void Net::ReadData(const mxArray *mx_data) {
LayerInput *firstlayer = static_cast<LayerInput*>(layers_[0]);
std::vector<size_t> data_dim = mexGetDimensions(mx_data);
size_t mapsize1, mapsize2;
if (kMapsOrder == kMatlabOrder) {
mapsize1 = data_dim[0];
mapsize2 = data_dim[1];
} else {
mapsize1 = data_dim[1];
mapsize2 = data_dim[0];
}
mexAssert(mapsize1 == firstlayer->mapsize_[0] &&
mapsize2 == firstlayer->mapsize_[1],
"Data and the first layer must have equal sizes");
size_t outputmaps = 1;
if (data_dim.size() > 2) {
outputmaps = data_dim[2];
}
mexAssert(outputmaps == firstlayer->outputmaps_,
"Data's 3rd dimension must be equal to the outputmaps on the input layer");
size_t samples_num = 1;
if (data_dim.size() > 3) {
samples_num = data_dim[3];
}
ftype *data_ptr = mexGetPointer(mx_data);
// transposed array
data_.attach(data_ptr, samples_num, mapsize1 * mapsize2 * outputmaps, 1, true);
if (firstlayer->norm_ > 0) {
MatCPU norm_data(data_.size1(), data_.size2());
norm_data.reorder(true, false);
norm_data = data_;
norm_data.Normalize(firstlayer->norm_);
Swap(data_, norm_data);
}
}
void Net::InitWeights(const mxArray *mx_weights_in) { // testing
size_t num_weights = NumWeights();
mexAssert(num_weights == mexGetNumel(mx_weights_in),
"In InitWeights the vector of weights has the wrong length!");
weights_.Init(mexGetPointer(mx_weights_in), num_weights);
size_t offset = 0;
for (size_t i = 0; i < layers_.size(); ++i) {
layers_[i]->InitWeights(weights_, offset, false);
}
}
void Net::ReadData(const mxArray *mx_data) {
std::vector<size_t> data_dim = mexGetDimensions(mx_data);
mexAssert(data_dim.size() == 4, "The data array must have 4 dimensions");
mexAssert(data_dim[0] == layers_[0]->mapsize_[0] &&
data_dim[1] == layers_[0]->mapsize_[1],
"Data and the first layer must have equal sizes");
mexAssert(data_dim[2] == layers_[0]->outputmaps_,
"Data's 3rd dimension must be equal to the outputmaps on the input layer");
mexAssert(data_dim[3] > 0, "Input data array is empty");
ftype *data = mexGetPointer(mx_data);
data_.attach(data, data_dim[3], data_dim[0] * data_dim[1] * data_dim[2]);
}
void Net::InitWeights(const mxArray *mx_weights_in, mxArray *&mx_weights) {
size_t num_weights = NumWeights();
bool isgen = false;
if (mx_weights_in != NULL) { // training
mexAssert(num_weights == mexGetNumel(mx_weights_in),
"In InitWeights the vector of weights has the wrong length!");
mx_weights = mexDuplicateArray(mx_weights_in);
} else { // genweights
mx_weights = mexNewMatrix(1, num_weights);
isgen = true;
}
weights_.Init(mexGetPointer(mx_weights), num_weights);
size_t offset = 0;
for (size_t i = 0; i < layers_.size(); ++i) {
layers_[i]->InitWeights(weights_, offset, isgen);
}
}
void Net::GetWeights(mxArray *&mx_weights) const {
size_t num_weights = NumWeights();
mx_weights = mexNewMatrix(num_weights, 1);
Mat weights_cpu;
weights_cpu.attach(mexGetPointer(mx_weights), num_weights, 1);
Mat weights_mat(num_weights, 1);
#if COMP_REGIME != 2 // CPU
weights_mat.attach(weights_cpu);
#endif
size_t offset = 0;
for (size_t i = 0; i < layers_.size(); ++i) {
layers_[i]->GetWeights(weights_mat, offset);
}
#if COMP_REGIME == 2 // GPU
DeviceToHost(weights_mat, weights_cpu);
#endif
}
