TensorRT Release 18.08
The NVIDIA container image of TensorRT, release 18.08, is available.
Contents of TensorRT
- The TensorRT documentation and C++ samples. The samples can be built by running make in the /workspace/tensorrt/samples directory. The resulting executables are in the /workspace/tensorrt/bin directory.
- The TensorRT Python examples. The Python examples can be found in the /workspace/tensorrt/python/examples directory. Most Python examples can be run using python <script.py> /workspace/tensorrt/python/data. The Python API documentation can be found in the /usr/lib/python<x.y>/dist-packages/docs directory.
- Ubuntu 16.04
- NVIDIA CUDA 9.0.176 (see Errata section and 2.1) including CUDA® Basic Linear Algebra Subroutines library™ (cuBLAS) 9.0.425
- NVIDIA CUDA® Deep Neural Network library™ (cuDNN) 7.2.1
- NCCL 2.2.13 (optimized for NVLink™ )
Key Features and Enhancements
- TensorRT container image version 18.08 is based on TensorRT 4.0.1.
- Latest version of cuDNN 7.2.1.
- A new script has been added to the container that will install uff, graphsurgeon, as well as other Python modules that are required to execute all of the Python examples.
- Ubuntu 16.04 with July 2018 updates
Installing Required Python Modules
Some samples require data files that are not included within the TensorRT container either due to licensing restrictions or because they are too large. The following script has been added to the container to install these missing Python modules and their dependencies if desired: /opt/tensorrt/python/python_setup.sh
Samples which do not include all the required data files include a README.txt file in the corresponding source directory informing you how to obtain the necessary data files. You may need to first run the Python setup script in order to complete some of the samples.
Known Issues
There are no known issues in this release.