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class ov::op::v1::AvgPool

Overview

Batched average pooling operation. More…

#include <avg_pool.hpp>

class AvgPool: public ov::op::Op
{
public:
    // fields

     BWDCMP_RTTI_DECLARATION;

    // construction

    AvgPool();

    AvgPool(
        const Output<Node>& arg,
        const Strides& strides,
        const Shape& pads_begin,
        const Shape& pads_end,
        const Shape& kernel,
        bool exclude_pad,
        op::RoundingType rounding_type = op::RoundingType::FLOOR,
        const PadType& auto_pad = op::PadType::EXPLICIT
        );

    // methods

    OPENVINO_OP("AvgPool", "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 Shape& get_kernel() const;
    void set_kernel(const Shape& kernel);
    const Strides& get_strides() const;
    void set_strides(const Strides& strides);
    const Shape& get_pads_begin() const;
    void set_pads_begin(const Shape& pads_begin);
    const Shape& get_pads_end() const;
    void set_pads_end(const Shape& pads_end);
    bool get_exclude_pad() const;
    void set_exclude_pad(bool exclude_pad);
    const PadType& get_auto_pad() const;
    void set_auto_pad(const PadType& auto_pad);
    op::RoundingType get_rounding_type() const;
    void set_rounding_type(op::RoundingType rounding_type);
    virtual OPENVINO_SUPPRESS_DEPRECATED_START std::shared_ptr<Node> get_default_value() const;
};

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_lower(const ov::HostTensorVector& output_values) const;
    virtual bool evaluate_upper(const ov::HostTensorVector& output_values) 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;
    const std::string& get_output_tensor_name(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;
    const std::string& get_input_tensor_name(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

Batched average pooling operation.

Construction

AvgPool()

Constructs a batched average pooling operation.

AvgPool(
    const Output<Node>& arg,
    const Strides& strides,
    const Shape& pads_begin,
    const Shape& pads_end,
    const Shape& kernel,
    bool exclude_pad,
    op::RoundingType rounding_type = op::RoundingType::FLOOR,
    const PadType& auto_pad = op::PadType::EXPLICIT
    )

Constructs a batched average pooling operation.

Parameters:

arg	The output producing the input data batch tensor. [d1, dn]
strides	The strides. [n]
pads_begin	The beginning of padding shape. [n]
pads_end	The end of padding shape. [n]
kernel	The kernel shape. [n]
exclude_pad	If false then averages include padding elements, each treated as the number zero. If true, padding elements are entirely ignored when computing averages.
rounding_type	Whether to use ceiling or floor rounding type while computing output shape.
auto_pad	Padding type to use for additional padded dimensions

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 Shape& get_kernel() const

Returns:

The kernel shape.

const Strides& get_strides() const

Returns:

The strides.

const Shape& get_pads_begin() const

Returns:

The beginning of padding shape.

const Shape& get_pads_end() const

Returns:

The end of padding shape.

const PadType& get_auto_pad() const

Returns:

The pad type for pooling.

virtual OPENVINO_SUPPRESS_DEPRECATED_START std::shared_ptr<Node> get_default_value() const

Returns:

The default value for AvgPool.

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