# MLVC_Docker Manual

## 0. Images
### mlvc/pytorch
Installed applications

| app | ver |
| --- | --- |
| vim | |
| git | |
| openssh-server| |
| python | 3.6.8 |

Installed python packages

| package | ver |
| --- | --- |
| pytorch | 1.0.1 |
| torchvision | 0.2.2 |
| numpy | 1.15.4 |
| pandas | 0.24.2 |
| scikit-learn | 0.20.3 |
| scipy | 1.2.1 |

## 1. Quick Start
### Make container
```
$ nvidia-docker run -it --name YOUR_CONTAINER_NAME mlvc/pytorch
```
### List container
```
$ docker ps     // active container
$ docker ps -a  // all container
```

### Remove container
> WARNING: Be careful. Deleted container cannot be restored. DO NOT DELETE other user's container.
```
$ docker rm <CONTAINER_ID>
or
$ docker rm <CONTAINER_NAME>
```

## 2. Multi GPU
In multi GPU system, Each container can use specefic GPUs.
```
$ NV_GPU=0,1 nvidia-docker -it <IMAGE>
```

## 3. Make container options
### Port mapping
```
$ nvidia-docker -it -p HOST:CONTAINER <IMAGE>
ex) ssh port mapping
$ nvidia-docer -it -p 2211:22 mlvc/pytorch
```

### Sharing volume
```
$ nvidia-docker -it -v /HOST/DIR:/CONTAINER/DIR <IMAGE>
ex)
$ nvidia-docker -it -v /data:/data mlvc/pytorch
```

## 4. ETC
### Use ssh
The `mlvc/pytorch` image already installed ssh server
You can use ssh after following commands.

```
// make container
$ nvidia-docer -it -p <outer port>:22 mlvc/pytorch
```

> Be sure, the HOST port can allready used. Request port number to junhyn, server manager.

In Container
```
# service ssh restart
# passwd    // change root password
```

Access is same as common.
```
ssh root@<host> -P <port>
```