### 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)

containers=[
                    k8s.V1Container(
                        image=self.image,
                        name=self.BASE_CONTAINER_NAME,
                        command=self.cmds,
                        ports=self.ports,
                        image_pull_policy=self.image_pull_policy,
                        resources=self.container_resources,
                        volume_mounts=self.volume_mounts,
                        args=self.arguments,
                        env=self.env_vars,
                        env_from=self.env_from,
                        security_context=self.container_security_context,
                    )
                ],
                image_pull_secrets=self.image_pull_secrets,
                service_account_name=self.service_account_name,
                host_network=self.hostnetwork,
                security_context=self.security_context,
                dns_policy=self.dnspolicy,
                scheduler_name=self.schedulername,
                restart_policy="Never",
                priority_class_name=self.priority_class_name,
                volumes=self.volumes,
            ),
        )
        pod = PodGenerator.reconcile_pods(pod_template, pod)
        if not pod.metadata.name:
            pod.metadata.name = _task_id_to_pod_name(self.task_id)
        if self.random_name_suffix: