Submitting Workloads

Open the Volume pane, and press Volume to add a volume to your training.

1. Select the Storage class from the dropdown.
2. Select the Access mode from the dropdown.
3. Enter a claim size, and select the units.
4. Select a Volume system, mode from the dropdown.
5. Enter the Container path for volume target location.
6. Select a *Volume persistency.

In the Data sources pane, press add a new data source. For more information, see Creating a new data source When complete press, Create Data Source.

In the General pane, add special settings for your training (optional):

1. Press Auto-deletion to delete the training automatically when it either completes or fails. You can configure the timeframe in days, hours, minuets, and seconds. If the timeframe is set to 0, the training will be deleted immediately after it completes or fails.
2. Press Annotation to a name and value to annotate the training. Repeat this step to add multiple annotations.
3. Press Label to a name and value to label the training. Repeat this step to add multiple labels.

When complete, press *Create workspace.

In the Compute resource pane:

1. Select the number of workers for your training.
2. Select Compute resources for your training or create a new compute resource. Use the search box to find resources that are not listed. Press More settings to use Node Affinity to limit the resources to a specific node.

(Optional) Open the Volume pane, and press Volume to add a volume to your training.

1. Select the Storage class from the dropdown.
2. Select the Access mode from the dropdown.
3. Enter a claim size, and select the units.
4. Select a Volume system, mode from the dropdown.
5. Enter the Container path for volume target location.
6. Select a *Volume persistency.

(Optional) In the Data sources pane, press add a new data source. For more information, see Creating a new data source When complete press, Create Data Source.

(Optional) In the General pane, add special settings for your training (optional):

1. Press Auto-deletion to delete the training automatically when it either completes or fails. You can configure the timeframe in days, hours, minuets, and seconds. If the timeframe is set to 0, the training will be deleted immediately after it completes or fails.
2. Press Annotation to a name and value to annotate the training. Repeat this step to add multiple annotations.
3. Press Label to a name and value to label the training. Repeat this step to add multiple labels.

If you if selected Workers & master Press Continue to Configure the master and go to the next step. If not, then press Create training.

If you do not want a different setup for the master, press Create training. If you would like to have a different setup for the master, toggle the switch to enable to enable a different setup.

1. In the Environment pane select or create a new environment. Use the search box to find environments that are not listed. Press More settings to add an Environment variable or to edit the Command and Arguments field for the environment you selected.
2. In the Compute resource pane, select a Compute resources for your training or create a new compute resource. Use the search box to find resources that are not listed. Press More settings to use Node Affinity to limit the resources to a specific node.

3. (Optional) Open the Volume pane, and press Volume to add a volume to your training.

   1. Select the Storage class from the dropdown.
   2. Select the Access mode from the dropdown.
   3. Enter a claim size, and select the units.
   4. Select a Volume system, mode from the dropdown.
   5. Enter the Container path for volume target location.
   6. Select a *Volume persistency.

4. (Optional) In the Data sources pane, press add a new data source. For more information, see Creating a new data source When complete press, Create Data Source.

!!! Note Data sources that have private credentials that have the status of issues found will be greyed out.

1. (Optional) In the General pane, add special settings for your training (optional):

   1. Press Auto-deletion to delete the training automatically when it either completes or fails. You can configure the timeframe in days, hours, minuets, and seconds. If the timeframe is set to 0, the training will be deleted immediately after it completes or fails.
   2. Press Annotation to a name and value to annotate the training. Repeat this step to add multiple annotations.
   3. Press Label to a name and value to label the training. Repeat this step to add multiple labels.

When your training configuration is complete. press Create training.

In the Inference by type pane select Custom or model.

When you select Model:

1. Select a model from the tiles. Use the search box to find a model that is not listed. If you can't find the model, see your system administrator.
2. In the Inference name field, enter a name for the workload.
3. In the Compute resource field, select a compute resource from the tiles.
   1. In the Replica autoscaling section, set the minimum and maximum replicas for your inference. Then select Never or After one minute of inactivity to set when the replicas should be automatically scaled down to zero.
   2. In the Nodes field, change the order of priority of the node pools, or add a new node pool to the list.
4. When complete, press Create inference.

When you select Custom:

1. In the Inference name field, enter a name for the workload.
2. In the Environment field, select an environment. Use the search box to find an environment that is not listed. If you can't find an environment, press New environment or see your system administrator.
   1. In the Set the connection for your tool(s) pane, choose a tool for your environment (if available).
   2. In the Runtime settings field, Set commands and arguments for the container running in the pod. (optional)
   3. In the Environment variable field, you can set one or more environment variables. (optional)
3. In the Compute resource field, select a compute resource from the tiles. Use the search box to find a compute resource that is not listed. If you can't find an environment, press New compute resource or see your system administrator.
   1. In the Replica autoscaling section, set the minimum and maximum replicas for your inference. Then select Never or After one minute of inactivity to set when the replicas should be automatically scaled down to zero.
   2. In the Nodes field, change the order of priority of the node pools, or add a new node pool to the list.

4. In the Data sources field, add a New data source. (optional)

   Note

   • Data sources that are not available will be greyed out.
   • Assets that are cluster syncing will be greyed out.
   • Only PVC, Git, and ConfigMap resources are supported.

5. In the General field you can:

   1. Add an Auto-deletion time. This sets the timeframe between inference completion/failure and auto-deletion. (optional)
   2. Add one or more Annotation. (optional)
   3. Add one or more Labels. (optional)
6. When complete, press Create inference.