This tutorial introduces how to install PaddleClas and its requirements.
## Introduction
## 1. Install PaddlePaddle
This document introduces how to install PaddleClas and its requirements.
`PaddlePaddle 2.0` or later is required for PaddleClas. You can use the following steps to install PaddlePaddle.
## Install PaddlePaddle
### 1.1 Environment requirements
Python 3.x, CUDA 10.0, CUDNN7.6.4 nccl2.1.2 and later version are required at first, For now, PaddleClas only support training on the GPU device. Please follow the instructions in the [Installation](http://www.paddlepaddle.org.cn/install/quick) if the PaddlePaddle on the device is lower than 2.0.0.
- python 3.x
- cuda >= 10.1 (necessary if you want to use paddlepaddle-gpu)
- cudnn >= 7.6.4 (necessary if you want to use paddlepaddle-gpu)
- nccl >= 2.1.2 (necessary if you want the use distributed training/eval)
- gcc >= 8.2
Docker is recomended to run Paddleclas, for more detailed information about docker and nvidia-docker, you can refer to the [tutorial](https://www.runoob.com/docker/docker-tutorial.html).
### Install PaddlePaddle using pip
When you use cuda10.1, the driver version needs to be larger or equal than 418.39. When you use cuda10.2, the driver version needs to be larger or equal than 440.33. For more cuda versions and specific driver versions, you can refer to the [link](https://docs.nvidia.com/deploy/cuda-compatibility/index.html).
If you do not want to use docker, you can skip section 1.2 and go into section 1.3 directly.
### 1.2 (Recommended) Prepare a docker environment. The first time you use this docker image, it will be downloaded automatically. Please be patient.
```
# Switch to the working directory
cd /home/Projects
# You need to create a docker container for the first run, and do not need to run the current command when you run it again
# Create a docker container named ppcls and map the current directory to the /paddle directory of the container
# It is recommended to set a shared memory greater than or equal to 8G through the --shm-size parameter
You can also compile PaddlePaddle from source code, please refer to [Installation](http://www.paddlepaddle.org.cn/install/quick).
**Note:**
* If you have already installed CPU version of PaddlePaddle and want to use GPU version now, you should uninstall CPU version of PaddlePaddle and then install GPU version to avoid package confusion.
* You can also compile PaddlePaddle from source code, please refer to [PaddlePaddle Installation tutorial](http://www.paddlepaddle.org.cn/install/quick) to more compilation options.
- Make sure the compiled version is later than PaddlePaddle2.0.
- Make sure the compiled source code is later than PaddlePaddle2.0.
- Indicate **WITH_DISTRIBUTE=ON** when compiling, Please refer to [Instruction](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/install/Tables.html#id3) for more details.
- When running in docker, in order to ensure that the container has enough shared memory for data read acceleration of Paddle, please set the parameter `--shm_size=8g` at creating a docker container, if conditions permit, you can set it to a larger value.
- When running in docker, in order to ensure that the container has enough shared memory for dataloader acceleration of Paddle, please set the parameter `--shm_size=8g` at creating a docker container, if conditions permit, you can set it to a larger value.
