TensorRT 4.0 Python API Documentation

TensorRT 4.0 includes support for Python, allowing developers to integrate a TensorRT inference engine into a python development environment or to experiment with TensorRT in an accessible fashion.

TensorRT 4.0 includes the Universial Framework Format (UFF): a way to convert models trained in TensorFlow and soon other frameworks like Caffe2 to a single model format. TensorRT is also now able to generate engines from UFF models.

Installing TensorRT and the UFF Toolkit

Workflows and Use Cases

There are a few use cases for which the Python API for TensorRT excels.

We have included a few sample applications with the TensorRT Python package which cover many of these use cases.

  1. There is an existing TensorFlow (or other UFF compatable framework) model that a developer wants to try out with TensorRT.
  2. There is a Caffe1 model that a developer want to try out with TensorRT
  3. A developer wants to deploy a TensorRT engine as a part of a larger application such as a web backend

Indices and tables