### Description

Make resources in KubernetesPodOperator as templated. We need to modify this during several runs and it needs code change for each run.

### Use case/motivation

For running CPU and memory intensive workloads, we want to continuously optimise the "limt_cpu" and "limit_memory" parameters. Hence, we want to provide these parameters as a part of the pipeline definition.

### Related issues

_No response_

### Are you willing to submit a 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)

assert pod.metadata.name != name_base
        else:
            assert pod.metadata.name == name_base
        assert pod.spec.containers[0].image == image
        
        
        assert pod.metadata.labels == {
            "foo": "bar",
            "hello": "world",
            "dag_id": "dag",
            "kubernetes_pod_operator": "True",
            "task_id": "task",
            "try_number": "1",
            "airflow_version": mock.ANY,
            "airflow_kpo_in_cluster": str(k.hook.is_in_cluster),
            "run_id": "test",
        }
    @pytest.fixture
    def pod_template_file(self, tmp_path):
        pod_template_yaml = b"""
            apiVersion: v1
            kind: Pod
            metadata:
              name: hello
              namespace: templatenamespace
              labels:
                foo: bar
            spec:
              serviceAccountName: foo
              affinity: