std1.0.0-beta-7 SafeC docs

std :: ml::convnet

Struct std::ConvLayer

#include <std/ml/convnet.h> source

struct ConvLayer {
    int kind;
    int act;
    unsigned long inC;
    unsigned long inH;
    unsigned long inW;
    unsigned long outC;
    unsigned long outH;
    unsigned long outW;
    struct Conv2dSpec conv;
    struct Pool2dSpec pool;
    unsigned long factor;
    int mode;
    int flag;
    float prob;
    unsigned long slot;
    unsigned long skipC;
    unsigned long skipH;
    unsigned long skipW;
    unsigned long param;
    unsigned long buffer;
    int spectral;
}

Fields

§int kindsource

CONV_LAYER_*

§int actsource

ACT_* after the layer

§unsigned long inCsource
§unsigned long inHsource
§unsigned long inWsource
§unsigned long outCsource
§unsigned long outHsource
§unsigned long outWsource
§struct Conv2dSpec convsource

CONV / DECONV, and ADD's projection

§struct Pool2dSpec poolsource

MAXPOOL / AVGPOOL

§unsigned long factorsource

UPSAMPLE factor, GROUPNORM groups

§int modesource

RESIZE mode

§int flagsource

RESIZE alignCorners, DROPOUT by channel, ADD projection

§float probsource

DROPOUT

§unsigned long slotsource

SAVE / ADD / CONCAT

§unsigned long skipCsource

ADD / CONCAT: the saved activation's geometry

§unsigned long skipHsource
§unsigned long skipWsource
§unsigned long paramsource

first trained tensor's index in params (weight / gamma; bias / beta next)

§unsigned long buffersource

BATCHNORM running mean (variance next), spectral norm's u, DROPOUT's rng

§int spectralsource

CONV / DECONV / DENSE: weight spectrally normalized (u in buffers[buffer])