The code block that the team is using is correct and does not need any changes to accomplish the task. The update_registered_model method of the MlflowClient class can be used to update the metadata of a registered model, such as its name or description. The method takes the following parameters:
name: The name of the registered model to update.
description: The new description for the registered model.
new_name: The new name for the registered model.
The method returns a RegisteredModel object that represents the updated registered model1
The other options are incorrect because:
A. Replacing update_registered_model with update_model_version would not update the metadata of the registered model, but rather the metadata of a specific model version. The update_model_version method can be used to update the stage, description, or name of a model version. The method takes the following parameters:
name: The name of the registered model that contains the model version to update.
version: The version number of the model version to update.
stage: The new stage for the model version.
description: The new description for the model version.
archive_existing_versions: Whether to archive other model versions in the same stage.
new_name: The new name for the model version.
The method returns a ModelVersion object that represents the updated model version2
C. Replacing description with artifact would not update the description of the registered model, but rather raise an error, as artifact is not a valid parameter for the update_registered_model method. The artifact parameter is used for the log_model or save_model methods, which can be used to log or save a model with a specific flavor and artifact path34
D. Replacing client.update_registered_model with mlflow would not update the registered model, but rather raise an error, as mlflow is not a valid method, but rather a module that contains various submodules and functions. The mlflow module does not have an update_registered_model function, but rather the MlflowClient class has an update_registered_model method5
E. Adding a Python model as an argument to update_registered_model would not update the registered model, but rather raise an error, as a Python model is not a valid argument for the update_registered_model method. The update_registered_model method does not take a model as an argument, but rather the name and description of the registered model to update. To add a Python model to the Model Registry, the create_model_version method of the MlflowClient class can be used, which takes the following parameters:
name: The name of the registered model to which to add the model version.
source: The source of the model, such as a local path, a run ID, or a model URI.
run_id: The run ID that generated the model, if any.
tags: A dictionary of key-value pairs to tag the model version with.
description: A description for the model version.
The method returns a ModelVersion object that represents the created model version6
References:
mlflow.tracking.client.MlflowClient.update_registered_model — MLflow 2.9.1 documentation
mlflow.tracking.client.MlflowClient.update_model_version — MLflow 2.9.1 documentation
mlflow..log_model — MLflow 2.9.1 documentation
mlflow..save_model — MLflow 2.9.1 documentation
mlflow — MLflow 2.9.1 documentation
mlflow.tracking.client.MlflowClient.create_model_version — MLflow 2.9.1 documentation
