Configure a Project
You can configure additional settings for your projects. Some of these settings, such as project name, are optional. Some other settings, such as data remotes, may be required depending on how your Git repository has been set up.
Scenarios where project settings are required
If you are connecting to a DVC repo which is at the root of the Git repository and does not reference remote/cloud storage, then you can successfully visualize it without configuring additional settings.
Alternatively, you could create projects from:
- Non-DVC repositories
- Sub-directories in a monorepo
- Custom files in your repository or remote/cloud storage
If you are connecting to a non-DVC repository, if your metrics are in some custom files, if you are connecting to a monorepo, or if your metrics are in cloud or other remote storage, you will need to configure project settings.
In each of these scenarios, you will need to configure additional settings for Iterative Studio to be able to access the data required for visualization.
Additionally, you can also configure project settings to change the name of your project and to select columns to import in your project.
To go to project settings, click on the
the project. In the menu that opens up, click on
In the section on preparing your repositories, you saw that you can use Iterative Studio with DVC as well as non-DVC repositories. If you are connecting to a non-DVC repository, then you will need to specify the custom files that contain the metrics and hyperparameters that you want to visualize.
Depending on how you have set up your Git repositories, your DVC repo (to which you are trying to connect from Iterative Studio) may not be in the root of your Git repo. Instead, it could be in a sub-directory of a monorepo. If this is the case, you will need to specify the full path to the sub-directory that contains the data you want to visualize in Iterative Studio.
Data remotes (cloud/remote storage)
The metrics and parameters that you want to include in the project may also be present in a data remote (cloud storage or another location outside the Git repo). If you want to include such data in your projects, then you will have to grant Iterative Studio access to the data remote.
Configuring project settings
You can configure a project's settings at any time after creating the project.
For this, click on the
the project. In the menu that opens up, click on
To change the project name, enter the new name for your project as shown below.
If you have connected to a monorepo, then specify the full path to the sub-directory that contains the DVC repo to which you are trying to connect.
Data remotes / cloud storage credentials
If you need to provide credentials for a data remote, you will need to do it
after your project has been created. First, create your project without
specifying the data remotes. Once your project is created, open its settings.
Data remotes / cloud storage credentials section. The data remotes
that are used in your DVC repo will be listed.
Now, click on
Add new credentials. In the form that opens up, select the
provider (Amazon S3, GCP, etc.). For details on what types of remote storage
(protocols) are supported, refer to the DVC documentation on supported storage
Depending on the provider, you will be asked for more details such as the credentials name, username, password etc. Note that for each supported storage type, the required details may be different.
You will also have to ensure that the credentials you enter have the required permissions on the cloud / remote storage. Refer to the DVC Remote config parameters for more details about this.
Note that Iterative Studio uses the credentials only to read plots/metrics files if they are not saved into Git. It does not access any other data in your remote storage. And you do not need to provide the credentials if any DVC data remote in not used in your Git repository.
In the "Columns" setting, you can specify which columns should be imported from your Git repository to your project in Iterative Studio. Any unselected column cannot be displayed in your project table.
If you would like to hide imported columns from your project, you can do so in the project's Display preferences.
If your project is missing some required columns, then it is likely that they have not been imported or are hidden.
The Columns setting was earlier called Tracking scope or Mandatory columns and behaved slightly differently. Iterative Studio would always import up to 200 columns. This meant that if you selected only 5 columns, Iterative Studio would still import another 195 columns, unless your repository did not have so many columns. This behavior is now obsolete, and only selected columns are imported.
Custom metrics and parameters
If you want to connect custom files, you can add them by clicking the
button. Enter the full file path within your Git repository, and specify whether
the file is for