* constraint input value to [-127, +127]

* keep new line at the end

* fix windows avx2 error in convolution_3x3.h and convolution_sgemm.h

* fix compatibility of avx2 under Linux and Windows

* Update CMakeLists.txt

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* Update convolution_3x3.h

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* Update convolution_sgemm.h

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* initial the ncnn post training quantization tools

* clear some comments of tools

* fix the Travis ci compiler error

* optimize conv sgemm with sse

* Update convolution_x86.cpp

* add the "Tu Fa" conv sgemm fp32 with avx2 for x86

* add avx2 cmake option

* fix some bugs of avx2 pull request

* add the implement of int8 winograd F(4,3)

* add int8 winograd F(4,3) naive c to arm64-v8a platform

* optimize int8 winograd F(4,3) with neon

* merge dequant op into int8 winograd F(4,3)

* enable int8 wino F(4,3) case with all size

* optimize the conv sgemm int8 on arm64-v8a platform

* optimize int8 arm64-v8a with sadalp ins

* merge requantize op  into latest conv layer

* merge requantize op into conv-int8 op

* update the mobilenet.param in the benchmark

* Update README.md

update Kirin970 and RK3399

* try to fix the travis build error

* requantize layer arm64-v8a neon implement

* convdw3x3s1 arm64-v8a neon implement

* convdw3x3s2 arm64-v8a neon implement

* conv1x1s1 arm64-v8a is optimized by neon assembly

* conv sgemm int8 optimized with neon assembly,kernel transform is offline

* conv conv winograd int8 optimized with neon assembly,fix ci build failed

* conv3x3s2 int8 arm64-v8a optimized with neon assembly,remove old codes.

* add the armv7a conv3x3s1 implement without overflow,remove old codes

* fix the bug of conv3x3s2 packed int8

* new int8 implement,weight quant by perchanel,better accuracy~

* fix the bug of conv3x3s1 packed int8 neon

* add the naive c fp32 and int8 winograd F(2,3)

* add the neon intrinsic int8 winograd F(2,3)

* optimize the armv7a int8 winograd F(2,3) with neon assembly

* optimize the armv7a int8 winograd F(2,3) input transform with assembly.

* add the requantize layer and int8 relu implement.

* add graph optimize conv1x1s2 -> conv1x1s1,begin optimize int8 aarch64.

* fix int8 bugs

* add the c naive im2col with sgemm

* add aarch64 int8 winograd f23, conv3x3s2 naive implement

* add the int8 sgemm conv7x7s2 on x86/armv7a platform

* optimize the int8 sgemm by neon intrinsic and packed kernel

* optimize the int8 sgemm with packed data

* optimize the int8 sgemm with armv7a neon assembly

* add the int8 sgemm on arm64-v8a platform

* perpare to merge latest codes from master

* add the int8 param files

* In the Class Net,add the fuse_network method

* innerproduce layer with int8 impl,the type of top_blob shoud be integer.

* fix the dequantize_arm bug