OpenCV: cv::dnn::RNNLayer Class Reference

| OpenCV 3.4.2 Open Source Computer Vision

Public Member Functions | Static Public Member Functions | List of all members
cv::dnn::RNNLayer Class Referenceabstract
Deep Neural Network module » Partial List of Implemented Layers

Classical recurrent layer. More...

`#include "all_layers.hpp"`

Inheritance diagram for cv::dnn::RNNLayer:

## Public Member Functions
virtual void | setProduceHiddenOutput (bool produce=false)=0
| If this flag is set to true then layer will produce \( h_t \) as second output. More...
virtual void | setWeights (const Mat &Wxh, const Mat &bh, const Mat &Whh, const Mat &Who, const Mat &bo)=0
Public Member Functions inherited from cv::dnn::Layer
| Layer ()
| Layer (const LayerParams &params)
| Initializes only name, type and blobs fields. More...
virtual | ~Layer ()
virtual void | applyHalideScheduler (Ptr< BackendNode > &node, const std::vector< Mat *> &inputs, const std::vector< Mat > &outputs, int targetId) const
| Automatic Halide scheduling based on layer hyper-parameters. More...
virtual void | finalize (const std::vector< Mat *> &input, std::vector< Mat > &output)
| Computes and sets internal parameters according to inputs, outputs and blobs. More...
void | finalize (const std::vector< Mat > &inputs, std::vector< Mat > &outputs)
std::vector< Mat > | finalize (const std::vector< Mat > &inputs)
virtual void | forward (std::vector< Mat *> &input, std::vector< Mat > &output, std::vector< Mat > &internals)=0
| Given the `input` blobs, computes the output `blobs`. More...
virtual void | forward (InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals)=0
| Given the `input` blobs, computes the output `blobs`. More...
void | forward_fallback (InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals)
| Given the `input` blobs, computes the output `blobs`. More...
virtual int64 | getFLOPS (const std::vector< MatShape > &inputs, const std::vector< MatShape > &outputs) const
virtual bool | getMemoryShapes (const std::vector< MatShape > &inputs, const int requiredOutputs, std::vector< MatShape > &outputs, std::vector< MatShape > &internals) const
virtual void | getScaleShift (Mat &scale, Mat &shift) const
| Returns parameters of layers with channel-wise multiplication and addition. More...
virtual Ptr< BackendNode > | initHalide (const std::vector< Ptr< BackendWrapper > > &inputs)
| Returns Halide backend node. More...
virtual Ptr< BackendNode > | initInfEngine (const std::vector< Ptr< BackendWrapper > > &inputs)
virtual int | inputNameToIndex (String inputName)
| Returns index of input blob into the input array. More...
virtual int | outputNameToIndex (const String &outputName)
| Returns index of output blob in output array. More...
void | run (const std::vector< Mat > &inputs, std::vector< Mat > &outputs, std::vector< Mat > &internals)
| Allocates layer and computes output. More...
virtual bool | setActivation (const Ptr< ActivationLayer > &layer)
| Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case. More...
void | setParamsFrom (const LayerParams &params)
| Initializes only name, type and blobs fields. More...
virtual bool | supportBackend (int backendId)
| Ask layer if it support specific backend for doing computations. More...
virtual Ptr< BackendNode > | tryAttach (const Ptr< BackendNode > &node)
| Implement layers fusing. More...
virtual bool | tryFuse (Ptr< Layer > &top)
| Try to fuse current layer with a next one. More...
virtual void | unsetAttached ()
| "Deattaches" all the layers, attached to particular layer. More...
Public Member Functions inherited from cv::Algorithm
| Algorithm ()
virtual | ~Algorithm ()
virtual void | clear ()
| Clears the algorithm state. More...
virtual bool | empty () const
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
virtual String | getDefaultName () const
virtual void | read (const FileNode &fn)
| Reads algorithm parameters from a file storage. More...
virtual void | save (const String &filename) const
virtual void | write (FileStorage &fs) const
| Stores algorithm parameters in a file storage. More...
void | write (const Ptr< FileStorage > &fs, const String &name=String()) const
| simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

## Static Public Member Functions
static Ptr< RNNLayer > | create (const LayerParams &params)
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp > | load (const String &filename, const String &objname=String())
| Loads algorithm from the file. More...
template<typename _Tp >
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String())
| Loads algorithm from a String. More...
template<typename _Tp >
static Ptr< _Tp > | read (const FileNode &fn)
| Reads algorithm from the file node. More...

## Additional Inherited Members
Public Attributes inherited from cv::dnn::Layer
std::vector< Mat > | blobs
| List of learned parameters must be stored here to allow read them by using Net::getParam(). More...
String | name
| Name of the layer instance, can be used for logging or other internal purposes. More...
int | preferableTarget
| prefer target for layer forwarding More...
String | type
| Type name which was used for creating layer by layer factory. More...
Protected Member Functions inherited from cv::Algorithm
void | writeFormat (FileStorage &fs) const

## Detailed Description

Classical recurrent layer.

Accepts two inputs \(x_t\) and \(h_{t-1}\) and compute two outputs \(o_t\) and \(h_t\).

- input: should contain packed input \(x_t\).
- output: should contain output \(o_t\) (and \(h_t\) if setProduceHiddenOutput() is set to true).

input[0] should have shape [`T`, `N`, `data_dims`] where `T` and `N` is number of timestamps and number of independent samples of \(x_t\) respectively.

output[0] will have shape [`T`, `N`, \(N_o\)], where \(N_o\) is number of rows in \( W_{xo} \) matrix.

If setProduceHiddenOutput() is set to true then `output`[1] will contain a Mat with shape [`T`, `N`, \(N_h\)], where \(N_h\) is number of rows in \( W_{hh} \) matrix.

## Member Function Documentation

## ◆ create()

static Ptr<RNNLayer> cv::dnn::RNNLayer::create | ( | const LayerParams & | params | ) |
| static

Creates instance of RNNLayer

## ◆ setProduceHiddenOutput()

virtual void cv::dnn::RNNLayer::setProduceHiddenOutput | ( | bool | produce = `false` | ) |
| pure virtual

If this flag is set to true then layer will produce \( h_t \) as second output.

Shape of the second output is the same as first output.

## ◆ setWeights()

virtual void cv::dnn::RNNLayer::setWeights | ( | const Mat & | Wxh,
|  | const Mat & | bh,
|  | const Mat & | Whh,
|  | const Mat & | Who,
|  | const Mat & | bo
| ) |  |
| pure virtual

Setups learned weights.

Recurrent-layer behavior on each step is defined by current input \( x_t \), previous state \( h_t \) and learned weights as follows:

\begin{eqnarray*} h_t &= tanh&(W_{hh} h_{t-1} + W_{xh} x_t + b_h), \\ o_t &= tanh&(W_{ho} h_t + b_o), \end{eqnarray*}

Parameters

  Wxh | is \( W_{xh} \) matrix
  bh | is \( b_{h} \) vector
  Whh | is \( W_{hh} \) matrix
  Who | is \( W_{xo} \) matrix
  bo | is \( b_{o} \) vector

The documentation for this class was generated from the following file:

- dnn/include/opencv2/dnn/all_layers.hpp