class ngraph::pass::low_precision::MultiplyToGroupConvolutionTransformation¶
Overview¶
MultiplyToGroupConvolutionTransformation replace quantized Multiply operations to GroupConvolution to speed up inference. More…
#include <multiply_to_group_convolution.hpp>
class MultiplyToGroupConvolutionTransformation: public ngraph::pass::low_precision::LayerTransformation
{
public:
// construction
MultiplyToGroupConvolutionTransformation(
const Params& params = Params(),
const PrecisionsRestriction::PrecisionsByPorts& restrictions = {}
);
// methods
OPENVINO_RTTI("MultiplyToGroupConvolutionTransformation", "0");
virtual bool transform(
TransformationContext& context,
ngraph::pattern::Matcher& m
);
virtual bool canBeTransformed(
const TransformationContext& context,
std::shared_ptr<Node> layer
) const;
virtual bool isPrecisionPreserved(std::shared_ptr<Node> layer) const;
virtual bool isQuantized(
const std::shared_ptr<const Node>& layer,
const std::vector<ngraph::element::Type>& defaultPrecisions
) const;
void setGroupSize(const size_t groupSize);
size_t getGroupSize() const;
static bool canBeTransformedToGroupConvolution(const std::shared_ptr<const Node>& layer);
static bool isDynamicOrScalar(const std::shared_ptr<const Node>& node);
};
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¶
MultiplyToGroupConvolutionTransformation replace quantized Multiply operations to GroupConvolution to speed up inference.
For more details about the transformation, refer to MultiplyToGroupConvolutionTransformation page in the Inference Engine Developer Guide.