问题
I am trying to convert a trained model from checkpoint file to tflite. I am using tf.lite.LiteConverter. The float conversion went fine with reasonable inference speed. But the inference speed of the INT8 conversion is very slow. I tried to debug by feeding in a very small network. I found that inference speed for INT8 model is generally slower than float model.
In the INT8 tflite file, I found some tensors called ReadVariableOp, which doesn't exist in TensorFlow's official mobilenet tflite model.
I wonder what causes the slowness of INT8 inference.
回答1:
You possibly used x86 cpu instead of one with arm instructions. You can refer it here https://github.com/tensorflow/tensorflow/issues/21698#issuecomment-414764709
来源：https://stackoverflow.com/questions/58349690/tflite-quantized-inference-very-slow