Last updated 29th October, 2020.
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>
For more information you should consult the job logs:
ovhai job logs <job-id>
The second information you have is the
stateInfo, in which you can evaluate the error message, i.e. whether a command failed or the Docker image was not found.
- My job is in « pending » status, what does it mean ?
You job might be in queue status 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 you 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 sur you are exposing one of the accepted port listed here
- 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.
- Add how to build my first Datascience container ?
Please send us your questions, feedback and suggestions to improve the service:
- On the OVHcloud AI community forum
Did you find this guide useful?
Please feel free to give any suggestions in order to improve this documentation.
Whether your feedback is about images, content, or structure, please share it, so that we can improve it together.
Your support requests will not be processed via this form. To do this, please use the "Create a ticket" form.
Thank you. Your feedback has been received.