class ov::op::v1::BinaryConvolution

Overview

BinaryConvolution operation. More…

#include <binary_convolution.hpp>

class BinaryConvolution: public ov::op::Op
{
public:
    // enums

    enum BinaryConvolutionMode;

    // construction

    BinaryConvolution();

    BinaryConvolution(
        const Output<Node>& data,
        const Output<Node>& kernel,
        const Strides& strides,
        const CoordinateDiff& pads_begin,
        const CoordinateDiff& pads_end,
        const Strides& dilations,
        BinaryConvolutionMode mode,
        float pad_value,
        const PadType& auto_pad = PadType::EXPLICIT
        );

    BinaryConvolution(
        const Output<Node>& data,
        const Output<Node>& kernel,
        const Strides& strides,
        const CoordinateDiff& pads_begin,
        const CoordinateDiff& pads_end,
        const Strides& dilations,
        const std::string& mode,
        float pad_value,
        const PadType& auto_pad = PadType::EXPLICIT
        );

    // methods

    OPENVINO_OP("BinaryConvolution", "opset1", op::Op, 1);
    virtual void validate_and_infer_types();
    virtual bool visit_attributes(AttributeVisitor& visitor);
    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const;
    const Strides& get_strides() const;
    void set_strides(const Strides& strides);
    const Strides& get_dilations() const;
    void set_dilations(const Strides& dilations);
    const CoordinateDiff& get_pads_begin() const;
    void set_pads_begin(const CoordinateDiff& pads_begin);
    const CoordinateDiff& get_pads_end() const;
    void set_adding_above(const CoordinateDiff& pads_end);
    const PadType& get_auto_pad() const;
    void set_auto_pad(const PadType& auto_pad);
    const BinaryConvolutionMode& get_mode() const;
    void set_mode(const BinaryConvolutionMode& mode);
    float get_pad_value() const;
    void set_pad_value(float pad_value);
};

Inherited Members

public:
    // typedefs

    typedef DiscreteTypeInfo type_info_t;
    typedef std::map<std::string, Any> RTMap;

    // methods

    virtual void validate_and_infer_types();
    void constructor_validate_and_infer_types();
    virtual bool visit_attributes(AttributeVisitor&);
    virtual const ov::op::AutoBroadcastSpec& get_autob() const;
    virtual bool has_evaluate() const;

    virtual bool evaluate(
        const ov::HostTensorVector& output_values,
        const ov::HostTensorVector& input_values
        ) const;

    virtual bool evaluate(
        const ov::HostTensorVector& output_values,
        const ov::HostTensorVector& input_values,
        const EvaluationContext& evaluationContext
        ) const;

    virtual bool evaluate(
        ov::TensorVector& output_values,
        const ov::TensorVector& input_values
        ) const;

    virtual bool evaluate(
        ov::TensorVector& output_values,
        const ov::TensorVector& input_values,
        const ov::EvaluationContext& evaluationContext
        ) const;

    virtual bool evaluate_lower(ov::TensorVector& output_values) const;
    virtual bool evaluate_upper(ov::TensorVector& output_values) const;
    virtual bool evaluate_label(TensorLabelVector& output_labels) const;

    virtual bool constant_fold(
        OutputVector& output_values,
        const OutputVector& inputs_values
        );

    virtual OutputVector decompose_op() const;
    virtual const type_info_t& get_type_info() const = 0;
    const char \* get_type_name() const;
    void set_arguments(const NodeVector& arguments);
    void set_arguments(const OutputVector& arguments);
    void set_argument(size_t position, const Output<Node>& argument);

    void set_output_type(
        size_t i,
        const element::Type& element_type,
        const PartialShape& pshape
        );

    void set_output_size(size_t output_size);
    void invalidate_values();
    virtual void revalidate_and_infer_types();
    virtual std::string description() const;
    const std::string& get_name() const;
    void set_friendly_name(const std::string& name);
    const std::string& get_friendly_name() const;
    virtual bool is_dynamic() const;
    size_t get_instance_id() const;
    virtual std::ostream& write_description(std::ostream& os, uint32_t depth = 0) const;
    const std::vector<std::shared_ptr<Node>>& get_control_dependencies() const;
    const std::vector<Node \*>& get_control_dependents() const;
    void add_control_dependency(std::shared_ptr<Node> node);
    void remove_control_dependency(std::shared_ptr<Node> node);
    void clear_control_dependencies();
    void clear_control_dependents();
    void add_node_control_dependencies(std::shared_ptr<Node> source_node);
    void add_node_control_dependents(std::shared_ptr<Node> source_node);
    void transfer_control_dependents(std::shared_ptr<Node> replacement);
    size_t get_output_size() const;
    const element::Type& get_output_element_type(size_t i) const;
    const element::Type& get_element_type() const;
    const Shape& get_output_shape(size_t i) const;
    const PartialShape& get_output_partial_shape(size_t i) const;
    Output<const Node> get_default_output() const;
    Output<Node> get_default_output();
    virtual size_t get_default_output_index() const;
    size_t no_default_index() const;
    const Shape& get_shape() const;
    descriptor::Tensor& get_output_tensor(size_t i) const;
    descriptor::Tensor& get_input_tensor(size_t i) const;
    std::set<Input<Node>> get_output_target_inputs(size_t i) const;
    size_t get_input_size() const;
    const element::Type& get_input_element_type(size_t i) const;
    const Shape& get_input_shape(size_t i) const;
    const PartialShape& get_input_partial_shape(size_t i) const;
    Node \* get_input_node_ptr(size_t index) const;
    std::shared_ptr<Node> get_input_node_shared_ptr(size_t index) const;
    Output<Node> get_input_source_output(size_t i) const;
    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& inputs) const = 0;
    std::shared_ptr<Node> copy_with_new_inputs(const OutputVector& new_args) const;

    std::shared_ptr<Node> copy_with_new_inputs(
        const OutputVector& inputs,
        const std::vector<std::shared_ptr<Node>>& control_dependencies
        ) const;

    bool has_same_type(std::shared_ptr<const Node> node) const;
    RTMap& get_rt_info();
    const RTMap& get_rt_info() const;
    NodeVector get_users(bool check_is_used = false) const;
    virtual size_t get_version() const;
    virtual std::shared_ptr<Node> get_default_value() const;
    bool operator < (const Node& other) const;
    std::vector<Input<Node>> inputs();
    std::vector<Input<const Node>> inputs() const;
    std::vector<Output<Node>> input_values() const;
    std::vector<Output<Node>> outputs();
    std::vector<Output<const Node>> outputs() const;
    Input<Node> input(size_t input_index);
    Input<const Node> input(size_t input_index) const;
    Output<Node> input_value(size_t input_index) const;
    Output<Node> output(size_t output_index);
    Output<const Node> output(size_t output_index) const;
    OPENVINO_SUPPRESS_DEPRECATED_START void set_op_annotations(std::shared_ptr<ngraph::op::util::OpAnnotations> op_annotations);
    std::shared_ptr<ngraph::op::util::OpAnnotations> get_op_annotations() const;

    virtual OPENVINO_SUPPRESS_DEPRECATED_END bool match_value(
        ov::pass::pattern::Matcher \* matcher,
        const Output<Node>& pattern_value,
        const Output<Node>& graph_value
        );

    virtual bool match_node(
        ov::pass::pattern::Matcher \* matcher,
        const Output<Node>& graph_value
        );

    static _OPENVINO_HIDDEN_METHODconst ::ov::Node::type_info_t& get_type_info_static();
    virtual const ::ov::Node::type_info_t& get_type_info() const;

Detailed Documentation

BinaryConvolution operation.

Construction

BinaryConvolution()

Constructs a binary convolution operation.

BinaryConvolution(
    const Output<Node>& data,
    const Output<Node>& kernel,
    const Strides& strides,
    const CoordinateDiff& pads_begin,
    const CoordinateDiff& pads_end,
    const Strides& dilations,
    BinaryConvolutionMode mode,
    float pad_value,
    const PadType& auto_pad = PadType::EXPLICIT
    )

Constructs a binary convolution operation.

Output [N, C_OUT, R1, ... Rf]

Parameters:

data

The node producing the input data batch tensor.

kernel

The node producing the filters tensor.

strides

The strides.

pads_begin

The beginning of padding shape.

pads_end

The end of padding shape.

dilations

The dilations.

mode

Defines how input tensor 0/1 values and weights 0/1 are interpreted.

pad_value

Floating-point value used to fill pad area.

auto_pad

The pad type for automatically computing padding sizes.

Methods

virtual void validate_and_infer_types()

Verifies that attributes and inputs are consistent and computes output shapes and element types. Must be implemented by concrete child classes so that it can be run any number of times.

Throws if the node is invalid.

const Strides& get_strides() const

Returns:

The strides.

const Strides& get_dilations() const

Returns:

The dilations.

const CoordinateDiff& get_pads_begin() const

Returns:

The padding-below sizes (possibly negative).

const CoordinateDiff& get_pads_end() const

Returns:

The padding-above sizes (possibly negative).

const PadType& get_auto_pad() const

Returns:

The pad type for convolution.

const BinaryConvolutionMode& get_mode() const

Returns:

The mode of convolution.

float get_pad_value() const

Returns:

The pad value.