### Apache Airflow version

2.1.3 (latest released)

### Operating System

macOS Big Sur 11.3.1

### Versions of Apache Airflow Providers

n/a

### Deployment

Astronomer

### Deployment details

default Astronomer deployment with some test DAGs

### What happened

In the UI for DAGRuns there are checkboxes that allow multiple DAGRuns to be selected.

![image](https://user-images.githubusercontent.com/89415310/133841290-94cda771-9bb3-4677-8530-8c2861525719.png)

Within the Actions menu on this same view, there is a Delete option which allows multiple DAGRuns to be deleted at the same time.

![image](https://user-images.githubusercontent.com/89415310/133841362-3c7fc81d-a823-4f41-8b1d-64be425810ce.png)

Task instance view on the UI does not offer the same option, even though Task Instances can be individually deleted with the trash can button.

![image](https://user-images.githubusercontent.com/89415310/133841442-3fee0930-a6bb-4035-b172-1d10b85f3bf6.png)


### What you expected to happen

I expect that the Task Instances can also be bulk deleted, in the same way that DAGRuns can be.

### How to reproduce

Open up Task Instance and DAGRun views from the Browse tab and compare the options in the Actions dropdown menus.

### Anything else

_No response_

### Are you willing to submit PR?

- [X] 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/www/views.py
self,
        dag_runs: Iterable[DagRun],
        dag: DAG,
        base_date: DateTime,
        session: settings.Session,
    ):
        """Returns formatted dag_runs for Tree view"""
        dates = sorted(dag_runs.keys())
        min_date = min(dag_runs, default=None)
        task_instances = {
            (ti.task_id, ti.execution_date): ti
            for ti in dag.get_task_instances(start_date=min_date, end_date=base_date, session=session)
        }
        expanded = set()
        
        
        
        node_count = 0
        node_limit = 5000 / max(1, len(dag.leaves))
        def encode_ti(task_instance: Optional[models.TaskInstance]) -> Optional[List]: