doxygen/rnn__layer_8hpp_source.html

 #ifndef CAFFE_RNN_LAYER_HPP_
 #define CAFFE_RNN_LAYER_HPP_

 #include <string>
 #include <utility>
 #include <vector>

 #include "caffe/blob.hpp"
 #include "caffe/common.hpp"
 #include "caffe/layer.hpp"
 #include "caffe/layers/recurrent_layer.hpp"
 #include "caffe/net.hpp"
 #include "caffe/proto/caffe.pb.h"

 namespace caffe {

 template <typename Dtype> class RecurrentLayer;

 template <typename Dtype>
 class RNNLayer : public RecurrentLayer<Dtype> {
  public:
   explicit RNNLayer(const LayerParameter& param)
       : RecurrentLayer<Dtype>(param) {}

   virtual inline const char* type() const { return "RNN"; }

  protected:
   virtual void FillUnrolledNet(NetParameter* net_param) const;
   virtual void RecurrentInputBlobNames(vector<string>* names) const;
   virtual void RecurrentOutputBlobNames(vector<string>* names) const;
   virtual void RecurrentInputShapes(vector<BlobShape>* shapes) const;
   virtual void OutputBlobNames(vector<string>* names) const;
 };

 }  // namespace caffe

 #endif  // CAFFE_RNN_LAYER_HPP_
caffe::RNNLayer::OutputBlobNames
virtual void OutputBlobNames(vector< string > *names) const
Fills names with the names of the output blobs, concatenated across all timesteps. Should return a name for each top Blob. Subclasses should define this – see RNNLayer and LSTMLayer for examples.
Definition: rnn_layer.cpp:36

caffe::RNNLayer::RecurrentInputShapes
virtual void RecurrentInputShapes(vector< BlobShape > *shapes) const
Fills shapes with the shapes of the recurrent input Blob&s. Subclasses should define this – see RNNL...
Definition: rnn_layer.cpp:26

caffe
A layer factory that allows one to register layers. During runtime, registered layers can be called b...
Definition: blob.hpp:14

caffe::RecurrentLayer
An abstract class for implementing recurrent behavior inside of an unrolled network. This Layer type cannot be instantiated – instead, you should use one of its implementations which defines the recurrent architecture, such as RNNLayer or LSTMLayer.
Definition: lstm_layer.hpp:17

caffe::RNNLayer::FillUnrolledNet
virtual void FillUnrolledNet(NetParameter *net_param) const
Fills net_param with the recurrent network architecture. Subclasses should define this – see RNNLaye...
Definition: rnn_layer.cpp:42

caffe::RNNLayer::type
virtual const char * type() const
Returns the layer type.
Definition: rnn_layer.hpp:35

caffe::RNNLayer::RecurrentOutputBlobNames
virtual void RecurrentOutputBlobNames(vector< string > *names) const
Fills names with the names of the Tth timestep recurrent output Blob&s. Subclasses should define this...
Definition: rnn_layer.cpp:20

caffe::RNNLayer
Processes time-varying inputs using a simple recurrent neural network (RNN). Implemented as a network...
Definition: rnn_layer.hpp:30

caffe::RNNLayer::RecurrentInputBlobNames
virtual void RecurrentInputBlobNames(vector< string > *names) const
Fills names with the names of the 0th timestep recurrent input Blob&s. Subclasses should define this ...
Definition: rnn_layer.cpp:14