swish_layer.hpp
#ifndef CAFFE_SWISH_LAYER_HPP_
#define CAFFE_SWISH_LAYER_HPP_
#include <vector>
#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"
#include "caffe/layers/neuron_layer.hpp"
#include "caffe/layers/sigmoid_layer.hpp"
namespace caffe {
template <typename Dtype>
class SwishLayer : public NeuronLayer<Dtype> {
public:
explicit SwishLayer(const LayerParameter& param)
: NeuronLayer<Dtype>(param),
sigmoid_layer_(new SigmoidLayer<Dtype>(param)),
sigmoid_input_(new Blob<Dtype>()),
sigmoid_output_(new Blob<Dtype>()) {}
virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual inline const char* type() const { return "Swish"; }
protected:
virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
virtual void Backward_gpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
shared_ptr<SigmoidLayer<Dtype> > sigmoid_layer_;
shared_ptr<Blob<Dtype> > sigmoid_input_;
shared_ptr<Blob<Dtype> > sigmoid_output_;
vector<Blob<Dtype>*> sigmoid_bottom_vec_;
vector<Blob<Dtype>*> sigmoid_top_vec_;
};
} // namespace caffe
#endif // CAFFE_SWISH_LAYER_HPP_
caffe::SwishLayer::sigmoid_output_
shared_ptr< Blob< Dtype > > sigmoid_output_
sigmoid_output_ stores the output of the SigmoidLayer.
Definition: swish_layer.hpp:87
caffe::SigmoidLayer
Sigmoid function non-linearity , a classic choice in neural networks.
Definition: sigmoid_layer.hpp:23
caffe::SwishLayer::Forward_gpu
virtual void Forward_gpu(const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
Using the GPU device, compute the layer output. Fall back to Forward_cpu() if unavailable.
caffe::NeuronLayer
An interface for layers that take one blob as input ( ) and produce one equally-sized blob as output ...
Definition: neuron_layer.hpp:19
caffe::SwishLayer::sigmoid_bottom_vec_
vector< Blob< Dtype > * > sigmoid_bottom_vec_
bottom vector holder to call the underlying SigmoidLayer::Forward
Definition: swish_layer.hpp:89
caffe::SwishLayer::SwishLayer
SwishLayer(const LayerParameter &param)
Definition: swish_layer.hpp:31
caffe::SwishLayer::Reshape
virtual void Reshape(const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs.
Definition: swish_layer.cpp:21
caffe::SwishLayer::Forward_cpu
virtual void Forward_cpu(const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
Definition: swish_layer.cpp:29
caffe::Blob
A wrapper around SyncedMemory holders serving as the basic computational unit through which Layers,...
Definition: blob.hpp:24
caffe::SwishLayer::Backward_gpu
virtual void Backward_gpu(const vector< Blob< Dtype > * > &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > * > &bottom)
Using the GPU device, compute the gradients for any parameters and for the bottom blobs if propagate_...
caffe::SwishLayer::LayerSetUp
virtual void LayerSetUp(const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
Does layer-specific setup: your layer should implement this function as well as Reshape.
Definition: swish_layer.cpp:10
caffe::SwishLayer
Swish non-linearity . A novel activation function that tends to work better than ReLU [1].
Definition: swish_layer.hpp:23
caffe::SwishLayer::type
virtual const char * type() const
Returns the layer type.
Definition: swish_layer.hpp:41
caffe::SwishLayer::Backward_cpu
virtual void Backward_cpu(const vector< Blob< Dtype > * > &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > * > &bottom)
Computes the error gradient w.r.t. the sigmoid inputs.
Definition: swish_layer.cpp:43
caffe::SwishLayer::sigmoid_input_
shared_ptr< Blob< Dtype > > sigmoid_input_
sigmoid_input_ stores the input of the SigmoidLayer.
Definition: swish_layer.hpp:85
caffe
A layer factory that allows one to register layers. During runtime, registered layers can be called b...
Definition: blob.hpp:14
caffe::SwishLayer::sigmoid_layer_
shared_ptr< SigmoidLayer< Dtype > > sigmoid_layer_
The internal SigmoidLayer.
Definition: swish_layer.hpp:83
caffe::SwishLayer::sigmoid_top_vec_
vector< Blob< Dtype > * > sigmoid_top_vec_
top vector holder to call the underlying SigmoidLayer::Forward
Definition: swish_layer.hpp:91