1 #ifndef CAFFE_SWISH_LAYER_HPP_
2 #define CAFFE_SWISH_LAYER_HPP_
6 #include "caffe/blob.hpp"
7 #include "caffe/layer.hpp"
8 #include "caffe/proto/caffe.pb.h"
10 #include "caffe/layers/neuron_layer.hpp"
11 #include "caffe/layers/sigmoid_layer.hpp"
22 template <
typename Dtype>
41 virtual inline const char*
type()
const {
return "Swish"; }
78 const vector<bool>& propagate_down,
const vector<
Blob<Dtype>*>& bottom);
80 const vector<bool>& propagate_down,
const vector<
Blob<Dtype>*>& bottom);
96 #endif // CAFFE_SWISH_LAYER_HPP_
shared_ptr< Blob< Dtype > > sigmoid_output_
sigmoid_output_ stores the output of the SigmoidLayer.
Definition: swish_layer.hpp:87
Sigmoid function non-linearity , a classic choice in neural networks.
Definition: sigmoid_layer.hpp:23
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.
An interface for layers that take one blob as input ( ) and produce one equally-sized blob as output ...
Definition: neuron_layer.hpp:19
vector< Blob< Dtype > * > sigmoid_bottom_vec_
bottom vector holder to call the underlying SigmoidLayer::Forward
Definition: swish_layer.hpp:89
SwishLayer(const LayerParameter ¶m)
Definition: swish_layer.hpp:31
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
virtual void Forward_cpu(const vector< Blob< Dtype > * > &bottom, const vector< Blob< Dtype > * > &top)
Definition: swish_layer.cpp:29
A wrapper around SyncedMemory holders serving as the basic computational unit through which Layers,...
Definition: blob.hpp:24
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_...
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
Swish non-linearity . A novel activation function that tends to work better than ReLU [1].
Definition: swish_layer.hpp:23
virtual const char * type() const
Returns the layer type.
Definition: swish_layer.hpp:41
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
shared_ptr< Blob< Dtype > > sigmoid_input_
sigmoid_input_ stores the input of the SigmoidLayer.
Definition: swish_layer.hpp:85
A layer factory that allows one to register layers. During runtime, registered layers can be called b...
Definition: blob.hpp:14
shared_ptr< SigmoidLayer< Dtype > > sigmoid_layer_
The internal SigmoidLayer.
Definition: swish_layer.hpp:83
vector< Blob< Dtype > * > sigmoid_top_vec_
top vector holder to call the underlying SigmoidLayer::Forward
Definition: swish_layer.hpp:91