void TestForward() {
LayerParameter layer_param;
const Dtype kLossWeight = 3.7;
layer_param.add_loss_weight(kLossWeight);
FillerParameter data_filler_param;
data_filler_param.set_std(1);
GaussianFiller<Dtype> data_filler(data_filler_param);
FillerParameter targets_filler_param;
targets_filler_param.set_min(0.0);
targets_filler_param.set_max(1.0);
UniformFiller<Dtype> targets_filler(targets_filler_param);
Dtype eps = tol<Dtype>(2e-2, 5e-2);
for (int i = 0; i < 100; ++i) {
// Fill the data vector
data_filler.Fill(this->blob_bottom_data_);
// Fill the targets vector
targets_filler.Fill(this->blob_bottom_targets_);
SigmoidCrossEntropyLossLayer<Dtype, Dtype> layer(layer_param);
layer.SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
Dtype layer_loss =
layer.Forward(this->blob_bottom_vec_, this->blob_top_vec_);
const int count = this->blob_bottom_data_->count();
const int num = this->blob_bottom_data_->num();
const Dtype* blob_bottom_data = this->blob_bottom_data_->cpu_data();
const Dtype* blob_bottom_targets =
this->blob_bottom_targets_->cpu_data();
Dtype reference_loss = kLossWeight * SigmoidCrossEntropyLossReference(
count, num, blob_bottom_data, blob_bottom_targets);
EXPECT_NEAR(reference_loss, layer_loss, eps) << "debug: trial #" << i;
}
}
OneVersusAllLossLayerTest()
: blob_bottom_data_(new Blob<Dtype>(10, 1, 5, 5)),
blob_bottom_targets_(new Blob<Dtype>(10, 1, 5, 5)),
blob_top_loss_(new Blob<Dtype>()) {
// Fill the data vector
FillerParameter data_filler_param;
data_filler_param.set_min(0.011); // gradient checker adds +/- 0.01
data_filler_param.set_max(0.989);
UniformFiller<Dtype> data_filler(data_filler_param);
data_filler.Fill(blob_bottom_data_);
blob_bottom_vec_.push_back(blob_bottom_data_);
// Fill the targets vector
/*FillerParameter targets_filler_param;
targets_filler_param.set_min(0);
targets_filler_param.set_max(1);
UniformFiller<Dtype> targets_filler(targets_filler_param);
targets_filler.Fill(blob_bottom_targets_);*/
int temp;
for (int i = 0; i < blob_bottom_targets_->count(); ++i) {
temp = caffe_rng_rand() % 12;
assert(temp < 12);
if(temp < 11) {
blob_bottom_targets_->mutable_cpu_data()[i] =
((Dtype)temp) / ((Dtype)10);
} else {
blob_bottom_targets_->mutable_cpu_data()[i] = 253; // ignore label
}
}
blob_bottom_vec_.push_back(blob_bottom_targets_);
blob_top_vec_.push_back(blob_top_loss_);
}
void TestForward() {
LayerParameter layer_param;
FillerParameter data_filler_param;
data_filler_param.set_std(1);
GaussianFiller<Dtype> data_filler(data_filler_param);
FillerParameter targets_filler_param;
targets_filler_param.set_min(-1);
targets_filler_param.set_max(1);
UniformFiller<Dtype> targets_filler(targets_filler_param);
const int count = this->blob_bottom_data_->count();
Dtype eps = 2e-2;
for (int i = 0; i < 10; ++i) {
// Fill the data vector
data_filler.Fill(this->blob_bottom_data_);
// Fill the targets vector
targets_filler.Fill(this->blob_bottom_targets_);
// Make negatives into -1 and positives into 1
Dtype* targets = this->blob_bottom_targets_->mutable_cpu_data();
caffe_cpu_sign(count, targets, targets);
MultiLabelLossLayer<Dtype> layer(layer_param);
layer.SetUp(this->blob_bottom_vec_, &(this->blob_top_vec_));
Dtype layer_loss =
layer.Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
const int num = this->blob_bottom_data_->num();
const Dtype* blob_bottom_data = this->blob_bottom_data_->cpu_data();
const Dtype* blob_bottom_targets =
this->blob_bottom_targets_->cpu_data();
Dtype reference_loss = this->SigmoidMultiLabelLossReference(
count, num, blob_bottom_data, blob_bottom_targets);
EXPECT_NEAR(reference_loss, layer_loss, eps) << "debug: trial #" << i;
}
}
SigmoidCrossEntropyLossLayerTest()
: blob_bottom_data_(new Blob<Dtype>(10, 5, 1, 1)),
blob_bottom_targets_(new Blob<Dtype>(10, 5, 1, 1)) {
// Fill the data vector
FillerParameter data_filler_param;
data_filler_param.set_std(1);
GaussianFiller<Dtype> data_filler(data_filler_param);
data_filler.Fill(blob_bottom_data_);
blob_bottom_vec_.push_back(blob_bottom_data_);
// Fill the targets vector
FillerParameter targets_filler_param;
targets_filler_param.set_min(0);
targets_filler_param.set_max(1);
UniformFiller<Dtype> targets_filler(targets_filler_param);
targets_filler.Fill(blob_bottom_targets_);
blob_bottom_vec_.push_back(blob_bottom_targets_);
}
MultiLabelLossLayerTest()
: blob_bottom_data_(new Blob<Dtype>(10, 5, 1, 1)),
blob_bottom_targets_(new Blob<Dtype>(10, 5, 1, 1)) {
// Fill the data vector
FillerParameter data_filler_param;
data_filler_param.set_std(1);
GaussianFiller<Dtype> data_filler(data_filler_param);
data_filler.Fill(blob_bottom_data_);
blob_bottom_vec_.push_back(blob_bottom_data_);
// Fill the targets vector
FillerParameter targets_filler_param;
targets_filler_param.set_min(-1);
targets_filler_param.set_max(1);
UniformFiller<Dtype> targets_filler(targets_filler_param);
targets_filler.Fill(blob_bottom_targets_);
int count = blob_bottom_targets_->count();
caffe_cpu_sign(count, this->blob_bottom_targets_->cpu_data(),
this->blob_bottom_targets_->mutable_cpu_data());
blob_bottom_vec_.push_back(blob_bottom_targets_);
}
MilLossLayerTest()
: blob_bottom_data_(new Blob<Dtype>(1, 5, 1, 1)),
blob_bottom_targets_(new Blob<Dtype>(1, 5, 1, 1)),
blob_top_loss_(new Blob<Dtype>()) {
// Fill the data vector
FillerParameter data_filler_param;
data_filler_param.set_min(0);
data_filler_param.set_max(1);
UniformFiller<Dtype> data_filler(data_filler_param);
data_filler.Fill(blob_bottom_data_);
blob_bottom_vec_.push_back(blob_bottom_data_);
// Fill the targets vector
FillerParameter targets_filler_param;
targets_filler_param.set_min(0);
targets_filler_param.set_max(1);
UniformFiller<Dtype> targets_filler(targets_filler_param);
targets_filler.Fill(blob_bottom_targets_);
blob_bottom_vec_.push_back(blob_bottom_targets_);
blob_top_vec_.push_back(blob_top_loss_);
propogate_down_.push_back(true);
}
