### 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)

ti = context["ti"]
        run_id = context["run_id"]
        labels = {
            "dag_id": ti.dag_id,
            "task_id": ti.task_id,
            "run_id": run_id,
            "kubernetes_pod_operator": "True",
        }
        map_index = ti.map_index
        if map_index >= 0:
            labels["map_index"] = map_index
        if include_try_number:
            labels.update(try_number=ti.try_number)
        
        if context["dag"].parent_dag:
            labels["parent_dag_id"] = context["dag"].parent_dag.dag_id
        
        
        for label_id, label in labels.items():
            safe_label = pod_generator.make_safe_label_value(str(label))
            labels[label_id] = safe_label
        return labels
    @cached_property
    def pod_manager(self) -> PodManager:
        return PodManager(kube_client=self.client)
    def get_hook(self):
        warnings.warn("get_hook is deprecated. Please use hook instead.", DeprecationWarning, stacklevel=2)
        return self.hook
    @cached_property
    def hook(self) -> KubernetesHook: