Classes
class	Optional

class	Version_t

class	IDiagLog

class	IDlContainer

class	IOBufferDataTypeMap

class	ITensor

class	ITensorFactory

class	UserBufferEncoding

class	UserBufferSource

class	UserBufferSourceGLBuffer

class	UserBufferEncodingUnsigned8Bit

class	UserBufferEncodingFloatN

class	UserBufferEncodingFloat

class	UserBufferEncodingTfN

class	UserBufferEncodingIntN

class	UserBufferEncodingUintN

class	IUserBuffer

class	IUserBufferFactory

class	Options

struct	UserGLConfig

struct	UserGpuConfig

class	PlatformConfig

class	zdl

class	RuntimeList

class	SNPE::SNPE

class	SNPE::SNPEBuilder

class	SNPE::SNPEFactory

class	StringList

class	TensorMap

class	TensorShape

class	TensorShapeMap

struct	SnpeUdo_Version_t

struct	SnpeUdo_LibVersion_t

struct	Udo_PkgVersion_t

union	SnpeUdo_Value_t

struct	SnpeUdo_ScalarParam_t

struct	SnpeUdo_TFQuantize_t

struct	SnpeUdo_QuantizeParams_t

struct	SnpeUdo_PerCoreDatatype_t

struct	SnpeUdo_TensorParam_t

struct	SnpeUdo_TensorInfo_t

struct	SnpeUdo_Param_t

struct	SnpeUdo_OpCoreInfo_t

struct	SnpeUdo_OperationInfo_t

struct	SnpeUdo_LibraryInfo_t

struct	SnpeUdo_RegInfo_t

struct	SnpeUdo_ImpInfo_t

struct	SnpeUdo_OpDefinition_t

struct	SnpeUdo_CpuInfrastructure_t

struct	dspGlobalInfrastructure

struct	hexnnv2OpFactoryInfra

struct	SnpeUdo_GpuInfrastructure_t

struct	SnpeUdo_GpuOpFactoryInfrastructure_t

struct	SnpeUdo_GpuTensorData_t

class	UserBufferMap

class	UserMemoryMap

Typedefs
using	Dimension = size_t

typedef SnpeUdo_ErrorType_t(*	SnpeUdo_ExternalNotify_t) (const uint32_t ID)

typedef struct dspGlobalInfrastructure	SnpeUdo_DspGlobalInfrastructure_t

typedef struct hexnnv2OpFactoryInfra	SnpeUdo_HexNNv2OpFactoryInfra_t

typedef void *	SnpeUdo_HexNNv2OpInfra_t

typedef SnpeUdo_ErrorType_t(*	SnpeUdo_getProgram_t) (void programCache, const char programName, cl_program *program)

typedef SnpeUdo_ErrorType_t(*	SnpeUdo_storeProgram_t) (void programCache, const char programName, cl_program program)

Enumerations
enum	Runtime_t { CPU_FLOAT32 = 0, GPU_FLOAT32_16_HYBRID = 1, DSP_FIXED8_TF = 2, GPU_FLOAT16 = 3, AIP_FIXED8_TF = 5 , CPU = CPU_FLOAT32, GPU = GPU_FLOAT32_16_HYBRID, DSP = DSP_FIXED8_TF }

enum	RuntimeCheckOption_t

enum	PerformanceProfile_t { DEFAULT = 0 }

enum	ProfilingLevel_t { OFF = 0, BASIC = 1, DETAILED = 2, MODERATE = 3 }

enum	ExecutionPriorityHint_t

enum	SnpeUdo_ErrorType_t

enum	SnpeUdo_DataType_t

enum	SnpeUdo_TensorLayout_t

enum	SnpeUdo_CoreType_t

enum	SnpeUdo_ParamType_t

enum	SnpeUdo_QuantizationType_t

Functions
ZDL_EXPORT ErrorCode	getLastErrorCode ()

ZDL_EXPORT const char *	getLastErrorString ()

ZDL_EXPORT const char *	getLastInfoString ()

ZDL_EXPORT uint32_t	enumToUInt32 (zdl::DlSystem::ErrorCode code)

	Optional ()

template<typename Q = T>
	Optional (const T &v, typename std::enable_if<!std::is_pointer< Q >::value >::type *=0)

	operator bool () const noexcept

const T &	operator* ()

const T &	operator* () const

const std::string	toString () const

const zdl::DlSystem::String	asString () const

virtual bool	setOptions (const Options &loggingOptions)=0

virtual Options	getOptions ()=0

virtual bool	setDiagLogMask (const std::string &mask)=0

virtual bool	setDiagLogMask (const zdl::DlSystem::String &mask)=0

virtual bool	start (void)=0

static std::unique_ptr< IDlContainer >	open (const std::string &filename) noexcept

static std::unique_ptr< IDlContainer >	open (const zdl::DlSystem::String &filename) noexcept

static std::unique_ptr< IDlContainer >	open (const std::vector< uint8_t > &buffer) noexcept

static std::unique_ptr< IDlContainer >	open (const uint8_t *buffer, const size_t size) noexcept

	IOBufferDataTypeMap ()

void	add (const char *name, zdl::DlSystem::IOBufferDataType_t bufferDataType)

void	remove (const char *name)

zdl::DlSystem::IOBufferDataType_t	getBufferDataType (const char *name)

zdl::DlSystem::IOBufferDataType_t	getBufferDataType ()

size_t	size ()

bool	find (const char *name)

bool	empty ()

virtual iterator	begin ()=0

virtual const_iterator	cbegin () const =0

virtual iterator	end ()=0

virtual const_iterator	cend () const =0

virtual TensorShape	getShape () const =0

virtual size_t	getSize () const =0

virtual void	serialize (std::ostream &output) const =0

virtual std::unique_ptr< ITensor >	createTensor (const TensorShape &shape) noexcept=0

virtual std::unique_ptr< ITensor >	createTensor (std::istream &input) noexcept=0

virtual std::unique_ptr< ITensor >	createTensor (const TensorShape &shape, const unsigned char *data, size_t dataSize) noexcept=0

	RuntimeList ()

	RuntimeList (const RuntimeList &other)

	RuntimeList (const zdl::DlSystem::Runtime_t &runtime)

RuntimeList &	operator= (const RuntimeList &other)

Runtime_t &	operator[] (size_t index)

bool	add (const zdl::DlSystem::Runtime_t &runtime)

void	remove (const zdl::DlSystem::Runtime_t runtime) noexcept

void	clear () noexcept

zdl::DlSystem::StringList	getRuntimeListNames () const

static zdl::DlSystem::Runtime_t	stringToRuntime (const char *runtimeStr)

static const char *	runtimeToString (const zdl::DlSystem::Runtime_t runtime)

	StringList (size_t length)

void	append (const char *str)

const char *	at (size_t idx) const noexcept

const char **	begin () const noexcept

const char **	end () const noexcept

size_t	size () const noexcept

StringList &	operator= (const StringList &) noexcept

	StringList (const StringList &other)

	StringList (StringList &&other) noexcept

	TensorMap ()

	TensorMap (const TensorMap &other)

TensorMap &	operator= (const TensorMap &other)

void	add (const char name, zdl::DlSystem::ITensor tensor)

void	remove (const char *name) noexcept

void	clear () noexcept

zdl::DlSystem::ITensor *	getTensor (const char *name) const noexcept

zdl::DlSystem::StringList	getTensorNames () const

	TensorShape (std::initializer_list< Dimension > dims)

	TensorShape (const Dimension *dims, size_t size)

	TensorShape (std::vector< Dimension > dims)

	TensorShape (const TensorShape &other)

TensorShape &	operator= (const TensorShape &other)

	TensorShape ()

void	concatenate (std::initializer_list< Dimension > dims)

void	concatenate (const Dimension *dims, size_t size)

void	concatenate (const Dimension &dim)

Dimension &	operator[] (size_t index)

size_t	rank () const

const Dimension *	getDimensions () const

	TensorShapeMap ()

	TensorShapeMap (const TensorShapeMap &other)

TensorShapeMap &	operator= (const TensorShapeMap &other)

void	add (const char *name, const zdl::DlSystem::TensorShape &tensorShape)

void	remove (const char *name) noexcept

void	clear () noexcept

zdl::DlSystem::TensorShape	getTensorShape (const char *name) const noexcept

zdl::DlSystem::StringList	getTensorShapeNames () const

SnpeUdo_ErrorType_t	SnpeUdo_initImplLibrary (void *globalInfrastructure)

SnpeUdo_ErrorType_t	SnpeUdo_getImplVersion (SnpeUdo_LibVersion_t **version)

SnpeUdo_ErrorType_t	SnpeUdo_terminateImplLibrary (void)

SnpeUdo_ErrorType_t	SnpeUdo_getImpInfo (SnpeUdo_ImpInfo_t **implementationInfo)

SnpeUdo_ErrorType_t	SnpeUdo_createOpFactory (SnpeUdo_CoreType_t udoCoreType, void perFactoryInfrastructure, SnpeUdo_String_t operationType, uint32_t numOfStaticParams, SnpeUdo_Param_t staticParams, SnpeUdo_OpFactory_t *opFactory)

SnpeUdo_ErrorType_t	SnpeUdo_releaseOpFactory (SnpeUdo_OpFactory_t opFactory)

SnpeUdo_ErrorType_t	SnpeUdo_createOperation (SnpeUdo_OpFactory_t opFactory, void perOpInfrastructure, uint32_t numOfInputs, SnpeUdo_TensorParam_t inputs, uint32_t numOfOutputs, SnpeUdo_TensorParam_t outputs, SnpeUdo_Operation_t operation)

SnpeUdo_ErrorType_t	SnpeUdo_executeOp (SnpeUdo_Operation_t operation, bool blocking, const uint32_t ID, SnpeUdo_ExternalNotify_t notifyFunc)

SnpeUdo_ErrorType_t	SnpeUdo_setOpIO (SnpeUdo_Operation_t operation, SnpeUdo_TensorParam_t inputs, SnpeUdo_TensorParam_t outputs)

SnpeUdo_ErrorType_t	SnpeUdo_profileOp (SnpeUdo_Operation_t operation, uint32_t *executionTime)

SnpeUdo_ErrorType_t	SnpeUdo_releaseOp (SnpeUdo_Operation_t operation)

SnpeUdo_ErrorType_t	SnpeUdo_validateOperation (SnpeUdo_String_t operationType, uint32_t numOfStaticParams, const SnpeUdo_Param_t *staticParams)

SnpeUdo_ErrorType_t	SnpeUdo_queryOperation (SnpeUdo_String_t operationType, uint32_t numOfStaticParams, const SnpeUdo_Param_t staticParams, uint32_t numOfInputs, SnpeUdo_QuantizationType_t inputsQuantTypes, SnpeUdo_HexNNTensorLayout_t inputsLayouts, uint32_t numOfOutputs, SnpeUdo_QuantizationType_t outputsQuantTypes, SnpeUdo_HexNNTensorLayout_t *outputsLayouts)

SnpeUdo_ErrorType_t	SnpeUdo_initRegLibrary (void)

SnpeUdo_ErrorType_t	SnpeUdo_getRegLibraryVersion (SnpeUdo_LibVersion_t **version)

SnpeUdo_ErrorType_t	SnpeUdo_terminateRegLibrary (void)

SnpeUdo_ErrorType_t	SnpeUdo_getRegInfo (SnpeUdo_RegInfo_t **registrationInfo)

SnpeUdo_ErrorType_t	SnpeUdo_validateOperation (SnpeUdo_OpDefinition_t *opDefinition)

SnpeUdo_ErrorType_t	SnpeUdo_getVersion (SnpeUdo_LibVersion_t **version)

Variables
int32_t	Major

int32_t	Minor

int32_t	Teeny

std::string	Build

Detailed Description

This module defines the SNPE C++ APIs

Class Documentation

◆ zdl::DlSystem::Optional

class zdl::DlSystem::Optional

Class to manage a value that may or may not exist. The boolean value of the Optional class is true if the object contains a value and false if it does not contain a value.

The class must be evaluated and confirmed as true (containing a value) before being dereferenced.

Public Member Functions
	Optional ()

template<typename Q = T>
	Optional (const T &v, typename std::enable_if<!std::is_pointer< Q >::value >::type *=0)

	operator bool () const noexcept

const T &	operator* ()

const T &	operator* () const

◆ zdl::DlSystem::Version_t

class zdl::DlSystem::Version_t

A class that contains the different portions of a version number.

Public Member Functions
const std::string	toString () const

const zdl::DlSystem::String	asString () const

Public Attributes
int32_t	Major

int32_t	Minor

int32_t	Teeny

std::string	Build

◆ zdl::DiagLog::IDiagLog

class zdl::DiagLog::IDiagLog

Interface for controlling logging for zdl components.

Public Member Functions
virtual bool	setOptions (const Options &loggingOptions)=0

virtual Options	getOptions ()=0

virtual bool	setDiagLogMask (const std::string &mask)=0

virtual bool	setDiagLogMask (const zdl::DlSystem::String &mask)=0

virtual bool	start (void)=0

◆ zdl::DlContainer::IDlContainer

class zdl::DlContainer::IDlContainer

Represents a container for a neural network model which can be used to load the model into the SNPE runtime.

Public Member Functions
virtual bool	save (const std::string &filename)=0

virtual bool	save (const zdl::DlSystem::String &filename)=0

Static Public Member Functions
static std::unique_ptr< IDlContainer >	open (const std::string &filename) noexcept

static std::unique_ptr< IDlContainer >	open (const zdl::DlSystem::String &filename) noexcept

static std::unique_ptr< IDlContainer >	open (const std::vector< uint8_t > &buffer) noexcept

static std::unique_ptr< IDlContainer >	open (const uint8_t *buffer, const size_t size) noexcept

Member Function Documentation

◆ save() [1/2]

virtual bool save ( const std::string & filename )

pure virtual

Save the container to an archive on disk. This function will save the container if the filename is different from the file that it was opened from, or if at least one record was modified since the container was opened.

It will truncate any existing file at the target path.

Parameters

filename Container archive file path.

Returns: indication of success/failure

◆ save() [2/2]

virtual bool save ( const zdl::DlSystem::String & filename )

pure virtual

Save the container to an archive on disk. This function will save the container if the filename is different from the file that it was opened from, or if at least one record was modified since the container was opened.

It will truncate any existing file at the target path.

Parameters

filename Container archive file path.

Returns: indication of success/failure

◆ zdl::DlSystem::IOBufferDataTypeMap

class zdl::DlSystem::IOBufferDataTypeMap

The IoBufferDataTypeMap class definition

Public Member Functions
	IOBufferDataTypeMap ()

void	add (const char *name, zdl::DlSystem::IOBufferDataType_t bufferDataType)

void	remove (const char *name)

zdl::DlSystem::IOBufferDataType_t	getBufferDataType (const char *name)

zdl::DlSystem::IOBufferDataType_t	getBufferDataType ()

size_t	size ()

bool	find (const char *name)

bool	empty ()

◆ zdl::DlSystem::ITensor

class zdl::DlSystem::ITensor

Represents a tensor which holds n-dimensional data. It is important to understand how the tensor data is represented in memory relative to the tensor dimensions. Tensors store data in memory in row-major order (i.e. the last tensor dimension is the fastest varying one). For example, if you have a two dimensional tensor with 3 rows and 2 columns (i.e. the tensor dimensions are 3,2 as returned in tensor dimension vectors) with the following data in terms rows and columns:

| 1 2 |
| 3 4 |
| 5 6 |

This data would be stored in memory as 1,2,3,4,5,6.

Public Member Functions
virtual iterator	begin ()=0

virtual const_iterator	cbegin () const =0

virtual iterator	end ()=0

virtual const_iterator	cend () const =0

virtual TensorShape	getShape () const =0

virtual size_t	getSize () const =0

virtual void	serialize (std::ostream &output) const =0

◆ zdl::DlSystem::ITensorFactory

class zdl::DlSystem::ITensorFactory

Factory interface class to create ITensor objects.

Public Member Functions
virtual std::unique_ptr< ITensor >	createTensor (const TensorShape &shape) noexcept=0

virtual std::unique_ptr< ITensor >	createTensor (std::istream &input) noexcept=0

virtual std::unique_ptr< ITensor >	createTensor (const TensorShape &shape, const unsigned char *data, size_t dataSize) noexcept=0

◆ zdl::DlSystem::UserBufferEncoding

class zdl::DlSystem::UserBufferEncoding

A base class buffer encoding type

Public Types
enum	ElementType_t

Public Member Functions
virtual size_t	getElementSize () const noexcept=0

ElementType_t	getElementType () const noexcept

Member Enumeration Documentation

◆ ElementType_t

enum ElementType_t

strong

An enum class of all supported element types in a IUserBuffer

Enumerator
UNKNOWN	Unknown element type.
FLOAT	Each element is presented by 32-bit float.
UNSIGNED8BIT	Each element is presented by an unsigned int.
FLOAT16	Each element is presented by 16-bit float.
TF8	Each element is presented by an 8-bit quantized value.
TF16	Each element is presented by an 16-bit quantized value.
INT32	Each element is presented by Int32.
UINT32	Each element is presented by UInt32.
INT8	Each element is presented by Int8.
UINT8	Each element is presented by UInt8.

Member Function Documentation

◆ getElementSize()

virtual size_t getElementSize ( ) const

pure virtualnoexcept

Retrieves the size of the element, in bytes.

Returns: Size of the element, in bytes.

Implemented in UserBufferEncodingUintN, UserBufferEncodingIntN, UserBufferEncodingTfN, UserBufferEncodingFloatN, and UserBufferEncodingUnsigned8Bit.

◆ getElementType()

ElementType_t getElementType ( ) const

inlinenoexcept

Retrieves the element type.

Returns: Element type

◆ zdl::DlSystem::UserBufferSource

class zdl::DlSystem::UserBufferSource

A base class buffer source type

Note: User buffer from CPU support all kinds of runtimes; User buffer from GLBUFFER support only GPU runtime.

Public Member Functions
SourceType_t	getSourceType () const noexcept

Member Enumeration Documentation

◆ SourceType_t

enum SourceType_t

strong

Enumerator
UNKNOWN	Unknown buffer source type.
CPU	The network inputs are from CPU buffer.
GLBUFFER	The network inputs are from OpenGL buffer.

Member Function Documentation

◆ getSourceType()

SourceType_t getSourceType ( ) const

inlinenoexcept

Retrieves the source type.

Returns: Source type

◆ zdl::DlSystem::UserBufferSourceGLBuffer

class zdl::DlSystem::UserBufferSourceGLBuffer

An source type where input data is delivered from OpenGL buffer

Additional Inherited Members
Public Member Functions inherited from UserBufferSource
SourceType_t	getSourceType () const noexcept

◆ zdl::DlSystem::UserBufferEncodingUnsigned8Bit

class zdl::DlSystem::UserBufferEncodingUnsigned8Bit

An encoding type where each element is represented by an unsigned int

Public Member Functions
size_t	getElementSize () const noexcept override

Public Member Functions inherited from UserBufferEncoding
ElementType_t	getElementType () const noexcept

Additional Inherited Members
Public Types inherited from UserBufferEncoding
enum	ElementType_t

Member Function Documentation

◆ getElementSize()

size_t getElementSize ( ) const

overridevirtualnoexcept

Retrieves the size of the element, in bytes.

Returns: Size of the element, in bytes.

Implements UserBufferEncoding.

◆ zdl::DlSystem::UserBufferEncodingFloatN

class zdl::DlSystem::UserBufferEncodingFloatN

An encoding type where each element is represented by a N-bit float

Public Member Functions
size_t	getElementSize () const noexcept override

Public Member Functions inherited from UserBufferEncoding
ElementType_t	getElementType () const noexcept

Additional Inherited Members
Public Types inherited from UserBufferEncoding
enum	ElementType_t

Member Function Documentation

◆ getElementSize()

size_t getElementSize ( ) const

overridevirtualnoexcept

Retrieves the size of the element, in bytes.

Returns: Size of the element, in bytes.

Implements UserBufferEncoding.

◆ zdl::DlSystem::UserBufferEncodingFloat

class zdl::DlSystem::UserBufferEncodingFloat

An encoding type where each element is represented by a 32-bit float

Additional Inherited Members
Public Types inherited from UserBufferEncoding
enum	ElementType_t

Public Member Functions inherited from UserBufferEncodingFloatN
size_t	getElementSize () const noexcept override

Public Member Functions inherited from UserBufferEncoding
ElementType_t	getElementType () const noexcept

◆ zdl::DlSystem::UserBufferEncodingTfN

class zdl::DlSystem::UserBufferEncodingTfN

An encoding type where each element is represented by tf8, which is an 8-bit quantizd value, which has an exact representation of 0.0

Public Member Functions
size_t	getElementSize () const noexcept override

void	setStepExactly0 (uint64_t stepExactly0)

void	setQuantizedStepSize (const float quantizedStepSize)

uint64_t	getStepExactly0 () const

float	getMin () const

float	getMax () const

float	getQuantizedStepSize () const

Public Member Functions inherited from UserBufferEncoding
ElementType_t	getElementType () const noexcept

Additional Inherited Members
Public Types inherited from UserBufferEncoding
enum	ElementType_t

Member Function Documentation

◆ getElementSize()

size_t getElementSize ( ) const

overridevirtualnoexcept

Retrieves the size of the element, in bytes.

Returns: Size of the element, in bytes.

Implements UserBufferEncoding.

◆ getMax()

float getMax ( ) const

inline

Calculates the maximum floating point value that can be represented with this encoding.

Returns: Maximum representable floating point value

◆ getMin()

float getMin ( ) const

inline

Calculates the minimum floating point value that can be represented with this encoding.

Returns: Minimum representable floating point value

◆ getQuantizedStepSize()

float getQuantizedStepSize ( ) const

inline

Retrieves the step size.

Returns: Step size

◆ getStepExactly0()

uint64_t getStepExactly0 ( ) const

inline

Retrieves the step that represents 0.0.

Returns: Step value

◆ setQuantizedStepSize()

void setQuantizedStepSize ( const float quantizedStepSize )

inline

Sets the float value that each step represents.

Parameters

[in] quantizedStepSize The float value of each step size

◆ setStepExactly0()

void setStepExactly0 ( uint64_t stepExactly0 )

inline

Sets the step value that represents 0.

Parameters

[in] stepExactly0 The step value that represents 0

◆ zdl::DlSystem::UserBufferEncodingIntN

class zdl::DlSystem::UserBufferEncodingIntN

An encoding type where each element is represented by intN, which is an

Public Member Functions
size_t	getElementSize () const noexcept override

Public Member Functions inherited from UserBufferEncoding
ElementType_t	getElementType () const noexcept

Additional Inherited Members
Public Types inherited from UserBufferEncoding
enum	ElementType_t

Member Function Documentation

◆ getElementSize()

size_t getElementSize ( ) const

overridevirtualnoexcept

Retrieves the size of the element, in bytes.

Returns: Size of the element, in bytes.

Implements UserBufferEncoding.

◆ zdl::DlSystem::UserBufferEncodingUintN

class zdl::DlSystem::UserBufferEncodingUintN

An encoding type where each element is represented by UintN, which is an

Public Member Functions
size_t	getElementSize () const noexcept override

Public Member Functions inherited from UserBufferEncoding
ElementType_t	getElementType () const noexcept

Additional Inherited Members
Public Types inherited from UserBufferEncoding
enum	ElementType_t

Member Function Documentation

◆ getElementSize()

size_t getElementSize ( ) const

overridevirtualnoexcept

Retrieves the size of the element, in bytes.

Returns: Size of the element, in bytes.

Implements UserBufferEncoding.

◆ zdl::DlSystem::IUserBuffer

class zdl::DlSystem::IUserBuffer

Public Member Functions
virtual const TensorShape &	getStrides () const =0

virtual size_t	getSize () const =0

virtual size_t	getOutputSize () const =0

virtual bool	setBufferAddress (void *buffer) noexcept=0

virtual const UserBufferEncoding &	getEncoding () const noexcept=0

virtual UserBufferEncoding &	getEncoding () noexcept=0

Member Function Documentation

◆ getEncoding() [1/2]

virtual const UserBufferEncoding& getEncoding ( ) const

pure virtualnoexcept

Gets a const reference to the data encoding object of the underlying buffer.

This is necessary when the UserBuffer is filled by SNPE with data types such as TF8, where the caller needs to know the quantization parameters in order to interpret the data properly

Returns: A read-only encoding object

◆ getEncoding() [2/2]

virtual UserBufferEncoding& getEncoding ( )

pure virtualnoexcept

Gets a reference to the data encoding object of the underlying buffer.

This is necessary when the UserBuffer is re-used, and the encoding parameters can change. For example, each input can be quantized with different step sizes.

Returns: Data encoding meta-data

◆ getOutputSize()

virtual size_t getOutputSize ( ) const

pure virtual

Retrieves the size of the inference data in the buffer, in bytes.

The inference results from a dynamic-sized model may not be exactly the same size as the UserBuffer provided to SNPE. This function can be used to get the amount of output inference data, which may be less or greater than the size of the UserBuffer.

If the inference results fit in the UserBuffer, getOutputSize() would be less than or equal to getSize(). But if the inference results were more than the capacity of the provided UserBuffer, the results would be truncated to fit the UserBuffer. But, getOutputSize() would be greater than getSize(), which indicates a bigger buffer needs to be provided to SNPE to hold all of the inference results.

Returns: Size required for the buffer to hold all inference results, which can be less or more than the size of the buffer, in bytes.

◆ getSize()

virtual size_t getSize ( ) const

pure virtual

Retrieves the size of the buffer, in bytes.

Returns: Size of the underlying buffer, in bytes.

◆ getStrides()

virtual const TensorShape& getStrides ( ) const

pure virtual

Retrieves the total number of bytes between elements in each dimension if the buffer were to be interpreted as a multi-dimensional array.

Returns: Number of bytes between elements in each dimension. e.g. A tightly packed tensor of floats with dimensions [4, 3, 2] would return strides of [24, 8, 4].

◆ setBufferAddress()

virtual bool setBufferAddress ( void * buffer )

pure virtualnoexcept

Changes the underlying memory that backs the UserBuffer.

This can be used to avoid creating multiple UserBuffer objects when the only thing that differs is the memory location.

Parameters

[in] buffer Pointer to the memory location

Returns: Whether the set succeeds.

◆ zdl::DlSystem::IUserBufferFactory

class zdl::DlSystem::IUserBufferFactory

Factory interface class to create IUserBuffer objects.

Public Member Functions
virtual std::unique_ptr< IUserBuffer >	createUserBuffer (void buffer, size_t bufSize, const zdl::DlSystem::TensorShape &strides, zdl::DlSystem::UserBufferEncoding userBufferEncoding) noexcept=0

virtual std::unique_ptr< IUserBuffer >	createUserBuffer (void buffer, size_t bufSize, const zdl::DlSystem::TensorShape &strides, zdl::DlSystem::UserBufferEncoding userBufferEncoding, zdl::DlSystem::UserBufferSource *userBufferSource) noexcept=0

Member Function Documentation

◆ createUserBuffer() [1/2]

virtual std::unique_ptr<IUserBuffer> createUserBuffer	(	void *	buffer,
		size_t	bufSize,
		const zdl::DlSystem::TensorShape &	strides,
		zdl::DlSystem::UserBufferEncoding *	userBufferEncoding
	)

pure virtualnoexcept

Creates a UserBuffer.

Parameters

[in]	buffer	Pointer to the buffer that the caller supplies
[in]	bufSize	Buffer size, in bytes
[in]	strides	Total number of bytes between elements in each dimension. E.g. A tightly packed tensor of floats with dimensions [4, 3, 2] would have strides of [24, 8, 4].
[in]	userBufferEncoding	Reference to an UserBufferEncoding object

Note: Caller has to ensure that memory pointed to by buffer stays accessible for the lifetime of the object created

◆ createUserBuffer() [2/2]

virtual std::unique_ptr<IUserBuffer> createUserBuffer	(	void *	buffer,
		size_t	bufSize,
		const zdl::DlSystem::TensorShape &	strides,
		zdl::DlSystem::UserBufferEncoding *	userBufferEncoding,
		zdl::DlSystem::UserBufferSource *	userBufferSource
	)

pure virtualnoexcept

Creates a UserBuffer.

Parameters

[in]	buffer	Pointer to the buffer that the caller supplies
[in]	bufSize	Buffer size, in bytes
[in]	strides	Total number of bytes between elements in each dimension. E.g. A tightly packed tensor of floats with dimensions [4, 3, 2] would have strides of [24, 8, 4].
[in]	userBufferEncoding	Reference to an UserBufferEncoding object
[in]	userBufferSource	Reference to an UserBufferSource object

Note: Caller has to ensure that memory pointed to by buffer stays accessible for the lifetime of the object created

◆ zdl::DiagLog::Options

class zdl::DiagLog::Options

Options for setting up diagnostic logging for zdl components.

Public Attributes
std::string	DiagLogMask

std::string	LogFileDirectory

std::string	LogFileName

uint32_t	LogFileRotateCount

Member Data Documentation

◆ DiagLogMask

std::string DiagLogMask

Enables diag logging only on the specified area mask (DNN_RUNTIME=ON | OFF)

◆ LogFileDirectory

std::string LogFileDirectory

The path to the directory where log files will be written. The path may be relative or absolute. Relative paths are interpreted from the current working directory. Default value is "diaglogs"

◆ LogFileName

std::string LogFileName

The name used for log files. If this value is empty then BaseName will be used as the default file name. Default value is "DiagLog"

◆ LogFileRotateCount

uint32_t LogFileRotateCount

The maximum number of log files to create. If set to 0 no log rotation will be used and the log file name specified will be used each time, overwriting any existing log file that may exist. Default value is 20

◆ zdl::DlSystem::UserGLConfig

struct zdl::DlSystem::UserGLConfig

A structure OpenGL configuration

Note: When certain OpenGL context and display are provided to UserGLConfig for using GPU buffer as input directly, the user MUST ensure the particular OpenGL context and display remain vaild throughout the execution of neural network models.

Class Members
void *	userGLContext	Holds user EGL context.
void *	userGLDisplay	Holds user EGL display.

◆ zdl::DlSystem::UserGpuConfig

struct zdl::DlSystem::UserGpuConfig

A structure Gpu configuration

Class Members
UserGLConfig	userGLConfig	Holds user OpenGL configuration.

◆ zdl::DlSystem::PlatformConfig

class zdl::DlSystem::PlatformConfig

A class user platform configuration

Public Types
enum	PlatformType_t

Public Member Functions
PlatformType_t	getPlatformType () const

bool	isValid () const

bool	getUserGpuConfig (UserGpuConfig &userGpuConfig) const

bool	setUserGpuConfig (UserGpuConfig &userGpuConfig)

bool	setPlatformOptions (std::string options)

bool	isOptionsValid () const

std::string	getPlatformOptions () const

bool	setPlatformOptionValue (const std::string &optionName, const std::string &value)

bool	removePlatformOptionValue (const std::string &optionName, const std::string &value)

Member Enumeration Documentation

◆ PlatformType_t

enum PlatformType_t

strong

An enum class of all supported platform types

Enumerator
UNKNOWN	Unknown platform type.
CPU	Snapdragon CPU.
GPU	Adreno GPU.
DSP	Hexagon DSP.

Member Function Documentation

◆ getPlatformOptions()

std::string getPlatformOptions ( ) const

inline

Gets the platform options.

Returns: Options as a string

◆ getPlatformType()

PlatformType_t getPlatformType ( ) const

inline

Retrieves the platform type.

Returns: Platform type

◆ getUserGpuConfig()

bool getUserGpuConfig ( UserGpuConfig & userGpuConfig ) const

inline

Retrieves the Gpu configuration.

Parameters

[out] userGpuConfig The passed in userGpuConfig populated with the Gpu configuration on return.

Returns: True if Gpu configuration was retrieved; false otherwise.

◆ isOptionsValid()

bool isOptionsValid ( ) const

Indicates whther the plaform configuration is valid.

Returns: True if the platform configuration is valid; false otherwise.

◆ isValid()

bool isValid ( ) const

inline

Indicates whther the plaform configuration is valid.

Returns: True if the platform configuration is valid; false otherwise.

◆ removePlatformOptionValue()

bool removePlatformOptionValue	(	const std::string &	optionName,
		const std::string &	value
	)

Removes the platform options.

Parameters

[in]	optionName	Name of platform options"
[in]	value	Value of specified optionName

Returns: If true, removed "optionName:value" to platform options if optionName don't exist, do nothing. If false, the platform options will not be changed.

◆ setPlatformOptions()

bool setPlatformOptions ( std::string options )

inline

Sets the platform options.

Parameters

[in] options Options as a string in the form of "keyword:options"

Returns: True if options are pass validation; otherwise false. If false, the options are not updated.

◆ setPlatformOptionValue()

bool setPlatformOptionValue	(	const std::string &	optionName,
		const std::string &	value
	)

Sets the platform options.

Parameters

[in]	optionName	Name of platform options"
[in]	value	Value of specified optionName

Returns: If true, add "optionName:value" to platform options if optionName don't exist, otherwise update the value of specified optionName. If false, the platform options will not be changed.

◆ setUserGpuConfig()

bool setUserGpuConfig ( UserGpuConfig & userGpuConfig )

inline

Sets the Gpu configuration.

Parameters

[in] userGpuConfig Gpu Configuration

Returns: True if Gpu configuration was successfully set; false otherwise.

◆ zdl

class zdl

The class for checking SNPE compatibility/capability of a device.

Public Member Functions
	PlatformValidator ()

void	setRuntime (zdl::DlSystem::Runtime_t runtime)

bool	isRuntimeAvailable ()

std::string	getCoreVersion ()

std::string	getLibVersion ()

bool	runtimeCheck ()

Member Function Documentation

◆ getCoreVersion()

std::string getCoreVersion ( )

Returns the core version for the Runtime selected.

Returns: String which contains the actual core version value

◆ getLibVersion()

std::string getLibVersion ( )

Returns the library version for the Runtime selected.

Returns: String which contains the actual lib version value

◆ isRuntimeAvailable()

bool isRuntimeAvailable ( )

Checks if the Runtime prerequisites for SNPE are available.

Returns: True if the Runtime prerequisites are available, else false.

◆ PlatformValidator()

PlatformValidator ( )

Default Constructor of the PlatformValidator Class.

Returns: A new instance of a PlatformValidator object that can be used to check the SNPE compatibility of a device

◆ runtimeCheck()

bool runtimeCheck ( )

Runs a small program on the runtime and Checks if SNPE is supported for Runtime.

Returns: If True, the device is ready for SNPE execution, else not.

◆ setRuntime()

void setRuntime ( zdl::DlSystem::Runtime_t runtime )

Sets the runtime processor for compatibility check.

Returns: Void

◆ zdl::DlSystem::RuntimeList

class zdl::DlSystem::RuntimeList

A class representing list of runtimes

Public Member Functions
	RuntimeList ()

	RuntimeList (const RuntimeList &other)

	RuntimeList (const zdl::DlSystem::Runtime_t &runtime)

RuntimeList &	operator= (const RuntimeList &other)

Runtime_t &	operator[] (size_t index)

bool	add (const zdl::DlSystem::Runtime_t &runtime)

void	remove (const zdl::DlSystem::Runtime_t runtime) noexcept

void	clear () noexcept

zdl::DlSystem::StringList	getRuntimeListNames () const

Static Public Member Functions
static zdl::DlSystem::Runtime_t	stringToRuntime (const char *runtimeStr)

static const char *	runtimeToString (const zdl::DlSystem::Runtime_t runtime)

◆ zdl::SNPE::SNPE

class zdl::SNPE::SNPE

The SNPE interface class definition

Public Member Functions
zdl::DlSystem::Optional< zdl::DlSystem::StringList >	getInputTensorNames () const noexcept

zdl::DlSystem::Optional< zdl::DlSystem::StringList >	getOutputTensorNames () const noexcept

zdl::DlSystem::StringList	getOutputTensorNamesByLayerName (const char *name) const noexcept

bool	execute (const zdl::DlSystem::TensorMap &input, zdl::DlSystem::TensorMap &output) noexcept

bool	execute (const zdl::DlSystem::ITensor *input, zdl::DlSystem::TensorMap &output) noexcept

bool	execute (const zdl::DlSystem::UserBufferMap &input, const zdl::DlSystem::UserBufferMap &output) noexcept

bool	registerIonBuffers (const zdl::DlSystem::UserMemoryMap &ionBufferMap) noexcept

bool	deregisterIonBuffers (const zdl::DlSystem::StringList &ionBufferNames) noexcept

zdl::DlSystem::String	getModelVersion () const noexcept

zdl::DlSystem::Optional< zdl::DlSystem::TensorShape >	getInputDimensions () const noexcept

zdl::DlSystem::Optional< zdl::DlSystem::StringList >	getOutputLayerNames () const noexcept

zdl::DlSystem::Optional< zdl::DlSystem::IBufferAttributes * >	getInputOutputBufferAttributes (const char *name) const noexcept

zdl::DlSystem::Optional< zdl::DiagLog::IDiagLog * >	getDiagLogInterface () noexcept

Member Function Documentation

◆ deregisterIonBuffers()

bool deregisterIonBuffers ( const zdl::DlSystem::StringList & ionBufferNames )

noexcept

Deregister Client ION Buffers.

Parameters

[in] A StringList of ION Buffer names

◆ execute() [1/3]

bool execute	(	const zdl::DlSystem::TensorMap &	input,
		zdl::DlSystem::TensorMap &	output
	)

noexcept

Processes the input data and returns the output.

Parameters

[in]	A	map of tensors that contains the input data for each input. The names of tensors needs to be matched with names retrieved through getInputTensorNames()
[in,out]	An	empty map of tensors that will contain the output data of potentially multiple layers (the key in the map is the layer name) upon return

Note: output tensormap has to be empty. To forward propagate and get results in user-supplied tensors, use executeWithSuppliedOutputTensors.

◆ execute() [2/3]

bool execute	(	const zdl::DlSystem::ITensor *	input,
		zdl::DlSystem::TensorMap &	output
	)

noexcept

Processes the input data and returns the output.

Parameters

[in]	A	single tensor contains the input data.
[in,out]	An	empty map of tensors that will contain the output data of potentially multiple layers (the key in the map is the layer name) upon return

Note: output tensormap has to be empty.

◆ execute() [3/3]

bool execute	(	const zdl::DlSystem::UserBufferMap &	input,
		const zdl::DlSystem::UserBufferMap &	output
	)

noexcept

Processes the input data and returns the output, using user-supplied buffers.

Parameters

[in]	A	map of UserBuffers that contains the input data for each input. The names of UserBuffers needs to be matched with names retrieved through getInputTensorNames()
[in,out]	A	map of UserBuffers that will hold the output data of potentially multiple layers (the key in the map is the UserBuffer name)

Note: input and output UserBuffer maps must be fully pre-populated. with dimensions matching what the network expects. For example, if there are 5 output UserBuffers they all have to be present in map.

Caller must guarantee that for the duration of execute(), the buffer stored in UserBuffer would remain valid. For more detail on buffer ownership and lifetime requirements, please refer to zdl::DlSystem::UserBuffer documentation.

◆ getDiagLogInterface()

zdl::DlSystem::Optional<zdl::DiagLog::IDiagLog*> getDiagLogInterface ( )

noexcept

Get the diagnostic logging interface

Note: Note that because the returned type is an Optional instance, it must be verified as a boolean true value before being dereferenced.

See also: zdl::DlSystem::Optional

◆ getInputDimensions()

zdl::DlSystem::Optional<zdl::DlSystem::TensorShape> getInputDimensions ( ) const

noexcept

Returns the dimensions of the input data to the model in the form of TensorShape. The dimensions in TensorShape corresponds to what the tensor dimensions would need to be for an input tensor to the model.

Parameters

[in] layer input name.

Note: Note that this function only makes sense for networks that have a fixed input size. For networks in which the input size varies with each call of Execute(), this function should not be used.; Because the returned type is an Optional instance, it must be verified as a boolean true value before being dereferenced.

Returns: An Optional instance of TensorShape that maintains dimensions, matching the tensor dimensions for input to the model, where the last entry is the fastest varying dimension, etc.

See also: zdl::DlSystem::ITensor; zdl::DlSystem::TensorShape; zdl::DlSystem::Optional

◆ getInputOutputBufferAttributes()

zdl::DlSystem::Optional<zdl::DlSystem::IBufferAttributes*> getInputOutputBufferAttributes ( const char * name ) const

noexcept

Returns attributes of buffers used to feed input tensors and receive result from output tensors.

Parameters

[in] Tensor name.

Returns: BufferAttributes of input/output tensor named

◆ getInputTensorNames()

zdl::DlSystem::Optional<zdl::DlSystem::StringList> getInputTensorNames ( ) const

noexcept

Gets the names of input tensors to the network.

To support multiple input scenarios, where multiple tensors are passed through execute() in a TensorMap, each tensor needs to be uniquely named. The names of tensors can be retrieved through this function.

In the case of a single input, one name will be returned.

Note: Note that because the returned value is an Optional list, the list must be verified as boolean true value before being dereferenced.

Returns: An Optional List of input tensor names.

See also: zdl::DlSystem::Optional

◆ getModelVersion()

zdl::DlSystem::String getModelVersion ( ) const

noexcept

Returns the version string embedded at model conversion time.

Returns: Model version string, which is a free-form string supplied at the time of the conversion

◆ getOutputLayerNames()

zdl::DlSystem::Optional<zdl::DlSystem::StringList> getOutputLayerNames ( ) const

noexcept

Gets the output layer(s) for the network.

Note that the output layers returned by this function may be different than those specified when the network was created via the zdl::SNPE::SNPEBuilder. For example, if the network was created in debug mode with no explicit output layers specified, this will contain all layers.

Note: Note that because the returned value is an Optional StringList, the list must be verified as a boolean true value before being dereferenced.

Returns: A List of output layer names.

See also: zdl::DlSystem::Optional

◆ getOutputTensorNames()

zdl::DlSystem::Optional<zdl::DlSystem::StringList> getOutputTensorNames ( ) const

noexcept

Gets the names of output tensors to the network.

Returns: List of output tensor names.

◆ getOutputTensorNamesByLayerName()

zdl::DlSystem::StringList getOutputTensorNamesByLayerName ( const char * name ) const

noexcept

Gets the name of output tensor from the input layer name.

Returns: Output tensor name.

◆ registerIonBuffers()

bool registerIonBuffers ( const zdl::DlSystem::UserMemoryMap & ionBufferMap )

noexcept

Register Client ION Buffers.

Parameters

[in] A UserMemoryMap of virtual addresses

◆ zdl::SNPE::SNPEBuilder

class zdl::SNPE::SNPEBuilder

The builder class for creating SNPE objects. Not meant to be extended.

Public Member Functions
	SNPEBuilder (zdl::DlContainer::IDlContainer *container)

SNPEBuilder &	setRuntimeProcessor (zdl::DlSystem::Runtime_t targetRuntimeProcessor)

SNPEBuilder &	setPerformanceProfile (zdl::DlSystem::PerformanceProfile_t performanceProfile)

SNPEBuilder &	setProfilingLevel (zdl::DlSystem::ProfilingLevel_t profilingLevel)

SNPEBuilder &	setExecutionPriorityHint (zdl::DlSystem::ExecutionPriorityHint_t priority)

SNPEBuilder &	setOutputLayers (const zdl::DlSystem::StringList &outputLayerNames)

SNPEBuilder &	setOutputTensors (const zdl::DlSystem::StringList &outputTensorNames)

SNPEBuilder &	setUdlBundle (zdl::DlSystem::UDLBundle udlBundle)

SNPEBuilder &	setUseUserSuppliedBuffers (bool bufferMode)

SNPEBuilder &	setDebugMode (bool debugMode)

SNPEBuilder &	setCPUFallbackMode (bool mode)

SNPEBuilder &	setInputDimensions (const zdl::DlSystem::TensorShapeMap &inputDimensionsMap)

SNPEBuilder &	setInitCacheMode (bool cacheMode)

std::unique_ptr< SNPE >	build () noexcept

SNPEBuilder &	setPlatformConfig (const zdl::DlSystem::PlatformConfig &platformConfig)

SNPEBuilder &	setRuntimeProcessorOrder (const zdl::DlSystem::RuntimeList &runtimeList)

SNPEBuilder &	setUnconsumedTensorsAsOutputs (bool setOutput)

SNPEBuilder &	setTimeOut (uint64_t timeout)

SNPEBuilder &	setBufferDataType (const zdl::DlSystem::IOBufferDataTypeMap &dataTypeMap)

SNPEBuilder &	setSingleThreadedInit (bool singleThreadedInit)

Constructor & Destructor Documentation

◆ SNPEBuilder()

SNPEBuilder ( zdl::DlContainer::IDlContainer * container )

explicit

Constructor of NeuralNetwork Builder with a supplied model.

Parameters

[in] container A container holding the model.

Returns: A new instance of a SNPEBuilder object that can be used to configure and build an instance of SNPE.

Member Function Documentation

◆ build()

std::unique_ptr<SNPE> build ( )

noexcept

Returns an instance of SNPE based on the current parameters.

Returns: A new instance of a SNPE object that can be used to execute models or null if any errors occur.

◆ setBufferDataType()

SNPEBuilder& setBufferDataType ( const zdl::DlSystem::IOBufferDataTypeMap & dataTypeMap )

Sets the datatype of the buffer. Only valid for dsp runtime currently.

Parameters

[in] Map of the buffer names and the datatype that needs to be set.

Returns: The current instance of SNPEBuilder.

◆ setCPUFallbackMode()

SNPEBuilder& setCPUFallbackMode ( bool mode )

Sets the mode of CPU fallback functionality.

NOTE: DEPRECATED, MAY BE REMOVED IN THE FUTURE. Please use setRuntimeProcessorOrder()

Parameters

[in] mode This flag enables/disables the functionality of CPU fallback. When the CPU fallback functionality is enabled, layers in model that violates runtime constraints will run on CPU while the rest of non-violating layers will run on the chosen runtime processor. In disabled mode, models with layers violating runtime constraints will NOT run on the chosen runtime processor and will result in runtime exception. By default, the functionality is enabled.

Returns: The current instance of SNPEBuilder.

◆ setDebugMode()

SNPEBuilder& setDebugMode ( bool debugMode )

Sets the debug mode of the runtime.

Parameters

[in] debugMode This enables debug mode for the runtime. It does two things. For an empty outputLayerNames list, all layers will be output. It might also disable some internal runtime optimizations (e.g., some networks might be optimized by combining layers, etc.).

Returns: The current instance of SNPEBuilder.

◆ setExecutionPriorityHint()

SNPEBuilder& setExecutionPriorityHint ( zdl::DlSystem::ExecutionPriorityHint_t priority )

Sets a preference for execution priority.

This allows the caller to give coarse hint to SNPE runtime about the priority of the network. SNPE runtime is free to use this information to co-ordinate between different workloads that may or may not extend beyond SNPE.

Parameters

[in] ExecutionPriorityHint_t The target performance profile.

Returns: The current instance of SNPEBuilder.

◆ setInitCacheMode()

SNPEBuilder& setInitCacheMode ( bool cacheMode )

Sets the mode of init caching functionality.

Parameters

[in] mode This flag enables/disables the functionality of init caching. When init caching functionality is enabled, a set of init caches will be created during network building/initialization process and will be added to DLC container. If such DLC container is saved by the user, in subsequent network building/initialization processes these init caches will be loaded from the DLC so as to reduce initialization time. In disable mode, no init caches will be added to DLC container.

Returns: The current instance of SNPEBuilder.

◆ setInputDimensions()

SNPEBuilder& setInputDimensions ( const zdl::DlSystem::TensorShapeMap & inputDimensionsMap )

Sets network's input dimensions to enable resizing of the spatial dimensions of each layer for fully convolutional networks, and the batch dimension for all networks.

Parameters

[in] tensorShapeMap The map of input names and their new dimensions. The new dimensions overwrite the input dimensions embedded in the model and then resize each layer of the model. If the model contains layers whose dimensions cannot be resized e.g FullyConnected, exception will be thrown when SNPE instance is actually built. In general the batch dimension is always resizable. After resizing of layers' dimensions in model based on new input dimensions, the new model is revalidated against all runtime constraints, whose failures may result in cpu fallback situation.

Returns: The current instance of SNPEBuilder.

◆ setOutputLayers()

SNPEBuilder& setOutputLayers ( const zdl::DlSystem::StringList & outputLayerNames )

Sets the layers that will generate output.

Parameters

[in] outputLayerNames List of layer names to output. An empty list will result in only the final layer of the model being the output layer. The list will be copied.

Returns: The current instance of SNPEBuilder.

◆ setOutputTensors()

SNPEBuilder& setOutputTensors ( const zdl::DlSystem::StringList & outputTensorNames )

Sets the output tensor names.

Parameters

[in] outputTensorNames List of tensor names to output. An empty list will result in producing output for the final output tensor of the model. The list will be copied.

Returns: The current instance of SNPEBuilder.

◆ setPerformanceProfile()

SNPEBuilder& setPerformanceProfile ( zdl::DlSystem::PerformanceProfile_t performanceProfile )

Requests a performance profile.

Parameters

[in] targetRuntimeProfile The target performance profile.

Returns: The current instance of SNPEBuilder.

◆ setPlatformConfig()

SNPEBuilder& setPlatformConfig ( const zdl::DlSystem::PlatformConfig & platformConfig )

Sets the platform configuration.

Parameters

[in] platformConfig The platform configuration.

Returns: The current instance of SNPEBuilder.

◆ setProfilingLevel()

SNPEBuilder& setProfilingLevel ( zdl::DlSystem::ProfilingLevel_t profilingLevel )

Sets the profiling level. Default profiling level for SNPEBuilder is off. Off and basic only applies to DSP runtime.

Parameters

[in] profilingLevel The target profiling level.

Returns: The current instance of SNPEBuilder.

◆ setRuntimeProcessor()

SNPEBuilder& setRuntimeProcessor ( zdl::DlSystem::Runtime_t targetRuntimeProcessor )

Sets the runtime processor.

NOTE: DEPRECATED, MAY BE REMOVED IN THE FUTURE. Please use setRuntimeProcessorOrder()

Parameters

[in] targetRuntimeProcessor The target runtime.

Returns: The current instance of SNPEBuilder.

◆ setRuntimeProcessorOrder()

SNPEBuilder& setRuntimeProcessorOrder ( const zdl::DlSystem::RuntimeList & runtimeList )

Sets network's runtime order of precedence. Example: CPU_FLOAT32, GPU_FLOAT16, AIP_FIXED8_TF Note:- setRuntimeProcessor() or setCPUFallbackMode() will be silently ignored when setRuntimeProcessorOrder() is invoked.

Parameters

[in] runtimeList The list of runtime in order of precedence

Returns: The current instance of SNPEBuilder.

◆ setSingleThreadedInit()

SNPEBuilder& setSingleThreadedInit ( bool singleThreadedInit )

Sets up the entire initialization callflow to happen on the user's thread.

Returns: The current instance of SNPEBuilder.

◆ setTimeOut()

SNPEBuilder& setTimeOut ( uint64_t timeout )

Execution terminated when exceeding time limit. Only valid for dsp runtime currently.

Parameters

[in] timeout Time limit value

Returns: The current instance of SNPEBuilder.

◆ setUdlBundle()

SNPEBuilder& setUdlBundle ( zdl::DlSystem::UDLBundle udlBundle )

Passes in a User-defined layer.

Parameters

udlBundle Bundle of udl factory function and a cookie

Returns: The current instance of SNPEBuilder.

◆ setUnconsumedTensorsAsOutputs()

SNPEBuilder& setUnconsumedTensorsAsOutputs ( bool setOutput )

Sets the unconsumed tensors as output.

Parameters

[in] setOutput This enables unconsumed tensors (i.e) outputs which are not inputs to any layer (basically dead ends) to be marked for output

Returns: The current instance of SNPEBuilder.

◆ setUseUserSuppliedBuffers()

SNPEBuilder& setUseUserSuppliedBuffers ( bool bufferMode )

Sets whether this neural network will perform inference with input from user-supplied buffers, and write output to user-supplied buffers. Default behaviour is to use tensors created by ITensorFactory.

Parameters

[in] bufferMode Whether to use user-supplied buffer or not.

Returns: The current instance of SNPEBuilder.

◆ zdl::SNPE::SNPEFactory

class zdl::SNPE::SNPEFactory

The factory class for creating SNPE objects.

Static Public Member Functions
static bool	isRuntimeAvailable (zdl::DlSystem::Runtime_t runtime)

static bool	isRuntimeAvailable (zdl::DlSystem::Runtime_t runtime, zdl::DlSystem::RuntimeCheckOption_t option)

static zdl::DlSystem::ITensorFactory &	getTensorFactory ()

static zdl::DlSystem::IUserBufferFactory &	getUserBufferFactory ()

static zdl::DlSystem::Version_t	getLibraryVersion ()

static bool	setSNPEStorageLocation (const char *storagePath)

static bool	addOpPackage (const std::string &regLibraryPath)

static bool	isGLCLInteropSupported ()

static bool	initializeLogging (const zdl::DlSystem::LogLevel_t &level)

static bool	initializeLogging (const zdl::DlSystem::LogLevel_t &level, const std::string &logPath)

static bool	setLogLevel (const zdl::DlSystem::LogLevel_t &level)

static bool	terminateLogging (void)

Member Function Documentation

◆ addOpPackage()

static bool addOpPackage ( const std::string & regLibraryPath )

static

Register a user-defined op package with SNPE.

Parameters

[in] regLibraryPath Path to the registration library that allows clients to register a set of operations that are part of the package, and share op info with SNPE

Returns: True if successful, False otherwise.

◆ getLibraryVersion()

static zdl::DlSystem::Version_t getLibraryVersion ( )

static

Gets the version of the SNPE library.

Returns: Version of the SNPE library.

◆ getTensorFactory()

static zdl::DlSystem::ITensorFactory& getTensorFactory ( )

static

Gets a reference to the tensor factory.

Returns: A reference to the tensor factory.

◆ getUserBufferFactory()

static zdl::DlSystem::IUserBufferFactory& getUserBufferFactory ( )

static

Gets a reference to the UserBuffer factory.

Returns: A reference to the UserBuffer factory.

◆ initializeLogging() [1/2]

static bool initializeLogging ( const zdl::DlSystem::LogLevel_t & level )

static

Initializes logging with the specified log level. initializeLogging with level, is used on Android platforms and after successful initialization, SNPE logs are printed in android logcat logs.

It is recommended to initializeLogging before creating any SNPE instances, in order to capture information related to core initialization. If this is called again after first time initialization, subsequent calls are ignored. Also, Logging can be re-initialized after a call to terminateLogging API by calling initializeLogging again.

A typical usage of Logging life cycle can be initializeLogging() any other SNPE API like isRuntimeAvailable()

setLogLevel() - optional - can be called anytime between initializeLogging & terminateLogging SNPE instance creation, inference, destroy terminateLogging().

Please note, enabling logging can have performance impact.

Parameters

[in] LogLevel_t Log level (LOG_INFO, LOG_WARN, etc.).

Returns: True if successful, False otherwise.

◆ initializeLogging() [2/2]

static bool initializeLogging	(	const zdl::DlSystem::LogLevel_t &	level,
		const std::string &	logPath
	)

static

Initializes logging with the specified log level and log path. initializeLogging with level & log path, is used on non Android platforms and after successful initialization, SNPE logs are printed in std output & into log files created in the log path.

It is recommended to initializeLogging before creating any SNPE instances, in order to capture information related to core initialization. If this is called again after first time initialization, subsequent calls are ignored. Also, Logging can be re-initialized after a call to terminateLogging API by calling initializeLogging again.

A typical usage of Logging life cycle can be initializeLogging() any other SNPE API like isRuntimeAvailable()

setLogLevel() - optional - can be called anytime between initializeLogging & terminateLogging SNPE instance creation, inference, destroy terminateLogging()

Please note, enabling logging can have performance impact

Parameters

[in]	LogLevel_t	Log level (LOG_INFO, LOG_WARN, etc.).
[in]	Path	of directory to store logs. If path is empty, the default path is "./Log". For android, the log path is ignored.

Returns: True if successful, False otherwise.

◆ isGLCLInteropSupported()

static bool isGLCLInteropSupported ( )

static

Indicates whether the OpenGL and OpenCL interoperability is supported on GPU platform.

Returns: True if the OpenGL and OpenCl interop is supported; false, otherwise.

◆ isRuntimeAvailable() [1/2]

static bool isRuntimeAvailable ( zdl::DlSystem::Runtime_t runtime )

static

Indicates whether the supplied runtime is available on the current platform.

Parameters

[in] runtime The target runtime to check.

Returns: True if the supplied runtime is available; false, otherwise.

◆ isRuntimeAvailable() [2/2]

static bool isRuntimeAvailable	(	zdl::DlSystem::Runtime_t	runtime,
		zdl::DlSystem::RuntimeCheckOption_t	option
	)

static

Indicates whether the supplied runtime is available on the current platform.

Parameters

[in]	runtime	The target runtime to check.
[in]	option	Extent to perform runtime available check.

Returns: True if the supplied runtime is available; false, otherwise.

◆ setLogLevel()

static bool setLogLevel ( const zdl::DlSystem::LogLevel_t & level )

static

Updates the current logging level with the specified level. setLogLevel is optional, called anytime after initializeLogging and before terminateLogging, to update the log level set. Log levels can be updated multiple times by calling setLogLevel A call to setLogLevel() is ignored if it is made before initializeLogging() or after terminateLogging()

Parameters

[in] LogLevel_t Log level (LOG_INFO, LOG_WARN, etc.).

Returns: True if successful, False otherwise.

◆ setSNPEStorageLocation()

static bool setSNPEStorageLocation ( const char * storagePath )

static

Set the SNPE storage location for all SNPE instances in this process. Note that this may only be called once, and if so must be called before creating any SNPE instances.

Parameters

[in] storagePath Absolute path to a directory which SNPE may use for caching and other storage purposes.

Returns: True if the supplied path was succesfully set as the SNPE storage location, false otherwise.

◆ terminateLogging()

static bool terminateLogging ( void )

static

Terminates logging.

It is recommended to terminateLogging after initializeLogging in order to disable logging information. If this is called before initialization or after first time termination, calls are ignored.

Returns: True if successful, False otherwise.

◆ zdl::DlSystem::StringList

class zdl::DlSystem::StringList

Class for holding an order list of null-terminated ASCII strings.

Public Member Functions
	StringList (size_t length)

void	append (const char *str)

const char *	at (size_t idx) const noexcept

const char **	begin () const noexcept

const char **	end () const noexcept

size_t	size () const noexcept

StringList &	operator= (const StringList &) noexcept

	StringList (const StringList &other)

	StringList (StringList &&other) noexcept

◆ zdl::DlSystem::TensorMap

class zdl::DlSystem::TensorMap

A class representing the map of tensor.

Public Member Functions
	TensorMap ()

	TensorMap (const TensorMap &other)

TensorMap &	operator= (const TensorMap &other)

void	add (const char name, zdl::DlSystem::ITensor tensor)

void	remove (const char *name) noexcept

void	clear () noexcept

zdl::DlSystem::ITensor *	getTensor (const char *name) const noexcept

zdl::DlSystem::StringList	getTensorNames () const

◆ zdl::DlSystem::TensorShape

class zdl::DlSystem::TensorShape

A class representing the shape of tensor. It is used at the time of creation of tensor.

Public Member Functions
	TensorShape (std::initializer_list< Dimension > dims)

	TensorShape (const Dimension *dims, size_t size)

	TensorShape (std::vector< Dimension > dims)

	TensorShape (const TensorShape &other)

TensorShape &	operator= (const TensorShape &other)

	TensorShape ()

void	concatenate (std::initializer_list< Dimension > dims)

void	concatenate (const Dimension *dims, size_t size)

void	concatenate (const Dimension &dim)

Dimension &	operator[] (size_t index)

size_t	rank () const

const Dimension *	getDimensions () const

◆ zdl::DlSystem::TensorShapeMap

class zdl::DlSystem::TensorShapeMap

A class representing the map of names and tensorshapes.

Public Member Functions
	TensorShapeMap ()

	TensorShapeMap (const TensorShapeMap &other)

TensorShapeMap &	operator= (const TensorShapeMap &other)

void	add (const char *name, const zdl::DlSystem::TensorShape &tensorShape)

void	remove (const char *name) noexcept

void	clear () noexcept

zdl::DlSystem::TensorShape	getTensorShape (const char *name) const noexcept

zdl::DlSystem::StringList	getTensorShapeNames () const

◆ SnpeUdo_Version_t

struct SnpeUdo_Version_t

◆ SnpeUdo_LibVersion_t

struct SnpeUdo_LibVersion_t

◆ Udo_PkgVersion_t

struct Udo_PkgVersion_t

◆ SnpeUdo_Value_t

union SnpeUdo_Value_t

◆ SnpeUdo_ScalarParam_t

struct SnpeUdo_ScalarParam_t

◆ SnpeUdo_TFQuantize_t

struct SnpeUdo_TFQuantize_t

◆ SnpeUdo_QuantizeParams_t

struct SnpeUdo_QuantizeParams_t

◆ SnpeUdo_PerCoreDatatype_t

struct SnpeUdo_PerCoreDatatype_t

◆ SnpeUdo_TensorParam_t

struct SnpeUdo_TensorParam_t

Class Members
uint32_t *	currDimensions	The current dimensions of the tensor. An operation may modify the current dimensions of its output, to indicate cases where the output has been "resized". Note that for static parameters, the current and max dimensions must match.
SnpeUdo_DataType_t	dataType	The parameter data type: float, int, etc.
SnpeUdo_TensorLayout_t	layout	The tensor layout type: NCHW, NHWC, etc.
uint32_t *	maxDimensions	The maximum allowable dimensions of the tensor. The memory held in tensorData is guaranteed to be large enough for this.
SnpeUdo_QuantizeParams_t	quantizeParams	Quantization params applicable to the tensor. Currently only supports Tensorflow quantization style.
void *	tensorData	Opaque pointer to tensor data. User may be required to re-interpret the pointer based on core-specific definitions.
uint32_t	tensorRank	Number of dimensions to the tensor: 3D, 4D, etc.

◆ SnpeUdo_TensorInfo_t

struct SnpeUdo_TensorInfo_t

It describes an activation tensor object using its name, the intended layout and the datatype it will take depending on the intended runtime core. The repeated field indicates that that the tensor info describes several input/output activation tensors, which all share the aforementioned properties.

◆ SnpeUdo_Param_t

struct SnpeUdo_Param_t

◆ SnpeUdo_OpCoreInfo_t

struct SnpeUdo_OpCoreInfo_t

Class Members
SnpeUdo_Bitmask_t	operationCalculationTypes	Bitmask, defines supported internal calculation types (like FLOAT_32, etc) Based on SnpeUdo_DataType
SnpeUdo_CoreType_t	udoCoreType	The IP Core.

◆ SnpeUdo_OperationInfo_t

struct SnpeUdo_OperationInfo_t

Class Members
SnpeUdo_TensorInfo_t *	inputInfos	Array of input tensor infos for this operation.
SnpeUdo_String_t *	inputNames	Array of input tensor names to this operation.
uint32_t	numOfCoreInfo	Number of cores that the op can execute on.
uint32_t	numOfInputs	Number of input tensors this op receives.
uint32_t	numOfOutputs	Number of output tensors this op receives.
uint32_t	numOfStaticParams	Number of static parameters defined by the op.
SnpeUdo_String_t	operationType	Operation type.
SnpeUdo_OpCoreInfo_t *	opPerCoreInfo	Array of per-core information entries.
SnpeUdo_TensorInfo_t *	outputInfos	Array of output tensor infos for this operation.
SnpeUdo_String_t *	outputNames	Array of output tensor names to this operation.
SnpeUdo_Param_t *	staticParams	Array of static parameters. Can be scalar or tensor params.
SnpeUdo_Bitmask_t	supportedByCores	A bitmask describing which IP Cores (CPU, GPU, DSP ...) support this operation Translated based on SnpeUdo_CoreType

◆ SnpeUdo_LibraryInfo_t

struct SnpeUdo_LibraryInfo_t

◆ SnpeUdo_RegInfo_t

struct SnpeUdo_RegInfo_t

Class Members
SnpeUdo_LibraryInfo_t *	implementationLib	Array of implementation libraries names/types.
uint32_t	numOfImplementationLib	The number of implementation libraries in the package.
uint32_t	numOfOperations	Number of supported operations.
SnpeUdo_OperationInfo_t *	operationsInfo	Array of Operation info structs. Each entry describes one Operation (name, params, inputs, outputs)
SnpeUdo_String_t	operationsString	A string containing all operation types separated by space.
SnpeUdo_String_t	packageName	A string containing the package name.
SnpeUdo_Bitmask_t	supportedCoreTypes	A bitmask describing supported IP cores (CPU, GPU, DSP ...) Translated based on SnpeUdo_CoreType

◆ SnpeUdo_ImpInfo_t

struct SnpeUdo_ImpInfo_t

◆ SnpeUdo_OpDefinition_t

struct SnpeUdo_OpDefinition_t

Class Members
SnpeUdo_TensorParam_t *	inputs	Array of input tensors, providing layout, data type, sizes, etc When used to create an operation, also contains the initial location of the data
uint32_t	numOfInputs	The number of input parameters provided in inputs array. this number has to match the number provided by the UDO Registration library information
uint32_t	numOfOutputs	The number of output parameters provided in inputs array. this number has to match the number provided by the UDO Registration library information
uint32_t	numOfStaticParams	The number of static parameters provided in the staticParams array. this number has to match the number provided by the UDO Registration library information
SnpeUdo_String_t	operationType	Operation type.
SnpeUdo_TensorParam_t *	outputs	Array of output tensors, providing layout, data type, sizes, etc When used to create an operation, also contains the initial location of the data
SnpeUdo_Param_t *	staticParams	Array of static parameters.
SnpeUdo_CoreType_t	udoCoreType	The IP Core that the operation is defined for - CPU, GPU, DSP...

◆ SnpeUdo_CpuInfrastructure_t

struct SnpeUdo_CpuInfrastructure_t

The framework/runtime which loads the CPU UDO implementation library provides this infrastructure data to the loaded library at the time of op factory creation. as an opaque pointer. It contains hooks for the UDO library to invoke supported functionality at the time of execution

Parameters

getData	function pointer to retrieve raw tensor data from opaque pointer passed into the UDO when creating an instance.
getDataSize	function pointer to retrieve tensor data size from opaque pointer

Public Attributes
float (	getData )(void *)

Member Data Documentation

◆ getData

float*(* getData) (void *)

function pointer to retrieve raw tensor data from opaque pointer passed into the UDO when creating an instance.

◆ dspGlobalInfrastructure

struct dspGlobalInfrastructure

The framework/runtime which loads the Hexnn UDO implementation library provides this infrastructure to the loaded library by calling "SnpeUdo_initImplLibrary" function, and passing it (cast to void*). The Hexnn UDO library is expected to cast it back to this structure.

◆ hexnnv2OpFactoryInfra

struct hexnnv2OpFactoryInfra

hexnn v2 per op factory infrastructure

The framework/runtime passes per op factory infrastructure as a void pointer to HexNN UDO implementation library by calling function "SnpeUdo_createOpFactory". UDO implementation library is expected to cast it back to this following struct.

◆ SnpeUdo_GpuInfrastructure_t

struct SnpeUdo_GpuInfrastructure_t

◆ SnpeUdo_GpuOpFactoryInfrastructure_t

struct SnpeUdo_GpuOpFactoryInfrastructure_t

Note: This version of the infrastructure definition guarantees that the same Per OpFactory infrastructure pointer will be provided to all OpFactories in the same network.

◆ SnpeUdo_GpuTensorData_t

struct SnpeUdo_GpuTensorData_t

The following is a list of all SnpeUdoTensorLayout_t values supported by the GPU UDO implementation, and how the parameters of the struct should be interpreted in each case:

SNPE_UDO_LAYOUT_NHWC: mem shall be single-element array, pointing to a cl buffer memory object. the dimensions of this object match the dimensions specified in the encompassing SnpeUdoTensorParam_t's currDimensions.

memCount shall be 1.

paddedRank and paddedDimensions are undefined and shall be ignored by the UDO implementation.

◆ zdl::DlSystem::UserBufferMap

class zdl::DlSystem::UserBufferMap

A class representing the map of UserBuffer.

Public Member Functions
	UserBufferMap ()

	UserBufferMap (const UserBufferMap &other)

UserBufferMap &	operator= (const UserBufferMap &other)

void	add (const char name, zdl::DlSystem::IUserBuffer buffer)

void	remove (const char *name) noexcept

void	clear () noexcept

zdl::DlSystem::IUserBuffer *	getUserBuffer (const char *name) const noexcept

zdl::DlSystem::StringList	getUserBufferNames () const

Constructor & Destructor Documentation

◆ UserBufferMap() [1/2]

UserBufferMap ( )

Creates a new empty UserBuffer map

◆ UserBufferMap() [2/2]

UserBufferMap ( const UserBufferMap & other )

copy constructor.

Parameters

[in] other object to copy.

Member Function Documentation

◆ add()

void add	(	const char *	name,
		zdl::DlSystem::IUserBuffer *	buffer
	)

Adds a name and the corresponding UserBuffer pointer to the map.

Parameters

[in]	name	The name of the UserBuffer
[in]	userBuffer	The pointer to the UserBuffer

Note: If a UserBuffer with the same name already exists, the new UserBuffer pointer would be updated.

◆ clear()

void clear ( )

noexcept

Removes all UserBuffers from the map

◆ getUserBuffer()

zdl::DlSystem::IUserBuffer* getUserBuffer ( const char * name ) const

noexcept

Returns the UserBuffer given its name.

Parameters

[in] name The name of the UserBuffer to get.

Returns: nullptr if no UserBuffer with the specified name is found; otherwise, a valid pointer to the UserBuffer.

◆ getUserBufferNames()

zdl::DlSystem::StringList getUserBufferNames ( ) const

Returns the names of all UserBuffers

Returns: A list of UserBuffer names.

◆ operator=()

UserBufferMap& operator= ( const UserBufferMap & other )

assignment operator.

◆ remove()

void remove ( const char * name )

noexcept

Removes a mapping of one UserBuffer and its name by its name.

Parameters

[in] name The name of UserBuffer to be removed

Note: If no UserBuffer with the specified name is found, nothing is done.

◆ zdl::DlSystem::UserMemoryMap

class zdl::DlSystem::UserMemoryMap

A class representing the map of UserMemory.

Public Member Functions
	UserMemoryMap ()

	UserMemoryMap (const UserMemoryMap &other)

UserMemoryMap &	operator= (const UserMemoryMap &other)

void	add (const char name, void address)

void	remove (const char *name) noexcept

void	clear () noexcept

zdl::DlSystem::StringList	getUserBufferNames () const

size_t	getUserMemoryAddressCount (const char *name) const noexcept

void *	getUserMemoryAddressAtIndex (const char *name, uint32_t index) const noexcept

Constructor & Destructor Documentation

◆ UserMemoryMap() [1/2]

UserMemoryMap ( )

Creates a new empty UserMemory map

◆ UserMemoryMap() [2/2]

UserMemoryMap ( const UserMemoryMap & other )

copy constructor.

Parameters

[in] other object to copy.

Member Function Documentation

◆ add()

void add	(	const char *	name,
		void *	address
	)

Adds a name and the corresponding buffer address to the map.

Parameters

[in]	name	The name of the UserMemory
[in]	address	The pointer to the Buffer Memory

Note: If a UserBuffer with the same name already exists, the new address would be updated.

◆ clear()

void clear ( )

noexcept

Removes all User Memory from the map

◆ getUserBufferNames()

zdl::DlSystem::StringList getUserBufferNames ( ) const

Returns the names of all User Memory

Returns: A list of Buffer names.

◆ getUserMemoryAddressAtIndex()

void* getUserMemoryAddressAtIndex	(	const char *	name,
		uint32_t	index
	)		const

noexcept

Returns address at a specified index corresponding to a UserMemory buffer name.

Parameters

[in]	name	The name of the buffer
[in]	index	The index in the list of addresses

◆ getUserMemoryAddressCount()

size_t getUserMemoryAddressCount ( const char * name ) const

noexcept

Returns the no of UserMemory addresses mapped to the buffer.

Parameters

[in] name The name of the UserMemory

◆ operator=()

UserMemoryMap& operator= ( const UserMemoryMap & other )

assignment operator.

◆ remove()

void remove ( const char * name )

noexcept

Removes a mapping of one Buffer address and its name by its name.

Parameters

[in] name The name of Memory address to be removed

Note: If no UserBuffer with the specified name is found, nothing is done.

Typedef Documentation

◆ Dimension

using Dimension = size_t

Convenient typedef to represent dimension

◆ SnpeUdo_DspGlobalInfrastructure_t

typedef struct dspGlobalInfrastructure SnpeUdo_DspGlobalInfrastructure_t

Infrastructures needed by a developer of DSP Hexnn UDO Implementation library.

The framework/runtime which loads the Hexnn UDO implementation library provides this infrastructure to the loaded library by calling "SnpeUdo_initImplLibrary" function, and passing it (cast to void*). The Hexnn UDO library is expected to cast it back to this structure.

◆ SnpeUdo_ExternalNotify_t

typedef SnpeUdo_ErrorType_t(* SnpeUdo_ExternalNotify_t) (const uint32_t ID)

A pointer to notification function.

The notification function supports the non-blocking (e.g. asynchronous) execution use-case. In case an "executeUdoOp" function is called with "blocking" set to zero, and a notify function, this function will be called by the implementation library at the end of execution. The implementation library will pass the notify function the ID that was provided to it when "executeUdoOp" was called.

Parameters

[in] ID 32-bit value, that was provided to executeUdoOp by the calling entity. Can be used to track the notifications, in case of multiple execute calls issued.

Returns: Error code

◆ SnpeUdo_getProgram_t

typedef SnpeUdo_ErrorType_t(* SnpeUdo_getProgram_t) (void *programCache, const char *programName, cl_program *program)

Function to retrieve opencl program from Program Cache repository.

This header defines version 0.0.0 of the GPU UDO Infrastructure. It defines the interpretation of the global and per-OpFactory infrastructure pointers as well as the interpretation of tensorData pointers.

The per-Operation infrastructure pointer is defined to be null, and should not be used.

The SnpeUdoTensorParam_t struct below provides the interpretation for the tensorData opaque pointer for SnpeUdoTensorParams representing inputs or outputs.

The tensorData opaque pointer populated in SnpeUdoScalarParam_t structs should be interpreted as a host-readable data pointer.

Parameters

programCache	is opaque pointer to Program Cache repository provided by SNPE GPU UDO runtime.
programName	is name associated with opencl program for UDO.
program	is pointer to opencl program which will be populated with valid opencl program if found in Program Cache repository.

Returns: SnpeUdo_ErrorType_t is error type returned. SNPE_UDO_NO_ERROR is returned on success.

◆ SnpeUdo_HexNNv2OpFactoryInfra_t

typedef struct hexnnv2OpFactoryInfra SnpeUdo_HexNNv2OpFactoryInfra_t

hexnn v2 per op factory infrastructure

The framework/runtime passes per op factory infrastructure as a void pointer to HexNN UDO implementation library by calling function "SnpeUdo_createOpFactory". UDO implementation library is expected to cast it back to this following struct.

◆ SnpeUdo_HexNNv2OpInfra_t

typedef void* SnpeUdo_HexNNv2OpInfra_t

hexnn v2 per operation infrastructure

The framework/runtime passes per operation infrastructure as a void pointer to HexNN UDO implementation library by calling function "SnpeUdo_createOperation". UDO implementation library is expected to cast it to the following type and save it.

This is needed to be passed back into some functions from global infrastructure.

◆ SnpeUdo_storeProgram_t

typedef SnpeUdo_ErrorType_t(* SnpeUdo_storeProgram_t) (void *programCache, const char *programName, cl_program program)

Function to store valid opencl program in Program Cache repository.

Parameters

programCache	is opaque pointer to Program Cache repository provided by SNPE GPU UDO runtime.
programName	is name associated with opencl program for UDO.
program	is valid opencl program after program is built.

Returns: SnpeUdo_ErrorType_t is error type returned. SNPE_UDO_NO_ERROR is returned on success.

Enumeration Type Documentation

◆ ExecutionPriorityHint_t

enum ExecutionPriorityHint_t

strong

Enumeration of various execution priority hints.

Enumerator
NORMAL	Normal priority.
HIGH	Higher than normal priority.
LOW	Lower priority.
NORMAL_HIGH	Between Normal and High priority.

◆ PerformanceProfile_t

enum PerformanceProfile_t

strong

Enumeration of various performance profiles that can be requested.

Enumerator
DEFAULT	Run in a standard mode. This mode will be deprecated in the future and replaced with BALANCED.
BALANCED	Run in a balanced mode.
HIGH_PERFORMANCE	Run in high performance mode.
POWER_SAVER	Run in a power sensitive mode, at the expense of performance.
SYSTEM_SETTINGS	Use system settings. SNPE makes no calls to any performance related APIs.
SUSTAINED_HIGH_PERFORMANCE	Run in sustained high performance mode.
BURST	Run in burst mode.
LOW_POWER_SAVER	Run in lower clock than POWER_SAVER, at the expense of performance.
HIGH_POWER_SAVER	Run in higher clock and provides better performance than POWER_SAVER.
LOW_BALANCED	Run in lower balanced mode.

◆ ProfilingLevel_t

enum ProfilingLevel_t

strong

Enumeration of various profilngLevels that can be requested.

Enumerator
OFF	No profiling. Collects no runtime stats in the DiagLog
BASIC	Basic profiling Collects some runtime stats in the DiagLog
DETAILED	Detailed profiling Collects more runtime stats in the DiagLog, including per-layer statistics Performance may be impacted
MODERATE	Moderate profiling Collects more runtime stats in the DiagLog, no per-layer statistics

◆ Runtime_t

enum Runtime_t

strong

Enumeration of supported target runtimes.

Enumerator
CPU_FLOAT32	Run the processing on Snapdragon CPU. Data: float 32bit Math: float 32bit
GPU_FLOAT32_16_HYBRID	Run the processing on the Adreno GPU. Data: float 16bit Math: float 32bit
DSP_FIXED8_TF	Run the processing on the Hexagon DSP. Data: 8bit fixed point Tensorflow style format Math: 8bit fixed point Tensorflow style format
GPU_FLOAT16	Run the processing on the Adreno GPU. Data: float 16bit Math: float 16bit
AIP_FIXED8_TF	Run the processing on Snapdragon AIX+HVX. Data: 8bit fixed point Tensorflow style format Math: 8bit fixed point Tensorflow style format
CPU	Default legacy enum to retain backward compatibility. CPU = CPU_FLOAT32
GPU	Default legacy enum to retain backward compatibility. GPU = GPU_FLOAT32_16_HYBRID
DSP	Default legacy enum to retain backward compatibility. DSP = DSP_FIXED8_TF
UNSET	Special value indicating the property is unset.

◆ RuntimeCheckOption_t

enum RuntimeCheckOption_t

strong

Enumeration of runtime available check options.

Enumerator
DEFAULT	Perform standard runtime available check.
NORMAL_CHECK	Perform standard runtime available check.
BASIC_CHECK	Perform basic runtime available check, may be runtime specific.
UNSIGNEDPD_CHECK	Perform unsignedPD runtime available check.

◆ SnpeUdo_CoreType_t

enum SnpeUdo_CoreType_t

An enum which holds the UDO library Core type . Designed to be used as single values or combined into a bitfield parameter (0x1, 0x2, 0x4, etc)

Enumerator
SNPE_UDO_CORETYPE_UNDEFINED	Library target IP Core is undefined.
SNPE_UDO_CORETYPE_CPU	Library target IP Core is CPU.
SNPE_UDO_CORETYPE_GPU	Library target IP Core is GPU.
SNPE_UDO_CORETYPE_DSP	Library target IP Core is DSP.

◆ SnpeUdo_DataType_t

enum SnpeUdo_DataType_t

An enum which holds the various data types. Designed to be used as single values or combined into a bitfield parameter (0x1, 0x2, 0x4, etc)
FIXED_XX types are targeted for data in tensors.
UINT / INT types are targeted for scalar params

Enumerator
SNPE_UDO_DATATYPE_FLOAT_16	data type: 16-bit floating point
SNPE_UDO_DATATYPE_FLOAT_32	data type: 32-bit floating point
SNPE_UDO_DATATYPE_FIXED_4	data type: 4-bit fixed point
SNPE_UDO_DATATYPE_FIXED_8	data type: 8-bit fixed point
SNPE_UDO_DATATYPE_FIXED_16	data type: 16-bit fixed point
SNPE_UDO_DATATYPE_FIXED_32	data type: 32-bit fixed point
SNPE_UDO_DATATYPE_UINT_8	data type: 8-bit unsigned integer
SNPE_UDO_DATATYPE_UINT_16	data type: 16-bit unsigned integer
SNPE_UDO_DATATYPE_UINT_32	data type: 32-bit unsigned integer
SNPE_UDO_DATATYPE_INT_8	data type: 8-bit signed integer
SNPE_UDO_DATATYPE_INT_16	data type: 16-bit signed integer
SNPE_UDO_DATATYPE_INT_32	data type: 32-bit signed integer

◆ SnpeUdo_ErrorType_t

enum SnpeUdo_ErrorType_t

An enum which holds the various error types. The error types are divided to classes : 0 - 99 : generic errors 100 - 200 : errors related to configuration

Enumerator
SNPE_UDO_NO_ERROR	No Error.
SNPE_UDO_WRONG_CORE	Unsupported value for core type.
SNPE_UDO_INVALID_ARGUMENT	Invalid attribute/argument passed into UDO API.
SNPE_UDO_UNSUPPORTED_FEATURE	Unsupported feature error.
SNPE_UDO_MEM_ALLOC_ERROR	Error relating to memory allocation.
SNPE_UDO_WRONG_OPERATION	No op with given attributes available in library.
SNPE_UDO_WRONG_CORE_TYPE	Unsupported value for core type in UDO configuration.
SNPE_UDO_WRONG_NUM_OF_PARAMS	Wrong number of params in UDO definition.
SNPE_UDO_WRONG_NUM_OF_DIMENSIONS	Wrong number of dimensions for tensor(s) in UDO definition.
SNPE_UDO_WRONG_NUM_OF_INPUTS	Wrong number of input tensors in UDO definition.
SNPE_UDO_WRONG_NUM_OF_OUTPUTS	Wrong number of output tensors in UDO definition.

◆ SnpeUdo_ParamType_t

enum SnpeUdo_ParamType_t

An enum to specify the parameter type : Scalar or Tensor

Enumerator
SNPE_UDO_PARAMTYPE_SCALAR	UDO static param type: scalar.
SNPE_UDO_PARAMTYPE_STRING	UDO static param type: string.
SNPE_UDO_PARAMTYPE_TENSOR	UDO static param type: tensor.

◆ SnpeUdo_QuantizationType_t

enum SnpeUdo_QuantizationType_t

An enum to specify quantization type

Enumerator
SNPE_UDO_QUANTIZATION_NONE	Tensor Quantization type: NONE. Signifies unquantized tensor data.
SNPE_UDO_QUANTIZATION_TF	Tensor Quantization type: Tensorflow-style.

◆ SnpeUdo_TensorLayout_t

enum SnpeUdo_TensorLayout_t

An enum which holds the various layouts. Designed to be used as single values or combined into a bitfield parameter (0x1, 0x2, 0x4, etc)

Enumerator
SNPE_UDO_LAYOUT_NHWC	data layout (4D): NHWC (batch-height-width-channel)
SNPE_UDO_LAYOUT_NCHW	data layout (4D): NCHW (batch-channel-height-width)
SNPE_UDO_LAYOUT_NDHWC	data layout (5D): NDHWC (batch-depth-height-width-channel)

Function Documentation

◆ add() [1/4]

void add	(	const char *	name,
		zdl::DlSystem::IOBufferDataType_t	bufferDataType
	)

Adds a name and the corresponding buffer data type to the map.

Parameters

[name]	name The name of the buffer
[bufferDataType]	buffer Data Type of the buffer

Note: If a buffer with the same name already exists, no new buffer is added.

◆ add() [2/4]

void add	(	const char *	name,
		zdl::DlSystem::ITensor *	tensor
	)

Adds a name and the corresponding tensor pointer to the map.

Parameters

[in]	name	The name of the tensor
[out]	tensor	The pointer to the tensor

Note: If a tensor with the same name already exists, the tensor is replaced with the existing tensor.

◆ add() [3/4]

void add	(	const char *	name,
		const zdl::DlSystem::TensorShape &	tensorShape
	)

Adds a name and the corresponding tensor pointer to the map.

Parameters

[in]	name	The name of the tensor
[out]	tensor	The pointer to the tensor

Note: If a tensor with the same name already exists, no new tensor is added.

◆ add() [4/4]

bool add ( const zdl::DlSystem::Runtime_t & runtime )

Adds runtime to the end of the runtime list order of precedence is former followed by latter entry.

Parameters

[in] runtime to add

Ruturns false If the runtime already exists

◆ append()

void append ( const char * str )

Append a string to the list.

Parameters

[in] str Null-terminated ASCII string to append to the list.

◆ asString()

const zdl::DlSystem::String asString ( ) const

Returns a string in the form Major.Minor.Teeny.Build.

Returns: A formatted string holding the version information.

◆ at()

const char* at ( size_t idx ) const

noexcept

Returns the string at the indicated position, or an empty string if the positions is greater than the size of the list.

Parameters

[in] idx Position in the list of the desired string

◆ begin() [1/2]

const char** begin ( ) const

noexcept

Pointer to the first string in the list. Can be used to iterate through the list.

◆ begin() [2/2]

virtual iterator begin ( )

pure virtual

Returns a tensor iterator pointing to the beginning of the data in the tensor.

Returns: A tensor iterator that points to the first data element in the tensor.

◆ cbegin()

virtual const_iterator cbegin ( ) const

pure virtual

Returns the const version of a tensor iterator pointing to the beginning of the data in the tensor.

Returns: A tensor const iterator that points to the first data element in the tensor.

◆ cend()

virtual const_iterator cend ( ) const

pure virtual

Returns the const version of a tensor iterator pointing to the end of the data in the tensor. This tensor should not be dereferenced.

Returns: A tensor const iterator that points to the end of the data (one past the last element) in the tensor.

◆ clear() [1/3]

void clear ( )

noexcept

Removes all tensors from the map

◆ clear() [2/3]

void clear ( )

noexcept

Removes all tensors from the map

◆ clear() [3/3]

void clear ( )

noexcept

Removes all runtime from the list

◆ concatenate() [1/3]

void concatenate ( std::initializer_list< Dimension > dims )

Concatenates additional dimensions specified in initializer list fashion to the existing dimensions.

Parameters

[in] dims The dimensions are specified in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.

◆ concatenate() [2/3]

void concatenate	(	const Dimension *	dims,
		size_t	size
	)

Concatenates additional dimensions specified in the array to the existing dimensions.

Parameters

[in]	dims	The dimensions are specified in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.
[in]	size	Size of the array.

◆ concatenate() [3/3]

void concatenate ( const Dimension & dim )

Concatenates an additional dimension to the existing dimensions.

Parameters

[in] dim The dimensions are specified in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.

◆ createTensor() [1/3]

virtual std::unique_ptr<ITensor> createTensor ( const TensorShape & shape )

pure virtualnoexcept

Creates a new ITensor with uninitialized data.

The strides for the tensor will match the tensor dimensions (i.e., the tensor data is contiguous in memory).

Parameters

[in] shape The dimensions for the tensor in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.

Returns: A pointer to the created tensor or nullptr if creating failed.

◆ createTensor() [2/3]

virtual std::unique_ptr<ITensor> createTensor ( std::istream & input )

pure virtualnoexcept

Creates a new ITensor by loading it from a file.

Parameters

[in] input The input stream from which to read the tensor data.

Returns: A pointer to the created tensor or nullptr if creating failed.

◆ createTensor() [3/3]

virtual std::unique_ptr<ITensor> createTensor	(	const TensorShape &	shape,
		const unsigned char *	data,
		size_t	dataSize
	)

pure virtualnoexcept

Create a new ITensor with specific data. (i.e. the tensor data is contiguous in memory). This tensor is primarily used to create a tensor where tensor size can't be computed directly from dimension. One such example is NV21-formatted image, or any YUV formatted image

Parameters

[in]	shape	The dimensions for the tensor in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.
[in]	data	The actual data with which the Tensor object is filled.
[in]	dataSize	The size of data

Returns: A pointer to the created tensor

◆ empty()

bool empty ( )

Checks whether the map is empty.

Returns: True if the map is empty, false otherwise.

◆ end() [1/2]

const char** end ( ) const

noexcept

Pointer to one after the last string in the list. Can be used to iterate through the list.

◆ end() [2/2]

virtual iterator end ( )

pure virtual

Returns a tensor iterator pointing to the end of the data in the tensor. This tensor should not be dereferenced.

Returns: A tensor iterator that points to the end of the data (one past the last element) in the tensor.

◆ enumToUInt32()

ZDL_EXPORT uint32_t zdl::DlSystem::enumToUInt32 ( zdl::DlSystem::ErrorCode code )

Returns the uint32_t representation of the error code enum.

Parameters

[in] code The error code to be converted.

Returns: uint32_t representation of the error code.

◆ find()

bool find ( const char * name )

Checks the existence of the named buffer in the map.

Returns: True if the named buffer exists, false otherwise.

◆ getBufferDataType() [1/2]

zdl::DlSystem::IOBufferDataType_t getBufferDataType ( const char * name )

Returns the type of the named buffer.

Parameters

[name] name The name of the buffer

Returns: The type of the buffer, or UNSPECIFIED if the buffer does not exist

◆ getBufferDataType() [2/2]

zdl::DlSystem::IOBufferDataType_t getBufferDataType ( )

Returns the type of the first buffer.

Returns: The type of the first buffer, or UNSPECIFIED if the map is empty.

◆ getDimensions()

const Dimension* getDimensions ( ) const

Retrieves a pointer to the first dimension of shape

Returns: nullptr if no dimension exists; otherwise, points to the first dimension.

◆ getLastErrorCode()

ZDL_EXPORT ErrorCode zdl::DlSystem::getLastErrorCode ( )

Returns the error code of the last error encountered.

Returns: The error code.

Note: The returned error code is significant only when the return value of the call indicated an error.

◆ getLastErrorString()

ZDL_EXPORT const char* zdl::DlSystem::getLastErrorString ( )

Returns the error string of the last error encountered.

Returns: The error string.

Note: The returned error string is significant only when the return value of the call indicated an error.

◆ getLastInfoString()

ZDL_EXPORT const char* zdl::DlSystem::getLastInfoString ( )

Returns the info string of the last error encountered.

◆ getOptions()

virtual Options getOptions ( )

pure virtual

Gets the curent options for the diag logger.

Returns: Diag log options object.

◆ getRuntimeListNames()

zdl::DlSystem::StringList getRuntimeListNames ( ) const

Returns a StringList of names from the runtime list in order of precedence

◆ getShape()

virtual TensorShape getShape ( ) const

pure virtual

Gets the shape of this tensor.

The last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying dimension, etc.

Returns: A shape class holding the tensor dimensions.

◆ getSize()

virtual size_t getSize ( ) const

pure virtual

Returns the element size of the data in the tensor (discounting strides). This is how big a buffer would need to be to hold the tensor data contiguously in memory.

Returns: The size of the tensor (in elements).

◆ getTensor()

zdl::DlSystem::ITensor* getTensor ( const char * name ) const

noexcept

Returns the tensor given its name.

Parameters

[in] name The name of the tensor to get.

Returns: nullptr if no tensor with the specified name is found; otherwise, a valid pointer to the tensor.

◆ getTensorNames()

zdl::DlSystem::StringList getTensorNames ( ) const

Returns the names of all tensors

◆ getTensorShape()

zdl::DlSystem::TensorShape getTensorShape ( const char * name ) const

noexcept

Returns the tensor given its name.

Parameters

[in] name The name of the tensor to get.

Returns: nullptr if no tensor with the specified name is found; otherwise, a valid pointer to the tensor.

◆ getTensorShapeNames()

zdl::DlSystem::StringList getTensorShapeNames ( ) const

Returns the names of all tensor shapes

◆ IOBufferDataTypeMap()

IOBufferDataTypeMap ( )

Creates a new Buffer Data type map

◆ open() [1/4]

static std::unique_ptr<IDlContainer> open ( const std::string & filename )

staticnoexcept

Initializes a container from a container archive file.

Parameters

[in] filename Container archive file path.

Returns: A pointer to the initialized container

◆ open() [2/4]

static std::unique_ptr<IDlContainer> open ( const zdl::DlSystem::String & filename )

staticnoexcept

Initializes a container from a container archive file.

Parameters

[in] filename Container archive file path.

Returns: A pointer to the initialized container

◆ open() [3/4]

static std::unique_ptr<IDlContainer> open ( const std::vector< uint8_t > & buffer )

staticnoexcept

Initializes a container from a byte buffer.

Parameters

[in] buffer Byte buffer holding the contents of an archive file.

Returns: A pointer to the initialized container

◆ open() [4/4]

static std::unique_ptr<IDlContainer> open	(	const uint8_t *	buffer,
		const size_t	size
	)

staticnoexcept

Initializes a container from a byte buffer.

Parameters

[in]	buffer	Byte buffer holding the contents of an archive file.
[in]	size	Size of the byte buffer.

Returns: A pointer to the initialized container

◆ operator bool()

operator bool ( ) const

inlinenoexcept

Boolean value of Optional class is only true when there exists a value.

◆ operator*() [1/2]

const T& operator* ( )

inline

Get reference of Optional object

Warning: User must validate Optional has value before.

◆ operator*() [2/2]

const T& operator* ( ) const

inline

Get reference of Optional object

Warning: User must validate Optional has value before.

◆ operator=() [1/5]

TensorMap& operator= ( const TensorMap & other )

assignment operator.

◆ operator=() [2/5]

TensorShapeMap& operator= ( const TensorShapeMap & other )

assignment operator.

◆ operator=() [3/5]

RuntimeList& operator= ( const RuntimeList & other )

assignment operator.

◆ operator=() [4/5]

StringList& operator= ( const StringList & )

noexcept

assignment operator.

◆ operator=() [5/5]

TensorShape& operator= ( const TensorShape & other )

assignment operator.

◆ operator[]() [1/2]

Runtime_t& operator[] ( size_t index )

subscript operator.

◆ operator[]() [2/2]

Dimension& operator[] ( size_t index )

Retrieves a single dimension, based on its index.

Returns: The value of dimension

Exceptions

std::out_of_range if the index is >= the number of dimensions (or rank).

◆ Optional() [1/2]

Optional ( )

inline

The default constructor is set to not have any value, and is therefore evaluated as false.

◆ Optional() [2/2]

Optional	(	const T &	v,
		typename std::enable_if<!std::is_pointer< Q >::value >::type *	= `0`
	)

inline

Construct an Optional class using an object.

Parameters

[in]	Reference	to an object v
[out]	Optional	instance of object v

◆ rank()

size_t rank ( ) const

Retrieves the rank i.e. number of dimensions.

Returns: The rank

◆ remove() [1/4]

void remove ( const char * name )

Removes a buffer name from the map.

Parameters

[name] name The name of the buffer

◆ remove() [2/4]

void remove ( const char * name )

noexcept

Removes a mapping of tensor and its name by its name.

Parameters

[in] name The name of tensor to be removed

Note: If no tensor with the specified name is found, nothing is done.

◆ remove() [3/4]

void remove ( const char * name )

noexcept

Removes a mapping of tensor and its name by its name.

Parameters

[in] name The name of tensor to be removed

Note: If no tensor with the specified name is found, nothing is done.

◆ remove() [4/4]

void remove ( const zdl::DlSystem::Runtime_t runtime )

noexcept

Removes the runtime from the list.

Parameters

[in] runtime to be removed

Note: If the runtime is not found, nothing is done.

◆ RuntimeList() [1/3]

RuntimeList ( )

Creates a new runtime list

◆ RuntimeList() [2/3]

RuntimeList ( const RuntimeList & other )

copy constructor.

Parameters

[in] other object to copy.

◆ RuntimeList() [3/3]

RuntimeList ( const zdl::DlSystem::Runtime_t & runtime )

constructor with single Runtime_t object

Parameters

[in] Runtime_t object

◆ runtimeToString()

static const char* runtimeToString ( const zdl::DlSystem::Runtime_t runtime )

static

Parameters

[in] runtime Returns a string corresponding to the in param runtime enum

◆ serialize()

virtual void serialize ( std::ostream & output ) const

pure virtual

Serializes the tensor to an output stream.

Parameters

[in] output The output stream to which to write the tensor

Exceptions

std::runtime_error If the stream is ever in a bad state before the tensor is fully serialized.

◆ setDiagLogMask() [1/2]

virtual bool setDiagLogMask ( const std::string & mask )

pure virtual

Allows for setting the log mask once diag logging has started

Returns: True if the level was set successfully, false if a failure occurred.

◆ setDiagLogMask() [2/2]

virtual bool setDiagLogMask ( const zdl::DlSystem::String & mask )

pure virtual

Allows for setting the log mask once diag logging has started

Returns: True if the level was set successfully, false if a failure occurred.

◆ setOptions()

virtual bool setOptions ( const Options & loggingOptions )

pure virtual

Sets the options after initialization occurs.

Parameters

[in] loggingOptions The options to set up diagnostic logging.

Returns: False if the options could not be set. Ensure logging is not started.

◆ size() [1/2]

size_t size ( ) const

noexcept

Return the number of valid string pointers held by this list.

◆ size() [2/2]

size_t size ( )

Returns the size of the buffer type map.

Returns: The size of the map

◆ SnpeUdo_createOperation()

SnpeUdo_ErrorType_t SnpeUdo_createOperation	(	SnpeUdo_OpFactory_t	opFactory,
		void *	perOpInfrastructure,
		uint32_t	numOfInputs,
		SnpeUdo_TensorParam_t *	inputs,
		uint32_t	numOfOutputs,
		SnpeUdo_TensorParam_t *	outputs,
		SnpeUdo_Operation_t *	operation
	)

A function to create an operation from the factory. The function receives array of inputs and array of outputs, and creates an operation instance, returning the operation instance handler.

Parameters

[in]	opFactory	OpFactory instance containing the parameters for this operation.
[in]	perOpInfrastructure	Per-Op infrastructure for this operation. The definition and semantics of this object will be defined in the implementation header appropriate to this core type.
[in]	numOfInputs	The number of input tensors this operation will receive.
[in]	inputs	Array of input tensors, providing both the sizes and initial location of the data.
[in]	numOfOutputs	Number of output tensors this operation will produce.
[in]	outputs	Array of output tensors, providing both the sizes and initial location of the data.
[in,out]	operation	Handle for newly created operation instance.

Returns: Error Code

◆ SnpeUdo_createOpFactory()

SnpeUdo_ErrorType_t SnpeUdo_createOpFactory	(	SnpeUdo_CoreType_t	udoCoreType,
		void *	perFactoryInfrastructure,
		SnpeUdo_String_t	operationType,
		uint32_t	numOfStaticParams,
		SnpeUdo_Param_t *	staticParams,
		SnpeUdo_OpFactory_t *	opFactory
	)

A function to create an operation factory. The function receives the operation type, and an array of static parameters, and returns operation factory handler.

Parameters

[in]	udoCoreType	The Core type to create the operation on. An error will be returned if this does not match the core type of the library.
[in]	perFactoryInfrastructure	CreateOpFactory infrastructure appropriate to this core type. The definition and semantics of this object will be defined in the corresponding implementation header for the core type.
[in]	operationType	A string containing Operation type. for example "MY_CONV"
[in]	numOfStaticParams	The number of static parameters.
[in]	staticParams	Array of static parameters
[in,out]	opFactory	Handler to Operation Factory, to be used when creating operations

Returns: Error Code

◆ SnpeUdo_executeOp()

SnpeUdo_ErrorType_t SnpeUdo_executeOp	(	SnpeUdo_Operation_t	operation,
		bool	blocking,
		const uint32_t	ID,
		SnpeUdo_ExternalNotify_t	notifyFunc
	)

Operation execution function.

Calling this function will run the operation on set of inputs, generating a set of outputs. The call can be blocking (synchronous) or non-blocking (asynchronous). To support the non-blocking mode, the calling entity can pass an ID and a notification function. At the end of the execution this notification function would be called, passing it the ID. NOTE: Asynchronous execution mode not supported in this release.

Parameters

[in]	operation	handle to the operation on which execute is invoked
[in]	blocking	flag to indicate execution mode. If set, execution is blocking, e.g SnpeUdo_executeOp call does not return until execution is done. If not set, SnpeUdo_executeOp returns immediately, and the library will call the notification function (if set) when execution is done.
[in]	ID	32-bit number that can be used by the calling entity to track execution in case of non-blocking execution. For example, it can be a sequence number, increased by one on each call.
[in]	notifyFunc	Pointer to notification function. if the pointer is set, and execution is non-blocking, the library will call this function at end of execution, passing the number provided as ID

Returns: Error code

◆ SnpeUdo_getImpInfo()

SnpeUdo_ErrorType_t SnpeUdo_getImpInfo ( SnpeUdo_ImpInfo_t ** implementationInfo )

A function to query info on the UDO implementation library. The function populates a structure which contains information about operations that are part of this library.

Parameters

[in,out] implementationInfo A pointer to struct which contains information on the operations

Returns: error code

◆ SnpeUdo_getImplVersion()

SnpeUdo_ErrorType_t SnpeUdo_getImplVersion ( SnpeUdo_LibVersion_t ** version )

A function to query the API version of the UDO implementation library. The function populates a SnpeUdo_LibVersion_t struct, which contains a SnpeUdo_Version_t struct for API version and library version.

Parameters

[in,out] version A pointer to struct which contains major, minor, teeny information for library and api versions.

Returns: Error code

◆ SnpeUdo_getRegInfo()

SnpeUdo_ErrorType_t SnpeUdo_getRegInfo ( SnpeUdo_RegInfo_t ** registrationInfo )

A function to query the info on the UDO set. The function populates a structure which contains information about the package and operations contained in it.

Parameters

[in,out] registrationInfo A struct which contains information on the set of UDOs

Returns: Error code

◆ SnpeUdo_getRegLibraryVersion()

SnpeUdo_ErrorType_t SnpeUdo_getRegLibraryVersion ( SnpeUdo_LibVersion_t ** version )

A function to query the API version of the UDO registration library. The function populates a SnpeUdo_LibVersion_t struct, which contains a SnpeUdo_Version_t struct for API version and library version.

Parameters

[in,out] version A pointer to struct which contains major, minor, teeny information for library and api versions.

Returns: Error code

◆ SnpeUdo_getVersion()

SnpeUdo_ErrorType_t SnpeUdo_getVersion ( SnpeUdo_LibVersion_t ** version )

A function to return the various versions as they relate to the UDO The function returns a struct containing the the following: libVersion: the version of the implementation library compiled for the UDO. Set by user apiVersion: the version of the UDO API used in compiling the implementation library. Set by SNPE.

Parameters

[in,out] version A pointer to Version struct of type SnpeUdo_LibVersion_t

Returns: Error code

◆ SnpeUdo_initImplLibrary()

SnpeUdo_ErrorType_t SnpeUdo_initImplLibrary ( void * globalInfrastructure )

Initialize the shared library's data structures. Calling any other library function before this one will result in error.

Parameters

[in] globalInfrastructure Global core-specific infrastructure to be used by operations created in this library. The definition and semantics of this object will be defined in the corresponding implementation header for the core type.

Returns: Error code

◆ SnpeUdo_initRegLibrary()

SnpeUdo_ErrorType_t SnpeUdo_initRegLibrary ( void )

Initialize the shared library's data structures. Calling any other library function before this one will result in an error being returned.

Returns: Error code

◆ SnpeUdo_profileOp()

SnpeUdo_ErrorType_t SnpeUdo_profileOp	(	SnpeUdo_Operation_t	operation,
		uint32_t *	executionTime
	)

A function to return execution times.

This function can be called to query the operation execution times on the IP core on which the operation is run. The time is provided in micro-seconds

Parameters

[in]	operation	Handle to operation whose execution time is being profiled
[in,out]	executionTime	pointer to a uint32 value.This function writes the operation execution time in usec into this value.

Returns: Error code

◆ SnpeUdo_queryOperation()

SnpeUdo_ErrorType_t SnpeUdo_queryOperation	(	SnpeUdo_String_t	operationType,
		uint32_t	numOfStaticParams,
		const SnpeUdo_Param_t *	staticParams,
		uint32_t *	numOfInputs,
		SnpeUdo_QuantizationType_t **	inputsQuantTypes,
		SnpeUdo_HexNNTensorLayout_t **	inputsLayouts,
		uint32_t *	numOfOutputs,
		SnpeUdo_QuantizationType_t **	outputsQuantTypes,
		SnpeUdo_HexNNTensorLayout_t **	outputsLayouts
	)

A function to query numbers of inputs and outputs, quantization type of each input and each output as arrays, and data layout (plain vs d32) of each input and each output as arrays of an operation. inputsQuantTypes and inputsLayouts should point to arrays of size numOfInputs outputsQuantTypes and outputsLayouts should point to arrays of size numOfOutputs.

Note: inputsLayouts and inputsLayouts can point to NULL, in this case, it is assumed all inputs and/or outputs have plain data layouts, i.e. no D32

Parameters

[in]	operationType	Operation type
[in]	numOfStaticParams	Number of static params defined by the op
[in]	staticParams	Array of static params to the op
[in,out]	numOfInputs	Number of input tensors to the op
[in,out]	inputsQuantTypes	Array of Quantization info for each input tensor
[in,out]	inputsLayouts	Array of layout type for each input tensor
[in,out]	numOfOutputs	Number of output tensors to the op
[in,out]	outputsQuantTypes	Array of Quantization info for each output tensor
[in,out]	outputsLayouts	Array of layout type for each output tensor

Returns: error code, indicating status of query

◆ SnpeUdo_releaseOp()

SnpeUdo_ErrorType_t SnpeUdo_releaseOp ( SnpeUdo_Operation_t operation )

A function to release the operation instance
When it is called, the implementation library needs to release all resources allocated for this operation instance.
Note that all function pointers which are part of SnpeUdo_Operation become invalid once releaseUdoOp call returns.

Parameters

[in] operation Handle to operation to be released

Returns: Error code

◆ SnpeUdo_releaseOpFactory()

SnpeUdo_ErrorType_t SnpeUdo_releaseOpFactory ( SnpeUdo_OpFactory_t opFactory )

A function to release the resources allocated for an operation factory created by this library.

Parameters

[in] factory The operation factory to release. Upon success this handle will be invalidated.

Returns: Error Code

◆ SnpeUdo_setOpIO()

SnpeUdo_ErrorType_t SnpeUdo_setOpIO	(	SnpeUdo_Operation_t	operation,
		SnpeUdo_TensorParam_t *	inputs,
		SnpeUdo_TensorParam_t *	outputs
	)

A function to setting the inputs & outputs. part of SnpeUdo_Operation struct, returned from creation of a new operation instance. Not supported in this release.

This function allows the calling entity to change some of the inputs and outputs between calls to execute. Note that the change is limited to changing the pointer to the tensor data only. Any other change may be rejected by the implementation library, causing immediate invalidation of the operation instance

Parameters

[in]	operation	Operation on which IO tensors are set
[in]	inputs	array of tensor parameters. The calling entity may provide a subset of the operation inputs, providing only those that it wants to change.
[in]	outputs	array of tensor parameters. The calling entity may provide a subset of the operation outputs, providing only those that it wants to change.

Returns: Error code

◆ SnpeUdo_terminateImplLibrary()

SnpeUdo_ErrorType_t SnpeUdo_terminateImplLibrary ( void )

Release the shared library's data structures, and invalidate any handles returned by the library. The behavior of any outstanding asynchronous calls made to this library when this function is called are undefined. All library functions (except SnpeUdo_initImplLibrary) will return an error after this function has been successfully called.

It should be possible to call SnpeUdo_initImplLibrary after calling this function, and re-initialize the library.

Returns: Error code

◆ SnpeUdo_terminateRegLibrary()

SnpeUdo_ErrorType_t SnpeUdo_terminateRegLibrary ( void )

Release the shared library's data structures, and invalidate any handles returned by the library. The behavior of any outstanding asynchronous calls made to this library when this function is called are undefined. All library functions (except SnpeUdo_InitRegLibrary) will return an error after this function has been successfully called.

It should be possible to call SnpeUdo_InitRegLibrary after calling this function, and re-initialize the library.

Returns: Error code

◆ SnpeUdo_validateOperation() [1/2]

SnpeUdo_ErrorType_t SnpeUdo_validateOperation	(	SnpeUdo_String_t	operationType,
		uint32_t	numOfStaticParams,
		const SnpeUdo_Param_t *	staticParams
	)

A function to validate that a set of params is supported by an operation This function is HexNN specific, use case is when registration library is not in use. Optional function.

Parameters

[in]	operationType	Operation type
[in]	numOfStaticParams	Number of static params defined by the op
[in]	staticParams	Array of static params to the op

Returns: Error code, indicating if the operation can be created on this set of configuration or not.

◆ SnpeUdo_validateOperation() [2/2]

SnpeUdo_ErrorType_t SnpeUdo_validateOperation ( SnpeUdo_OpDefinition_t * opDefinition )

A function to validate that a set of params is supported by an operation The function receives an operation definition struct, and returns if this configuration is supported (e.g. if an operation can be created using this configuration)

Parameters

[in] opDefinition A struct of SnpeUdo_OpDefinition type, containing the information needed to validate that an operation can be created with this configuration.

Returns: Error code, indicating is the operation can be created on this set or not.

◆ start()

virtual bool start ( void )

pure virtual

Enables logging for zdl components.

Logging should be started prior to the instantiation of zdl components to ensure all events are captured.

Returns: False if diagnostic logging could not be started.

◆ StringList() [1/3]

StringList ( size_t length )

explicit

Construct a string list with some pre-allocated memory.

Warning: Contents of the list will be uninitialized

Parameters

[in] length Number of elements for which to pre-allocate space.

◆ StringList() [2/3]

StringList ( const StringList & other )

copy constructor.

Parameters

[in] other object to copy.

◆ StringList() [3/3]

StringList ( StringList && other )

noexcept

move constructor.

Parameters

[in] other object to move.

◆ stringToRuntime()

static zdl::DlSystem::Runtime_t stringToRuntime ( const char * runtimeStr )

static

Parameters

[in] runtime string Returns a Runtime enum corresponding to the in param string

◆ TensorMap() [1/2]

TensorMap ( )

Creates a new empty tensor map

◆ TensorMap() [2/2]

TensorMap ( const TensorMap & other )

copy constructor.

Parameters

[in] other object to copy.

◆ TensorShape() [1/5]

TensorShape ( std::initializer_list< Dimension > dims )

Creates a new shape with a list of dims specified in initializer list fashion.

Parameters

[in] dims The dimensions are specified in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.

◆ TensorShape() [2/5]

TensorShape	(	const Dimension *	dims,
		size_t	size
	)

Creates a new shape with a list of dims specified in array

Parameters

[in]	dims	The dimensions are specified in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.
[in]	size	Size of the array.

◆ TensorShape() [3/5]

TensorShape ( std::vector< Dimension > dims )

Creates a new shape with a vector of dims specified in vector fashion.

Parameters

[in] dims The dimensions are specified in which the last element of the vector represents the fastest varying dimension and the zeroth element represents the slowest varying, etc.

◆ TensorShape() [4/5]

TensorShape ( const TensorShape & other )

copy constructor.

Parameters

[in] other object to copy.

◆ TensorShape() [5/5]

TensorShape ( )

Creates a new shape with no dims. It can be extended later by invoking concatenate.

◆ TensorShapeMap() [1/2]

TensorShapeMap ( )

Creates a new tensor shape map

◆ TensorShapeMap() [2/2]

TensorShapeMap ( const TensorShapeMap & other )

copy constructor.

Parameters

[in] other object to copy.

◆ toString()

const std::string toString ( ) const

Returns a string in the form Major.Minor.Teeny.Build.

Returns: A formatted string holding the version information.

Variable Documentation

◆ Build

std::string Build

This string holds information about the build version.

◆ Major

int32_t Major

Holds the major version number. Changes in this value indicate major changes that break backward compatibility.

◆ Minor

int32_t Minor

Holds the minor version number. Changes in this value indicate minor changes made to library that are backwards compatible (such as additions to the interface).

◆ Teeny

int32_t Teeny

Holds the teeny version number. Changes in this value indicate changes such as bug fixes and patches made to the library that do not affect the interface.

Classes

Typedefs

Enumerations

Functions

Variables

Detailed Description

Class Documentation

◆ zdl::DlSystem::Optional

Public Member Functions

◆ zdl::DlSystem::Version_t

Public Member Functions

Public Attributes

◆ zdl::DiagLog::IDiagLog

Public Member Functions

◆ zdl::DlContainer::IDlContainer

Public Member Functions

Static Public Member Functions

Member Function Documentation

◆ save() [1/2]

◆ save() [2/2]

◆ zdl::DlSystem::IOBufferDataTypeMap

Public Member Functions

◆ zdl::DlSystem::ITensor

Public Member Functions

◆ zdl::DlSystem::ITensorFactory

Public Member Functions

◆ zdl::DlSystem::UserBufferEncoding

Public Types

Public Member Functions

Member Enumeration Documentation

◆ ElementType_t

Member Function Documentation

◆ getElementSize()

◆ getElementType()

◆ zdl::DlSystem::UserBufferSource

Public Member Functions

Member Enumeration Documentation

◆ SourceType_t

Member Function Documentation

◆ getSourceType()

◆ zdl::DlSystem::UserBufferSourceGLBuffer

Additional Inherited Members

◆ zdl::DlSystem::UserBufferEncodingUnsigned8Bit

Public Member Functions

Additional Inherited Members

Member Function Documentation

◆ getElementSize()

◆ zdl::DlSystem::UserBufferEncodingFloatN

Public Member Functions

Additional Inherited Members

Member Function Documentation

◆ getElementSize()

◆ zdl::DlSystem::UserBufferEncodingFloat

Additional Inherited Members

◆ zdl::DlSystem::UserBufferEncodingTfN

Public Member Functions

Additional Inherited Members

Member Function Documentation

◆ getElementSize()

◆ getMax()

◆ getMin()

◆ getQuantizedStepSize()

◆ getStepExactly0()

◆ setQuantizedStepSize()

◆ setStepExactly0()

◆ zdl::DlSystem::UserBufferEncodingIntN

Public Member Functions

Additional Inherited Members

Member Function Documentation

◆ getElementSize()

◆ zdl::DlSystem::UserBufferEncodingUintN

Public Member Functions

Additional Inherited Members

Member Function Documentation

◆ getElementSize()

◆ zdl::DlSystem::IUserBuffer

Public Member Functions

Member Function Documentation

◆ getEncoding() [1/2]

◆ getEncoding() [2/2]