Last updated 20th April, 2021.
Here are the most frequently asked questions about AI Training.
- In which regions is the Private Registry solution available?
Private registry is currently available in Western Europe (GRA region).
- Do I need to master Docker to use AI Training?
It is not necessary to master Docker to use AI Training. A set of ready-to-use images is available on the
ovhcomorganization of Dockerhub to get you started. All images prefixed by
ai-trainingare images to be used with this service. They usually include classic tools such as JupyterLab or VScode along with some Machine Learning framework such as PyTorch.
However, jobs in AI Training are basically Docker containers, so a practical understanding of Docker is required to fully benefit from the service.
- Is there an expected format for data to upload?
You can upload any file or directory to the OVHcloud Object Storage without any format constraints.
- Is it possible to update a running job?
It is not possible to update a running job. If you wish to change the specification of a job, you need to interrupt the current one and recreate it.
- How to fix file access permission errors?
Within a job, code and users have no root/sudo privileges. To have access to your files, make sure to mount your data object at a location available for non-root users. For preset images provided by OVHcloud it is recommended that the destination path is of the form
/workspace/<your-path>to avoid such errors.
- Why did my job fail?
For more information about the failure of a job, start with retrieving the job ID with this command:
ovhai job list
Once you have your job ID, simply retrieve its information with:
ovhai job get <job-id>
You will see, among other information, the job's state and if the job has run its exit code.
There is also the
stateInfoin which you can evaluate the error message, i.e. whether a command failed or the Docker image was not found.
For more information you should consult the job logs:
ovhai job logs <job-id>
- My job is in « queued » or « pending » state, what does it mean ?
Your job might be in this state for 2 main reasons :
- You are using an external registry and the image is taking longer to pull. Potential resolution: wait a bit longer for the cluster to pull the external image or recompile the image on an OVHcloud managed Registry.
- The cluster is waiting for resources to be available. Potential resolution: try to launch the job with less resources or wait for resources to be available.
- Why can't I can't see my data volume in the container ?
Depending on how you build your container, make sure that the mapping between your data (/workspace/mybucket for instance) is not already existing within your image.
- Why can't I can't access my UI ?
Make sure your job is in a « running » state and that your UI is exposed either on the default port or that you specified the correct port in your URL (see public ports).
Only the HTTP layer is accessible and check that your UI is correctly binded to the network interfaces (e.g. with tensoboard user the
- Why is the image not executed with the expected linux user ?
For security purposes, we impersonate the linux default user which is ovh and group ovh with ids
Building a docker with a directory associated to this user and group should help you.
You could use the following command to copy a local folder with the
COPY --chown=42420:42420 my_local_folder my_folder_embeded_in_image
- How to start a notebook ?
All steps for starting and working on notebooks are described here
- How to add python library in a notebook ?
You can use
pipcommand inside console of notebooks to install libraries as long as the installation process doesn't require root access. If a specific library require root access you will have instead to build your own job image with all your libraries and use it instead of provided ones.
- How to build my first Datascience container ?
Please send us your questions, feedback and suggestions to improve the service:
- On the OVHcloud Discord server
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