The Intel nGraph C++ API. More...

Namespaces
	builder
	Convenience functions that create addional graph nodes to implement commonly-used recipes, for example auto-broadcast.

	descriptor
	Descriptors are compile-time representations of objects that will appear at run-time.

	onnx_import
	ONNX importer features namespace. Functions in this namespace make it possible to use ONNX models.

	op
	Ops used in graph-building.

	runtime
	The objects used for executing the graph.

Data Structures
class	ValueAccessor
	Provides access to an attribute of type AT as a value accessor type VAT. More...

class	ValueAccessor< void >
	ValueAccessor<void> provides an accessor for values that do not have get/set methonds via AttributeVistor.on_adapter. More...

class	ValueAccessor< void * >

class	DirectValueAccessor

class	IndirectScalarValueAccessor

class	IndirectVectorValueAccessor

class	AttributeAdapter
	An AttributeAdapter "captures" an attribute as an AT& and makes it available as a ValueAccessor<VAT>. More...

class	EnumAttributeAdapterBase
	Access an enum via a string. More...

class	VisitorAdapter
	Adapters will see visitor. More...

class	AttributeAdapter< float >

class	AttributeAdapter< double >
	Access a double as a double. More...

class	AttributeAdapter< std::string >
	Access a string as a string. More...

class	AttributeAdapter< bool >
	Access a bool as a bool. More...

class	AttributeAdapter< int8_t >
	Access an int8_t and an int64_t. More...

class	AttributeAdapter< int16_t >
	Access an int16_t as an int64_t. More...

class	AttributeAdapter< int32_t >
	Access an int32_t as an int64_t. More...

class	AttributeAdapter< int64_t >
	Access an int64_t as an int64_t. More...

class	AttributeAdapter< uint8_t >
	Access a uint8_t as an int64_t. More...

class	AttributeAdapter< uint16_t >
	Access a uint16_t as an int64_t. More...

class	AttributeAdapter< uint32_t >
	Access a uint32_t as an int64_t. More...

class	AttributeAdapter< uint64_t >
	Access a uint64_t as an int64_t. More...

class	AttributeAdapter< std::vector< int8_t > >
	Access a vector<int8_t> More...

class	AttributeAdapter< std::vector< int16_t > >
	Access a vector<int16_t> More...

class	AttributeAdapter< std::vector< int32_t > >
	Access a vector<int32_t> More...

class	AttributeAdapter< std::vector< int64_t > >
	Access a vector<int64_t> More...

class	AttributeAdapter< std::vector< uint8_t > >
	Access a vector<uint8_t> More...

class	AttributeAdapter< std::vector< uint16_t > >
	Access a vector<uint16_t> More...

class	AttributeAdapter< std::vector< uint32_t > >
	Access a vector<uint32_t> More...

class	AttributeAdapter< std::vector< uint64_t > >
	Access a vector<uint64_t> More...

class	AttributeAdapter< std::vector< float > >
	Access a vector<float> More...

class	AttributeAdapter< std::vector< double > >
	Access a vector<double> More...

class	AttributeAdapter< std::vector< std::string > >
	Access a vector<string> More...

class	AttributeVisitor
	Visits the attributes of a node, primarily for serialization-like tasks. More...

class	AxisSet
	A set of axes. More...

class	AttributeAdapter< AxisSet >

class	AxisVector
	A vector of axes. More...

class	AttributeAdapter< AxisVector >

struct	CheckLocInfo

class	CheckFailure
	Base class for check failure exceptions. More...

class	Coordinate
	Coordinates for a tensor element. More...

class	AttributeAdapter< Coordinate >

class	CoordinateDiff
	A difference (signed) of tensor element coordinates. More...

class	AttributeAdapter< CoordinateDiff >

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

class	AttributeAdapter< reduction::Type >

class	EnumNames

class	Evaluator
	Execute handlers on a subgraph to compute values. More...

class	ngraph_error
	Base error for ngraph runtime errors. More...

class	unsupported_op

class	FactoryRegistry
	Registry of factories that can construct objects derived from BASE_TYPE. More...

class	FactoryAttributeAdapter

class	Function
	A user-defined function. More...

class	AttributeAdapter< std::shared_ptr< Function > >

class	Interval
	Interval arithmetic. More...

class	ConstString

class	LogHelper

class	Logger

struct	NullLogger

class	Input

class	Output

class	Node

struct	RawNodeOutput

class	AttributeAdapter< std::shared_ptr< Node > >
	Visits a reference to a node that has been registered with the visitor. More...

class	AttributeAdapter< NodeVector >

class	NodeValidationFailure

class	Input< Node >
	A handle for one of a node's inputs. More...

class	Input< const Node >
	A handle for one of a node's inputs. More...

class	Output< Node >
	A handle for one of a node's outputs. More...

class	Output< const Node >

class	AttributeAdapter< op::v1::BinaryConvolution::BinaryConvolutionMode >

class	AttributeAdapter< op::v0::DepthToSpace::DepthToSpaceMode >

class	AttributeAdapter< op::v0::Interpolate::InterpolateMode >

class	AttributeAdapter< op::v4::Interpolate::InterpolateMode >

class	AttributeAdapter< op::v4::Interpolate::CoordinateTransformMode >

class	AttributeAdapter< op::v4::Interpolate::NearestMode >

class	AttributeAdapter< op::v4::Interpolate::ShapeCalcMode >

class	AttributeAdapter< op::v5::Loop::SpecialBodyPorts >

class	AttributeAdapter< op::LSTMWeightsFormat >

class	AttributeAdapter< op::MVNEpsMode >

class	AttributeAdapter< op::v1::NonMaxSuppression::BoxEncodingType >

class	AttributeAdapter< op::v3::NonMaxSuppression::BoxEncodingType >

class	AttributeAdapter< op::v5::NonMaxSuppression::BoxEncodingType >

class	AttributeAdapter< ParameterVector >

class	AttributeAdapter< ResultVector >

class	AttributeAdapter< op::v1::Reverse::Mode >

class	AttributeAdapter< op::v3::ROIAlign::PoolingMode >

class	AttributeAdapter< op::v5::Round::RoundMode >

class	AttributeAdapter< op::v0::SpaceToDepth::SpaceToDepthMode >

class	AttributeAdapter< op::PadMode >

class	AttributeAdapter< op::PadType >

class	AttributeAdapter< op::RoundingType >

class	AttributeAdapter< op::AutoBroadcastType >

class	AttributeAdapter< op::BroadcastType >

class	AttributeAdapter< op::EpsMode >

class	AttributeAdapter< op::TopKSortType >

class	AttributeAdapter< op::TopKMode >

class	AttributeAdapter< op::AutoBroadcastSpec >

class	AttributeAdapter< op::BroadcastModeSpec >

class	AttributeAdapter< op::RecurrentSequenceDirection >

class	AttributeAdapter< std::vector< std::shared_ptr< ngraph::op::util::SubGraphOp::InputDescription > > >

class	AttributeAdapter< std::vector< std::shared_ptr< ngraph::op::util::SubGraphOp::OutputDescription > > >

struct	VariableInfo

class	Variable

class	AttributeAdapter< std::shared_ptr< Variable > >

class	OpSet
	Run-time opset information. More...

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

class	AttributeAdapter< PartialShape >

class	AttributeAdapter< std::shared_ptr< runtime::AlignedBuffer > >

class	Shape
	Shape for a tensor. More...

class	AttributeAdapter< Shape >

struct	SlicePlan

class	Strides
	Strides for a tensor. More...

class	AttributeAdapter< Strides >

class	bfloat16

class	AttributeAdapter< element::Type_t >

class	AttributeAdapter< element::Type >

struct	element_type_traits

struct	element_type_traits< element::Type_t::boolean >

struct	element_type_traits< element::Type_t::bf16 >

struct	element_type_traits< element::Type_t::f16 >

struct	element_type_traits< element::Type_t::f32 >

struct	element_type_traits< element::Type_t::f64 >

struct	element_type_traits< element::Type_t::i8 >

struct	element_type_traits< element::Type_t::i16 >

struct	element_type_traits< element::Type_t::i32 >

struct	element_type_traits< element::Type_t::i64 >

struct	element_type_traits< element::Type_t::u1 >

struct	element_type_traits< element::Type_t::u8 >

struct	element_type_traits< element::Type_t::u16 >

struct	element_type_traits< element::Type_t::u32 >

struct	element_type_traits< element::Type_t::u64 >

class	float16

struct	DiscreteTypeInfo

class	stopwatch

class	EnumMask

class	Variant

class	VariantImpl

class	VariantWrapper

class	VariantWrapper< std::string >

class	VariantWrapper< int64_t >

Typedefs
using	HostTensorPtr = std::shared_ptr< runtime::HostTensor >

using	HostTensor = runtime::HostTensor

using	HostTensorVector = std::vector< HostTensorPtr >

using	ResultVector = std::vector< std::shared_ptr< op::v0::Result > >

using	NodeMap = std::unordered_map< ngraph::Node *, std::shared_ptr< ngraph::Node > >
	Alias useful for cloning.

using	NodeTypeInfo = Node::type_info_t

using	RawNodeOutputMap = std::map< RawNodeOutput, Output< Node > >

using	ParameterVector = std::vector< std::shared_ptr< op::Parameter > >

using	SinkVector = std::vector< std::shared_ptr< op::Sink > >

using	NodeVector = std::vector< std::shared_ptr< Node > >

using	OutputVector = std::vector< Output< Node > >

using	matcher_pass_callback = std::function< bool(ngraph::pattern::Matcher &m)>

using	graph_rewrite_callback = std::function< bool(ngraph::pattern::Matcher &m)>

using	recurrent_graph_rewrite_callback = std::function< bool(ngraph::pattern::RecurrentMatcher &m)>

using	handler_callback = std::function< bool(const std::shared_ptr< Node > &node)>

using	Rank = Dimension
	Alias for Dimension, used when the value represents the number of axes in a shape, rather than the size of one dimension in a shape. More...

using	VariantTypeInfo = DiscreteTypeInfo

Enumerations
enum class	LOG_TYPE { _LOG_TYPE_ERROR , _LOG_TYPE_WARNING , _LOG_TYPE_INFO , _LOG_TYPE_DEBUG }

Functions
template<typename A , typename B >
A	copy_from (B &b)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const AxisSet &axis_set)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const AxisVector &axis_vector)

static std::ostream &	write_all_to_stream (std::ostream &str)

template<typename T , typename... TS>
static std::ostream &	write_all_to_stream (std::ostream &str, const T &arg, TS &&... args)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const Coordinate &coordinate)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const CoordinateDiff &coordinate_diff)

NGRAPH_API std::ostream &	operator<< (std::ostream &str, const Dimension &dimension)
	Insert a human-readable representation of a dimension into an output stream. More...

template<typename Type , typename Value >
std::enable_if< std::is_convertible< Value, std::string >::value, Type >::type	as_enum (const Value &value)
	Returns the enum value matching the string.

template<typename Value >
const std::string &	as_string (Value value)
	Returns the string matching the enum value.

NGRAPH_API std::string	getenv_string (const char *env_var)
	Get the names environment variable as a string. More...

NGRAPH_API int32_t	getenv_int (const char *env_var, int32_t default_value=-1)
	Get the names environment variable as an integer. If the value is not a valid integer then an exception is thrown. More...

NGRAPH_API bool	getenv_bool (const char *env_var, bool default_value=false)
	Get the names environment variable as a boolean. If the value is not a valid boolean then an exception is thrown. Valid booleans are one of 1, 0, on, off, true, false All values are case insensitive. If the environment variable is not set the default_value is returned. More...

NGRAPH_API std::mutex &	get_registry_mutex ()

NGRAPH_API void	traverse_nodes (const std::shared_ptr< const Function > p, std::function< void(std::shared_ptr< Node >)> f)

NGRAPH_API void	traverse_nodes (const Function *p, std::function< void(std::shared_ptr< Node >)> f)

NGRAPH_API void	traverse_nodes (const NodeVector &subgraph_results, std::function< void(std::shared_ptr< Node >)> f, const NodeVector &subgraph_params={})
	Visit each node in a sub-graph of the entire graph. More...

NGRAPH_API void	replace_node (std::shared_ptr< Node > target, std::shared_ptr< Node > replacement, const std::vector< int64_t > &output_order)
	Replace the node `target` with the node `replacement`, i.e., redirect all users and control dependencies of `target` to `replacement`. More...

NGRAPH_API void	replace_node (const std::shared_ptr< Node > &target, const OutputVector &replacement_values)

NGRAPH_API void	replace_node (std::shared_ptr< Node > target, std::shared_ptr< Node > replacement)

NGRAPH_API void	replace_nodes (const std::shared_ptr< Function > &f, const std::unordered_map< std::shared_ptr< op::v0::Parameter >, std::shared_ptr< op::v0::Parameter >> &parameter_replacement_map, const std::unordered_map< std::shared_ptr< Node >, std::shared_ptr< Node >> &body_replacement_map)
	Replace multiple nodes in a function. More...

NGRAPH_API NodeVector	find_common_args (std::shared_ptr< Node > target, std::shared_ptr< Node > replacement)

template<typename T >
std::vector< std::shared_ptr< Node > >	topological_sort (T root_nodes)
	Topological sort of nodes needed to compute root_nodes.

template<typename T >
std::vector< std::shared_ptr< Node > >	subgraph_topological_sort (T nodes)
	Topological sort of just nodes.

template<typename T >
void	validate_nodes_and_infer_types (const T &nodes)

NGRAPH_API bool	is_post_dominated (Node X, Node Y)

NGRAPH_API bool	is_equal_to_const_value (std::string const_value, const Output< Node > &reduce_constant)

NGRAPH_API std::vector< std::shared_ptr< ngraph::Node > >	clone_nodes (const std::vector< std::shared_ptr< ngraph::Node >> &nodes, NodeMap &node_map)

NGRAPH_API std::list< std::shared_ptr< ngraph::Node > >	clone_nodes (const std::vector< std::shared_ptr< ngraph::Node >> &nodes, RawNodeOutputMap &node_map)

NGRAPH_API std::shared_ptr< ngraph::Function >	clone_function (const ngraph::Function &func, NodeMap &node_map)

NGRAPH_API std::shared_ptr< ngraph::Function >	clone_function (const ngraph::Function &func)

NGRAPH_API std::pair< std::shared_ptr< op::Result >, std::shared_ptr< op::v0::Parameter > >	insert_result_parameter_split (const std::shared_ptr< Node > &src_node, const std::shared_ptr< Node > &dst_node)

NGRAPH_API void	insert_new_node_between (const std::shared_ptr< Node > &src_node, const std::shared_ptr< Node > &dst_node, const std::shared_ptr< Node > &new_node)

NGRAPH_API std::shared_ptr< Node >	make_zero (const element::Type &element_type, const Shape &shape)

NGRAPH_API std::shared_ptr< Node >	make_constant_from_string (std::string val, const element::Type &element_type, const Shape &shape)

NGRAPH_API bool	is_zero (const Output< Node > &reduce_constant)

NGRAPH_API NodeVector	get_subgraph_outputs (const NodeVector &nodes, const NodeVector &exclusions, bool ignore_unused=false, bool ignore_output_duplicates=true)

NGRAPH_API NodeVector	extract_subgraph (const NodeVector &results, const NodeVector &args)

NGRAPH_API bool	is_one (const Output< Node > &reduce_constant)

NGRAPH_API bool	compare_constants (const std::shared_ptr< Node > &n1, const std::shared_ptr< Node > &n2)

NGRAPH_API bool	is_used (Node *node)

NGRAPH_API size_t	get_user_count (Node *node)

NGRAPH_API bool	possibly_overwritten (Node *node)

NGRAPH_API bool	is_strided (const Strides &strides)

NGRAPH_API bool	is_valid_rank (const std::shared_ptr< Node > &node, std::vector< size_t > valid_ranks)

NGRAPH_API void	plot_graph (std::shared_ptr< Function > f, const std::string &filename, std::function< void(const Node &node, std::vector< std::string > &attributes)>=nullptr)

NGRAPH_API std::vector< Input< Node > >	get_inputs_from (Node &src, Node &dst)

NGRAPH_API std::vector< Output< Node > >	get_outputs_to (Node &src, Node &dst)

NGRAPH_API bool	check_for_cycles (const ngraph::Function *func, ngraph::NodeVector &cycle_nodes, bool &is_bkwd_cycle)

NGRAPH_API bool	replace_output_update_name (Output< Node > node, const Output< Node > &node_input)

NGRAPH_API bool	replace_node_update_name (std::shared_ptr< Node > target, std::shared_ptr< Node > replacement)

NGRAPH_API std::ostream &	operator<< (std::ostream &str, const Interval &interval)

constexpr const char *	find_last (ConstString s, size_t offset, char ch)

constexpr const char *	find_last (ConstString s, char ch)

constexpr const char *	get_file_name (ConstString s)

constexpr const char *	trim_file_name (ConstString root, ConstString s)

NGRAPH_API void	default_logger_handler_func (const std::string &s)

template<typename T >
NullLogger &&	operator<< (NullLogger &&logger, T &&)

template<typename T >
NullLogger &&	operator<< (NullLogger &&logger, const T &)

NullLogger &&	operator<< (NullLogger &&logger, std::basic_ostream< char, std::char_traits< char >> &(&)(std::basic_ostream< char, std::char_traits< char >> &))

NGRAPH_API void	get_version (size_t &major, size_t &minor, size_t &patch, std::string &extra)
	Function to query parsed version information of the version of ngraph which contains this function. Version information strictly follows Semantic Versioning http://semver.org. More...

NGRAPH_API std::string	node_validation_failure_loc_string (const Node *node)

const std::shared_ptr< Node > &	check_single_output_arg (const std::shared_ptr< Node > &node, size_t i)

NGRAPH_API const NodeVector &	check_single_output_args (const NodeVector &args)

NGRAPH_API OutputVector	as_output_vector (const NodeVector &args)

NGRAPH_API NodeVector	as_node_vector (const OutputVector &values)

NGRAPH_API ResultVector	as_result_vector (const OutputVector &values)
	Returns a ResultVector referencing values.

NGRAPH_API std::ostream &	operator<< (std::ostream &, const Node &)

NGRAPH_API std::ostream &	operator<< (std::ostream &, const Node *)

template<typename T >
void	check_new_args_count (const Node *node, T new_args)

NGRAPH_API std::ostream &	operator<< (std::ostream &out, const Input< Node > &input)

NGRAPH_API std::ostream &	operator<< (std::ostream &out, const Input< const Node > &input)

NGRAPH_API std::ostream &	operator<< (std::ostream &out, const Output< Node > &output)

NGRAPH_API std::ostream &	operator<< (std::ostream &out, const Output< const Node > &output)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v1::BinaryConvolution::BinaryConvolutionMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v0::DepthToSpace::DepthToSpaceMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v0::Interpolate::InterpolateMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v4::Interpolate::InterpolateMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v4::Interpolate::CoordinateTransformMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v4::Interpolate::NearestMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v4::Interpolate::ShapeCalcMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::LSTMWeightsFormat &type)

NGRAPH_API std::shared_ptr< Node >	operator- (const Output< Node > &arg0)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v1::NonMaxSuppression::BoxEncodingType &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v3::NonMaxSuppression::BoxEncodingType &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v5::NonMaxSuppression::BoxEncodingType &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v1::Reverse::Mode &type)

std::ostream &	operator<< (std::ostream &s, const op::v3::ROIAlign::PoolingMode &mode)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v5::Round::RoundMode &type)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const op::v0::SpaceToDepth::SpaceToDepthMode &type)

const NGRAPH_API OpSet &	get_opset1 ()

const NGRAPH_API OpSet &	get_opset2 ()

const NGRAPH_API OpSet &	get_opset3 ()

const NGRAPH_API OpSet &	get_opset4 ()

const NGRAPH_API OpSet &	get_opset5 ()

const NGRAPH_API OpSet &	get_opset6 ()

PartialShape	operator+ (const PartialShape &s1, const PartialShape &s2)
	Elementwise addition of two PartialShape objects. More...

NGRAPH_API std::ostream &	operator<< (std::ostream &str, const PartialShape &shape)
	Inserts a human-readable representation of a PartialShape into an output stream. More...

NGRAPH_API void	set_provenance_enabled (bool enabled)

NGRAPH_API bool	get_provenance_enabled ()

NGRAPH_API void	copy_runtime_info (std::shared_ptr< ngraph::Node > from, std::shared_ptr< ngraph::Node > to)

NGRAPH_API void	copy_runtime_info (std::shared_ptr< ngraph::Node > from, ngraph::NodeVector to)

NGRAPH_API void	copy_runtime_info (const ngraph::NodeVector &from, std::shared_ptr< ngraph::Node > to)

NGRAPH_API void	copy_runtime_info (const ngraph::NodeVector &from, ngraph::NodeVector to)

template<typename SHAPE_TYPE >
size_t	shape_size (const SHAPE_TYPE &shape)
	Number of elements in spanned by a shape.

template<typename SHAPE_TYPE >
std::vector< size_t >	row_major_strides (const SHAPE_TYPE &shape)
	Row-major strides for a shape.

template<typename SHAPE_TYPE >
size_t	row_major_stride (const SHAPE_TYPE &shape, size_t axis)

template<typename SHAPE_TYPE >
bool	is_scalar (const SHAPE_TYPE &shape)

template<typename SHAPE_TYPE >
bool	is_vector (const SHAPE_TYPE &shape)

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const Shape &shape)

template<typename AXIS_VALUES >
AXIS_VALUES	project (const AXIS_VALUES &axis_values, const AxisSet &axes)

template<>
NGRAPH_API PartialShape	project (const PartialShape &shape, const AxisSet &axes)

template<typename AXIS_VALUES >
AXIS_VALUES	reduce (const AXIS_VALUES &axis_values, const AxisSet &deleted_axes, bool keep_dims)

template<>
NGRAPH_API PartialShape	reduce (const PartialShape &shape, const AxisSet &deleted_axes, bool keep_dims)

template<typename AXIS_VALUES , typename AXIS_VALUE >
AXIS_VALUES	inject_pairs (const AXIS_VALUES &axis_values, std::vector< std::pair< size_t, AXIS_VALUE >> new_axis_pos_value_pairs)

template<>
NGRAPH_API PartialShape	inject_pairs (const PartialShape &shape, std::vector< std::pair< size_t, Dimension >> new_axis_pos_value_pairs)

template<typename AXIS_VALUES , typename AXIS_VALUE >
AXIS_VALUES	inject (const AXIS_VALUES &axis_values, size_t new_axis_pos, AXIS_VALUE new_axis_val)

SlicePlan NGRAPH_API	make_slice_plan (const Shape &input_shape, const std::vector< int64_t > &begins, const std::vector< int64_t > &ends, const std::vector< int64_t > &strides, const AxisSet &lower_bounds_mask, const AxisSet &upper_bounds_mask, const AxisSet &new_axis_mask, const AxisSet &shrink_axis_mask, const AxisSet &ellipsis_mask)

NGRAPH_API std::shared_ptr< Function >	specialize_function (std::shared_ptr< Function > f, const std::vector< element::Type > &parameter_element_types, const std::vector< PartialShape > &parameter_shapes, const std::vector< void * > &parameter_values)
	Creates a "specialized" clone of a function. The partial shapes and element types of the function's parameters may be narrowed to more specific shapes and element types, and constant values may optionally be substituted for any or all of the parameters. More...

NGRAPH_API std::ostream &	operator<< (std::ostream &s, const Strides &strides)

size_t	compiler_byte_size (element::Type_t et)
	Return the number of bytes in the compile-time representation of the element type.

bool ::type	is_type (Value value)

template<typename Type , typename Value >
std::enable_if< std::is_convertible< decltype(static_cast< Type * >std::declval< Value >))), Type * >::value, Type * >::type	as_type (Value value)
	Casts a Value* to a Type* if it is of type Type, nullptr otherwise.

template<typename Type , typename Value >
std::enable_if< std::is_convertible< decltype(std::static_pointer_cast< Type >std::declval< Value >))), std::shared_ptr< Type > >::value, std::shared_ptr< Type > >::type	as_type_ptr (Value value)

template<typename T >
std::string	join (const T &v, const std::string &sep=", ")

template<typename T >
std::string	vector_to_string (const T &v)

NGRAPH_API size_t	hash_combine (const std::vector< size_t > &list)

NGRAPH_API void	dump (std::ostream &out, const void *, size_t)

NGRAPH_API std::string	to_lower (const std::string &s)

NGRAPH_API std::string	to_upper (const std::string &s)

NGRAPH_API std::string	trim (const std::string &s)

NGRAPH_API std::vector< std::string >	split (const std::string &s, char delimiter, bool trim=false)

template<typename T >
std::string	locale_string (T x)

template<typename T >
T	parse_string (const std::string &s)
	Parses a string containing a literal of the underlying type.

template<>
NGRAPH_API float	parse_string< float > (const std::string &s)

template<>
NGRAPH_API double	parse_string< double > (const std::string &s)

template<>
NGRAPH_API int8_t	parse_string< int8_t > (const std::string &s)

template<>
NGRAPH_API uint8_t	parse_string< uint8_t > (const std::string &s)

template<typename T >
std::vector< T >	parse_string (const std::vector< std::string > &ss)
	Parses a list of strings containing literals of the underlying type.

template<typename T >
T	ceil_div (const T &x, const T &y)

template<typename T >
T	subtract_or_zero (T x, T y)

NGRAPH_API void *	ngraph_malloc (size_t size)

NGRAPH_API void	ngraph_free (void *)

NGRAPH_API size_t	round_up (size_t size, size_t alignment)

bool	is_valid_permutation (ngraph::AxisVector permutation, ngraph::Rank rank=Rank::dynamic())

template<typename T >
T	apply_permutation (T input, ngraph::AxisVector order)

template NGRAPH_API AxisVector	apply_permutation< AxisVector > (AxisVector input, AxisVector order)

template NGRAPH_API Coordinate	apply_permutation< Coordinate > (Coordinate input, AxisVector order)

template NGRAPH_API Strides	apply_permutation< Strides > (Strides input, AxisVector order)

template NGRAPH_API Shape	apply_permutation< Shape > (Shape input, AxisVector order)

template<>
NGRAPH_API PartialShape	apply_permutation (PartialShape input, AxisVector order)

NGRAPH_API AxisVector	get_default_order (size_t rank)

NGRAPH_API AxisVector	get_default_order (const Shape &shape)

NGRAPH_API void	parse_version_string (std::string version, size_t &major, size_t &minor, size_t &patch, std::string &extra)
	Function to query parsed version information of the version of ngraph which contains this function. Version information strictly follows Semantic Versioning http://semver.org. More...

template<typename T >
T	double_to_int (double x, double float_to_int_converter(double))

NGRAPH_API Strides	conv_default_strides (const Node *node, const PartialShape &data_batch_shape, const PartialShape &filters_shape)

NGRAPH_API CoordinateDiff	conv_default_padding (const Node *node, const PartialShape &data_batch_shape, const PartialShape &filters_shape)

NGRAPH_API PartialShape	infer_windowed_reduction_output_shape (const Node *node, const PartialShape &data_shape, const Strides &data_dilation, const CoordinateDiff &data_padding_below, const CoordinateDiff &data_padding_above, const PartialShape &window_shape, const Strides &window_strides, const Strides &window_dilation, bool is_window_all_in_padding_allowed, bool ceil_mode=false)

NGRAPH_API PartialShape	infer_convolution_forward (const Node *node, const PartialShape &data_batch_shape, const Strides &data_dilation, const CoordinateDiff &data_padding_below, const CoordinateDiff &data_padding_above, const PartialShape &filters_shape, const Strides &filter_strides, const Strides &filter_dilation)

NGRAPH_API PartialShape	infer_batched_pooling_forward (const Node *node, const PartialShape &data_batch_shape, const CoordinateDiff &data_padding_below, const CoordinateDiff &data_padding_above, const PartialShape &window_shape, const Strides &window_strides, bool is_window_all_in_padding_allowed, bool ceil_mode=false)

NGRAPH_API std::tuple< element::Type, PartialShape, PartialShape >	infer_batch_norm_forward (const Node *node, element::Type input_element_type, element::Type gamma_element_type, element::Type beta_element_type, element::Type mean_element_type, element::Type variance_element_type, const PartialShape &input_shape, const PartialShape &gamma_shape, const PartialShape &beta_shape, const PartialShape &mean_shape, const PartialShape &variance_shape)

NGRAPH_API std::tuple< element::Type, PartialShape, PartialShape >	infer_batch_norm_forward (const Node *node, element::Type input_element_type, element::Type gamma_element_type, element::Type beta_element_type, const PartialShape &input_shape, const PartialShape &gamma_shape, const PartialShape &beta_shape)

NGRAPH_API bool	try_apply_auto_padding (const PartialShape &image_shape, const Shape &filter_shape, const Strides &filter_strides, const Strides &filter_dilations, const op::PadType pad_type, CoordinateDiff &padding_above, CoordinateDiff &padding_below)
	Apply auto padding to padding_above and padding_below inputs if all needed informations are known. More...

NGRAPH_API void	infer_auto_padding (const Shape &image_shape, const Shape &filter_shape, const Strides &filter_strides, const Strides &filter_dilations, const op::PadType pad_type, CoordinateDiff &padding_above, CoordinateDiff &padding_below)

NGRAPH_API PartialShape	infer_slice_shape (const Node *node, const PartialShape &input_shape, const std::vector< int64_t > &begin, const std::vector< int64_t > &end, const std::vector< int64_t > &strides, const AxisSet &begin_mask, const AxisSet &end_mask, const AxisSet &new_axis_mask, const AxisSet &shrink_axis_mask, const AxisSet &ellipsis_mask)

NGRAPH_API int64_t	normalize_axis (const Node *node, std::int64_t axis, const Rank &tensor_rank)
	Handle out of range axis. More...

NGRAPH_API std::vector< size_t >	normalize_axes (const std::string &node_description, const std::vector< int64_t > &axes, const Rank &tensor_rank)
	Handle out of range axes in vector. More...

NGRAPH_API int64_t	normalize_axis (const std::string &node_description, std::int64_t axis, const Rank &tensor_rank)
	Handle out of range axis. More...

NGRAPH_API int64_t	normalize_axis (const Node *node, std::int64_t axis, std::uint64_t tensor_rank, std::int64_t axis_range_min, std::int64_t axis_range_max)
	Handle out of range axis. More...

NGRAPH_API int64_t	normalize_axis (const std::string &node_description, std::int64_t axis, std::uint64_t tensor_rank, std::int64_t axis_range_min, std::int64_t axis_range_max)
	Handle out of range axis. More...

NGRAPH_API std::pair< bool, uint64_t >	maximum_value (const Output< Node > &value)
	Try to compute the maximum value of value. More...

NGRAPH_API void	evaluate_nodes (std::map< RawNodeOutput, HostTensorPtr > &value_map, std::map< RawNodeOutput, HostTensorPtr > &output_tensor_map, const OutputVector &outputs)
	Evaluates outputs, treating values in value_map as already computed. value_map is updated. More...

NGRAPH_API HostTensorPtr	evaluate_lower_bound (const Output< Node > &output)
	Evaluates lower value estimation of the output tensor. Traverses graph up to deduce estimation through it. More...

NGRAPH_API HostTensorPtr	evaluate_upper_bound (const Output< Node > &output)
	Evaluates lower value estimation of the output tensor. Traverses graph up to deduce estimation through it. More...

NGRAPH_API std::pair< HostTensorPtr, HostTensorPtr >	evaluate_both_bounds (const Output< Node > &output)
	Evaluates lower and upper value estimations of the output tensor. Traverses graph up to deduce estimation through it. More...

NGRAPH_API bool	evaluate_as_partial_shape (const Output< Node > &output, PartialShape &pshape)
	Evaluates lower and upper value estimations for the output tensor. Estimation would be represented as partial shape object using Dimension(min, max) for each element. More...

NGRAPH_API bool	default_upper_bound_evaluator (const Node *node, const HostTensorVector &output_values)
	Estimates upper bound for node output tensors using only upper bounds of the nodes inputs. More...

NGRAPH_API bool	default_lower_bound_evaluator (const Node *node, const HostTensorVector &output_values)
	Estimates lower bound for node output tensors using only lower bounds of the nodes inputs. More...

NGRAPH_API bool	interval_bound_evaluator (const Node *node, const HostTensorVector &lower_output_values, const HostTensorVector &upper_output_values)
	Estimates both bounds for node output tensors using both bounds of inputs. Works for operations with two inputs (in_1 and in_2). Brute forces all the pairs of bounds for inputs and evaluates all of them: {in_1_lower, in_2 lower}, {in_1_lower, in_2 upper}, {in_1_upper, in_2_lower}, {in_1_upper, in_2_upper}. Lower and upper values are selected from all the outputs calculated using input pairs. More...

NGRAPH_API bool	host_tensor_is_positive (const HostTensorPtr &bound)
	Checks if all the elements of the bound HostTensor are positive.

NGRAPH_API bool	has_and_set_equal_bounds (const Output< Node > &source)
	Checks if lower and upper bounds of the corresponding tensor are set (not nullptr) and pointers are the same. It doesn't check if lower and upper values are the same relying only on pointers comparison.

NGRAPH_API std::shared_ptr< op::Constant >	get_constant_from_source (const Output< Node > &source)
	Runs an estimation of source tensor. If it succeeded to calculate both bounds and they are the same returns Constant operation from the resulting bound, otherwise nullptr.

NGRAPH_API std::shared_ptr< op::Constant >	get_constant_max_of_type (element::Type_t t)
	Returns a Constant storing scalar value equal to std::numeric_limits<t>::max()

NGRAPH_API std::shared_ptr< op::Constant >	get_constant_min_of_type (element::Type_t t)
	Returns a Constant storing scalar value equal to std::numeric_limits<t>::min()

NGRAPH_API bool	validate_host_tensor_vector (const HostTensorVector &v, const size_t &size)
	Checks if size of HostTensorVector is the same as passed size attribute. Then checks that all the HostTensorPtrs are not equal to nullptr.

Variables
template class NGRAPH_API	VariantImpl< int64_t >

Detailed Description

The Intel nGraph C++ API.

Top level nGraph namespace.

Typedef Documentation

◆ Rank

using ngraph::Rank = typedef Dimension

Alias for Dimension, used when the value represents the number of axes in a shape, rather than the size of one dimension in a shape.

XXX: THIS TYPE IS EXPERIMENTAL AND THE ENTIRE DESIGN IS SUBJECT TO CHANGE.

Function Documentation

◆ as_type_ptr()

template<typename Type , typename Value >

std::enable_if< std::is_convertible<decltype(std::static_pointer_cast<Type>std::declval<Value>))), std::shared_ptr<Type> >::value, std::shared_ptr<Type> >::type ngraph::as_type_ptr ( Value value )

Casts a std::shared_ptr<Value> to a std::shared_ptr<Type> if it is of type Type, nullptr otherwise

◆ check_for_cycles()

NGRAPH_API bool ngraph::check_for_cycles	(	const ngraph::Function *	func,
		ngraph::NodeVector &	cycle_nodes,
		bool &	is_bkwd_cycle
	)

Checks the func for graph cycles starting from results going backwards, then from parameters going forward. It returns true if a cycle is found and the first cycle encountered.

◆ default_lower_bound_evaluator()

NGRAPH_API bool ngraph::default_lower_bound_evaluator	(	const Node *	node,
		const HostTensorVector &	output_values
	)

Estimates lower bound for node output tensors using only lower bounds of the nodes inputs.

Parameters

node	Operation to be performed
output_values	Vector of HostTensorPtrs representing resulting lower value estimations

Returns: boolean status if value evaluation was successful.

◆ default_upper_bound_evaluator()

NGRAPH_API bool ngraph::default_upper_bound_evaluator	(	const Node *	node,
		const HostTensorVector &	output_values
	)

Estimates upper bound for node output tensors using only upper bounds of the nodes inputs.

Parameters

node	Operation to be performed
output_values	Vector of HostTensorPtrs representing resulting upper value estimations

Returns: boolean status if value evaluation was successful.

◆ evaluate_as_partial_shape()

NGRAPH_API bool ngraph::evaluate_as_partial_shape	(	const Output< Node > &	output,
		PartialShape &	pshape
	)

Evaluates lower and upper value estimations for the output tensor. Estimation would be represented as partial shape object using Dimension(min, max) for each element.

Parameters

output	Node output pointing to the tensor for estimation.
pshape	Resulting estimation would be stored in this PartialShape.

Returns: boolean status if value evaluation was successful.

◆ evaluate_both_bounds()

NGRAPH_API std::pair<HostTensorPtr, HostTensorPtr> ngraph::evaluate_both_bounds ( const Output< Node > & output )

Evaluates lower and upper value estimations of the output tensor. Traverses graph up to deduce estimation through it.

Parameters

output Node output pointing to the tensor for estimation.

Returns: pair with HostTensorPtrs for lower and upper value estimation. Each object in pair could be HostTensorPtr to estimated value if particular bound can be determined, or nullptr.

◆ evaluate_lower_bound()

NGRAPH_API HostTensorPtr ngraph::evaluate_lower_bound ( const Output< Node > & output )

Evaluates lower value estimation of the output tensor. Traverses graph up to deduce estimation through it.

Parameters

Node	output pointing to the tensor for estimation.

Returns: HostTensorPtr to estimated value if can be determined, or nullptr.

◆ evaluate_nodes()

NGRAPH_API void ngraph::evaluate_nodes	(	std::map< RawNodeOutput, HostTensorPtr > &	value_map,
		std::map< RawNodeOutput, HostTensorPtr > &	output_tensor_map,
		const OutputVector &	outputs
	)

Evaluates outputs, treating values in value_map as already computed. value_map is updated.

Parameters

value_map	Key is RawNodeOutput in graph, value is the computed value. Updated by the function.
output_tensor_map	Tensors to use for particular outputs
outputs	Root set of values to try to compute

◆ evaluate_upper_bound()

NGRAPH_API HostTensorPtr ngraph::evaluate_upper_bound ( const Output< Node > & output )

Evaluates lower value estimation of the output tensor. Traverses graph up to deduce estimation through it.

Parameters

output Tensor to be estimated.

Returns: HostTensorPtr to estimated value if can be determined, or nullptr.

◆ get_inputs_from()

NGRAPH_API std::vector<Input<Node> > ngraph::get_inputs_from	(	Node &	src,
		Node &	dst
	)

Returns: A vector containing handles for each input of dst that is connected to an output of src.

◆ get_outputs_to()

NGRAPH_API std::vector<Output<Node> > ngraph::get_outputs_to	(	Node &	src,
		Node &	dst
	)

Returns: A vector containing a handle for each output of src that is connected to an input of dst.

◆ get_version()

NGRAPH_API void ngraph::get_version	(	size_t &	major,
		size_t &	minor,
		size_t &	patch,
		std::string &	extra
	)

Function to query parsed version information of the version of ngraph which contains this function. Version information strictly follows Semantic Versioning http://semver.org.

Parameters

major	Returns the major part of the version
minor	Returns the minor part of the version
patch	Returns the patch part of the version
extra	Returns the extra part of the version. This includes everything following the patch version number.

Note: Throws a runtime_error if there is an error during parsing

◆ getenv_bool()

NGRAPH_API bool ngraph::getenv_bool	(	const char *	env_var,
		bool	default_value = `false`
	)

Get the names environment variable as a boolean. If the value is not a valid boolean then an exception is thrown. Valid booleans are one of 1, 0, on, off, true, false All values are case insensitive. If the environment variable is not set the default_value is returned.

Parameters

env_var	The string name of the environment variable to get.
default_value	The value to return if the environment variable is not set.

Returns: Returns the boolean value of the environment variable.

◆ getenv_int()

NGRAPH_API int32_t ngraph::getenv_int	(	const char *	env_var,
		int32_t	default_value = `-1`
	)

Get the names environment variable as an integer. If the value is not a valid integer then an exception is thrown.

Parameters

env_var	The string name of the environment variable to get.
default_value	The value to return if the environment variable is not set.

Returns: Returns value or default_value if the environment variable is not set.

◆ getenv_string()

NGRAPH_API std::string ngraph::getenv_string ( const char * env_var )

Get the names environment variable as a string.

Parameters

env_var The string name of the environment variable to get.

Returns: Returns string by value or an empty string if the environment variable is not set.

◆ interval_bound_evaluator()

NGRAPH_API bool ngraph::interval_bound_evaluator	(	const Node *	node,
		const HostTensorVector &	lower_output_values,
		const HostTensorVector &	upper_output_values
	)

Estimates both bounds for node output tensors using both bounds of inputs. Works for operations with two inputs (in_1 and in_2). Brute forces all the pairs of bounds for inputs and evaluates all of them: {in_1_lower, in_2 lower}, {in_1_lower, in_2 upper}, {in_1_upper, in_2_lower}, {in_1_upper, in_2_upper}. Lower and upper values are selected from all the outputs calculated using input pairs.

Parameters

node	Operation to be performed
output_values	Vector of HostTensorPtrs representing resulting lower value estimations

Returns: boolean status if value evaluation was successful.

◆ maximum_value()

NGRAPH_API std::pair<bool, uint64_t> ngraph::maximum_value ( const Output< Node > & value )

Try to compute the maximum value of value.

Returns: (true, max_value) if can be determined, or (false, numeric_limits<uint64_t>::max()) if not.

◆ normalize_axes()

NGRAPH_API std::vector<size_t> ngraph::normalize_axes	(	const std::string &	node_description,
		const std::vector< int64_t > &	axes,
		const Rank &	tensor_rank
	)

Handle out of range axes in vector.

Parameters

[in]	node_description	The name of node with requested axes.
[in]	axes	The requested vector of axes.
[in]	tensor_rank	The corresponding tensor rank.

Returns: If any negative axis in vector, it counts from the last to the first axis, by adding tensor_rank to axis.

◆ normalize_axis() [1/4]

NGRAPH_API int64_t ngraph::normalize_axis	(	const Node *	node,
		std::int64_t	axis,
		const Rank &	tensor_rank
	)

Handle out of range axis.

Parameters

[in]	node	The node with requested axis.
[in]	axis	The requested axis value.
[in]	tensor_rank	The corresponding tensor rank.

Returns: Checking if axis is in range [-tensor_rank, tensor_rank-1], otherwise returns error. If negative axis, it counts from the last to the first axis, by adding tensor_rank to axis.

◆ normalize_axis() [2/4]

NGRAPH_API int64_t ngraph::normalize_axis	(	const Node *	node,
		std::int64_t	axis,
		std::uint64_t	tensor_rank,
		std::int64_t	axis_range_min,
		std::int64_t	axis_range_max
	)

Handle out of range axis.

Parameters

[in]	node	The node with requested axis.
[in]	axis	The requested axis value.
[in]	tensor_rank	The corresponding tensor rank.
[in]	axis_range_min	The min value of accepted range for axis.
[in]	axis_range_max	The max value of accepted range for axis.

Returns: Checking if axis is in range [axis_range_min, axis_range_max], otherwise returns error. If negative axis, it counts from the last to the first axis, by adding tensor_rank to axis.

◆ normalize_axis() [3/4]

NGRAPH_API int64_t ngraph::normalize_axis	(	const std::string &	node_description,
		std::int64_t	axis,
		const Rank &	tensor_rank
	)

Handle out of range axis.

Parameters

[in]	node_description	The node with requested axis.
[in]	axis	The requested axis value.
[in]	tensor_rank	The corresponding tensor rank.

Returns: Checking if axis is in range [-tensor_rank, tensor_rank-1], otherwise returns error. If negative axis, it counts from the last to the first axis, by adding tensor_rank to axis.

◆ normalize_axis() [4/4]

NGRAPH_API int64_t ngraph::normalize_axis	(	const std::string &	node_description,
		std::int64_t	axis,
		std::uint64_t	tensor_rank,
		std::int64_t	axis_range_min,
		std::int64_t	axis_range_max
	)

Handle out of range axis.

Parameters

[in]	node_description	The name of node with requested axis.
[in]	axis	The requested axis value.
[in]	tensor_rank	The corresponding tensor rank.
[in]	axis_range_min	The min value of accepted range for axis.
[in]	axis_range_max	The max value of accepted range for axis.

Returns: Checking if axis is in range [axis_range_min, axis_range_max], otherwise returns error. If negative axis, it counts from the last to the first axis, by adding tensor_rank to axis.

◆ operator+()

PartialShape ngraph::operator+	(	const PartialShape &	s1,
		const PartialShape &	s2
	)

Elementwise addition of two PartialShape objects.

Parameters

s1	Left operand for addition.
s2	Right operand for addition.

Returns: The result of elementwise adding s1 to s2 (see description).

Exceptions

std::invalid_argument If s1 and s2 have inconsistent ranks.

If s1 or s2 has dynamic rank, returns PartialShape::dynamic().
If s1 ands2` both have static rank, and their ranks are unequal, throws std::invalid_argument.
If s1 and s2 both have static rank, and their ranks are equal, returns a new shape whose ith dimension is s1[i] + s2[i].

◆ operator<<() [1/2]

NGRAPH_API std::ostream& ngraph::operator<<	(	std::ostream &	str,
		const Dimension &	dimension
	)

Insert a human-readable representation of a dimension into an output stream.

Parameters

str	The output stream targeted for insertion.
dimension	The dimension to be inserted into `str`.

Returns: A reference to str after insertion.

Inserts the string ? if dimension is dynamic; else inserts dimension.get_length().

◆ operator<<() [2/2]

NGRAPH_API std::ostream& ngraph::operator<<	(	std::ostream &	str,
		const PartialShape &	shape
	)

Inserts a human-readable representation of a PartialShape into an output stream.

Parameters

str	The output stream targeted for insertion.
shape	The shape to be inserted into `str`.

Returns: A reference to str after insertion.

The output to the stream is in "informal" notation. In other words:

If shape has dynamic rank, inserts the string ?.
If shape has static rank, inserts the string {, then inserts each dimension of shape into the output stream separated by commas, then inserts }.

Example:

PartialShape s1{PartialShape::dynamic())};
PartialShape s2{};
PartialShape s3{1,Dimension::dynamic(),2,3};
PartialShape s4{2,3,4};
std::cout << s1 << std::endl
          << s2 << std::endl
          << s3 << std::endl
          << s4 << std::endl;

Output:

?
{}
{1,?,2,3}
{2,3,4}

◆ parse_string< float >()

template<>

NGRAPH_API float ngraph::parse_string< float > ( const std::string & s )

template specializations for float and double to handle INFINITY, -INFINITY and NaN values.

◆ parse_string< int8_t >()

template<>

NGRAPH_API int8_t ngraph::parse_string< int8_t > ( const std::string & s )

template specializations for int8_t and uint8_t to handle the fact that default implementation ends up treating values as characters so that the number "0" turns into the parsed value 48, which is it's ASCII value

◆ parse_version_string()

NGRAPH_API void ngraph::parse_version_string	(	std::string	version,
		size_t &	major,
		size_t &	minor,
		size_t &	patch,
		std::string &	extra
	)

Function to query parsed version information of the version of ngraph which contains this function. Version information strictly follows Semantic Versioning http://semver.org.

Parameters

version	The major part of the version
major	Returns the major part of the version
minor	Returns the minor part of the version
patch	Returns the patch part of the version
extra	Returns the extra part of the version. This includes everything following the patch version number.

Note: Throws a runtime_error if there is an error during parsing

◆ replace_node() [1/2]

NGRAPH_API void ngraph::replace_node	(	const std::shared_ptr< Node > &	target,
		const OutputVector &	replacement_values
	)

Replace target.outputs[i] with replacement_values[i] and transfer control dependents and provenance from target to the node(s) in replacement_values.

◆ replace_node() [2/2]

NGRAPH_API void ngraph::replace_node	(	std::shared_ptr< Node >	target,
		std::shared_ptr< Node >	replacement,
		const std::vector< int64_t > &	output_order
	)

Replace the node target with the node replacement, i.e., redirect all users and control dependencies of target to replacement.

Parameters

target	Node to be replaced.
replacement	Node to replace `target` with.
output_order	Vector determines order of replacement node's outputs.

This is primarily used in graph-rewriting passes. For example, we might "fuse" two Concat operations as follows:

(Step 0: Original graph)

(Step 1: Construct replacement)

shared_ptr<Node> new_N1 = make_shared<op::Concat>({A,B,C},3);

A-------------------------------------—. | | | B-------------—)–. | | | | v v | | N0[Concat, concatenation_axis=3] C--—)–)–. | | | | | v v v v v N1[Concat, concatenation_axis=3] new_N1[Concat, concatenation_axis=3] | | v v some_user another_user

(Step 2: Replace N1 with new_N1)

replace_node(N1, new_N1);

A-------------------------------------—. | | | B-------------—)–. | | | | v v | | N0[Concat, concatenation_axis=3] C--—)–)–. | | | | | v v v v v N1[Concat, concatenation_axis=3] new_N1[Concat, concatenation_axis=3] | | v v some_user another_user

(Step 3: N0 and N1 are now dead, nodes will be freed)

[happens automatically, once all shared_ptrs to N1 are released]

A-------------------------------------—. | B-------------—)–. | | | | C--—)–)–. | | | v v v new_N1[Concat, concatenation_axis=3] | | v v some_user another_user

NOTE 1: replace_node is not type-safe (the graph is not revalidated). For example, the following is allowed, even if node some_user requires an input of shape 2x2:

(Before) A(shape=2x2) B(shape=3x3) | v some_user(requires 2x2 input)

(After – graph is now invalid)

 replace_node(A, B);

 A(shape=2x2)  B(shape=3x3)
               |
               v
            some_user(requires 2x2 input)

NOTE 2: it is possible to insert a cycle into the graph with replace_node, resulting in an invalid graph. Care must be taken to avoid this. One common example is when you are attempting to insert a new node M "after"a nodeN`. For example, you might expect this to work:

shared_ptr<Node> M = make_shared<SomeUnaryOp>(N); replace_node(M, N);

The problem is that at replacement time, N itself is a user of M. So we end up introducing a cycle as follows:

  N
  |
  v

other users...

|||
vvv

 N------------>M
 |
 v

other users...

|||
vvv

         .----.
        |      |
        |      |
 N      `----->M
               |
               v
          other users...

To avoid the cycle, a valid way to perform the above desired insertion would be,

   auto new_N = N->clone_with_new_inputs(N->input_values());
   shared_ptr<Node> M = make_shared<SomeUnaryOp>(new_N);
   replace_node(N, M);

◆ replace_nodes()

NGRAPH_API void ngraph::replace_nodes	(	const std::shared_ptr< Function > &	f,
		const std::unordered_map< std::shared_ptr< op::v0::Parameter >, std::shared_ptr< op::v0::Parameter >> &	parameter_replacement_map,
		const std::unordered_map< std::shared_ptr< Node >, std::shared_ptr< Node >> &	body_replacement_map
	)

Replace multiple nodes in a function.

Parameters

f	Function where replacement is taking place.
parameter_replacement_map	A mapping from parameter shared pointers to parameter shared pointers. For each pair (k,v) in the map, parameter k is replaced by parameter v, except if k==v or k is not a parameter bound by f, in which case the pair (k,v) is ignored.
body_replacement_map	A mapping from node shared pointers to node shared pointers. For each pair (k,v) in the map, node k is replaced by node v, except if k==v, the pair (k,v) is ignored. Note that if k is a parameter, its users will be redirected to v, but k will not be replaced in the function's parameter list.

Limitations:

No check is made that the replaced nodes in parameter_replacement_map are actually among the bound parameters of f. (If a parameter appears in the map that is not bound by f, it will be silently ignored.)
If a parameter node appears as a key in both parameter_replacement_map and in body_replacement_map, behavior is unspecified.

◆ specialize_function()

NGRAPH_API std::shared_ptr<Function> ngraph::specialize_function	(	std::shared_ptr< Function >	f,
		const std::vector< element::Type > &	parameter_element_types,
		const std::vector< PartialShape > &	parameter_shapes,
		const std::vector< void * > &	parameter_values
	)

Creates a "specialized" clone of a function. The partial shapes and element types of the function's parameters may be narrowed to more specific shapes and element types, and constant values may optionally be substituted for any or all of the parameters.

Parameters

f	The function to be cloned.
parameter_element_types	The new parameter element types to substitute. Length must be equal to the number of parameters of f.
parameter_shapes	The new parameter shapes to substitute. Length must be equal to the number of parameters of f.
parameter_values	Parameter values to substitute. Length must be equal to the number of parameters of f, with nullptr indicating that no substitution is to be made for the corresponding parameter.

Returns: A clone of f, with the parameter element types, shapes, and values specialized.

Exceptions

CheckFailure	if parameter_element_types, parameter_shapes is not valid (see details).
NodeValidationError	if node validation fails as the clone is being constructed.

Creates a "specialized" clone of an nGraph Function.

For example, suppose that a function f has three parameters with partial shapes:

param0: ?
param1: {1,?,3}
param2: {?,?,4}

Shape specialization would allow us to create a clone of f where the shapes are (for example):

param0: {1,2}
param1: {1,5,3}
param2: {3,?,4}

But not (for example):

param1: {1,5,3,4}  // rank doesn't match {1,?,3}
param1: {2,?,3}    // the "2" doesn't match the "1"
param1: {?,?,3}    // the new shape is too relaxed: it doesn't require 1 for the first dim

Note that validation errors can potentially occur during cloning. For example:

n = Parameter{shape=?}
m = Parameter{shape=?}
x = n + m
f = Function(x,{n,m})

If we specialize n to the shape {1,2,3} and m to the shape {4,5,6}, cloning will fail because when we reconstruct the new x node, it will see that the shapes are inconsistent for elementwise add.

Specialization of element types is also possible: element::dynamic can be specialized to a concrete element type or left dynamic; but a concrete element type can only be specialized to itself (e.g., specialization does not allow you to change element::i32 to element::i64).

Finally, it is possible to specialize parameter values. If the ith element of parameter_values is not nullptr, and fully static element type and shape has been specified for the ith parameter, a Constant node will be created and substituted for the ith parameter, with its data drawn from parameter_values[i]. Note that the Parameter node remains (in order to maintain the arity of the function), but will no longer have any users.

It is required that:

The length of parameter_element_types, parameter_shapes, and parameter_values is the same as the number of f's parameters.
Each shape in parameter_shapes is a refinement of the shape of the corresponding parameter of f. Roughly speaking, a shape s1 is said to "refine" s2 if s1 can be obtained from s2 by filling in s2's question marks. See PartialShape::refines for more details.
For all i, either the element type of fp_i is dynamic, or fp_i is the same as parameter_element_types[i]. (Here fp_i is the ith parameter of f.)
For all i where parameter_values[i] != nullptr and parameter_element_types[i] is static and parameter_shapes[i] is static, parameter_values[i] points to a buffer from which a Constant node with element type parameter_element_types[i] and shape parameter_shapes[i] can be created.

TODO(amprocte): convert this to a pass.

◆ traverse_nodes()

NGRAPH_API void ngraph::traverse_nodes	(	const NodeVector &	subgraph_results,
		std::function< void(std::shared_ptr< Node >)>	f,
		const NodeVector &	subgraph_params = `{}`
	)

Visit each node in a sub-graph of the entire graph.

Parameters

subgraph_results	The output nodes of the sub-graph
f	Function to execute at each node in the traversal
subgraph_params	Input nodes of the sub-graph (optional)

Traverses a sub-graph starting from subgraph_results moving up towards parameter nodes. Traversal stops if it hits a node in subgraph_params.

Most useful for finding parameters of a graph directly from the result nodes and not from function parameters or extracting a subgraph relevant to the computation of certain outputs

◆ try_apply_auto_padding()

NGRAPH_API bool ngraph::try_apply_auto_padding	(	const PartialShape &	image_shape,
		const Shape &	filter_shape,
		const Strides &	filter_strides,
		const Strides &	filter_dilations,
		const op::PadType	pad_type,
		CoordinateDiff &	padding_above,
		CoordinateDiff &	padding_below
	)

Apply auto padding to padding_above and padding_below inputs if all needed informations are known.

Parameters

image_shape	The shape of input image.
filter_shape	The shape of filter input.
filter_strides	The strides of applied padding.
filter_dilations	The dilations of applied padding.
pad_type	The type of padding. Auto padding is applied only for SAME_UPPER and SAME_LOWER mode.
padding_above	The beginning of padding shape.
end	The beginning of padding shape.

Returns: true if auto padding was applied successfully (all needed informations such as spatial dims are known), false otherwise.

Namespaces

Data Structures

Typedefs

Enumerations

Functions

Variables

Detailed Description

Typedef Documentation

◆ Rank

Function Documentation

◆ as_type_ptr()

◆ check_for_cycles()

◆ default_lower_bound_evaluator()

◆ default_upper_bound_evaluator()

◆ evaluate_as_partial_shape()

◆ evaluate_both_bounds()

◆ evaluate_lower_bound()

◆ evaluate_nodes()

◆ evaluate_upper_bound()

◆ get_inputs_from()

◆ get_outputs_to()

◆ get_version()

◆ getenv_bool()

◆ getenv_int()

◆ getenv_string()

◆ interval_bound_evaluator()

◆ maximum_value()

◆ normalize_axes()

◆ normalize_axis() [1/4]

◆ normalize_axis() [2/4]

◆ normalize_axis() [3/4]

◆ normalize_axis() [4/4]

◆ operator+()

◆ operator<<() [1/2]

◆ operator<<() [2/2]

◆ parse_string< float >()

◆ parse_string< int8_t >()

◆ parse_version_string()

◆ replace_node() [1/2]

◆ replace_node() [2/2]

◆ replace_nodes()

◆ specialize_function()

◆ traverse_nodes()

◆ try_apply_auto_padding()