class ngraph::pass::low_precision::FakeQuantizeTransformation

Overview

FakeQuantizeTransformation fuses dequantization operations into FakeQuantize operation. More…

#include <fake_quantize.hpp>

class FakeQuantizeTransformation: public ngraph::pass::low_precision::LayerTransformation
{
public:
    // construction

    FakeQuantizeTransformation(const Params& params = Params());

    // methods

    OPENVINO_RTTI("FakeQuantizeTransformation", "0");

    virtual bool transform(
        TransformationContext& context,
        ngraph::pattern::Matcher& m
        );

    virtual bool isPrecisionPreserved(std::shared_ptr<Node> layer) const;
    static bool checkElementwise(const std::shared_ptr<Node>& eltwise);

    static std::shared_ptr<opset1::FakeQuantize> fuseElementwise(
        TransformationContext& context,
        MatcherPass \* matcherPass,
        const std::shared_ptr<opset1::FakeQuantize>& fakeQuantize,
        const bool updatePrecisions
        );
};

Inherited Members

public:
    // typedefs

    typedef DiscreteTypeInfo type_info_t;

    // classes

    class Params;
    class PrecisionDetails;

    // methods

    bool get_property(const PassPropertyMask& prop_mask) const;
    void set_name(const std::string& name);
    std::string get_name() const;
    void set_callback(const param_callback& callback);
    virtual void set_pass_config(const std::shared_ptr<PassConfig>& pass_config);
    std::shared_ptr<PassConfig> get_pass_config();
    bool m_transformation_callback(const std::shared_ptr<const Node>& node);
    bool transformation_callback(const std::shared_ptr<const Node>& node);
    virtual const type_info_t& get_type_info() const = 0;
    OPENVINO_RTTI("ov::pass::MatcherPass");
    MatcherPass& operator = (const MatcherPass&);
    bool apply(std::shared_ptr<ov::Node> node);

    template <typename T, class... Args>
    std::shared_ptr<T> register_new_node(Args&&... args);

    template <typename T>
    std::shared_ptr<T> register_new_node(const std::shared_ptr<T>& node);

    std::shared_ptr<ov::Node> register_new_node_(const std::shared_ptr<ov::Node>& node);
    const std::vector<std::shared_ptr<ov::Node>>& get_new_nodes();
    void clear_new_nodes();
    std::shared_ptr<pattern::Matcher> get_matcher();

    virtual bool transform(
        TransformationContext& context,
        ngraph::pattern::Matcher& m
        ) = 0;

    void setContext(TransformationContext \* context);
    void setUpdatePrecisions(const bool updatePrecisions);
    void setDefaultPrecisions(const std::vector<ngraph::element::Type>& defaultPrecisions);

    virtual bool canBeTransformed(
        const TransformationContext& context,
        std::shared_ptr<Node> layer
        ) const;

    bool canSubtractBeHandled(
        const std::shared_ptr<Node>& op,
        const FakeQuantizeDequantization& dequantization
        ) const;

    virtual bool isQuantized(
        const std::shared_ptr<const Node>& layer,
        const std::vector<ngraph::element::Type>& defaultPrecisions
        ) const;

    virtual bool isPrecisionPreserved(std::shared_ptr<Node> layer) const = 0;

    static bool canBeTransformedStatic(
        const std::shared_ptr<Node>& layer,
        const std::vector<ngraph::element::Type>& defaultPrecisions = precision_set::int8_support
        );

    static PrecisionDetails getPrecisionDetails(
        const size_t quantizationLevels,
        const std::vector<float>& outputLowValues,
        const std::vector<float>& outputHighValues
        );

    static PrecisionDetails getPrecisionDetails(const QuantizationDetails& quantizationDetails);

    static bool isAsymmetricQuantization(
        const std::shared_ptr<const Node>& node,
        const std::vector<ngraph::element::Type>& defaultPrecisions = precision_set::int8_support
        );

    static DataPrecision getDataPrecision(
        const std::shared_ptr<Node>& layer,
        const QuantizationDetails& quantizationDetails,
        const std::vector<element::Type>& requiredPrecisions
        );

Detailed Documentation

FakeQuantizeTransformation fuses dequantization operations into FakeQuantize operation.

For more details about the transformation, refer to FakeQuantizeTransformation page in the Inference Engine Developer Guide.