Add capability to view metrics in graph/chart form at the parent job level.

Problem Statement

Currently metrics are only provided at the child job level. Because of this, charts/graphs can't be created properly to give better insights.

Proposed Solution

Metrics need to be visible at the parent job level to be able to create charts and graphs for the experiment.
Whenever a metrics log call is made, another call could be made with the run_id field populated with the parent's run id.

Example:

mlflow.log_metric("scoring_mse", mse) 
mlflow.log_metrics("scoring_mse", mse,  run_id=parent_run_id)

The following is an example of how to retrieve the parent run id:

current_run_id = active_run().info.run_id
parent_run = get_parent_run(run_id=current_run_id)
parent_run_id = parent_run.info.run_id

Once metrics are populated to the parent job, you can have dashboards like this:

Acceptance Criteria

• Metrics are propagated to the parent run.
• Charts/Graphs are populated.
• A markdown doc is created giving details on the why and how it was done.

No repository files or tests are named; start by tracing the Python MLflow metric-logging path and the active_run/get_parent_run entry points shown in the issue. Determine where parent-run metrics and chart data are handled. Done means metrics propagate to the parent run, charts or graphs are populated, and a markdown document explains the rationale and usage.