Creating a solution version (console)Creating a solution version (AWS CLI)Creating a solution version (AWS SDKs)

Creating a solution version

After you complete Creating and configuring a solution, you are ready to start training:

If your solution uses automatic training, the solution creates solution versions for you at the training frequency you specify. By default, all new solutions use automatic training to create a new solution version every 7 days. You can still manually create solution versions. For more information, see Configuring automatic training.
If you turn off auto training for your solution or you want to manually train, you can manually create a solution version. A solution version refers to a trained machine learning model. You can create a solution version using the console, AWS Command Line Interface (AWS CLI), or AWS SDKs. If your solution version has a status of CREATE_PENDING or CREATE_IN_PROGRESS, you can use the StopSolutionVersionCreation operation to stop the solution version creation process. See Stopping the creation of a solution version.

Topics

Creating a solution version (console)
Creating a solution version (AWS CLI)
Creating a solution version (AWS SDKs)
Stopping the creation of a solution version

Creating a solution version (console)

When you initially create your solution with the Amazon Personalize console, you also create a solution version. On the solution details page, you can track training progress in the Solution versions section. When training is complete, the status is Active and you are ready to . See Creating a campaign or Batch recommendations and user segments (custom resources).

If you want to create an additional solution version for an existing solution, create a new solution version from the solution overview page as follows.

To create a new solution version

Open the Amazon Personalize console at https://console.aws.amazon.com/personalize/home and sign into your account.
Navigate to the dataset groups page and choose the dataset group with your new solution.
In the navigation pane, under Custom resources, choose Solutions and recipes.
On the Solution and recipes page, choose the solution you want to create a solution version for.
On the solution overview page, choose Create solution version to start training a new model.

On the solution details page, you can track training progress in the Solution versions section. When training is complete, the status is Active you can evaluate it using metrics supplied by Amazon Personalize. For more information, see Evaluating a solution version with metrics.

If training does not complete because of an error, you are not charged for the training. If your solution version has a status of CREATE_PENDING or CREATE_IN_PROGRESS, you can stop the solution version creation process. To stop solution version creation, navigate to the solution version details page and choose Stop. See Stopping the creation of a solution version.

How you use an active solution version depends on how you get recommendations:

For real-time recommendations, you deploy an ACTIVE solution version with an Amazon Personalize campaign. You use the campaign to get recommendations for your users. See Creating a campaign.
For batch recommendations, you specify an ACTIVE solution version when you create a batch inference job or batch segment job. See Batch recommendations and user segments (custom resources).

Creating a solution version (AWS CLI)

When your solution is ACTIVE, train the model by running the following command. Replace solution arn with the solution Amazon Resource Name (ARN) from Creating and configuring a solution.


aws personalize create-solution-version \
  --solution-arn solution arn

The solution version ARN is displayed, for example:


{
  "solutionVersionArn": "arn:aws:personalize:us-west-2:acct-id:solution/SolutionName/<version-id>"
}

Check the training status of the solution version by using the describe-solution-version command. Provide the solution version ARN that was returned in the previous step. For more information about the API, see DescribeSolutionVersion.


aws personalize describe-solution-version \
  --solution-version-arn solution version arn

The properties of the solution version and the training status are displayed. Initially, the status shows as CREATE PENDING, for example:


{
  "solutionVersion": {
      "solutionVersionArn": "arn:aws:personalize:us-west-2:acct-id:solution/solutionName/<version-id>",
      ...,
      "status": "CREATE PENDING"
  }
}

Training is complete when the status is ACTIVE and you can evaluate it using metrics supplied by Amazon Personalize. For more information, see Evaluating a solution version with metrics. If training does not complete because of an error, you are not charged for the training.

If your solution version has a status of CREATE_PENDING or CREATE_IN_PROGRESS, you can use the StopSolutionVersionCreation operation to stop the solution version creation process. See Stopping the creation of a solution version.

How you use an active solution version depends on how you get recommendations:

For real-time recommendations, you deploy an ACTIVE solution version with an Amazon Personalize campaign. You use the campaign to get recommendations for your users. See Creating a campaign.
For batch recommendations, you specify an ACTIVE solution version when you create a batch inference job or batch segment job. See Batch recommendations and user segments (custom resources).

Creating a solution version (AWS SDKs)

When your solution is ACTIVE, use the following code to create a solution version. Specify the Amazon Resource Name (ARN) from Creating and configuring a solution. Use the DescribeSolutionVersion operation to retrieve the solution version's status.

SDK for Python (Boto3)


import boto3

personalize = boto3.client('personalize')
# Store the solution ARN
solution_arn = 'solution arn'
        
# Use the solution ARN to get the solution status.
solution_description = personalize.describe_solution(solutionArn = 'solution_arn')['solution']
print('Solution status: ' + solution_description['status'])

# Use the solution ARN to create a solution version.
print ('Creating solution version')
response = personalize.create_solution_version(solutionArn = solution_arn)
solution_version_arn = response['solutionVersionArn']
print('Solution version ARN: ' + solution_version_arn)

# Use the solution version ARN to get the solution version status.
solution_version_description = personalize.describe_solution_version(
    solutionVersionArn = solution_version_arn)['solutionVersion']
print('Solution version status: ' + solution_version_description['status'])

SDK for Java 2.x


public static String createPersonalizeSolutionVersion(PersonalizeClient personalizeClient, String solutionArn) {
        long maxTime = 0;
        long waitInMilliseconds = 30 * 1000; // 30 seconds
        String solutionStatus = "";
        String solutionVersionStatus = "";
        String solutionVersionArn = "";

        try {
            DescribeSolutionRequest describeSolutionRequest = DescribeSolutionRequest.builder()
                .solutionArn(solutionArn)
                .build();
            
            maxTime = Instant.now().getEpochSecond() + 3 * 60 * 60;

            // Wait until solution is active. 
            while (Instant.now().getEpochSecond() < maxTime) {

                solutionStatus = personalizeClient.describeSolution(describeSolutionRequest).solution().status();
                System.out.println("Solution status: " + solutionStatus);

                if (solutionStatus.equals("ACTIVE") || solutionStatus.equals("CREATE FAILED")) {
                    break;
                }
                try {
                    Thread.sleep(waitInMilliseconds);
                } catch (InterruptedException e) {
                    System.out.println(e.getMessage());
                }
            }
            
            // Once the solution is active, start creating a solution version.
            
            if (solutionStatus.equals("ACTIVE")) {

                CreateSolutionVersionRequest createSolutionVersionRequest = CreateSolutionVersionRequest.builder()
                    .solutionArn(solutionArn)
                    .build();
                
                CreateSolutionVersionResponse createSolutionVersionResponse = personalizeClient.createSolutionVersion(createSolutionVersionRequest);
                solutionVersionArn = createSolutionVersionResponse.solutionVersionArn();

                System.out.println("Solution version ARN: " + solutionVersionArn);

                DescribeSolutionVersionRequest describeSolutionVersionRequest = DescribeSolutionVersionRequest.builder() 
                    .solutionVersionArn(solutionVersionArn)
                    .build();
                
                maxTime = Instant.now().getEpochSecond() + 3 * 60 * 60;
                
                while (Instant.now().getEpochSecond() < maxTime) {

                    // Use the solution version ARN to get the solution version status.
                    solutionVersionStatus = personalizeClient.describeSolutionVersion(describeSolutionVersionRequest).solutionVersion().status();
                    System.out.println("Solution version status: " + solutionVersionStatus);
    
                    if (solutionVersionStatus.equals("ACTIVE") || solutionVersionStatus.equals("CREATE FAILED")) {
                        break;
                    }
                    try {
                        Thread.sleep(waitInMilliseconds);
                    } catch (InterruptedException e) {
                        System.out.println(e.getMessage());
                    }
                }
                return solutionVersionArn;
            }
        } catch(PersonalizeException e) {
            System.err.println(e.awsErrorDetails().errorMessage());
            System.exit(1);
        }
        return "";
    }

SDK for JavaScript v3


// Get service clients module and commands using ES6 syntax.
import { CreateSolutionVersionCommand } from
  "@aws-sdk/client-personalize";
import { personalizeClient } from "./libs/personalizeClients.js";
// Or, create the client here.
// const personalizeClient = new PersonalizeClient({ region: "REGION"});

// Set the solution version parameters.
export const solutionVersionParam = {
  solutionArn: 'SOLUTION_ARN' /* required */
}

export const run = async () => {
  try {
    const response = await personalizeClient.send(new CreateSolutionVersionCommand(solutionVersionParam));
    console.log("Success", response);
    return response; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();

To check the current solution version status, call the DescribeSolutionVersion operation and pass the ARN of the solution version returned from the CreateSolutionVersion operation. Training is complete when the status is ACTIVE and you can evaluate it using metrics supplied by Amazon Personalize. For more information, see Evaluating a solution version with metrics. If training does not complete because of an error, you are not charged for the training.

How you use an active solution version depends on how you get recommendations:

For real-time recommendations, you deploy an ACTIVE solution version with an Amazon Personalize campaign. You use the campaign to get recommendations for your users. See Creating a campaign.
For batch recommendations, you specify an ACTIVE solution version when you create a batch inference job or batch segment job. See Batch recommendations and user segments (custom resources).

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Document Conventions

Cloning a solution (console)

Stopping the creation of a solution version