### 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)

:param region: Cloud Dataproc region to handle the request.
        :param cluster_name: The cluster name.
        :param cluster: Changes to the cluster. If a dict is provided, it must
            be of the same form as the protobuf message
            :class:`~google.cloud.dataproc_v1.types.Cluster`.
        :param update_mask: Specifies the path, relative to ``Cluster``, of the
            field to update. For example, to change the number of workers in a
            cluster to 5, this would be specified as
            ``config.worker_config.num_instances``, and the ``PATCH`` request
            body would specify the new value:
            .. code-block:: python
                {"config": {"workerConfig": {"numInstances": "5"}}}
            Similarly, to change the number of preemptible workers in a cluster
            to 5, this would be ``config.secondary_worker_config.num_instances``
            and the ``PATCH`` request body would be:
            .. code-block:: python
                {"config": {"secondaryWorkerConfig": {"numInstances": "5"}}}
            If a dict is provided, it must be of the same form as the protobuf
            message :class:`~google.cloud.dataproc_v1.types.FieldMask`.
        :param graceful_decommission_timeout: Timeout for graceful YARN
            decommissioning. Graceful decommissioning allows removing nodes from
            the cluster without interrupting jobs in progress. Timeout specifies
            how long to wait for jobs in progress to finish before forcefully
            removing nodes (and potentially interrupting jobs). Default timeout
            is 0 (for forceful decommission), and the maximum allowed timeout is
            one day.
            Only supported on Dataproc image versions 1.2 and higher.
            If a dict is provided, it must be of the same form as the protobuf
            message :class:`~google.cloud.dataproc_v1.types.Duration`.
        :param request_id: A unique id used to identify the request. If the