MLflow model format required for the Register Model

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### Description & Motivation

I have problems when i want to register a model while using `pytorch-lightning`. It does not offer the option to `mlflow.log_model`. I would really appreciate if we can add this feature to `MLflowLogger` so it can improve experiments tracking and model versioning.

### Pitch

I want to know if it is possible to add this feature in this repo. If possible, then I would like to add the feature based on your guidelines.

### Alternatives

Refactor MLFlowLogger to bring mlflow.log_model into the picture.

### Additional context

When using pure `mlflow.log_model`, it enables "Register Model" in the experiment run of mlflow UI.

Since `MLFlowLogger` only support `log_artifact`, "Register Model" is never triggered.

cc @lantiga

Start with the MLFlowLogger entry point and trace its existing log_artifact support alongside the mlflow.log_model API. Clarify which model types and logger interface are in scope, then define completion as model logging that enables Register Model in the MLflow UI with appropriate coverage.

Written by the indexing model from the issue text.