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CPU version of smooth L1 loss layer implemented based #12

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CPU version of smooth L1 loss layer implemented based #12

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104 changes: 97 additions & 7 deletions src/caffe/layers/smooth_L1_loss_layer.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,13 @@ namespace caffe {
template <typename Dtype>
void SmoothL1LossLayer<Dtype>::LayerSetUp(
const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top) {
has_weights_ = (bottom.size() == 3);
SmoothL1LossParameter loss_param = this->layer_param_.smooth_l1_loss_param();
sigma2_ = loss_param.sigma() * loss_param.sigma();
has_weights_ = (bottom.size() >= 3);
if (has_weights_) {
CHECK_EQ(bottom.size(), 4) << "If weights are used, must specify both "
"inside and outside weights";
}
}

template <typename Dtype>
Expand All @@ -26,23 +32,107 @@ void SmoothL1LossLayer<Dtype>::Reshape(
CHECK_EQ(bottom[0]->channels(), bottom[2]->channels());
CHECK_EQ(bottom[0]->height(), bottom[2]->height());
CHECK_EQ(bottom[0]->width(), bottom[2]->width());
CHECK_EQ(bottom[0]->channels(), bottom[3]->channels());
CHECK_EQ(bottom[0]->height(), bottom[3]->height());
CHECK_EQ(bottom[0]->width(), bottom[3]->width());
}
diff_.Reshape(bottom[0]->num(), bottom[0]->channels(),
bottom[0]->height(), bottom[0]->width());
errors_.Reshape(bottom[0]->num(), bottom[0]->channels(),
bottom[0]->height(), bottom[0]->width());
// vector of ones used to sum
ones_.Reshape(bottom[0]->num(), bottom[0]->channels(),
bottom[0]->height(), bottom[0]->width());
for (int i = 0; i < bottom[0]->count(); ++i) {
ones_.mutable_cpu_data()[i] = Dtype(1);
}
}

template <typename Dtype>
void SmoothL1LossLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
NOT_IMPLEMENTED;
void SmoothL1LossLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top)
{
int count = bottom[0]->count();
caffe_sub(count, bottom[0]->cpu_data(), bottom[1]->cpu_data(), diff_.mutable_cpu_data()); // d := b0 - b1
if (has_weights_)
{
// apply "inside" weights
caffe_mul(count, bottom[2]->cpu_data(), diff_.cpu_data(), diff_.mutable_cpu_data()); // d := w_in * (b0 - b1)
}
for(int index =0; index<count; index++)
{
Dtype val = diff_.cpu_data()[index];
Dtype abs_val = abs(val);
if (abs_val < 1.0 / sigma2_)
{
errors_.mutable_cpu_data()[index] = 0.5 * val * val * sigma2_;
}
else
{
errors_.mutable_cpu_data()[index] = abs_val - 0.5 / sigma2_;
}
}
if (has_weights_)
{
// apply "outside" weights
caffe_mul(count, bottom[3]->cpu_data(), errors_.cpu_data(), errors_.mutable_cpu_data()); // d := w_out * SmoothL1(w_in * (b0 - b1))
}

Dtype loss = caffe_cpu_dot(count, ones_.cpu_data(), errors_.cpu_data());
top[0]->mutable_cpu_data()[0] = loss / bottom[0]->num();
}



template <typename Dtype>
void SmoothL1LossLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {
NOT_IMPLEMENTED;
void SmoothL1LossLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top, const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom)
{
// after forwards, diff_ holds w_in * (b0 - b1)
int count = diff_.count();

for(int index=0; index < count; index++)
{
// f'(x) = sigma * sigma * x if |x| < 1 / sigma / sigma
// = sign(x) otherwise
Dtype val = diff_.cpu_data()[index];
Dtype abs_val = abs(val);
if (abs_val < 1.0 / sigma2_)
{
diff_.mutable_cpu_data()[index] = sigma2_ * val;
}
else
{
diff_.mutable_cpu_data()[index] = (Dtype(0) < val) - (val < Dtype(0));
}
}
for (int i = 0; i < 2; ++i)
{
if (propagate_down[i])
{
const Dtype sign = (i == 0) ? 1 : -1;
const Dtype alpha = sign * top[0]->cpu_diff()[0] / bottom[i]->num();
caffe_cpu_axpby(
count, // count
alpha, // alpha
diff_.cpu_data(), // x
Dtype(0), // beta
bottom[i]->mutable_cpu_diff()); // y
if (has_weights_)
{
// Scale by "inside" weight
caffe_mul(
count,
bottom[2]->cpu_data(),
bottom[i]->cpu_diff(),
bottom[i]->mutable_cpu_diff());
// Scale by "outside" weight
caffe_mul(
count,
bottom[3]->cpu_data(),
bottom[i]->cpu_diff(),
bottom[i]->mutable_cpu_diff());
}
}
}
}

#ifdef CPU_ONLY
Expand Down