TfLiteRuntime Class Reference

Helper class that wraps the tflite c api. More...

#include <TfLiteRuntime.hpp>

Public Types
using	CreateResult

Public Member Functions
	~TfLiteRuntime ()
std::optional< TfLiteRunInferenceError >	run_inference (std::span< float > input, std::span< float > output)
	Run inference on the model, make sure input and output have the right amount of elements.
template<FloatTensorFormat InputFormat, FloatTensorFormat OutputFormat>
tl::expected< FloatTensorBuffer< OutputFormat >, TfLiteRunInferenceError >	run_inference (FloatTensorBuffer< InputFormat > &input)
std::span< const int >	get_input_shape () const
std::span< const int >	get_output_shape () const
	TfLiteRuntime (TfLiteRuntime &&)=delete
	TfLiteRuntime (const TfLiteRuntime &)=delete
void	operator= (TfLiteRuntime &&)=delete
void	operator= (const TfLiteRuntime &)=delete

Static Public Member Functions
static CreateResult	create (std::vector< int8_t > &&model_data, std::string_view delegate_serialization_dir, std::string_view model_token, FloatTensorFormat model_input_format, FloatTensorFormat model_output_format, TfLiteLogWarningCallback log_warning_callback, TfLiteLogErrorCallback log_error_callback, ProfilingFrame &profiling_frame, NpuConfiguration npu_config, bool enable_npu, std::string skel_library_dir)
	Create a TfLiteRuntime instance.

Detailed Description

Helper class that wraps the tflite c api.

Member Typedef Documentation

CreateResult

using TfLiteRuntime::CreateResult

Initial value:

 
        tl::expected<std::unique_ptr<TfLiteRuntime>, TfLiteCreateRuntimeError>

Constructor & Destructor Documentation

~TfLiteRuntime()

TfLiteRuntime::~TfLiteRuntime

(

)

TfLiteRuntime() [1/2]

TfLiteRuntime::TfLiteRuntime ( TfLiteRuntime && )

delete

TfLiteRuntime() [2/2]

TfLiteRuntime::TfLiteRuntime ( const TfLiteRuntime & )

delete

Member Function Documentation

create()

tl::expected< std::unique_ptr< TfLiteRuntime >, TfLiteCreateRuntimeError > TfLiteRuntime::create ( std::vector< int8_t > && model_data, std::string_view delegate_serialization_dir, std::string_view model_token, FloatTensorFormat model_input_format, FloatTensorFormat model_output_format, TfLiteLogWarningCallback log_warning_callback, TfLiteLogErrorCallback log_error_callback, ProfilingFrame & profiling_frame, NpuConfiguration npu_config, bool enable_npu, std::string skel_library_dir )

staticnodiscard

Create a TfLiteRuntime instance.

get_input_shape()

std::span< const int > TfLiteRuntime::get_input_shape ( ) const

nodiscard

get_output_shape()

std::span< const int > TfLiteRuntime::get_output_shape ( ) const

nodiscard

operator=() [1/2]

void TfLiteRuntime::operator= ( const TfLiteRuntime & )

delete

operator=() [2/2]

void TfLiteRuntime::operator= ( TfLiteRuntime && )

delete

run_inference() [1/2]

template<FloatTensorFormat InputFormat, FloatTensorFormat OutputFormat>

tl::expected< FloatTensorBuffer< OutputFormat >, TfLiteRunInferenceError > TfLiteRuntime::run_inference ( FloatTensorBuffer< InputFormat > & input )

inlinenodiscard

run_inference() [2/2]

std::optional< TfLiteRunInferenceError > TfLiteRuntime::run_inference ( std::span< float > input, std::span< float > output )

nodiscard

Run inference on the model, make sure input and output have the right amount of elements.

Parameters

input	input will be modified by input operators, should be in format model_input_format
output	output will be modified by output operators, should be in format model_output_format