int PtwiseProductLayer::doUpdateState(double timef, double dt, const PVLayerLoc * loc, pvdata_t * A, pvdata_t * V, int num_channels, pvdata_t * gSynHead) {
int nx = loc->nx;
int ny = loc->ny;
int nf = loc->nf;
int num_neurons = nx*ny*nf;
int nbatch = loc->nbatch;
updateV_PtwiseProductLayer(nbatch, num_neurons, V, gSynHead);
setActivity_HyPerLayer(nbatch, num_neurons, A, V, nx, ny, nf, loc->halo.lt, loc->halo.rt, loc->halo.dn, loc->halo.up);
return PV_SUCCESS;
}
int TrainingLayer::updateState(double timed, double dt, const PVLayerLoc * loc, pvdata_t * A, pvdata_t * V, int numTrainingLabels, int * trainingLabels, int traininglabelindex, int strength) {
int nx = loc->nx;
int ny = loc->ny;
int nf = loc->nf;
int num_neurons = nx*ny*nf;
int status = updateV_TrainingLayer(num_neurons, V, numTrainingLabels, trainingLabels, curTrainingLabelIndex, strength);
assert(status == PV_SUCCESS);
curTrainingLabelIndex++;
setActivity_HyPerLayer(num_neurons, A, V, nx, ny, nf, loc->halo.lt, loc->halo.rt, loc->halo.dn, loc->halo.up);
return PV_SUCCESS;
}
int KmeansLayer::setActivity()
{
const PVLayerLoc * loc = getLayerLoc();
int nx = loc->nx;
int ny = loc->ny;
int nf = loc->nf;
PVHalo const * halo = &loc->halo;
int num_neurons = nx*ny*nf;
int nbatch = loc->nbatch;
int status;
status = setActivity_HyPerLayer(nbatch, num_neurons, getCLayer()->activity->data, getV(), nx, ny, nf, halo->lt, halo->rt, halo->dn, halo->up);
return status;
}
int MatchingPursuitResidual::updateState(double timed, double dt) {
pvdata_t * V = getV();
if (inputInV) {
for (int k=0; k<getNumNeuronsAllBatches(); k++) {
V[k] -= GSyn[1][k];
}
}
else {
for (int k=0; k<getNumNeuronsAllBatches(); k++) {
V[k] = GSyn[0][k];
}
inputInV = true;
}
PVLayerLoc const * loc = getLayerLoc();
setActivity_HyPerLayer(loc->nbatch, getNumNeurons(), getActivity(), V, loc->nx, loc->ny, loc->nf, loc->halo.lt, loc->halo.rt, loc->halo.dn, loc->halo.up);
return PV_SUCCESS;
}