- Release Notes
- Before you begin
- Getting started
- Installing Automation Suite
- Migration and upgrade
- Projects
- Datasets
- ML packages
- Pipelines
- Managing pipelines
- Closing the loop
- ML Skills
- ML Logs
- Document Understanding in AI Center
- Licensing
- How To
- Basic Troubleshooting Guide
Managing pipelines
- In the Pipelines page, click the Create new button. The Create new pipeline run page is displayed.
Alternatively, in the ML Package Details of a specific package, select the Pipeline Runs, and then click the Create new button. The Create new pipeline run page is displayed.
- In the Create new pipeline run page, select the type of the pipeline run. The available options are Training run,Evaluation run, and Full pipeline run.
- Select the package for the pipeline run.
- Select the package's major and minor versions.
- Select datasets. According to the selected pipeline type, the following datasets must be specified:
- For training pipeline, specify the input dataset.
- For evaluation pipeline, specify the evaluation dataset.
- For full pipeline run, specify the input dataset and the evaluation dataset.
- (Optionally) Enter parameters for the pipeline runs. Click Add new to display the parameters section, then enter the environment variable and its corresponding value. Multiple parameters are accepted.
- Select whether the pipeline requires a GPU, by default it is set to No.
- (Optionally) Toggle the Enable Infra Settings if you want to customize the resources and storage size for this specific deployment. If infra settings is enabled, the following
fields can be customized:
- The request and limit sizes for RAM (GB).
- The request and limit sizes for CPU.
- Storage zise (GB).
Note: Only change these values if you are sure they are the correct ones. - Select when the pipeline should run. The possible options are:
- Run now - the pipeline starts running immediately after its creation.
- Time based - the pipeline starts running at the date and time you specify in the Date and Time fields.
- Recurring - the pipeline starts running according to the recurring schedule you set up in the Set Recurring Schedule window. You can set it up to run on specific weekdays at a certain time, or you can use cron expressions. Read here more information about scheduling pipelines.
- Click Create to create the pipeline or Cancel to abort the process. The Create new pipeline run page is closed.
The pipeline is created and displayed along with its details in the Pipelines page and in the selected package's ML Package Details page's Pipeline Runs tab. The pipeline runs according to the timeframe you chose while creating it.
During creation, any pipeline type can be either scheduled at a single future date and time, or with a recurring schedule. For example, a schedule may be set for a pipeline to execute on Sunday nights at 1am. This allows for models to be continuously updated as data is sent back from Human-In-the-Loop tasks and additionally allows for more efficient usage of AI Robot licenses.
To create a pipeline to be scheduled at a single future date, select the Time based option in the Create new pipeline run page.
To create a pipeline with a recurring schedule, select the Recurring option in the Create new pipeline run page.
A more complex schedule than daily at some time can be set by selecting the Advanced tab in the Set Recurring Schedule window and entering a cron expression. There are many free online tools to easily generate cron expressions.
You can only edit pipelines that haven't run yet.
- In the Pipelines page, click ⁝ next to a scheduled pipeline and select Details.
Alternatively, in the ML Package Details of a specific package, select the Pipeline Runs tab, click ⁝ next to a scheduled pipeline and select Details. The Pipeline Details page is displayed.
- Click Edit pipeline. The Edit pipeline run page is displayed.
- You can change the data directory of the scheduled pipeline, as well as the recurring schedule.
- Click Submit to save the changes. The scheduled pipeline is displayed in the Pipelines page with its updated information.
- In the Pipelines page, click ⁝ next to a pipeline and select Remove.
Alternatively, in the ML Package Details of a specific package, select the Pipeline Runs tab, click ⁝ next to a pipeline and select Remove. A confirmation dialog is displayed.
- Click Ok to delete the pipeline.
Note: Removing a queued or running pipeline first stops it and then removes it.
If you just want to stop a queued or running pipeline and look at its logs, click ⁝ next to it and select the Details option to navigate its corresponding Pipeline Details page. You can stop the pipeline from there.
You can consult more information about a specific pipeline or perform other actions.
- In the Pipelines page, click ⁝ next to a scheduled pipeline and select Details.
- Or, in the ML Package Details of a specific package, select the Pipeline Runs tab, click ⁝ next to a scheduled pipeline and select Details. The Pipeline Details page is displayed.
The information displayed and the actions you can perform here depend on the pipeline status.
The Pipeline Details page for Scheduled pipelines shows an information tab.
You can perform the following actions:
- Delete the pipeline.
- Edit the pipeline. In the displayed Edit pipeline run page, any fields can be updated. Selecting Run Now does not create a new pipeline, instead, it executes this pipeline immediately, thus removing it from the list of scheduled pipelines.
The Pipeline Details page for Queued pipelines shows an information tab.
You can perform the following action:
- Kill the pipeline. This removes the pipeline from the queue, so it won't be executed and it won't consume AI Robots. Its status changes to Killed.
The Pipeline Details page for Running pipelines shows an information tab and real-time logs.
You can perform the following action:
- Kill the pipeline. This immediately stops the pipeline and changes its status to Killed. The logs show the snapshot at the time the kill action was executed.
The Pipeline Details page for Failed pipelines shows an information tab and logs. Depending on the stage at which this pipeline failed, (partial) pipeline outputs are displayed.
You can perform the following action:
- Restart the pipeline. This adds a new pipeline to the queue, with the exact same parameters with which it was created. If the queue is empty, the pipeline immediately starts executing.
The Pipeline Details page for Killed pipelines shows an information tab. In addition, depending on the point at which this pipeline was killed, the pipeline details page may also include logs.
You can perform the following actions:
- Restart the pipeline.
- Remove the pipeline.
