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// TanH neuron activation function layer.
// Adapted from ReLU layer code written by Yangqing Jia
#include <algorithm>
#include <vector>
#include "caffe/layer.hpp"
#include "caffe/vision_layers.hpp"
namespace caffe {
template <typename Dtype>
void TanHLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
const Dtype* bottom_data = bottom[0]->cpu_data();
Dtype* top_data = top[0]->mutable_cpu_data();
const int count = bottom[0]->count();
for (int i = 0; i < count; ++i) {
top_data[i] = tanh(bottom_data[i]);
}
}
template <typename Dtype>
void TanHLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down,
const vector<Blob<Dtype>*>& bottom) {
if (propagate_down[0]) {
const Dtype* top_data = top[0]->cpu_data();
const Dtype* top_diff = top[0]->cpu_diff();
Dtype* bottom_diff = bottom[0]->mutable_cpu_diff();
const int count = bottom[0]->count();
Dtype tanhx;
for (int i = 0; i < count; ++i) {
tanhx = top_data[i];
bottom_diff[i] = top_diff[i] * (1 - tanhx * tanhx);
}
}
}
#ifdef CPU_ONLY
STUB_GPU(TanHLayer);
#endif
INSTANTIATE_CLASS(TanHLayer);
} // namespace caffe
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