#include <onnxruntime_lite_custom_op.h>

Inheritance diagram for Ort::Custom::OrtLiteCustomOp:

Public Types
using	ConstOptionalFloatTensor = std::optional< const Custom::Tensor< float > & >

using	OptionalFloatTensor = std::optional< Custom::Tensor< float >>

Static Public Member Functions
template<size_t ith_input, size_t ith_output, typename... Ts>
static std::enable_if < sizeof...(Ts)==0, std::tuple <> >::type	CreateTuple (OrtKernelContext *, ArgPtrs &, size_t, size_t, const std::string &)

template<size_t ith_input, size_t ith_output, typename T , typename... Ts>
static std::enable_if < std::is_same< T, OrtKernelContext * >::value, std::tuple< T, Ts...> >::type	CreateTuple (OrtKernelContext *context, ArgPtrs &args, size_t num_input, size_t num_output, const std::string &ep)

template<size_t ith_input, size_t ith_output, typename T , typename... Ts>
static std::enable_if < std::is_same< T, OrtKernelContext & >::value, std::tuple< T, Ts...> >::type	CreateTuple (OrtKernelContext *context, ArgPtrs &args, size_t num_input, size_t num_output, const std::string &ep)

template<size_t ith_input, size_t ith_output, typename T , typename... Ts>
static std::enable_if < std::is_same< T, const TensorArray * >::value, std::tuple< T, Ts...> >::type	CreateTuple (OrtKernelContext *context, ArgPtrs &args, size_t num_input, size_t num_output, const std::string &ep)

template<size_t ith_input, size_t ith_output, typename T , typename... Ts>
static std::enable_if < std::is_same< T, const TensorArray & >::value, std::tuple< T, Ts...> >::type	CreateTuple (OrtKernelContext *context, ArgPtrs &args, size_t num_input, size_t num_output, const std::string &ep)

template<size_t ith_input, size_t ith_output, typename T , typename... Ts>
static std::enable_if < std::is_same< T, TensorArray * > ::value, std::tuple< T, Ts...> >::type	CreateTuple (OrtKernelContext *context, ArgPtrs &args, size_t num_input, size_t num_output, const std::string &ep)

template<size_t ith_input, size_t ith_output, typename T , typename... Ts>
static std::enable_if < std::is_same< T, TensorArray & > ::value, std::tuple< T, Ts...> >::type	CreateTuple (OrtKernelContext *context, ArgPtrs &args, size_t num_input, size_t num_output, const std::string &ep)

template<typename... Ts>
static std::enable_if < 0==sizeof...(Ts)>::type	ParseArgs (std::vector< ONNXTensorElementDataType > &, std::vector< ONNXTensorElementDataType > &)

Public Attributes
const std::string	op_name_

const std::string	execution_provider_

std::vector < ONNXTensorElementDataType >	input_types_

std::vector < ONNXTensorElementDataType >	output_types_

ShapeInferFn	shape_infer_fn_ = {}

int	start_ver_ = 1

int	end_ver_ = MAX_CUSTOM_OP_END_VER

void *	compute_fn_ = {}

void *	compute_fn_return_status_ = {}

Static Public Attributes
template<typename T , typename... Ts>
static std::enable_if < 0<=sizeof...(Ts)&&std::is_same < T, OrtKernelContext * > ::value >::type ParseArgs(std::vector < ONNXTensorElementDataType > &input_types, std::vector < ONNXTensorElementDataType > &output_types){ParseArgs < Ts...>input_types, output_types);}template < typename T, typename...Ts > static typename std::enable_if< 0<=sizeof...(Ts)&&std::is_same < T, OrtKernelContext & > ::value >::type ParseArgs(std::vector < ONNXTensorElementDataType > &input_types, std::vector < ONNXTensorElementDataType > &output_types){ParseArgs < Ts...>input_types, output_types);}template < typename T, typename...Ts > static typename std::enable_if< 0<=sizeof...(Ts)&&std::is_same < T, const TensorArray & > ::value >::type ParseArgs(std::vector < ONNXTensorElementDataType > &input_types, std::vector < ONNXTensorElementDataType > &output_types){input_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED);ParseArgs < Ts...>input_types, output_types);}template < typename T, typename...Ts > static typename std::enable_if< 0<=sizeof...(Ts)&&std::is_same < T, const TensorArray * > ::value >::type ParseArgs(std::vector < ONNXTensorElementDataType > &input_types, std::vector < ONNXTensorElementDataType > &output_types){input_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED);ParseArgs < Ts...>input_types, output_types);}template < typename T, typename...Ts > static typename std::enable_if< 0<=sizeof...(Ts)&&std::is_same < T, TensorArray & >::value > ::type ParseArgs(std::vector < ONNXTensorElementDataType > &input_types, std::vector < ONNXTensorElementDataType > &output_types){output_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED);ParseArgs < Ts...>input_types, output_types);}template < typename T, typename...Ts > static typename std::enable_if< 0<=sizeof...(Ts)&&std::is_same < T, TensorArray * >::value > ::type ParseArgs(std::vector < ONNXTensorElementDataType > &input_types, std::vector < ONNXTensorElementDataType > &output_types){output_types.push_back(ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED);ParseArgs < Ts...>input_types, output_types);}#define PARSE_INPUT_BASE(pack_type, onnx_type)#define PARSE_INPUT(data_type, onnx_type)#define PARSE_OUTPUT(data_type, onnx_type)#define PARSE_ARGS(data_type, onnx_type) PARSE_ARGS(std::string_view, ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING) OrtLiteCustomOp(const char op_name, const char execution_provider, ShapeInferFn shape_infer_fn, int start_ver=1, int end_ver=MAX_CUSTOM_OP_END_VER):op_name_(op_name), execution_provider_(execution_provider), shape_infer_fn_(shape_infer_fn), start_ver_(start_ver), end_ver_(end_ver){OrtCustomOp::version=ORT_API_VERSION;OrtCustomOp::GetName=[](const OrtCustomOp op){return static_cast< const OrtLiteCustomOp >op) -> op_name_.c_str();};OrtCustomOp::GetExecutionProviderType=[](const OrtCustomOp op){return((OrtLiteCustomOp ) op) -> execution_provider_.c_str();};OrtCustomOp::GetInputMemoryType=[](const OrtCustomOp , size_t){return OrtMemTypeDefault;};OrtCustomOp::GetInputTypeCount=[](const OrtCustomOp op){auto self=reinterpret_cast < const OrtLiteCustomOp * >op);return self->input_types_.size();};OrtCustomOp::GetInputType=[](const OrtCustomOp op, size_t indice){auto self=reinterpret_cast< const OrtLiteCustomOp >op);return self->input_types_[indice];};OrtCustomOp::GetOutputTypeCount=[](const OrtCustomOp op){auto self=reinterpret_cast < const OrtLiteCustomOp >op);return self->output_types_.size();};OrtCustomOp::GetOutputType=[](const OrtCustomOp op, size_t indice){auto self=reinterpret_cast< const OrtLiteCustomOp >op);return self->	output_types_ [indice]

Detailed Description

Definition at line 411 of file onnxruntime_lite_custom_op.h.

Member Typedef Documentation

using Ort::Custom::OrtLiteCustomOp::ConstOptionalFloatTensor = std::optional<const Custom::Tensor<float>&>

Definition at line 412 of file onnxruntime_lite_custom_op.h.

using Ort::Custom::OrtLiteCustomOp::OptionalFloatTensor = std::optional<Custom::Tensor<float>>

Definition at line 413 of file onnxruntime_lite_custom_op.h.

Member Function Documentation

template<size_t ith_input, size_t ith_output, typename... Ts>

static std::enable_if<sizeof...(Ts) == 0, std::tuple<> >::type Ort::Custom::OrtLiteCustomOp::CreateTuple	(	OrtKernelContext *	,
		ArgPtrs &	,
		size_t	,
		size_t	,
		const std::string &
	)

inlinestatic

Definition at line 418 of file onnxruntime_lite_custom_op.h.