Group runs into experiments

Group individual jobs into experiments by passing a unique group name to wandb.init().

Use cases

1. Distributed training: Use grouping if your experiments are split up into different pieces with separate training and evaluation scripts that should be viewed as parts of a larger whole.
2. Multiple processes: Group multiple smaller processes together into an experiment.
3. K-fold cross-validation: Group together runs with different random seeds to see a larger experiment. Here’s an example of k-fold cross-validation with sweeps and grouping.

There are several ways to set grouping:

1. Set group in your script

Pass an optional group and job_type to wandb.init(). This gives you a dedicated group page for each experiment, which contains the individual runs. For example:wandb.init(group="experiment_1", job_type="eval")

2. Set a group environment variable

Use WANDB_RUN_GROUP to specify a group for your runs as an environment variable. For more on this, check our docs for Environment Variables. Group should be unique within your project and shared by all runs in the group. You can use wandb.util.generate_id() to generate a unique 8 character string to use in all your processes— for example, os.environ["WANDB_RUN_GROUP"] = "experiment-" + wandb.util.generate_id()

3. Set a group in the UI

After a run is initialized, you can move it to a new group from your workspace or its Runs page.

1. Navigate to your W&B project.

2. Select the Workspace or Runs tab from the project sidebar.

3. Search or scroll to the run you want to rename.

   Hover over the run name, click the three vertical dots, then click Move to another group.

4. To create a new group, click New group. Type a group name, then submit the form.

5. Select the run’s new group from the list, then click Move.

4. Toggle grouping by columns in the UI

You can dynamically group by any column, including a column that is hidden. For example, if you use wandb.config to log batch size or learning rate, you can then group by those hyperparameters dynamically in the web app. The Group by feature is distinct from a run’s run group. You can group runs by run group. To move a run to a different run group, refer to Set a group in the UI.

To group runs by one or more columns:

1. Click Group.
2. Click the names of one or more columns.
3. If you selected more than one column, drag them to change the grouping order.
4. Click anywhere outside of the form to dismiss it.

Customize how runs are displayed

You can customize how runs are displayed in your project from the Workspace or Runs tabs. Both tabs use the same display configuration.

To customize which columns are visible:

1. Above the list of runs, click Columns.

2. Click the name of a hidden column to show it. Click the name of a visible column to hide it.

   You can optionally search by column name using fuzzy search, an exact match, or regular expressions. Drag columns to change their order.

3. Click Done to close the column browser.

To sort the list of runs by any visible column:

1. Hover over the column name, then click its action ... menu.
2. Click Sort ascending or Sort descending.

Pinned columns are shown on the right-hand side. To pin or unpin a column:

1. Hover over the column name, then click its action ... menu.
2. Click Pin column or Unpin column.

By default, long run names are truncated in the middle for readability. To customize the truncation of run names:

1. Click the action ... menu at the top of the list of runs.
2. Set Run name cropping to crop the end, middle, or beginning.

Distributed training with grouping

Suppose you set grouping in wandb.init(), we will group runs by default in the UI. You can toggle this on and off by clicking the Group button at the top of the table. Here’s an example project generated from sample code where we set grouping. You can click on each “Group” row in the sidebar to get to a dedicated group page for that experiment.

From the project page above, you can click a Group in the left sidebar to get to a dedicated page like this one:

Grouping dynamically in the UI

You can group runs by any column, for example by hyperparameter. Here’s an example of what that looks like:

• Sidebar: Runs are grouped by the number of epochs.
• Graphs: Each line represents the group’s mean, and the shading indicates the variance. This behavior can be changed in the graph settings.

Turn off grouping

Click the grouping button and clear group fields at any time, which returns the table and graphs to their ungrouped state.

Grouping graph settings

Click the edit button in the upper right corner of a graph and select the Advanced tab to change the line and shading. You can select the mean, minimum, or maximum value for the line in each group. For the shading, you can turn off shading, and show the min and max, the standard deviation, and the standard error.