AI Notebooks - Manage and use data in a notebook via UI – Support Guides

Learn how to access Object Storage data from your notebooks via the OVHcloud Control Panel.

Requirements

A Public Cloud project in your OVHcloud account
Access to the OVHcloud Control Panel
A Public Cloud user with the Administrator or AI Training operator role (see this guide for more information)

Instructions

Upload data to your Object Storage

First, you need to push some data to Object Storage before accessing it from the notebook.

You can find it in the OVHcloud Control Panel by selecting the Public Cloud tab and then Object Storage from the left navigation menu.

You can upload different types of data: datasets, code, notebooks, connection weights, text or CSV files, etc.

To upload your data, click + Create an object container.

Let's assume that a file named my-dataset.zip exists locally on your computer and contains your dataset. You will be able to upload it into an object container in your Object Storage by following these steps.

Order your Object Storage container

Follow the instructions in this guide to order your Object Storage container.

NOTE:

Your container must be located in the same region as your AI Notebook will be.
For a dataset that you use to train your model, the Restricted level of Confidentiality is appropriate.

Add objects to your container

To upload your dataset into your object container (object-storage-1, in this case), click on the container and then + Add objects.

Add your my-dataset.zip file, and it will be displayed in your object container.

You can also create a new empty my-weights container in which you can save your connection weights (or your validated model) at the end of your training.

We assume that we now have two object containers available:

my-dataset, containing the file my-dataset.zip
my-weights, empty

You are now ready to launch a notebook with your data!

Launch a notebook with attached data

To launch an AI notebook, access the AI Notebooks section of your Public Cloud project via the Public Cloud menu.

Use this tutorial to complete the setup of your AI Notebook until the Advanced configuration step.

Attach a container or a Git repository

You can attach your different types of data to your notebook.

NOTE: As mentioned before, S3™ compatible buckets are not yet compatible with our AI products from the Control Panel. To use S3™ compatible solutions, you will need to use the ovhai.

Access with Read-Only permissions

You can load the container my-dataset in the /workspace/dataset directory with Read-only permission.

You will not be able to modify the dataset from this notebook because you loaded it with Read-only permission.

Read-only permissions are to ensure you don't modify your data by mistake. If you want to modify data from your notebooks to store a trained neural network, for example, you can use the Read-write permission instead.

Access with Read-Write permissions

Similarly to the Read-only mode, you can load data with Read-write permission.

Once you have some data that you want to save from the notebook to Object Storage (connection weights in this example), you can simply write it to the /workspace/weights folder.

This folder will be uploaded to your Object Storage when you stop your notebook.

As long as your notebook is in the STOPPING state, this means that the upload is still in progress. Once the state changes to STOPPED, it means all the data was uploaded to your Object Storage.

Attach a public Git repository

If Python code, notebooks, or other files are available on a public GitHub repository, you can attach them to your notebook. To be able to edit and make changes easily, use the Read-write permission.

The command is as follows:

NOTE: To make your command valid, don't forget to add a .git at the end of the GitHub repository URL.

Use cached volumes

When loading large files from the Object Storage, it can take some time to download to your notebooks. In these cases, you can cache the volumes so that it does not need to be downloaded again when you start new notebooks that use the same data.

To do so, you can check Cache.

Cached volumes will be deleted at least 72 hours after the last notebook using it has stopped. Note that the cache is shared with all users in your project. The main consequence you need to be careful about is the fact that if someone else modifies the data in your cached volume, you will also see the modifications on your side.

Launch and access the notebook

Once you have ordered your AI Notebook, read the Accessing your AI Notebook section of our AI Notebooks - Getting started guide to learn how to find your access URL.

As soon as you access your notebook, you will see the different folders containing your data.

Go further

For more information and tutorials, please see our other AI & Machine Learning support guides or explore the guides for other OVHcloud products and services.

If you need training or technical assistance to implement our solutions, contact your sales representative or click on this link to get a quote and ask our Professional Services experts for a custom analysis of your project.

*S3 is a trademark filed by Amazon Technologies, Inc. OVHcloud's service is not sponsored by, endorsed by, or otherwise affiliated with Amazon Technologies, Inc.