### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Airflow version: 2.3.4 (Composer 2.1.12)

I've been using the DataprocCreateBatchOperator with the deferrable=True option. It worked well for the past few months, but an error started appearing on June 21, 2023, at 16:51 UTC. The error message is as follows:
```
grpc.aio._call.AioRpcError: <AioRpcError of RPC that terminated with:
	status = StatusCode.INVALID_ARGUMENT
	details = "Request contains an invalid argument."
	debug_error_string = "UNKNOWN:Error received from peer ipv4:74.125.69.95:443 {grpc_message:"Request contains an invalid argument.", grpc_status:3, created_time:"2023-06-21T16:51:22.992951359+00:00"}"
```

### What you think should happen instead

The name argument in the [hook code](https://github.com/apache/airflow/blob/main/airflow/providers/google/cloud/hooks/dataproc.py#L1746) follows the format "projects/PROJECT_ID/regions/DATAPROC_REGION/batches/BATCH_ID". However, according to the [Google Cloud DataProc API Reference](https://cloud.google.com/dataproc-serverless/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.GetBatchRequest), it should be in the format "projects/PROJECT_ID/locations/DATAPROC_REGION/batches/BATCH_ID .

### How to reproduce

just run a dataproc operator like this
```
create_batch = DataprocCreateBatchOperator(
        task_id="create_batch",
        batch_id="batch_test",
        deferrable=True,
)
```

### Operating System

Ubuntu 20.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Google Cloud Composer

### Deployment details

Composer 2.1.12

### 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)

self,
        batch_id: str,
        region: str,
        project_id: str,
        wait_check_interval: int = 10,
        retry: Retry | _MethodDefault = DEFAULT,
        timeout: float | None = None,
        metadata: Sequence[tuple[str, str]] = (),
    ) -> Batch:
        """Wait for a batch job to complete.
        After submission of a batch job, the operator waits for the job to
        complete. This hook is, however, useful in the case when Airflow is
        restarted or the task pid is killed for any reason. In this case, the
        creation would happen again, catching the raised AlreadyExists, and fail
        to this function for waiting on completion.
        :param batch_id: The batch ID.
        :param region: Cloud Dataproc region to handle the request.
        :param project_id: Google Cloud project ID that the cluster belongs to.
        :param wait_check_interval: The amount of time to pause between checks
            for job completion.
        :param retry: A retry object used to retry requests. If *None*, requests
            will not be retried.
        :param timeout: The amount of time, in seconds, to wait for the request
            to complete. If *retry* is specified, the timeout applies to each
            individual attempt.
        :param metadata: Additional metadata that is provided to the method.
        """