class ngraph::op::v1::AvgPool


Batched average pooling operation. More…

#include <avg_pool.hpp>

class AvgPool: public ngraph::op::Op
    // construction


        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

    virtual size_t get_version() const;
    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 std::shared_ptr<Node> get_default_value() const;

Inherited Members

    // typedefs

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

    // fields

    NGRAPH_DEPRECATED("The tensor name was deprecated. Use get_input_tensor(i).get_names() instead.") const std std::unordered_set<descriptor::Tensor*> liveness_new_list;
    std::unordered_set<descriptor::Tensor*> liveness_free_list;

    // methods

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

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

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

    virtual bool evaluate_lower(const HostTensorVector& output_values) const;
    virtual bool evaluate_upper(const HostTensorVector& output_values) 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;
    NGRAPH_DEPRECATED("The tensor name was deprecated. Use get_output_tensor(i).get_names() instead.") const std 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;
    const std::unordered_set<std::string>& get_provenance_tags() const;
    void add_provenance_tag(const std::string& tag);

    template <typename T>
    void add_provenance_tags(T tag_set);

    void add_provenance_tags_above(
        const OutputVector& base,
        const std::unordered_set<std::string>& tag_set

    void remove_provenance_tag(const std::string& tag);
    void add_provenance_group_member(const std::shared_ptr<Node>& node);
    void remove_provenance_group_member(const std::shared_ptr<Node>& node);

    void replace_provenance_group_member(
        const std::shared_ptr<Node>& current_node,
        const std::shared_ptr<Node>& replacement_node

    const std::set<std::shared_ptr<Node>>& get_provenance_group_members() const;
    std::shared_ptr<Node> add_provenance_group_members_above(const OutputVector& base);
    void merge_provenance_tags_from(const std::shared_ptr<const Node>& source);
    void transfer_provenance_tags(const std::shared_ptr<Node>& replacement);
    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;
    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 bool match_value(
        pattern::Matcher* matcher,
        const Output<Node>& pattern_value,
        const Output<Node>& graph_value

    virtual bool match_node(
        pattern::Matcher* matcher,
        const Output<Node>& graph_value

Detailed Documentation

Batched average pooling operation.



Constructs a batched average pooling operation.

    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.



The output producing the input data batch tensor.

[d1, dn]


The strides.



The beginning of padding shape.



The end of padding shape.



The kernel shape.



If false then averages include padding elements, each treated as the number zero. If true, padding elements are entirely ignored when computing averages.


Whether to use ceiling or floor rounding type while computing output shape.


Padding type to use for additional padded dimensions


virtual size_t get_version() const


Version of this node

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


The kernel shape.

const Strides& get_strides() const


The strides.

const Shape& get_pads_begin() const


The beginning of padding shape.

const Shape& get_pads_end() const


The end of padding shape.

const PadType& get_auto_pad() const


The pad type for pooling.

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


The default value for AvgPool.