### Apache Airflow version

2.4.1

### What happened

![image](https://user-images.githubusercontent.com/24224756/194797283-6c26ad63-d432-4c41-9f91-2dbc47417ec7.png)
when the sensor running, I can see the log above, but when I manual set the task state to failed or the task failed by other reason, I can't see log at here
![image](https://user-images.githubusercontent.com/24224756/194797633-0c7bf825-8e83-42af-8298-03491a26b7c9.png)
In other version airflow, like 2.3/2.2, this still happens

### What you think should happen instead

_No response_

### How to reproduce

_No response_

### Operating System

Ubuntu 20.04.4 LTS (Focal Fossa)

### Versions of Apache Airflow Providers

_No response_

### Deployment

Docker-Compose

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit 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)

pool: str | None = None,
        cfg_path: str | None = None,
        map_index: int = -1,
    ) -> list[str]:
        """
        Generates the shell command required to execute this task instance.
        :param dag_id: DAG ID
        :param task_id: Task ID
        :param run_id: The run_id of this task's DagRun
        :param mark_success: Whether to mark the task as successful
        :param ignore_all_deps: Ignore all ignorable dependencies.
            Overrides the other ignore_* parameters.
        :param ignore_depends_on_past: Ignore depends_on_past parameter of DAGs
            (e.g. for Backfills)
        :param wait_for_past_depends_before_skipping: Wait for past depends before marking the ti as skipped
        :param ignore_task_deps: Ignore task-specific dependencies such as depends_on_past
            and trigger rule
        :param ignore_ti_state: Ignore the task instance's previous failure/success
        :param local: Whether to run the task locally
        :param pickle_id: If the DAG was serialized to the DB, the ID
            associated with the pickled DAG
        :param file_path: path to the file containing the DAG definition
        :param raw: raw mode (needs more details)
        :param job_id: job ID (needs more details)
        :param pool: the Airflow pool that the task should run in
        :param cfg_path: the Path to the configuration file
        :return: shell command that can be used to run the task instance
        """
        cmd = ["airflow", "tasks", "run", dag_id, task_id, run_id]
        if mark_success: