### Apache Airflow version

main (development)

### What happened

The DataprocCreateBatchOperator (Google provider) handles the case when a batch_id already exists in the Dataproc API by 'reattaching' to a potentially running job.  

Current reattachment logic uses the non-deferrable method even when the operator is in deferrable mode.  

### What you think should happen instead

The operator should reattach in deferrable mode. 

### How to reproduce

Create a DAG with a task of DataprocCreateBatchOperator that is long running.  Make DataprocCreateBatchOperator deferrable in the constructor.  

Restart local Airflow to simulate having to 'reattach' to a running job in Google Cloud Dataproc. 

The operator resumes using the running job but in the code path for the non-derferrable logic.  

### Operating System

macOS 13.4.1 (22F82)

### Versions of Apache Airflow Providers

Current main.

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_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)

if not self.graceful_decommission_timeout:
            return None
        timeout = None
        match = re.match(r"^(\d+)([smdh])$", self.graceful_decommission_timeout)
        if match:
            if match.group(2) == "s":
                timeout = int(match.group(1))
            elif match.group(2) == "m":
                val = float(match.group(1))
                timeout = int(timedelta(minutes=val).total_seconds())
            elif match.group(2) == "h":
                val = float(match.group(1))
                timeout = int(timedelta(hours=val).total_seconds())
            elif match.group(2) == "d":
                val = float(match.group(1))
                timeout = int(timedelta(days=val).total_seconds())
        if not timeout:
            raise AirflowException(
                "DataprocClusterScaleOperator "
                " should be expressed in day, hours, minutes or seconds. "
                " i.e. 1d, 4h, 10m, 30s"
            )
        return {"seconds": timeout}
    def execute(self, context: Context) -> None: