/*************************************************************************
Prepares HPC compuations of chunked gradient with HPCChunkedGradient().
You have to call this function before calling HPCChunkedGradient() for
a new set of weights. You have to call it only once, see example below:
HOW TO PROCESS DATASET WITH THIS FUNCTION:
Grad:=0
HPCPrepareChunkedGradient(Weights, WCount, NTotal, NOut, Buf)
foreach chunk-of-dataset do
HPCChunkedGradient(...)
HPCFinalizeChunkedGradient(Buf, Grad)
*************************************************************************/
public static void hpcpreparechunkedgradient(double[] weights,
int wcount,
int ntotal,
int nin,
int nout,
mlpbuffers buf)
{
int i = 0;
int batch4size = 0;
int chunksize = 0;
chunksize = 4;
batch4size = 3 * chunksize * ntotal + chunksize * (2 * nout + 1);
if (alglib.ap.rows(buf.xy) < chunksize || alglib.ap.cols(buf.xy) < nin + nout)
{
buf.xy = new double[chunksize, nin + nout];
}
if (alglib.ap.rows(buf.xy2) < chunksize || alglib.ap.cols(buf.xy2) < nin + nout)
{
buf.xy2 = new double[chunksize, nin + nout];
}
if (alglib.ap.len(buf.xyrow) < nin + nout)
{
buf.xyrow = new double[nin + nout];
}
if (alglib.ap.len(buf.x) < nin)
{
buf.x = new double[nin];
}
if (alglib.ap.len(buf.y) < nout)
{
buf.y = new double[nout];
}
if (alglib.ap.len(buf.desiredy) < nout)
{
buf.desiredy = new double[nout];
}
if (alglib.ap.len(buf.batch4buf) < batch4size)
{
buf.batch4buf = new double[batch4size];
}
if (alglib.ap.len(buf.hpcbuf) < wcount)
{
buf.hpcbuf = new double[wcount];
}
if (alglib.ap.len(buf.g) < wcount)
{
buf.g = new double[wcount];
}
if (!hpcpreparechunkedgradientx(weights, wcount, buf.hpcbuf))
{
for (i = 0; i <= wcount - 1; i++)
{
buf.hpcbuf[i] = 0.0;
}
}
buf.wcount = wcount;
buf.ntotal = ntotal;
buf.nin = nin;
buf.nout = nout;
buf.chunksize = chunksize;
}
/*************************************************************************
Finalizes HPC compuations of chunked gradient with HPCChunkedGradient().
You have to call this function after calling HPCChunkedGradient() for
a new set of weights. You have to call it only once, see example below:
HOW TO PROCESS DATASET WITH THIS FUNCTION:
Grad:=0
HPCPrepareChunkedGradient(Weights, WCount, NTotal, NOut, Buf)
foreach chunk-of-dataset do
HPCChunkedGradient(...)
HPCFinalizeChunkedGradient(Buf, Grad)
*************************************************************************/
public static void hpcfinalizechunkedgradient(mlpbuffers buf,
double[] grad)
{
int i = 0;
if (!hpcfinalizechunkedgradientx(buf.hpcbuf, buf.wcount, grad))
{
for (i = 0; i <= buf.wcount - 1; i++)
{
grad[i] = grad[i] + buf.hpcbuf[i];
}
}
}
public override alglib.apobject make_copy()
{
mlpbuffers _result = new mlpbuffers();
_result.chunksize = chunksize;
_result.ntotal = ntotal;
_result.nin = nin;
_result.nout = nout;
_result.wcount = wcount;
_result.batch4buf = (double[])batch4buf.Clone();
_result.hpcbuf = (double[])hpcbuf.Clone();
_result.xy = (double[,])xy.Clone();
_result.xy2 = (double[,])xy2.Clone();
_result.xyrow = (double[])xyrow.Clone();
_result.x = (double[])x.Clone();
_result.y = (double[])y.Clone();
_result.desiredy = (double[])desiredy.Clone();
_result.e = e;
_result.g = (double[])g.Clone();
_result.tmp0 = (double[])tmp0.Clone();
return _result;
}