File SNPEUtil.h

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Definition (SNPE/SNPEUtil.h)

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Snpe_IUserBuffer_Handle_t Snpe_Util_CreateUserBuffer(void *buffer, size_t bufSize, Snpe_TensorShape_Handle_t stridesHandle, Snpe_IUserBuffer_Handle_t userBufferEncodingHandle)

Creates a UserBuffer.

Parameters

  • buffer – [in] Pointer to the buffer that the caller supplies

  • bufSize – [in] Buffer size, in bytes

  • stridesHandle – [in] 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].

  • userBufferEncodingHandle – [in] Handle to a UserBufferEncoding object

Returns

Handle to the created UserBuffer

Note

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

Snpe_IUserBuffer_Handle_t Snpe_Util_CreateUserBufferShared(void *buffer, size_t bufSize, uint64_t addrOffset, Snpe_TensorShape_Handle_t stridesHandle, Snpe_IUserBuffer_Handle_t userBufferEncodingHandle)

Creates a UserBuffer.

Parameters

  • buffer – [in] Pointer to the buffer that the caller supplies

  • bufSize – [in] Buffer size, in bytes

  • addrOffset – [in] byte offset to the actual address from the start of the allocated buffer. This is useful for sharing a large buffer amongst different tensors. When set to 0 this API behaves like Snpe_Util_CreateUserBuffer()

  • stridesHandle – [in] 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].

  • userBufferEncodingHandle – [in] Handle to a UserBufferEncoding object

Returns

Handle to the created UserBuffer

Note

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

Snpe_IUserBuffer_Handle_t Snpe_Util_CreateUserBufferFromSource(void *buffer, size_t bufSize, Snpe_TensorShape_Handle_t stridesHandle, Snpe_IUserBuffer_Handle_t userBufferEncodingHandle, Snpe_UserBufferSource_Handle_t userBufferSourceHandle)

Creates a UserBuffer with a provided UserBufferSource.

Parameters

  • buffer – [in] Pointer to the buffer that the caller supplies

  • bufSize – [in] Buffer size, in bytes

  • stridesHandle – [in] 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].

  • userBufferEncodingHandle – [in] Handle to a UserBufferEncoding object

  • userBufferSourceHandle – [in] Handle to a UserBufferSource object

Returns

Handle to the created UserBuffer

bool Snpe_Util_Convert_Float32ToTfN(const float *inputBuffer, size_t inputBufferSizeBytes, bool isDynamicEncoding, float *scale, uint64_t *offset, void *outputBuffer, size_t outputBufferSizeBytes, unsigned bitWidth)

Converts/Quantizes a float32 buffer to an unsigned fixed point 8/16 bit buffer.

Parameters

  • inputBuffer – [in] Pointer to the float32 buffer that the caller supplies

  • inputBufferSizeBytes – [in] Input buffer size, in bytes. Must be at least 4 bytes

  • isDynamicEncoding – [in] When set to false, scale and offset provided (next 2 argumets) will be used to qunatize. When set to true, scale and offset provided will be ignored and min/max will be computed from the inputBuffer to derrive the scale and offset for quantization. The computed scale and offset will be populated back to the caller in the next two arguments

  • [in/out] – scale Pointer to qunatization encoding scale to be passed in by the caller when isDynamicEncoding is true. When isDynamicEncoding is false this argument is ignored and is populated as an outparam.

  • [in/out] – offset Pointer to qunatization encoding offset to be passed in by the caller when isDynamicEncoding is true. When isDynamicEncoding is false this argument is ignored and is populated as an outparam.

  • outputBuffer – [in] Pointer to the unsigned fixed point 8/16 bit buffer that the caller supplies

  • outputBufferSizeBytes – [in] Output buffer size, in bytes. Must be large enough for all the inputs

  • bitWidth – [in] Quantization bitwidth (8 or 16)

Note

This API can do in-place quantization i.e. when outputBuffer equals inputBuffer pointer. But the output buffer CANNOT start at an offset from input buffer which will lead to corrupting inputs at sbsequent indexes.

bool Snpe_Util_Convert_TfNToFloat32(const void *inputBuffer, size_t inputBufferSizeBytes, float scale, uint64_t offset, float *outputBuffer, size_t outputBufferSizeBytes, unsigned bitWidth)

Converts/De-Quantizes an unsigned fixed point 8/16 bit buffer to a float32 buffer.

Parameters

  • inputBuffer – [in] Pointer to the unsigned fixed point 8/16 bit buffer that the caller supplies

  • inputBufferSizeBytes – [in] Input buffer size, in bytes

  • [in/out] – scale Qunatization encoding scale to be passed in by the caller

  • [in/out] – offset Qunatization encoding offset to be passed in by the caller

  • outputBuffer – [in] Pointer to the float32 buffer that the caller supplies

  • outputBufferSizeBytes – [in] Output buffer size, in bytes. Must be large enough for all the inputs

  • bitWidth – [in] Quantization bitwidth (8 or 16)

Note

This API CANNOT in place de-quantization. The input and output buffers must have no overlap

Snpe_IUserBuffer_Handle_t Snpe_Util_CreateUserGlBuffer(void *buffer, size_t bufSize, Snpe_TensorShape_Handle_t stridesHandle, Snpe_IUserBuffer_Handle_t userBufferEncodingHandle, Snpe_IUserBuffer_Handle_t userBufferSourceHandle)

Creates a UserBuffer.

Parameters

  • buffer – [in] Pointer to the buffer that the caller supplies

  • bufSize – [in] Buffer size, in bytes

  • stridesHandle – [in] 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].

  • userBufferEncodingHandle – [in] Reference to an UserBufferEncoding object

  • userBufferSourceHandle – [in] Reference to an UserBufferSource object

Returns

the created UserBuffer

Note

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

Snpe_ITensor_Handle_t Snpe_Util_CreateITensor(Snpe_TensorShape_Handle_t shapeHandle)

Creates a new ITensor with uninitialized data.

ITensor buffer size assumes float32 encoding for each element. (i.e., a tensor with dimensions (2,3) will be represented by (2 * 3) * 4 = 24 bytes in memory)

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

Parameters

shapeHandle – [in] 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

The created tensor

Snpe_ITensor_Handle_t Snpe_Util_CreateITensorDataSize(Snpe_TensorShape_Handle_t shapeHandle, const uint8_t *data, size_t dataSize)

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

  • shapeHandle – [in] 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.

  • data – [in] The actual data with which the Tensor object is filled.

  • dataSize – [in] The size of data

Returns

A handle to the created tensor

Snpe_ITensor_Handle_t Snpe_Util_CreateITensor_NV21(Snpe_TensorShape_Handle_t shapeHandle, unsigned char *data, size_t dataSize)

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

  • shapeHandle – [in] 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.

  • data – [in] The actual data with which the Tensor object is filled.

  • dataSize – [in] The size of data

Returns

the created tensor

int Snpe_Util_IsRuntimeAvailable(Snpe_Runtime_t runtime)

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

Note: It is advised to use this function to check DSP availability. If the DSP is not already initialized, it will conduct the initialization - therefore, please ensure that the appropriate arguments are passed, where relevant.

Parameters

runtime – [in] The target runtime to check.

Returns

Boolean: Non-zero if the supplied runtime is available; 0 otherwise

int Snpe_Util_IsRuntimeAvailableForDevice(Snpe_Runtime_t runtime, uint32_t deviceId)

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

Note: It is advised to use this function to check DSP availability. If the DSP is not already initialized, it will conduct the initialization - therefore, please ensure that the appropriate arguments are passed, where relevant.

Parameters

  • runtime – [in] The target runtime to check.

  • deviceId – [in] deviceId in case of multi NSP devices.

Returns

Boolean: Non-zero if the supplied runtime is available; 0 otherwise

int Snpe_Util_IsRuntimeAvailableCheckOption(Snpe_Runtime_t runtime, Snpe_RuntimeCheckOption_t runtimeCheckOption)

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

Note: It is advised to use this function to check DSP availability. If the DSP is not already initialized, it will conduct the initialization - therefore, please ensure that the appropriate arguments are passed, where relevant.

Parameters

  • runtime – [in] The target runtime to check.

  • runtimeCheckOption – [in] Extent to perform runtime available check.

Returns

Boolean: Non-zero if the supplied runtime is available; 0 otherwise

int Snpe_Util_IsRuntimeAvailableCheckOptionForDevice(Snpe_Runtime_t runtime, Snpe_RuntimeCheckOption_t runtimeCheckOption, uint32_t deviceId)

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

Note: It is advised to use this function to check DSP availability. If the DSP is not already initialized, it will conduct the initialization - therefore, please ensure that the appropriate arguments are passed, where relevant.

Parameters

  • runtime – [in] The target runtime to check.

  • runtimeCheckOption – [in] Extent to perform runtime available check.

  • deviceId – [in] deviceId in case of multi NSP devices

Returns

Boolean: Non-zero if the supplied runtime is available; 0 otherwise

Snpe_DlVersion_Handle_t Snpe_Util_GetLibraryVersion()

Gets the version of the SNPE library.

Returns

Version of the SNPE library.

int Snpe_Util_SetSNPEStorageLocation(const char *storagePath)

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

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

Returns

Boolean: Non-zero if the supplied path was succesfully set as the SNPE storage location, 0 otherwise.

int Snpe_Util_AddOpPackage(const char *regLibraryPath)

Register a user-defined op package with SNPE.

Parameters

regLibraryPath – [in] 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

Boolean: Non-zero if successful, 0 otherwise.

int Snpe_Util_IsGLCLInteropSupported()

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

Returns

Boolean: Non-zero if the OpenGL and OpenCl interop is supported; 0 otherwise

const char *Snpe_Util_GetLastError()
Returns

A string description of the last error

int Snpe_Util_InitializeLogging(Snpe_LogLevel_t level)

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

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

Returns

Boolean: non-zero if successful, 0 otherwise.

int Snpe_Util_InitializeLoggingPath(Snpe_LogLevel_t level, const char *logPath)

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

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

  • logPath – [in] of directory to store logs. If path is empty, the default path is “./Log”. For android, the log path is ignored.

Returns

Boolean: non-zero if successful, 0 otherwise.

int Snpe_Util_SetLogLevel(Snpe_LogLevel_t level)

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

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

Returns

Boolean: non-zero if successful, 0 otherwise.

int Snpe_Util_TerminateLogging()

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

Boolean: non-zero if successful, 0 otherwise.

Warning

Snpe_Util_TerminateLogging() must not be called while another thread is executing. In a multi-threaded use case, the individual threads must have a cooperative life cycle management strategy for the logger.