## 0. FastDeployFastDeploy is an Easy-to-use and High Performance AI model deployment toolkit for Cloud, Mobile and Edge with out-of-the-box and unified experience, end-to-end optimization for over 150+ Text, Vision, Speech and Cross-modal AI models. FastDeploy Supports AI model deployment on**X86 CPU、NVIDIA GPU、ARM CPU、XPU、NPU、IPU** etc. You can switch different inference backends and hardware with a single line of code.Deploying AI model in 3 steps with FastDeploy: (1)Install FastDeploy SDK; (2)Use FastDeploy's API to implement the deployment code; (3) Deploy.**Notes** : This document downloads FastDeploy examples to complete the high performance deployment experience; only X86 CPUs, NVIDIA GPUs are shown for reasoning and GPU environments are ready by default (e.g. CUDA >= 11.2, etc.), if you need to deploy AI model on other hardware or learn about FastDeploy's full capabilities, please refer to [FastDeploy GitHub](https://github.com/PaddlePaddle/FastDeploy).## 1. Install FastDeploy SDK```pip install fastdeploy-gpu-python==0.0.0 -f https://www.paddlepaddle.org.cn/whl/fastdeploy_nightly_build.html```## 2. Run Deployment Example```# download deployment examplegit clone https://github.com/PaddlePaddle/FastDeploy.gitcd FastDeploy/examples/vision/sr/ppmsvsr/python# download VSR model and test imagewget https://bj.bcebos.com/paddlehub/fastdeploy/PP-MSVSR_reds_x4.tartar -xvf PP-MSVSR_reds_x4.tarwget https://bj.bcebos.com/paddlehub/fastdeploy/vsr_src.mp4# CPU deploymentpython infer.py --model PP-MSVSR_reds_x4 --video person.mp4 --frame_num 2 --device cpu# GPU deploymentpython infer.py --model PP-MSVSR_reds_x4 --video person.mp4 --frame_num 2 --device gpu# TensorRT inference on GPU (note: if you run TensorRT inference the first time, there is a serialization of the model, which is time-consuming and requires patience)python infer.py --model PP-MSVSR_reds_x4 --video person.mp4 --frame_num 2 --device gpu --use_trt True```The results of the completed visualisation are shown below:<divalign="center"><imgsrc="https://user-images.githubusercontent.com/44053467/200456062-426b047a-3571-4463-94cf-c8d02ca25d16.png"width = "50%"></div>