bjacob
commented
4 years ago gemmlowp provides a fixed-point computation library for this purpose. It contains implementations of exp, tanh and logistic functions. See: https://github.com/google/gemmlowp/blob/master/fixedpoint/fixedpoint.h
For Softmax, an implementation is found in TensorFlow Lite here, built on top of the aforementioned gemmlowp fixedpoint library: https://github.com/tensorflow/tensorflow/blob/305fec9fddc3bdb5bb574a134b955bf4b07fd795/tensorflow/lite/kernels/internal/reference/softmax.h#L60
For 8bit quantization, zero point and scale are applied. But when in non-linear function layer, I want to know if I can process the input data without converting it to a real number. Or is there any way to calibrate? please answer about my question.
non-linear function : tanh / sigmoid / softmax / exp(x)