class ngraph::op::util::UnaryElementwiseArithmetic

Overview

Abstract base class for elementwise unary arithmetic operations, i.e., operations where the same scalar arithmetic operation is applied to each element. More…

#include <unary_elementwise_arithmetic.hpp>

class UnaryElementwiseArithmetic: public ngraph::op::Op
{
public:
    // methods

    virtual void validate_and_infer_types();
    virtual bool visit_attributes(AttributeVisitor& visitor);
};

// direct descendants

class Abs;
class Acos;
class Asin;
class Atan;
class Ceiling;
class Cos;
class Cosh;
class Erf;
class Exp;
class Floor;
class Log;
class Negative;
class Relu;
class Sigmoid;
class Sign;
class Sin;
class Sinh;
class Sqrt;
class Tan;
class Tanh;
class Acosh;
class Asinh;
class Atanh;
class HSwish;
class HSigmoid;
class Gelu;

Inherited Members

public:
    // 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

Abstract base class for elementwise unary arithmetic operations, i.e., operations where the same scalar arithmetic operation is applied to each element.

For example, if the underlying operation (determined by the subclass) is \(\mathit{op}(x)\), the input tensor \([[x,y],[z,w]]\) will be mapped to \([[\mathit{op}(x),\mathit{op}(y)],[\mathit{op}(z),\mathit{op}(w)]]\).

Inputs

Type

Description

arg

\(N[d_1,\dots,d_n]~(n \geq 0)\)

A tensor of any shape. The element type \(N\) may be any numeric type.

Type

Description

\(N[d_1,\dots,d_n]\)

The tensor \(T\) , where \(T[i_1,\dots,i_n] = \mathit{op}(\texttt{arg}[i_1,\dots,i_n])\) . This will always have the same shape and element type as the input tensor.

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.