void Scale2Layer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top){
num_output = this->layer_param_.convolution_param().num_output();
vector<int> scale_shape(1, bottom[0]->channels());
if (this->blobs_.size() > 0){
if (scale_shape != this->blobs_[0]->shape()){
Blob<Dtype> scale_shaped_blob(scale_shape);
LOG(FATAL) << "Incorrect weight shape: expected shape "
<< scale_shaped_blob.shape_string() << "; instead, shape was "
<< this->blobs_[0]->shape_string();
}
}
else{
this->blobs_.resize(2);
}
this->blobs_[0].reset(new Blob<Dtype>(scale_shape));
shared_ptr<Filler<Dtype> > scale_filler(GetFiller<Dtype>(
this->layer_param_.convolution_param().weight_filler()));
scale_filler->Fill(this->blobs_[0].get());
this->blobs_[1].reset(new Blob<Dtype>(scale_shape));
caffe_set(this->blobs_[1]->count(), (Dtype)-1, this->blobs_[1]->mutable_cpu_data());
}
void ScaleLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top) {
const ScaleParameter& param = this->layer_param_.scale_param();
if (bottom.size() == 1 && this->blobs_.size() > 0) {
LOG(INFO) << "Skipping parameter initialization";
} else if (bottom.size() == 1) {
// scale is a learned parameter; initialize it
axis_ = bottom[0]->CanonicalAxisIndex(param.axis());
const int num_axes = param.num_axes();
CHECK_GE(num_axes, -1) << "num_axes must be non-negative, "
<< "or -1 to extend to the end of bottom[0]";
if (num_axes >= 0) {
CHECK_GE(bottom[0]->num_axes(), axis_ + num_axes)
<< "scale blob's shape extends past bottom[0]'s shape when applied "
<< "starting with bottom[0] axis = " << axis_;
}
this->blobs_.resize(1);
const vector<int>::const_iterator& shape_start =
bottom[0]->shape().begin() + axis_;
const vector<int>::const_iterator& shape_end =
(num_axes == -1) ? bottom[0]->shape().end() : (shape_start + num_axes);
vector<int> scale_shape(shape_start, shape_end);
this->blobs_[0].reset(new Blob<Dtype>(scale_shape));
FillerParameter filler_param(param.filler());
if (!param.has_filler()) {
// Default to unit (1) filler for identity operation.
filler_param.set_type("constant");
filler_param.set_value(1);
}
shared_ptr<Filler<Dtype> > filler(GetFiller<Dtype>(filler_param));
filler->Fill(this->blobs_[0].get());
}
if (param.bias_term()) {
LayerParameter layer_param(this->layer_param_);
layer_param.set_type("Bias");
BiasParameter* bias_param = layer_param.mutable_bias_param();
bias_param->set_axis(param.axis());
if (bottom.size() > 1) {
bias_param->set_num_axes(bottom[1]->num_axes());
} else {
bias_param->set_num_axes(param.num_axes());
}
bias_param->mutable_filler()->CopyFrom(param.bias_filler());
bias_layer_ = LayerRegistry<Dtype>::CreateLayer(layer_param);
bias_bottom_vec_.resize(1);
bias_bottom_vec_[0] = bottom[0];
bias_layer_->SetUp(bias_bottom_vec_, top);
bias_param_id_ = this->blobs_.size();
this->blobs_.resize(bias_param_id_ + 1);
this->blobs_[bias_param_id_] = bias_layer_->blobs()[0];
bias_propagate_down_.resize(1, false);
}
this->param_propagate_down_.resize(this->blobs_.size(), true);
}
