void LRNLayerTest<Dtype>::ReferenceLRNForward(
const Blob<Dtype>& blob_bottom, const LayerParameter& layer_param,
Blob<Dtype>* blob_top) {
blob_top->Reshape(blob_bottom.num(), blob_bottom.channels(),
blob_bottom.height(), blob_bottom.width());
const Dtype* bottom_data = blob_bottom.cpu_data();
Dtype* top_data = blob_top->mutable_cpu_data();
Dtype alpha = layer_param.alpha();
Dtype beta = layer_param.beta();
int size = layer_param.local_size();
for (int n = 0; n < blob_bottom.num(); ++n) {
for (int c = 0; c < blob_bottom.channels(); ++c) {
for (int h = 0; h < blob_bottom.height(); ++h) {
for (int w = 0; w < blob_bottom.width(); ++w) {
int c_start = c - (size - 1) / 2;
int c_end = min(c_start + size, blob_bottom.channels());
c_start = max(c_start, 0);
Dtype scale = 1.;
for (int i = c_start; i < c_end; ++i) {
Dtype value = blob_bottom.data_at(n, i, h, w);
scale += value * value * alpha / size;
}
*(top_data + blob_top->offset(n, c, h, w)) =
blob_bottom.data_at(n, c, h, w) / pow(scale, beta);
}
}
}
}
}
