Skip to content

samples

Directory actions

More options

Directory actions

More options

Latest commit

 

History

History
 
 

samples

README.md

TensorRT Samples

Contents

1. "Hello World" Samples

Sample Language Format Description
sampleOnnxMNIST C++ ONNX “Hello World” For TensorRT With ONNX
network_api_pytorch_mnist Python INetwork “Hello World” For TensorRT Using Pytorch

2. TensorRT API Samples

Sample Language Format Description
[DEPRECATED] sampleCharRNN C++ INetwork Building An RNN Network Layer By Layer
sampleCudla C++ INetwork Using The CuDLA API To Run A TensorRT Engine (aarch64 only)
sampleDynamicReshape C++ ONNX Digit Recognition With Dynamic Shapes In TensorRT
sampleEditableTimingCache C++ INetwork Create a deterministic build using editable timing cache
[DEPRECATED] sampleINT8API C++ ONNX Performing Inference In INT8 Precision
sampleNamedDimensions C++ ONNX Working with named input dimensions
sampleNonZeroPlugin C++ INetwork Adding plugin with data-dependent output shapes
sampleOnnxMnistCoordConvAC C++ ONNX Implementing CoordConv with a custom plugin
sampleIOFormats C++ ONNX Specifying TensorRT I/O Formats
sampleProgressMonitor C++ ONNX Progress Monitor API usage
trtexec C++ All TensorRT Command-Line Wrapper: trtexec
engine_refit_onnx_bidaf Python ONNX refitting an engine built from an ONNX model via parsers.
introductory_parser_samples Python ONNX Introduction To Importing Models Using TensorRT Parsers
onnx_packnet Python ONNX TensorRT Inference Of ONNX Models With Custom Layers
simpleProgressMonitor Python ONNX Progress Monitor API usage
python_plugin Python INetwork/ONNX Python-based TRT plugins
non_zero_plugin Python INetwork/ONNX Python-based TRT plugin for NonZero op

3. Application Samples

Sample Language Format Description
detectron2 Python ONNX Support for Detectron 2 Mask R-CNN R50-FPN 3x model in TensorRT
[DEPRECATED] efficientdet Python ONNX EfficientDet Object Detection with TensorRT
[DEPRECATED] tensorflow_object_detection_api Python ONNX TensorFlow Object Detection API Models in TensorRT
[DEPRECATED] yolov3_onnx Python ONNX Object Detection Using YOLOv3 With TensorRT ONNX Backend

4. Safety Samples

Sample Language Format Description
sampleSafeMNIST C++ ONNX Build a Safety Engine for MNIST
sampleSafePluginV3 C++ ONNX Use Safety-Supported Plugins With Safety Engines
trtSafeExec C++ ONNX TensorRT Command-Line Wrapper With Safety Options

Preparing sample data

Many samples require the TensorRT sample data package. If not already mounted under /usr/src/tensorrt/data (NVIDIA NGC containers), download and extract it:

  1. Download the sample data from TensorRT GitHub Releases.

  2. Extract and set up the data:

    unzip tensorrt_sample_data_xxx.zip
mkdir -p /usr/src/tensorrt/data
cp -r tensorrt_sample_data_*/* /usr/src/tensorrt/data/
export TRT_DATADIR=/usr/src/tensorrt/data

After extraction, the data directory structure should be:

$TRT_DATADIR/
├── char-rnn/
├── int8_api/
├── mnist/
└── resnet50/