class ngraph::pass::low_precision::MarkupCanBeQuantized¶

Overview¶

MarkupCanBeQuantized transformation marks Convolution, ConvolutionBackpropData, GroupConvolution and Concat operations as able to be quantized or not. If an operation is not quantized, then PrecisionsAttribute attribute instance is created with empty precisions. More…

#include <markup_can_be_quantized.hpp>

class MarkupCanBeQuantized: public ov::pass::ModelPass
{
public:
    // construction

    MarkupCanBeQuantized();

    // methods

    "MarkupCanBeQuantized""0" OPENVINO_RTTI(, );
    boolconst std::shared_ptr<ngraph::Function>& run_on_model();
};

Inherited Members¶

public:
    // typedefs

    typedef DiscreteTypeInfo type_info_t;

    // methods

    boolconst PassPropertyMask& get_property() const;
    voidconst std::string& set_name();
    std::string get_name() const;
    voidconst param_callback& set_callback();
    virtual voidconst std::shared_ptr<PassConfig>& set_pass_config();
    std::shared_ptr<PassConfig> get_pass_config();
    boolconst std::shared_ptr<const Node>& transformation_callback();
    virtual const type_info_t& get_type_info() const = 0;
    "ov::pass::ModelPass" OPENVINO_RTTI();
    virtual boolconst std::shared_ptr<ov::Model>& run_on_model() = 0;

Detailed Documentation¶

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