TensorRT 训练后推理的利器
TensorRT is a large and flexible project. It can handle a variety of conversion and deployment workflows, and which workflow is best for you will depend on your specific use case and problem setting.
TensorRT provides several options for deployment, but all workflows involve the conversion of your model to an optimized representation, which TensorRT refers to as an engine.
Building a TensorRT workflow for your model involves picking the right deployment option, and the right combination of parameters for engine creation.
refer to https://docs.nvidia.com/deeplearning/tensorrt/quick-start-guide/index.html
TensorRT是一个高性能的深度学习推理（Inference）优化器，可以为深度学习应用提供低延迟、高吞吐率的部署推理。TensorRT可用于对超大规模数据中心、嵌入式平台或自动驾驶平台进行推理加速。TensorRT现已能支持TensorFlow、Caffe、Mxnet、Pytorch等几乎所有的深度学习框架，将TensorRT和NVIDIA的GPU结合起来，能在几乎所有的框架中进行快速和高效的部署推理。
TensorRT 是一个C++库，从 TensorRT 3 开始提供C++ API和Python API，主要用来针对 NVIDIA GPU进行 高性能推理（Inference）加速。
