public Tensor(snLSize lsz)
{
lsz_ = lsz;
int sz = (int)(lsz.w * lsz.h * lsz.ch * lsz.bsz * sizeof(float));
if (sz > 0)
{
data_ = (float *)Marshal.AllocHGlobal(sz);
}
}
public Tensor(snLSize lsz, float *data)
{
lsz_ = lsz;
UInt64 sz = lsz.w * lsz.h * lsz.ch * lsz.bsz * sizeof(float);
if (sz > 0)
{
data_ = (float *)Marshal.AllocHGlobal((int)sz);
MemCopy((IntPtr)data_, (IntPtr)data, sz);
}
}
static extern bool snSetWeightNode(void *net, IntPtr name, snLSize wsz, float *wData);
static extern bool snTraining(void *net, float lr, snLSize insz, float *iLayer,
snLSize osz, float *outData, float *targetData, float *outAccurate);
static extern bool snBackward(void *net, float lr, snLSize gsz, float *grad);
static extern bool snForward(void *net, bool isLern, snLSize isz, float *iLayer, snLSize osz, float *outData);
public Tensor(snLSize lsz = new snLSize(), float[] data = null){
lsz_ = lsz;
data_ = data;
}
