### 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)

#
#
from __future__ import annotations
import re
from contextlib import nullcontext
from unittest import mock
from unittest.mock import MagicMock, patch
import pendulum
import pytest
from kubernetes.client import ApiClient, models as k8s
from airflow.exceptions import AirflowException
from airflow.models import DAG, DagModel, DagRun, TaskInstance
from airflow.models.xcom import XCom
from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import (
    KubernetesPodOperator,
    _suppress,
    _task_id_to_pod_name,
)
from airflow.utils import timezone
from airflow.utils.session import create_session
from airflow.utils.types import DagRunType
from tests.test_utils import db
DEFAULT_DATE = timezone.datetime(2016, 1, 1, 1, 0, 0)
KPO_MODULE = "airflow.providers.cncf.kubernetes.operators.kubernetes_pod"
POD_MANAGER_CLASS = "airflow.providers.cncf.kubernetes.utils.pod_manager.PodManager"
POD_MANAGER_MODULE = "airflow.providers.cncf.kubernetes.utils.pod_manager"
HOOK_CLASS = "airflow.providers.cncf.kubernetes.operators.kubernetes_pod.KubernetesHook"
@pytest.fixture(scope="function", autouse=True)
def clear_db():