### Apache Airflow Provider(s)

docker

### Versions of Apache Airflow Providers

apache-airflow-providers-celery==3.1.0
apache-airflow-providers-docker==3.3.0

### Apache Airflow version

2.5.0

### Operating System

centos 7

### Deployment

Other Docker-based deployment

### Deployment details

Running an a docker-swarm cluster deployed locally. 

### What happened

Same issue as https://github.com/apache/airflow/issues/13675

With logging_enabled=True the DAG never completes and stays in running. 

When using DockerSwarmOperator together with the default enable_logging=True option, tasks do not succeed and stay in state running. When checking the docker service logs I can clearly see that the container ran and ended successfully. Airflow however does not recognize that the container finished and keeps the tasks in state running.

### What you think should happen instead

DAG should complete.

### How to reproduce

Docker-compose deployment:
```console
curl -LfO 'https://airflow.apache.org/docs/apache-airflow/2.5.0/docker-compose.yaml'
docker compose up airflow-init
docker compose up -d
```

DAG code:

```python
from airflow import DAG
from docker.types import Mount, SecretReference
from airflow.providers.docker.operators.docker_swarm import DockerSwarmOperator
from datetime import timedelta
from airflow.utils.dates import days_ago
from airflow.models import Variable


# Setup default args for the job
default_args = {
	'owner': 'airflow',
	'start_date': days_ago(2),
	'retries': 0
}
 
# Create the DAG
dag = DAG(
    'test_dag',         # DAG ID
    default_args=default_args,
    schedule_interval='0 0 * * *', 
    catchup=False
)

# # Create the DAG object
with dag as dag:
	  docker_swarm_task = DockerSwarmOperator(
			task_id="job_run",
			image="<any image>",
			execution_timeout=timedelta(minutes=5),
			command="<specific code>",
			api_version='auto',
			tty=True,
			enable_logging=True
		)
```

### 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)

"""
    Execute a command as an ephemeral docker swarm service.
    Example use-case - Using Docker Swarm orchestration to make one-time
    scripts highly available.
    A temporary directory is created on the host and
    mounted into a container to allow storing files
    that together exceed the default disk size of 10GB in a container.
    The path to the mounted directory can be accessed
    via the environment variable ``AIRFLOW_TMP_DIR``.
    If a login to a private registry is required prior to pulling the image, a
    Docker connection needs to be configured in Airflow and the connection ID
    be provided with the parameter ``docker_conn_id``.
    :param image: Docker image from which to create the container.
        If image tag is omitted, "latest" will be used.
    :param api_version: Remote API version. Set to ``auto`` to automatically
        detect the server's version.
    :param auto_remove: Auto-removal of the container on daemon side when the
        container's process exits.
        The default is False.
    :param command: Command to be run in the container. (templated)
    :param docker_url: URL of the host running the docker daemon.
        Default is unix://var/run/docker.sock
    :param environment: Environment variables to set in the container. (templated)
    :param force_pull: Pull the docker image on every run. Default is False.
    :param mem_limit: Maximum amount of memory the container can use.
        Either a float value, which represents the limit in bytes,
        or a string like ``128m`` or ``1g``.
    :param tls_ca_cert: Path to a PEM-encoded certificate authority
        to secure the docker connection.