow Lite now supports converting weights to 16-bit floating point values during
model conversion from TensorFlow to TensorFlow Lite's flat buffer format. This results in
a 2x reduction in model size. 
   
   However, this will insert new `dequantize` for ops (like `conv2d`) used for `dequantize`
fp16 weight to fp32.  TVM doesn't support this behavior. List the things we mainly should
to do:
   
   - Support float16 type inside tflite parser
   - Extend `dequantize` to support fp16 to fp32 


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