Group Basics#

group ov_model_cpp_api

OpenVINO Core C++ API to work with ov::Model, dynamic and static shapes, types

Functions

template<typename ForwardIt>
size_t shape_size(ForwardIt start_dim, const ForwardIt end_dim)#

Number of elements in a subset of dimensions of a shape. Returns a product of dimensions in a range [start_dim;end_dim)

template<typename SHAPE_TYPE>
size_t shape_size(const SHAPE_TYPE &shape)#

Number of elements in spanned by a shape.

class Dimension
#include <dimension.hpp>

Class representing a dimension, which may be dynamic (undetermined until runtime), in a shape or shape-like object.

Static dimensions may be implicitly converted from value_type. A dynamic dimension is constructed with Dimension() or Dimension::dynamic().

Public Functions

Dimension(value_type dimension)

Construct a static dimension.

Parameters:

dimension – Value of the dimension.

Dimension(value_type min_dimension, value_type max_dimension)

Construct a dynamic dimension with bounded range.

Parameters:
  • min_dimension – The lower inclusive limit for the dimension

  • max_dimension – The upper inclusive limit for the dimension

Dimension(const std::string &str)

Construct a dimension from string.

Parameters:

str – String to parse to dimension.

Dimension() = default

Construct a dynamic dimension with range [0, …].

inline bool is_static() const

Check whether this dimension is static.

Returns:

true if the dimension is static, else false.

inline bool is_dynamic() const

Check whether this dimension is dynamic.

Returns:

false if the dimension is static, else true.

value_type get_length() const

Convert this dimension to value_type. This dimension must be static and non-negative.

Throws:

std::invalid_argument – If this dimension is dynamic or negative.

inline const Interval &get_interval() const

Return the interval of valid lengths.

bool same_scheme(const Dimension &dim) const

Check whether this dimension represents the same scheme as the argument (both dynamic, or equal).

Parameters:

dim – The other dimension to compare this dimension to.

Returns:

true if this dimension and dim are both dynamic, or if they are both static and equal; otherwise, false.

bool compatible(const Dimension &d) const

Check whether this dimension is capable of being merged with the argument dimension.

Two dimensions are considered compatible if it is possible to merge them. (See Dimension::merge.)

Parameters:

d – The dimension to compare this dimension with.

Returns:

true if this dimension is compatible with d, else false.

bool relaxes(const Dimension &d) const

Check whether this dimension is a relaxation of the argument.

A dimension d1 relaxes (or is a relaxation of) d2 if d1 and d2 are static and equal, or d1 is dynamic.

d1.relaxes(d2) is equivalent to d2.refines(d1).

Parameters:

d – The dimension to compare this dimension with.

Returns:

true if this dimension relaxes d, else false.

bool refines(const Dimension &d) const

Check whether this dimension is a refinement of the argument.

A dimension d2 refines (or is a refinement of) d1 if d1 and d2 are static and equal, or d2 is dynamic.

d1.refines(d2) is equivalent to d2.relaxes(d1).

Parameters:

d – The dimension to compare this dimension with.

Returns:

true if this dimension relaxes d, else false.

Dimension operator+(const Dimension &dim) const

Addition operator for Dimension.

Parameters:

dim – Right operand for addition.

Returns:

Smallest interval dimension enclosing inputs

Dimension operator-(const Dimension &dim) const

Subtraction operator for Dimension.

Parameters:

dim – Right operand for subtraction.

Returns:

Smallest interval dimension enclosing inputs

Dimension operator/(const value_type divisor) const

Division operator for Dimension divided by a value_type parameter.

Parameters:

divisor – Right operand for division.

Returns:

Smallest interval dimension enclosing inputs

inline Dimension &operator/=(const value_type divisor)

Divided-into operator for Dimension.

Parameters:

divisor – Right operand for multiplication.

Returns:

A reference to *this, after updating *this to the value *this * dim.

Dimension operator*(const Dimension &dim) const

Multiplication operator for Dimension.

Parameters:

dim – Right operand for multiplicaiton.

Returns:

Smallest interval containing all “produces” which are 0 if either of this or dim has length 0, else unbounded if either is unbounded, else product of lengths.

inline Dimension &operator+=(const Dimension &dim)

Add-into operator for Dimension.

Parameters:

dim – Right operand for addition.

Returns:

A reference to *this, after updating *this to the value *this + dim.

inline Dimension &operator*=(const Dimension &dim)

Multiply-into operator for Dimension.

Parameters:

dim – Right operand for multiplication.

Returns:

A reference to *this, after updating *this to the value *this * dim.

Dimension operator&(const Dimension &dim) const

Intersection of dimensions.

Dimension &operator&=(const Dimension &dim)

Intersection of dimensions.

std::string to_string() const

String representation of Dimension.

bool has_symbol() const

Indicates if meaningful symbol was set to the Dimension.

std::shared_ptr<ov::Symbol> get_symbol() const

Returns symbol of the Dimension.

void set_symbol(const std::shared_ptr<ov::Symbol> &s)

Sets symbol of the Dimension.

Public Static Functions

static bool merge(Dimension &dst, const Dimension &d1, const Dimension &d2)

Try to merge two Dimension objects together.

  • If d1 is dynamic, writes d2 to dst and returns true.

  • If d2 is dynamic, writes d1 to dst and returns true.

  • If d1 and d2 are static and equal, writes d1 to dst and returns true.

  • If d1 and d2 are both static and unequal, leaves dst unchanged and returns false.

Parameters:
  • dst[out] Reference to write the merged Dimension into.

  • d1 – First dimension to merge.

  • d2 – Second dimension to merge.

Returns:

true if merging succeeds, else false.

static bool broadcast_merge(Dimension &dst, const Dimension &d1, const Dimension &d2)

Try to merge two Dimension objects together with implicit broadcasting of unit-sized dimension to non unit-sized dimension.

static inline Dimension dynamic()

Create a dynamic dimension.

Returns:

A dynamic dimension.

Friends

inline friend void swap(Dimension &a, Dimension &b)

Swap of dimensions.

class Extension
#include <extension.hpp>

The class provides the base interface for OpenVINO extensions.

Subclassed by ov::BaseOpExtension, ov::frontend::ConversionExtensionBase, ov::frontend::DecoderTransformationExtension, ov::frontend::ProgressReporterExtension, ov::frontend::TelemetryExtension

class Model : public std::enable_shared_from_this<Model>
#include <model.hpp>

A user-defined model.

Public Functions

explicit Model(const ov::OutputVector &results, const std::string &name = "")

Constructs a Model. Lists of parameters and variables will be generated automatically based on traversing the graph from the results.

Model(const ov::OutputVector &results, const ov::SinkVector &sinks, const std::string &name = "")

Constructs a Model. Lists of parameters and variables will be generated automatically based on traversing the graph from the results and the sinks.

size_t get_output_size() const

Return the number of outputs for this Model.

std::shared_ptr<ov::Node> get_output_op(size_t i) const

Return the op that generates output i.

std::shared_ptr<ov::Model> clone() const

Clones the original model.

std::vector<ov::Output<ov::Node>> outputs()

Model outputs.

std::vector<ov::Output<ov::Node>> inputs()

Model inputs.

const ov::element::Type &get_output_element_type(size_t i) const

Return the element type of output i.

const Shape &get_output_shape(size_t i) const

Return the shape of element i.

const PartialShape &get_output_partial_shape(size_t i) const

Return the partial shape of element i.

std::shared_ptr<ov::Node> get_result() const

Check that there is a single result and return it.

const std::string &get_name() const

Get the unique name of the model.

Returns:

A const reference to the model’s unique name.

void set_friendly_name(const std::string &name)

Sets a friendly name for a model. This does not overwrite the unique name of the model and is retrieved via get_friendly_name(). Used mainly for debugging.

Parameters:

name – is the friendly name to set

const std::string &get_friendly_name() const

Gets the friendly name for a model. If no friendly name has been set via set_friendly_name then the model’s unique name is returned.

Returns:

A const reference to the model’s friendly name.

size_t get_graph_size() const

Returns the sum of the size of all nodes in the graph plus the size of all constant data. This has little value beyond comparing the relative size of graphs and should not be considered the actual memory consumption of a graph.

bool is_dynamic() const

Returns true if any of the op’s defined in the model contains partial shape.

void replace_parameter(size_t parameter_index, const std::shared_ptr<ov::op::v0::Parameter> &parameter)

Replace the parameter_indexth parameter of the model with parameter.

All users of the parameter_indexth parameter are redirected to parameter, and the parameter_indexth entry in the model parameter list is replaced with parameter.

Parameters:
  • parameter_index – The index of the parameter to replace.

  • parameter – The parameter to substitute for the parameter_indexth parameter.

inline const ov::ParameterVector &get_parameters() const

Return the model parameters.

inline const ov::ResultVector &get_results() const

Return a list of model’s outputs.

int64_t get_parameter_index(const std::shared_ptr<ov::op::v0::Parameter> &parameter) const

Index for parameter, or -1.

int64_t get_result_index(const ov::Output<ov::Node> &value) const

Return the index of this model’s Result represented by the “value” Output object. This method returns -1 if an the passed output is not related to the Results of a model.

Parameters:

valueOutput containing Node

int64_t get_result_index(const ov::Output<const ov::Node> &value) const

Return the index of this model’s Result represented by the “value” Output object. This method returns -1 if an the passed output is not related to the Results of a model.

Parameters:

valueOutput containing Node

bool evaluate(ov::TensorVector &output_tensors, const ov::TensorVector &input_tensors, ov::EvaluationContext &evaluation_context) const

Evaluate the model on inputs, putting results in outputs.

Parameters:
  • output_tensors – Tensors for the outputs to compute. One for each result

  • input_tensors – Tensors for the inputs. One for each inputs.

  • evaluation_context – Storage of additional settings and attributes that can be used when evaluating the model. This additional information can be shared across nodes.

bool evaluate(ov::TensorVector &output_tensors, const ov::TensorVector &input_tensors) const

Evaluate the model on inputs, putting results in outputs.

Parameters:
  • output_tensors – Tensors for the outputs to compute. One for each result

  • input_tensors – Tensors for the inputs. One for each inputs.

inline const ov::SinkVector &get_sinks() const

Return a list of model’s sinks.

void add_sinks(const ov::SinkVector &sinks)

Add new sink nodes to the list. Method doesn’t validate graph, it should be done manually after all changes.

Parameters:

sinks – new sink nodes

void remove_sink(const std::shared_ptr<ov::op::Sink> &sink)

Delete sink node from the list of sinks. Method doesn’t delete node from graph.

Parameters:

sink – Sink to delete

void add_results(const ov::ResultVector &results)

Add new Result nodes to the list. Method doesn’t validate graph, it should be done manually after all changes.

Parameters:

results – new Result nodes

void remove_result(const std::shared_ptr<ov::op::v0::Result> &result)

Delete Result node from the list of results. Method will not delete node from graph.

Parameters:

result – Result node to delete

void add_parameters(const ov::ParameterVector &params)

Add new Parameter nodes to the list.

Method doesn’t change or validate graph, it should be done manually. For example, if you want to replace ReadValue node by Parameter, you should do the following steps:

  • replace node ReadValue by Parameter in graph

  • call add_parameter() to add new input to the list

  • call graph validation to check correctness of changes

Parameters:

params – new Parameter nodes

void remove_parameter(const std::shared_ptr<ov::op::v0::Parameter> &param)

Delete Parameter node from the list of parameters. Method will not delete node from graph. You need to replace Parameter with other operation manually. Attention: Indexing of parameters can be changed.

Possible use of method is to replace input by variable. For it the following steps should be done:

  • Parameter node should be replaced by ReadValue

  • call remove_parameter(param) to remove input from the list

  • check if any parameter indexes are saved/used somewhere, update it for all inputs because indexes can be changed

  • call graph validation to check all changes

Parameters:

param – Parameter node to delete

void add_variables(const ov::op::util::VariableVector &variables)

Add new variables to the list. Method doesn’t validate graph, it should be done manually after all changes.

Parameters:

variables – new variables to add

void remove_variable(const ov::op::util::Variable::Ptr &variable)

Delete variable from the list of variables. Method doesn’t delete nodes that used this variable from the graph.

Parameters:

variable – Variable to delete

inline const ov::op::util::VariableVector &get_variables() const

Return a list of model’s variables.

ov::op::util::Variable::Ptr get_variable_by_id(const std::string &variable_id) const

Return a variable by specified variable_id.

inline RTMap &get_rt_info()

Returns a runtime info.

Returns:

reference to ov::AnyMap with runtime info

inline const RTMap &get_rt_info() const

Returns a constant runtime info.

Returns:

reference to const ov::AnyMap with runtime info

template<class T, class ...Args, typename std::enable_if<!std::is_same<T, ov::Any>::value, bool>::type = true>
inline const T &get_rt_info(Args... args) const

Returns a runtime attribute for the path, throws an ov::Exception if path doesn’t exist.

Template Parameters:
  • T – the type of returned value

  • Args – types of variadic arguments

Parameters:

args – path to the runtime attribute

Returns:

constant reference to value from runtime info

template<class T, class ...Args, typename std::enable_if<std::is_same<T, ov::Any>::value, bool>::type = true>
inline const T &get_rt_info(Args... args) const

Returns a runtime attribute for the path, throws an ov::Exception if path doesn’t exist.

Template Parameters:
  • T – the type of returned value

  • Args – types of variadic arguments

Parameters:

args – path to the runtime attribute

Returns:

constant reference to value from runtime info

template<class T, typename std::enable_if<!std::is_same<T, ov::Any>::value, bool>::type = true>
inline const T &get_rt_info(const std::vector<std::string> &args) const

Returns a runtime attribute for the path, throws an ov::Exception if path doesn’t exist.

Template Parameters:

T – the type of returned value

Parameters:

args – vector with path to the runtime attribute

Returns:

constant reference to value from runtime info

template<class T, typename std::enable_if<std::is_same<T, ov::Any>::value, bool>::type = true>
inline const T &get_rt_info(const std::vector<std::string> &args) const

Returns a runtime attribute for the path, throws an ov::Exception if path doesn’t exist.

Template Parameters:

T – the type of returned value

Parameters:

args – vector with path to the runtime attribute

Returns:

constant reference to value from runtime info

template<class ...Args>
inline bool has_rt_info(Args... args) const

Checks if given path exists in runtime info.

Template Parameters:

Args – types of variadic arguments

Parameters:

args – path to the runtime attribute

Returns:

true if path exists, otherwise false

bool has_rt_info(const std::vector<std::string> &args) const

Checks if given path exists in runtime info.

Parameters:

args – vector with path to the runtime attribute

Returns:

true if path exists, otherwise false

template<class T, class ...Args>
inline void set_rt_info(const T &argument, Args... args)

Add value inside the runtime info.

Template Parameters:
  • T – type of new value

  • Args – types of variadic arguments

Parameters:
  • argument – value for the runtime info

  • args – path to the runtime attribute

template<class T>
inline void set_rt_info(const T &argument, const std::vector<std::string> &args)

Add value inside the runtime info.

Template Parameters:

T – type of new value

Parameters:
  • argument – value for the runtime info

  • args – vector with path to the runtime attribute

class Node : public std::enable_shared_from_this<Node>
#include <node.hpp>

Nodes are the backbone of the graph of Value dataflow. Every node has zero or more nodes as arguments and one value, which is either a tensor or a (possibly empty) tuple of values.

Subclassed by ov::op::Op, ov::pass::pattern::op::Pattern

Public Functions

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.

virtual const ov::op::AutoBroadcastSpec &get_autob() const
Returns:

the autobroadcasr spec

virtual bool has_evaluate() const

Allows to get information about availability of evaluate method for the current operation.

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

Evaluates the op on input_values putting results in output_values.

Parameters:
  • output_values – Tensors for the outputs to compute. One for each result

  • input_values – Tensors for the inputs. One for each inputs.

Returns:

true if successful

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

Evaluates the op on input_values putting results in output_values.

Parameters:
  • output_values – Tensors for the outputs to compute. One for each result

  • input_values – Tensors for the inputs. One for each inputs.

  • evaluation_context – Storage of additional settings and attributes that can be used when evaluating the op.

Returns:

true if successful

inline virtual OutputVector decompose_op() const

Decomposes the FusedOp into a sub-graph consisting of core openvino ops.

Returns:

A vector of nodes comprising the sub-graph. The order of output tensors must match the match output tensors of the FusedOp

virtual const type_info_t &get_type_info() const = 0

Returns the NodeTypeInfo for the node’s class. During transition to type_info, returns a dummy type_info for Node if the class has not been updated yet.

void set_arguments(const NodeVector &arguments)

Sets/replaces the arguments with new arguments.

void set_arguments(const OutputVector &arguments)

Sets/replaces the arguments with new arguments.

void set_argument(size_t position, const Output<Node> &argument)

Sets/replaces the arguments with new arguments.

void set_output_size(size_t output_size)

Sets the number of outputs.

virtual std::string description() const

Get the string name for the type of the node, such as Add or Multiply. The class name, must not contain spaces as it is used for codegen.

Returns:

A const reference to the node’s type name

const std::string &get_name() const

Get the unique name of the node.

Returns:

A const reference to the node’s unique name.

void set_friendly_name(const std::string &name)

Sets a friendly name for a node. This does not overwrite the unique name of the node and is retrieved via get_friendly_name(). Used mainly for debugging. The friendly name may be set exactly once.

Parameters:

name – is the friendly name to set

const std::string &get_friendly_name() const

Gets the friendly name for a node. If no friendly name has been set via set_friendly_name then the node’s unique name is returned.

Returns:

A const reference to the node’s friendly name.

virtual std::ostream &write_description(std::ostream &os, uint32_t depth = 0) const

Writes a description of a node to a stream.

Parameters:
  • os – The stream; should be returned

  • depth – How many levels of inputs to describe

Returns:

The stream os

const std::vector<std::shared_ptr<Node>> &get_control_dependencies() const

Get control dependencies registered on the node.

const std::vector<Node*> &get_control_dependents() const

Get nodes dependent on this node.

void add_control_dependency(std::shared_ptr<Node> node)

This node cannot execute until node executes.

void remove_control_dependency(std::shared_ptr<Node> node)

Remove the dependency of this node on node.

void clear_control_dependencies()

Remove all dependencies from this node.

void clear_control_dependents()

Remove this node as a dependency from all dependent nodes.

void add_node_control_dependencies(const std::shared_ptr<const Node> &source_node)

This node absorbs the control dependencies of source_node.

void add_node_control_dependents(const std::shared_ptr<const Node> &source_node)

This node becomes a dependent of every node dependent on source_node.

void transfer_control_dependents(std::shared_ptr<Node> replacement)

This node’s control dependencies are replaced by replacement.

size_t get_output_size() const

Returns the number of outputs from the node.

const element::Type &get_output_element_type(size_t i) const

Returns the element type for output i.

const element::Type &get_element_type() const

Checks that there is exactly one output and returns its element type.

const Shape &get_output_shape(size_t i) const

Returns the shape for output i.

const PartialShape &get_output_partial_shape(size_t i) const

Returns the partial shape for output i.

Output<const Node> get_default_output() const

Return the output to use when converting to an Output<Node> with no index specified. Throws when not supported.

virtual size_t get_default_output_index() const

Returns the output of the default output, or throws if there is none.

size_t no_default_index() const

Throws no default.

const Shape &get_shape() const

Checks that there is exactly one output and returns its shape.

descriptor::Tensor &get_output_tensor(size_t i) const

Returns the tensor for output or input i.

size_t get_input_size() const

Returns the number of inputs for the op.

const element::Type &get_input_element_type(size_t i) const

Returns the element type of input i.

const Shape &get_input_shape(size_t i) const

Returns the shape of input i.

const PartialShape &get_input_partial_shape(size_t i) const

Returns the partial shape of input i.

bool has_same_type(std::shared_ptr<const Node> node) const

True if this and node have one output with same element type and shape.

NodeVector get_users(bool check_is_used = false) const

Get all the nodes that uses the current node.

inline bool operator<(const Node &other) const

Use instance ids for comparison instead of memory addresses to improve determinism.

std::vector<Input<Node>> inputs()
Returns:

A vector containing a handle for each of this node’s inputs, in order.

std::vector<Input<const Node>> inputs() const
Returns:

A vector containing a handle for each of this node’s inputs, in order.

std::vector<Output<Node>> input_values() const
Returns:

A vector containing the values for each input

std::vector<Output<Node>> outputs()
Returns:

A vector containing a handle for each of this node’s outputs, in order.

std::vector<Output<const Node>> outputs() const
Returns:

A vector containing a handle for each of this node’s outputs, in order.

Input<Node> input(size_t input_index)
Throws:

std::out_of_range – if the node does not have at least input_index+1 inputs.

Returns:

A handle to the input_indexth input of this node.

Input<const Node> input(size_t input_index) const
Throws:

std::out_of_range – if the node does not have at least input_index+1 inputs.

Returns:

A handle to the input_indexth input of this node.

Output<Node> output(size_t output_index)
Throws:

std::out_of_range – if the node does not have at least output_index+1 outputs.

Returns:

A handle to the output_indexth output of this node.

Output<const Node> output(size_t output_index) const
Throws:

std::out_of_range – if the node does not have at least output_index+1 outputs.

Returns:

A handle to the output_indexth output of this node.

template<>
class Input<Node>
#include <node_input.hpp>

A handle for one of a node’s inputs.

Public Functions

Input(Node *node, size_t index)

Constructs a Input.

Parameters:
  • node – Pointer to the node for the input handle.

  • index – The index of the input.

Node *get_node() const
Returns:

A pointer to the node referenced by this input handle.

size_t get_index() const
Returns:

The index of the input referred to by this input handle.

OV_NO_DANGLING const element::Type & get_element_type () const
Returns:

The element type of the input referred to by this input handle.

OV_NO_DANGLING const Shape & get_shape () const
Returns:

The shape of the input referred to by this input handle.

OV_NO_DANGLING const PartialShape & get_partial_shape () const
Returns:

The partial shape of the input referred to by this input handle.

Output<Node> get_source_output() const
Returns:

A handle to the output that is connected to this input.

OV_NO_DANGLING descriptor::Tensor & get_tensor () const
Returns:

A reference to the tensor descriptor for this input.

std::shared_ptr<descriptor::Tensor> get_tensor_ptr() const
Returns:

A shared pointer to the tensor descriptor for this input.

bool get_is_relevant_to_shapes() const
Returns:

true if this input is relevant to its node’s output shapes; else false.

bool get_is_relevant_to_values() const
Returns:

true if this input is relevant to its node’s output values; else false.

void replace_source_output(const Output<Node> &new_source_output) const

Replaces the source output of this input.

Parameters:

new_source_output – A handle for the output that will replace this input’s source.

RTMap &get_rt_info()
Returns:

The reference to runtime info map

OV_NO_DANGLING const RTMap & get_rt_info () const
Returns:

The constant reference to runtime info map

template<>
class Input<const Node>
#include <node_input.hpp>

A handle for one of a node’s inputs.

Public Functions

Input(const Node *node, size_t index)

Constructs a Input.

Parameters:
  • node – Pointer to the node for the input handle.

  • index – The index of the input.

const Node *get_node() const
Returns:

A pointer to the node referenced by this input handle.

size_t get_index() const
Returns:

The index of the input referred to by this input handle.

OV_NO_DANGLING const element::Type & get_element_type () const
Returns:

The element type of the input referred to by this input handle.

OV_NO_DANGLING const Shape & get_shape () const
Returns:

The shape of the input referred to by this input handle.

OV_NO_DANGLING const PartialShape & get_partial_shape () const
Returns:

The partial shape of the input referred to by this input handle.

Output<Node> get_source_output() const
Returns:

A handle to the output that is connected to this input.

OV_NO_DANGLING descriptor::Tensor & get_tensor () const
Returns:

A reference to the tensor descriptor for this input.

std::shared_ptr<descriptor::Tensor> get_tensor_ptr() const
Returns:

A shared pointer to the tensor descriptor for this input.

bool get_is_relevant_to_shapes() const
Returns:

true if this input is relevant to its node’s output shapes; else false.

bool get_is_relevant_to_values() const
Returns:

true if this input is relevant to its node’s output values; else false.

OV_NO_DANGLING const RTMap & get_rt_info () const
Returns:

The constant reference to runtime info map

template<>
class Output<Node>
#include <node_output.hpp>

A handle for one of a node’s outputs.

Public Functions

Output(Node *node, size_t index)

Constructs a Output.

Parameters:
  • node – A pointer to the node for the output handle.

  • index – The index of the output.

Output(const std::shared_ptr<Node> &node, size_t index)

Constructs a Output.

Parameters:
  • node – A shared_ptr to the node for the output handle.

  • index – The index of the output.

template<typename T>
inline Output(const std::shared_ptr<T> &node)

Constructs a Output, referencing the default output of the node. If the node doesn’t have a default output, an exception will be thrown.

Parameters:

node – A shared_ptr to the node for the output handle.

Output() = default

A null output.

Node *get_node() const
Returns:

A pointer to the node referred to by this output handle.

std::shared_ptr<Node> get_node_shared_ptr() const
Returns:

A shared_ptr to the node referred to by this output handle.

size_t get_index() const
Returns:

The index of the output referred to by this output handle.

OV_NO_DANGLING descriptor::Tensor & get_tensor () const
Returns:

A reference to the tensor descriptor for this output.

std::shared_ptr<descriptor::Tensor> get_tensor_ptr() const
Returns:

A shared point to the tensor ptr for this output.

void set_tensor_ptr(std::shared_ptr<descriptor::Tensor> tensor_ptr)
Returns:

Set new tensor desc shared pointer to this output

OV_NO_DANGLING const element::Type & get_element_type () const
Returns:

The element type of the output referred to by this output handle.

OV_NO_DANGLING const Shape & get_shape () const
Returns:

The shape of the output referred to by this output handle.

OV_NO_DANGLING const PartialShape & get_partial_shape () const
Returns:

The partial shape of the output referred to by this output handle.

RTMap &get_rt_info()
Returns:

The reference to runtime info map

OV_NO_DANGLING const RTMap & get_rt_info () const
Returns:

The constant reference to runtime info map

OV_NO_DANGLING const std::unordered_set< std::string > & get_names () const
Returns:

The tensor names associated with this output

std::string get_any_name() const
Returns:

Any tensor names associated with this output

void set_names(const std::unordered_set<std::string> &names)
Returns:

Set tensor names associated with this output

void add_names(const std::unordered_set<std::string> &names)
Returns:

Add tensor names associated with this output

std::set<Input<Node>> get_target_inputs() const
Returns:

A set containing handles for all inputs targeted by the output referenced by this output handle.

void remove_target_input(const Input<Node> &target_input) const

Removes a target input from the output referenced by this output handle.

Parameters:

target_input – The target input to remove.

void replace(const Output<Node> &replacement)

Replace all users of this value with replacement.

template<>
class Output<const Node>
#include <node_output.hpp>

A handle for one of a node’s outputs.

Public Functions

Output(const Node *node, size_t index)

Constructs a Output.

Parameters:
  • node – A pointer to the node for the output handle.

  • index – The index of the output.

Output(const std::shared_ptr<const Node> &node, size_t index)

Constructs a Output.

Parameters:
  • node – A shared_ptr to the node for the output handle.

  • index – The index of the output.

template<typename T>
inline Output(const std::shared_ptr<const T> &node)

Constructs a Output, referencing the zeroth output of the node.

Parameters:

node – A shared_ptr to the node for the output handle.

Output() = default

A null output.

const Node *get_node() const
Returns:

A pointer to the node referred to by this output handle.

std::shared_ptr<const Node> get_node_shared_ptr() const
Returns:

A shared_ptr to the node referred to by this output handle.

size_t get_index() const
Returns:

The index of the output referred to by this output handle.

OV_NO_DANGLING descriptor::Tensor & get_tensor () const
Returns:

A reference to the tensor descriptor for this output.

std::shared_ptr<descriptor::Tensor> get_tensor_ptr() const
Returns:

A shared point to the tensor ptr for this output.

OV_NO_DANGLING const element::Type & get_element_type () const
Returns:

The element type of the output referred to by this output handle.

OV_NO_DANGLING const Shape & get_shape () const
Returns:

The shape of the output referred to by this output handle.

OV_NO_DANGLING const PartialShape & get_partial_shape () const
Returns:

The partial shape of the output referred to by this output handle.

OV_NO_DANGLING const RTMap & get_rt_info () const
Returns:

The constant reference to runtime info map

OV_NO_DANGLING const std::unordered_set< std::string > & get_names () const
Returns:

The tensor names associated with this output

std::string get_any_name() const
Returns:

Any tensor name associated with this output

std::set<Input<Node>> get_target_inputs() const
Returns:

A set containing handles for all inputs targeted by the output referenced by this output handle.

class PartialShape
#include <partial_shape.hpp>

Class representing a shape that may be partially or totally dynamic.

A PartialShape may have:

  • Dynamic rank. (Informal notation: ?)

  • Static rank, but dynamic dimensions on some or all axes. (Informal notation examples: {1,2,?,4}, {?,?,?})

  • Static rank, and static dimensions on all axes. (Informal notation examples: {1,2,3,4}, {6}, {})

Public Functions

PartialShape(std::initializer_list<Dimension> init)

Constructs a shape with static rank from an initializer list of Dimension.

Examples:

PartialShape s{2,3,4};                     // rank=3, all dimensions static
PartialShape s{};                          // rank=0
PartialShape s{2,Dimension::dynamic(),3};  // rank=3, dimension 1 dynamic
Parameters:

init – The Dimension values for the constructed shape.

PartialShape(std::vector<Dimension> dimensions)

Constructs a PartialShape with static rank from a vector of Dimension.

Parameters:

dimensions – The Dimension values for the constructed shape.

PartialShape(const std::vector<Dimension::value_type> &dimensions)

Constructs a PartialShape with static rank from a vector of dimensions values.

Parameters:

dimensions – The Dimension values for the constructed shape.

PartialShape()

Constructs a static PartialShape with zero rank (the shape of a scalar).

PartialShape(const Shape &shape)

Constructs a static PartialShape from a PartialShape.

Parameters:

shape – The PartialShape to convert into PartialShape.

PartialShape(const std::string &shape)

Constructs a static PartialShape from a string.

Parameters:

shape – The string to parse into PartialShape.

bool is_static() const

Check if this shape is static.

A shape is considered static if it has static rank, and all dimensions of the shape are static.

Returns:

true if this shape is static, else false.

inline bool is_dynamic() const

Check if this shape is dynamic.

A shape is considered static if it has static rank, and all dimensions of the shape are static.

Returns:

false if this shape is static, else true.

inline Rank rank() const

Get the rank of the shape.

Returns:

The rank of the shape. This will be Rank::dynamic() if the rank of the shape is dynamic.

bool compatible(const PartialShape &s) const

Check whether this shape is compatible with the argument, i.e., whether it is possible to merge them.

Two shapes are compatible if

  • one or both of them has dynamic rank, or

  • both shapes have dynamic and equal rank, and their dimensions are elementwise compatible (see Dimension::compatible()).

Parameters:

s – The shape to be checked for compatibility with this shape.

Returns:

true if this shape is compatible with s, else false.

bool same_scheme(const PartialShape &s) const

Check whether this shape represents the same scheme as the argument.

Two shapes s1 and s2 represent the same scheme if

  • they both have dynamic rank, or

  • they both have static and equal rank r, and for every i from 0 to r-1, s1[i] represents the same scheme as s2[i] (see Dimension::same_scheme()).

Parameters:

s – The shape whose scheme is being compared with this shape.

Returns:

true if this shape represents the same scheme as s, else false.

bool relaxes(const PartialShape &s) const

Check whether this shape is a relaxation of the argument.

Intuitively, a PartialShape s1 is said to relax s2 (or is a relaxation of s2) if it is “more permissive” than s2. In other words, s1 is a relaxation of s2 if anything you can form by plugging things into the dynamic dimensions of s2 is also something you can form by plugging things into the dynamic dimensions of s1, but not necessarily the other way around.

s1.relaxes(s2) is equivalent to s2.refines(s1).

Formally, PartialShape s1 is said to relax PartialShape s2 if:

  • For every i from 0 to r-1, either s1[i] contains s2[i].

Parameters:

s – The shape which is being compared against this shape.

Returns:

true if this shape relaxes s, else false.