### Description

Recently, we added [a new DAG dependencies view](https://github.com/apache/airflow/pull/13199) to the webserver. It would be helpful if a similar diagram could also be displayed/generated using the CLI. For now, only [one DAG can be displayed](http://airflow.apache.org/docs/apache-airflow/stable/usage-cli.html#exporting-dag-structure-as-an-image) using CLI.
![image](https://user-images.githubusercontent.com/12058428/137945580-6a33f919-2648-4980-bd2c-b40cfcacc9fe.png)

If anyone is interested, I will be happy to help with the review.

### Use case/motivation

* Keep parity between CLI and web serwer.
* Enable the writing of scripts that use these diagrams, e.g. for attaching in the documentation.

### Related issues

https://github.com/apache/airflow/pull/13199/files

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/cli/commands/dag_command.py
dag = dag.partial_subset(
            task_ids_or_regex=args.task_regex, include_upstream=not args.ignore_dependencies
        )
        if not dag.task_dict:
            raise AirflowException(
                f"There are no tasks that match '{args.task_regex}' regex. Nothing to run, exiting..."
            )
    run_conf = None
    if args.conf:
        run_conf = json.loads(args.conf)
    if args.dry_run:
        print(f"Dry run of DAG {args.dag_id} on {args.start_date}")
        dr = DagRun(dag.dag_id, execution_date=args.start_date)
        for task in dag.tasks:
            print(f"Task {task.task_id}")
            ti = TaskInstance(task, run_id=None)
            ti.dag_run = dr
            ti.dry_run()
    else:
        if args.reset_dagruns:
            DAG.clear_dags(
                [dag],
                start_date=args.start_date,
                end_date=args.end_date,
                confirm_prompt=not args.yes,
                include_subdags=True,
                dag_run_state=State.NONE,
            )
        try:
            dag.run(