CLI - Commands reference
Learn how to use the CLI to interact with AI Training
Learn how to use the CLI to interact with AI Training
Last updated 20th April, 2021.
This guide covers the usage of the ovhai CLI.
ovhai
CLI how to install ovhai CLITo submit a job you need a docker image and optionally some data.
First let's submit a simple job, a public ubuntu image which executes a command echo
:
ovhai job run ubuntu --gpu 1 -- echo "Hello from my first job"
--help
to get more information about a command.--gpu <x>
or choose to use CPUs with the flag --cpu <x>
.You can then list your current and old jobs with:
ovhai job list
--watch
to watch changes in live.--output <format>
if you want a different output (JSON or YAML)You should see the job you just ran, you need its ID
to get more information about it.
To see information about a job use the following command:
ovhai job get <job-id>
To see its logs in live use the following command:
ovhai job logs <job-id> --follow
You should see the output of the echo
command:
Hello from my first job
You can upload data to the Object Storage and mount that data when you run a job. If you mount that data with read/write it will be saved to the Object Storage when the job ends.
Let's upload some data and use it in a job that will produce more data.
ovhai data upload <region> <container> some-file.txt
Now that you have some data in a container you can mount it when you run a job with the flag --volume
.
ovhai job run <image> --volume <container>@<region>:/data:rw
--volume
more than one time if you want to mount more containers.You can list and download data you uploaded or generated by a job with:
ovhai data list <region> <container>
ovhai data download <region> <container> --prefix /some-data
You can synchronize data to the Object Storage while a job is running with:
ovhai job push-data <job-id>
You can see the progress with:
ovhai job get <job-id>
You can execute commands (like bash
) while a job is running.
ovhai job exec -it <id> -- bash
This way you can interact with a running job.
You can create a job with some ssh access:
ovhai job run -s ~/.ssh/id_ed25519.pub ovhcom/ai-training-fastai
Multiple -s
arguments can be used to provide multiple SSH public keys.
Once the job is in RUNNING
state, you can retrieve the sshUrl
with:
ovhai job get <job-id>
---
id: 0d916855-1cd4-4b66-8803-b4782bc13902
createdAt: "2021-02-23T08:45:01.297780Z"
updatedAt: "2021-02-23T08:45:19.823082Z"
user: user-xxx
spec:
image: ovhcom/ai-training-fastai
env: []
defaultHttpPort: 8080
resources:
gpu: 1
gpuModel: Tesla-V100S
cpu: 7
volumes: []
timeout: 0
name: ai-training-fastai-kind
sshPublicKeys:
- ssh-ed25519 AAAAC3NzaC1someKey
status:
state: RUNNING
queuedAt: "2021-02-23T08:45:01.297318Z"
startedAt: "2021-02-23T08:45:13Z"
stoppedAt: ~
ip: 10.42.155.122
infos: ~
history:
- state: QUEUED
date: "2021-02-23T08:45:01.297012Z"
- state: INITIALIZING
date: "2021-02-23T08:45:04.356856Z"
- state: PENDING
date: "2021-02-23T08:45:10.163754Z"
- state: RUNNING
date: "2021-02-23T08:45:19.822354Z"
duration: 6
jobUrl: "http://0d916855-1cd4-4b66-8803-b4782bc13902.job.gra.training.ai.cloud.ovh.net"
sshUrl: "ssh://0d916855-1cd4-4b66-8803-b4782bc13902@gra.training.ai.cloud.ovh.net"
monitoringUrl: "http://monitoring.gra.training.ai.cloud.ovh.net/d/job/job-monitoring?var-job=0d916855-1cd4-4b66-8803-b4782bc13902&from=1614069913000"
Then you can connect to it with a terminal:
ssh 0d916855-1cd4-4b66-8803-b4782bc13902@gra.training.ai.cloud.ovh.net -i ~/.ssh/id_ed25519
You can list available registries with:
ovhai registry list
By default, you have access to public registries, and a shared registry scoped to your project. To add a private registry, use:
ovhai registry add <url>
You will be asked to type your credentials.
The regions available to install and use the ovhai
CLI are GRA
and BHS
. If you want to change the region in the CLI, you can use the following commands.
You can list the Names and URLs of the available regions with:
ovhai config list
The region in green is the one you are currently in.
To change the region, use:
ovhai config set <region>
<region>
is the new region name (GRA
or BHS
), in which you want to be placed.
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