### Apache Airflow version

main (development)

### Operating System

macOS 11.5.2

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### Deployment details

_No response_

### What happened

If your first try fails and you have retries enabled, the subsequent tries skip right to the final `next_method(**next_kwargs)` instead of starting with `execute` again.

### What you expected to happen

Like we reset things like start date, we should wipe `next_method` and `next_kwargs` so we can retry the task from the beginning.

### How to reproduce

_No response_

### 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/models/taskinstance.py
if activate_dag_runs is not None:
        warnings.warn(
            "`activate_dag_runs` parameter to clear_task_instances function is deprecated. "
            "Please use `dag_run_state`",
            DeprecationWarning,
            stacklevel=2,
        )
        if not activate_dag_runs:
            dag_run_state = False
    if dag_run_state is not False and tis:
        from airflow.models.dagrun import DagRun  
        run_ids_by_dag_id = defaultdict(set)
        for instance in tis:
            run_ids_by_dag_id[instance.dag_id].add(instance.run_id)
        drs = (
            session.query(DagRun)
            .filter(
                or_(
                    and_(DagRun.dag_id == dag_id, DagRun.run_id.in_(run_ids))
                    for dag_id, run_ids in run_ids_by_dag_id.items()
                )
            )
            .all()
        )
        for dr in drs:
            dr.state = dag_run_state
            dr.start_date = None
            if dag_run_state == State.QUEUED:
                dr.last_scheduling_decision = None
class TaskInstanceKey(NamedTuple):