class InferenceEngine::RNNCellBase


Base class for recurrent cell layers. More…

#include <ie_layers.h>

class RNNCellBase: public InferenceEngine::WeightableLayer
    // enums

    enum CellType;

    // fields

    CellType cellType = LSTM;
    int hidden_size = 0;
    float clip = 0.0f;
    std::vector<std::string> activations;
    std::vector<float> activation_alpha;
    std::vector<float> activation_beta;

    // methods

    WeightableLayer(const LayerParams& prms);

// direct descendants

class GRUCell;
class LSTMCell;
class RNNCell;
class RNNSequenceLayer;

Inherited Members

    // typedefs

    typedef std::shared_ptr<CNNLayer> Ptr;

    // fields

    std::string name;
    std::string type;
    Precision precision;
    std::vector<DataPtr> outData;
    std::vector<DataWeakPtr> insData;
    Ptr _fusedWith;
    UserValue userValue;
    std::string affinity;
    std::map<std::string, std::string> params;
    std::map<std::string, Blob::Ptr> blobs;
    Blob::Ptr _weights;
    Blob::Ptr _biases;

    // methods

    std::shared_ptr<ngraph::Node> getNode() const;
    void fuse(Ptr& layer);
    virtual const DataPtr input() const;
    void parseParams();
    float GetParamAsFloat(const char \* param, float def) const;
    float GetParamAsFloat(const char \* param) const;
    std::vector<float> GetParamAsFloats(const char \* param, std::vector<float> def) const;
    std::vector<float> GetParamAsFloats(const char \* param) const;
    int GetParamAsInt(const char \* param, int def) const;
    int GetParamAsInt(const char \* param) const;
    std::vector<int> GetParamAsInts(const char \* param, std::vector<int> def) const;
    std::vector<int> GetParamAsInts(const char \* param) const;
    unsigned int GetParamAsUInt(const char \* param, unsigned int def) const;
    unsigned int GetParamAsUInt(const char \* param) const;
    size_t GetParamAsSizeT(const char \* param, size_t def) const;
    size_t GetParamAsSizeT(const char \* param) const;

    std::vector<unsigned int> GetParamAsUInts(
        const char \* param,
        std::vector<unsigned int> def
        ) const;

    std::vector<unsigned int> GetParamAsUInts(const char \* param) const;
    bool GetParamAsBool(const char \* param, bool def) const;
    bool GetParamAsBool(const char \* param) const;
    std::string GetParamAsString(const char \* param, const char \* def) const;
    bool CheckParamPresence(const char \* param) const;
    std::string GetParamAsString(const char \* param) const;
    std::string getBoolStrParamAsIntStr(const char \* param) const;

    std::vector<std::string> GetParamAsStrings(
        const char \* param,
        std::vector<std::string> def
        ) const;

    static float ie_parse_float(const std::string& str);
    static std::string ie_serialize_float(float value);
    CNNLayer(const LayerParams& prms);
    CNNLayer(const CNNLayer& other);

Detailed Documentation

Base class for recurrent cell layers.

Deprecated Migrate to IR v10 and work with ngraph::Function directly. The method will be removed in 2021.1


CellType cellType = LSTM

Direct type of recurrent cell (including subtypes) Description of particular cell semantics is in LSTMCell, GRUCell, RNNCell.

int hidden_size = 0

Size of hidden state data.

In case of batch output state tensor will have shape [N, hidden_size]

float clip = 0.0f

Clip data into range [-clip, clip] on input of activations.

clip==0.0f means no clipping

std::vector<std::string> activations

Activations used inside recurrent cell.

Valid values: sigmoid, tanh, relu

std::vector<float> activation_alpha

Alpha parameters of activations.

Respective to activation list.

std::vector<float> activation_beta

Beta parameters of activations.

Respective to activation list.


WeightableLayer(const LayerParams& prms)

A default constructor. Constructs a WeightableLayer instance and initiates layer parameters with the given values.



Initial layer parameters