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CreateSolutionVersionRequest

Source code in docs_src/capo_personalize/types/create_solution_version_request.py 
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class CreateSolutionVersionRequest(TypedDict, closed=True):
    name: NotRequired["capo_personalize.types.name.Name"]
    """<p>The name of the solution version.</p>"""
    solution_arn: "capo_personalize.types.arn.Arn"
    """<p>The Amazon Resource Name (ARN) of the solution containing the training configuration information.</p>"""
    training_mode: NotRequired["capo_personalize.types.training_mode.TrainingMode"]
    """<p>The scope of training to be performed when creating the solution version. The default is <code>FULL</code>. This creates a completely new model based on the entirety of the training data from the datasets in your dataset group. </p> <p>If you use <a href="https://docs.aws.amazon.com/personalize/latest/dg/native-recipe-new-item-USER_PERSONALIZATION.html">User-Personalization</a>, you can specify a training mode of <code>UPDATE</code>. This updates the model to consider new items for recommendations. It is not a full retraining. You should still complete a full retraining weekly. If you specify <code>UPDATE</code>, Amazon Personalize will stop automatic updates for the solution version. To resume updates, create a new solution with training mode set to <code>FULL</code> and deploy it in a campaign. For more information about automatic updates, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/use-case-recipe-features.html#maintaining-with-automatic-updates">Automatic updates</a>. </p> <p>The <code>UPDATE</code> option can only be used when you already have an active solution version created from the input solution using the <code>FULL</code> option and the input solution was trained with the <a href="https://docs.aws.amazon.com/personalize/latest/dg/native-recipe-new-item-USER_PERSONALIZATION.html">User-Personalization</a> recipe or the legacy <a href="https://docs.aws.amazon.com/personalize/latest/dg/native-recipe-hrnn-coldstart.html">HRNN-Coldstart</a> recipe.</p>"""
    tags: NotRequired["capo_personalize.types.tags.Tags"]
    """<p>A list of <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">tags</a> to apply to the solution version.</p>"""

name instance-attribute 

name: NotRequired[Name]

The name of the solution version.

solution_arn instance-attribute 

solution_arn: Arn

The Amazon Resource Name (ARN) of the solution containing the training configuration information.

tags instance-attribute 

tags: NotRequired[Tags]

A list of tags to apply to the solution version.

training_mode instance-attribute 

training_mode: NotRequired[TrainingMode]

The scope of training to be performed when creating the solution version. The default is FULL. This creates a completely new model based on the entirety of the training data from the datasets in your dataset group.

If you use User-Personalization, you can specify a training mode of UPDATE. This updates the model to consider new items for recommendations. It is not a full retraining. You should still complete a full retraining weekly. If you specify UPDATE, Amazon Personalize will stop automatic updates for the solution version. To resume updates, create a new solution with training mode set to FULL and deploy it in a campaign. For more information about automatic updates, see Automatic updates.

The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the legacy HRNN-Coldstart recipe.