RKNPU Execution Provider
PREVIEW
RKNPU DDK is an advanced interface to access Rockchip NPU. The RKNPU Execution Provider enables deep learning inference on Rockchip NPU via RKNPU DDK.
Contents
Build
For build instructions, please see the BUILD page.
Usage
C/C++
To use RKNPU as an execution provider for inferencing, please register it as below.
Ort::Env env = Ort::Env{ORT_LOGGING_LEVEL_ERROR, "Default"};
Ort::SessionOptions sf;
Ort::ThrowOnError(OrtSessionOptionsAppendExecutionProvider_RKNPU(sf));
Ort::Session session(env, model_path, sf);
The C API details are here.
Support Coverage
Supported Platform
- RK1808 Linux
Note: RK3399Pro platform is not supported.
Supported Operators
The table below shows the ONNX Ops supported using the RKNPU Execution Provider and the mapping between ONNX Ops and RKNPU Ops.
| ONNX Ops | RKNPU Ops |
|---|---|
| Add | ADD |
| Mul | MULTIPLY |
| Conv | CONV2D |
| QLinearConv | CONV2D |
| Gemm | FULLCONNECT |
| Softmax | SOFTMAX |
| AveragePool | POOL |
| GlobalAveragePool | POOL |
| MaxPool | POOL |
| GlobalMaxPool | POOL |
| LeakyRelu | LEAKY_RELU |
| Concat | CONCAT |
| BatchNormalization | BATCH_NORM |
| Reshape | RESHAPE |
| Flatten | RESHAPE |
| Squeeze | RESHAPE |
| Unsqueeze | RESHAPE |
| Transpose | PERMUTE |
| Relu | RELU |
| Sub | SUBTRACT |
| Clip(0~6) | RELU6 |
| DequantizeLinear | DATACONVERT |
| Clip | CLIP |
Supported Models
The following models from the ONNX model zoo are supported using the RKNPU Execution Provider
Image Classification
- squeezenet
- mobilenetv2-1.0
- resnet50v1
- resnet50v2
- inception_v2
Object Detection
- ssd
- yolov3