### 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)

@pytest.fixture(autouse=True)
    def setup(self, dag_maker):
        self.create_pod_patch = patch(f"{POD_MANAGER_CLASS}.create_pod")
        self.await_pod_patch = patch(f"{POD_MANAGER_CLASS}.await_pod_start")
        self.await_pod_completion_patch = patch(f"{POD_MANAGER_CLASS}.await_pod_completion")
        self._default_client_patch = patch(f"{HOOK_CLASS}._get_default_client")
        self.create_mock = self.create_pod_patch.start()
        self.await_start_mock = self.await_pod_patch.start()
        self.await_pod_mock = self.await_pod_completion_patch.start()
        self._default_client_mock = self._default_client_patch.start()
        self.dag_maker = dag_maker
        yield
        patch.stopall()
    def run_pod(self, operator: KubernetesPodOperator, map_index: int = -1) -> k8s.V1Pod:
        with self.dag_maker(dag_id="dag") as dag:
            operator.dag = dag
        dr = self.dag_maker.create_dagrun(run_id="test")
        (ti,) = dr.task_instances
        ti.map_index = map_index
        self.dag_run = dr
        context = ti.get_template_context(session=self.dag_maker.session)
        self.dag_maker.session.commit()  
        remote_pod_mock = MagicMock()
        remote_pod_mock.status.phase = "Succeeded"
        self.await_pod_mock.return_value = remote_pod_mock
        operator.execute(context=context)
        return self.await_start_mock.call_args[1]["pod"]
    def sanitize_for_serialization(self, obj):