Exporting model artifacts from AWS Clean Rooms ML - AWS Clean Rooms

Exporting model artifacts from AWS Clean Rooms ML

This task is optional and should be completed when you have assigned the CAN_RECEIVE_MODEL_OUTPUT member ability to a member of the collaboration.

After model training has completed, the member who trained the model can initiate the export of model artifacts. The member who trained the model chooses who will receive model artifacts, provided that member can receive results and a valid ML configuration.

Console
To configure a custom ML model algorithm (console)
  1. Sign in to the AWS Management Console and open the AWS Clean Rooms console at https://console.aws.amazon.com/cleanrooms.

  2. In the left navigation pane, choose Collaborations.

  3. On the Collaborations page, choose the collaboration that contains the custom model that you want to export.

  4. After the collaboration opens, choose the ML Models tab, then choose your model from the Custom trained model table

  5. On the custom trained model details page, click Export model output.

  6. For Export model output, for Export model output details, enter a Name and optional Description.

    Choose which member will receive the model artifacts in the Model output exported to members of collaboration drop down list.

  7. Choose Export.

    The results are exported to the following path in the Amazon S3 location that was specified in the ML configuration: yourSpecifiedS3Path/collaborationIdentifier/trainedModelName/callerAccountId/jobName. Only the Files to export, up to the maximum file size specified, that you selected when associating the configured model algorithm are exported.

API

To configure a custom ML model algorithm (API)

Initiate the model export by running the following code:

import boto3 acr_ml_client= boto3.client('cleanroomsml') acr_ml_client.start_trained_model_export_job( membershipIdentifier='membership_id', trainedModelArn='arn:aws:cleanrooms-ml:region:account:membership/membershipIdentifier/trained-model/identifier', outputConfiguration={ 'member': { 'accountId': 'model_output_receiver_account' } }, name='export_job_name' )

The results are exported to the following path in the Amazon S3 location that was specified in the ML configuration: yourSpecifiedS3Path/collaborationIdentifier/trainedModelName/callerAccountId/jobName. Only the filesToExport, up to the maxSize specified, that you selected when associating the configured model algorithm are exported.