For enabling ONNX Runtime launcher you need to add framework: onnx_runtime
in launchers section of your configuration file and provide following parameters:
device
- specifies which device will be used for infer (cpu
, gpu
and so on). Optional, cpu used as default or can depend on used executable provider.model
- path to the network file in ONNX format.adapter
- approach how raw output will be converted to representation of dataset problem, some adapters can be specific to framework. You can find detailed instruction how to use adapters here.execution_providers
- list of execution providers for evaluation, e.g. OpenVINO Execution Provider. Default [CPUExecutionProvider
] used.Note: execution providers available only with newest versions of ONNXRuntime, if your installed version does not support such API, please update or does not specify this field.
In case when you model has several inputs you should provide list of input layers in launcher config section using key inputs
. Each input description should has following info:
name
- input layer name in networktype
- type of input values, it has impact on filling policy. Available options:CONST_INPUT
- input will be filled using constant provided in config. It also requires to provide value
.IMAGE_INFO
- specific key for setting information about input shape to layer (used in Faster RCNN based topologies). You do not need provide value
, because it will be calculated in runtime. Format value is Nx[H, W, S]
, where N
is batch size, H
- original image height, W
- original image width, S
- scale of original image (default 1).INPUT
- network input for main data stream (e. g. images). If you have several data inputs, you should provide regular expression for identifier as value
for specifying which one data should be provided in specific input. Optionally you can determine shape
of input (actually does not used, ONNX Runtime launcher uses info given from network),layout
in case when your model was trained with non-standard data layout (For ONNX Runtime default layout is NCHW
) and precision
(Supported precisions: FP32
- float, FP16
- signed shot, U8
- unsigned char, U16
- unsigned short int, I8
- signed char, I16
- short int, I32
- int, I64
- long int).MXNet launcher config example: