class ov::op::v1::DeformableConvolution


DeformableConvolution operation. More…

#include <deformable_convolution.hpp>

class DeformableConvolution: public ov::op::util::DeformableConvolutionBase
    // construction

    DeformableConvolution(, , , , , , , , , );

    // methods

    "DeformableConvolution""opset1"op::util::DeformableConvolutionBase OPENVINO_OP(


    virtual std::shared_ptr<Node>const OutputVector& clone_with_new_inputs() const;
    virtual void validate_and_infer_types();

Inherited Members

    // 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 boolAttributeVisitor& visit_attributes();
    virtual const ov::op::AutoBroadcastSpec& get_autob() const;
    virtual bool has_evaluate() const;
    virtual boolconst ov::HostTensorVector&const ov::HostTensorVector& evaluate(, ) const;

    virtual boolconst ov::HostTensorVector&const ov::HostTensorVector&const EvaluationContext& evaluate(

        ) const;

    virtual boolov::TensorVector&const ov::TensorVector& evaluate(, ) const;

    virtual boolov::TensorVector&const ov::TensorVector&const ov::EvaluationContext& evaluate(

        ) const;

    virtual boolov::TensorVector& evaluate_lower() const;
    virtual boolov::TensorVector& evaluate_upper() const;
    virtual boolTensorLabelVector& evaluate_label() const;
    virtual boolOutputVector&const OutputVector& constant_fold(, );
    virtual OutputVector decompose_op() const;
    virtual const type_info_t& get_type_info() const = 0;
    const char \* get_type_name() const;
    voidconst NodeVector& set_arguments();
    voidconst OutputVector& set_arguments();
    voidsize_tconst Output<Node>& set_argument(, );
    voidsize_tconst element::Type&const PartialShape& set_output_type(, , );
    voidsize_t set_output_size();
    void invalidate_values();
    virtual void revalidate_and_infer_types();
    virtual std::string description() const;
    const std::string& get_name() const;
    voidconst std::string& set_friendly_name();
    const std::string& get_friendly_name() const;
    virtual bool is_dynamic() const;
    size_t get_instance_id() const;
    virtual std::ostream&std::ostream&uint32_t write_description(, ) const;
    const std::vector<std::shared_ptr<Node>>& get_control_dependencies() const;
    const std::vector<Node \*>& get_control_dependents() const;
    voidstd::shared_ptr<Node> add_control_dependency();
    voidstd::shared_ptr<Node> remove_control_dependency();
    void clear_control_dependencies();
    void clear_control_dependents();
    voidconst std::shared_ptr<const Node>& add_node_control_dependencies();
    voidconst std::shared_ptr<const Node>& add_node_control_dependents();
    voidstd::shared_ptr<Node> transfer_control_dependents();
    size_t get_output_size() const;
    const element::Type&size_t get_output_element_type() const;
    const element::Type& get_element_type() const;
    const Shape&size_t get_output_shape() const;
    const PartialShape&size_t get_output_partial_shape() 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&size_t get_output_tensor() const;
    descriptor::Tensor&size_t get_input_tensor() const;
    std::set<Input<Node>>size_t get_output_target_inputs() const;
    size_t get_input_size() const;
    const element::Type&size_t get_input_element_type() const;
    const Shape&size_t get_input_shape() const;
    const PartialShape&size_t get_input_partial_shape() const;
    Node \*size_t get_input_node_ptr() const;
    std::shared_ptr<Node>size_t get_input_node_shared_ptr() const;
    Output<Node>size_t get_input_source_output() const;
    virtual std::shared_ptr<Node>const OutputVector& clone_with_new_inputs() const = 0;
    std::shared_ptr<Node>const OutputVector& copy_with_new_inputs() const;

    std::shared_ptr<Node>const OutputVector&const std::vector<std::shared_ptr<Node>>& copy_with_new_inputs(

        ) const;

    boolstd::shared_ptr<const Node> has_same_type() const;
    RTMap& get_rt_info();
    const RTMap& get_rt_info() const;
    NodeVectorbool get_users() const;
    boolconst Node& operator < () 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>size_t input();
    Input<const Node>size_t input() const;
    Output<Node>size_t input_value() const;
    Output<Node>size_t output();
    Output<const Node>size_t output() const;

    virtual boolov::pass::pattern::Matcher \*const Output<Node>&const Output<Node>& match_value(


    virtual boolov::pass::pattern::Matcher \*const Output<Node>& match_node(, );
    static _OPENVINO_HIDDEN_METHODconst ::ov::Node::type_info_t& get_type_info_static();
    virtual const ::ov::Node::type_info_t& get_type_info() const;
    "ConvolutionBase""util" OPENVINO_OP(, );
    const Strides& get_strides() const;
    voidconst Strides& set_strides();
    const Strides& get_dilations() const;
    voidconst Strides& set_dilations();
    const CoordinateDiff& get_pads_begin() const;
    voidconst CoordinateDiff& set_pads_begin();
    const CoordinateDiff& get_pads_end() const;
    voidconst CoordinateDiff& set_adding_above();
    voidconst CoordinateDiff& set_pads_end();
    const PadType& get_auto_pad() const;
    voidconst PadType& set_auto_pad();
    "DeformableConvolutionBase""util" OPENVINO_OP(, );
    virtual boolAttributeVisitor& visit_attributes();
    int64_t get_group() const;
    voidconst int64_t set_group();
    int64_t get_deformable_group() const;
    voidconst int64_t set_deformable_group();

Detailed Documentation

DeformableConvolution operation.



Constructs a conversion operation.

DeformableConvolution(, , , , , , , , , )

Constructs a conversion operation.



Node that produces the input tensor.


Node producing the deformable values tensor.


Node producing the filters(kernels) tensor with OIZYX layout.


Convolution strides.


Amount of padding to be added to the beginning along each axis. For example in case of a 2D input the value of (1, 2) means that 1 element will be added to the top and 2 elements to the left.


Amount of padding to be added to the end along each axis.


The distance in width and height between the weights in the filters tensor.


Specifies how the automatic calculation of padding should be done.


The number of groups which both output and input should be split into.


The number of groups which deformable values and output should be split into along the channel axis.


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.