# Contributing training data in AWS Clean Rooms ML
<a name="custom-model-training-data"></a>

After the collaboration creator has created the collaboration and invited members have joined, you are ready to contribute training data to the collaboration. Any member can contribute training data.

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#### [ Console ]

**To contribute training data (console)**

1. Sign in to the AWS Management Console and open the AWS Clean Rooms console at [https://console.aws.amazon.com/cleanrooms](https://console.aws.amazon.com/cleanrooms/home).

1. In the left navigation pane, choose **Tables**.

1. On the **Tables** page, choose **Configure new table**.

1. For **Configure new table**, for **Data source,** choose **Amazon S3**, **Amazon Athena**, or **Snowflake** and complete the following steps, based on your data source:    
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/clean-rooms/latest/userguide/custom-model-training-data.html)

1. Choose **Configure new table**. 

1. On the table details page, choose **Configure analysis rule** to configure a custom analysis rule for this table. A custom analysis rule limits access to your data. You can either allow a specific set of pre-authorized queries on your data or allow a specific set of accounts to query your data.

   1. For **Analysis rule type**, choose **Custom** and for **Creation method**, choose **Guided flow**.

   1. Choose **Next**.

   1. For **Specify analysis controls**, choose between **Review each new analysis** and **Allow any analysis by specific collaborators**. 

   1. Choose **Next**.

   1. (Optional) For **Specify analysis results controls**, for **Columns not allowed in output** specify whether you want to exclude any columns from the output. If you choose **None**, no columns are excluded from the output. If you choose **Custom list**, you can specify certain columns that will be removed from the output.

   1. For **Additional analyses applied to output** specify whether you want to allow, deny, or require an additional analysis before results are generated.

   1. Choose **Next**.

   1. (Optional) For **Set differential privacy**, choose **Turn off**.

   1. Choose **Next**.

   1. Review the information on the **Review and configure** page, then choose **Configure analysis rule**.

1. From the table details page, choose **Associate to collaboration**.

1. In the **Associate table** dialog box, select the collaboration that you want to associate this table to and choose **Choose collaboration**. 

1. On the **Associate table** page, review and verify the information in **Table association details**, **Service access**, and **Tags**. Choose **Associate table**.

1. In the **Tables associated by you** table, select the radio button next to the table that you just associated. From the **Actions** menu, choose **Configure** in the **Collaboration analysis rule** group.

1. On the **Configure collaboration analysis rule** page, for **Allowed additional analyses**, choose whether any collaboration members or specific collaboration members can perform additional analyses.

   For **Results delivery**, choose which members are allowed to receive results from query outputs.

1. Choose **Configure analysis rule**.

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#### [ API ]

To contribute training data (API)

1. Configure an existing AWS Glue table for use in AWS Clean Rooms by providing the table and the columns that can be used.

   Run the following code with your specific parameters.

   ```
   import boto3 
   acr_client= boto3.client('cleanrooms')
   
   acr_client.create_configured_table(
       name='configured_table_name',
       tableReference= {
           'glue': {
               'tableName': 'glue_table_name',
               'databaseName': 'glue_database_name'
           }
       },
       analysisMethod="DIRECT_QUERY",
       allowedColumns=["column1", "column2", "column3",...]
   )
   ```

1. Configure a custom analysis rule that limits access to your data. You can either allow a specific set of pre-authorized queries on your data or allow a specific set of accounts to query your data.

   Run the following code with your specific parameters.

   ```
   import boto3 
   acr_client= boto3.client('cleanrooms')
   
   acr_client.create_configured_table_analysis_rule(
       configuredTableIdentifier='configured_table_id',
       analysisRuleType='CUSTOM',
       analysisRulePolicy= {
           'v1': {
               'custom': {
                   'allowedAnalyses': ['ANY_QUERY'],
                   'allowedAnalysisProviders': ['query_runner_account'],
                   'additionalAnalyses': "REQUIRED"
               }
           }
       }
   )
   ```

   In this example, a specific account is allowed to run any query on the data and an additional analysis is required.

1. Associate a configured table to the collaboration and provide a service access role to the AWS Glue tables.

   Run the following code with your specific parameters.

   ```
   import boto3 
   acr_client= boto3.client('cleanrooms')
   
   acr_client.create_configured_table_association(
       name='configured_table_association_name',
       membershipIdentifier='membership_id',
       configuredTableIdentifier='configured_table_id',
       roleArn='arn:aws:iam::account:role/role_name'
   )
   ```
**Note**  
This service role has permissions to the tables. The service role is assumable only by AWS Clean Rooms to run allowed queries on behalf of the member who can query. No collaboration members (other than the data owner) have access to the underlying tables in the collaboration. The data owner can turn off differential privacy to make their tables available for querying by other members.

1. Finally, add an analysis rule to the configured table association.

   Run the following code with your specific parameters.

   ```
   import boto3
   acr_client= boto3.client('cleanrooms')
   
   acr_client.create_configured_table_association_analysis_rule(
       configuredTableAssociationIdentifier='configured_table_association_identifier',
       membershipIdentifier='membership_id',
       configuredTableIdentifier='configured_table_id',
       analysisRuleType = 'CUSTOM',
       analysisRulePolicy= {
           'v1': {
               'custom': {
                   'allowedAdditionalAnalyses': ['configured_model_algorithm_association_arns'],
                   'allowedResultReceivers': ['query_runner_account']
               }
           }
       }
   )
   ```

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