The "template_ext" mechanism is useful for automatically loading and jinja-processing files which are specified in parameters of Operators. However this might lead to certain problems for example (from slack conversation):

```
The templated_fields in  KubernetesPodOperator seems cause the error airflow jinja2.exceptions.TemplateNotFound when some character in the column, e.g / in env_vars.
The code got error.
env_vars=[
            k8s.V1EnvVar(
                name="GOOGLE_APPLICATION_CREDENTIALS",
                value="/var/secrets/google/service-account.json",
            ),
```

I believe the behaviour changed comparing to not-so-long-past. Some of the changes with processing parameters with jinja recursively caused this template behaviour to be applied also nested parameters like above.

There were also several discussions and user confusion with this behaviour: #15942, #16922

There are two ways we could improve the situation:
1) limit the "template_extension" resolution to only direct string kwargs passed to the operator (I think this is no brainer and we should do it)

2) propose some "escaping" mechanism, where you could either disable template_extension processing entirely or somehow mark the parameters that should not be treated as templates.

Here I have several proposals:

a) we could add "skip_template_ext_processing" or similar parameter in BaseOperator <- I do not like it as many operators rely on this behaviour for a good reason
b) we could add "template_ext" parameter in the operator that could override the original class-level-field <- I like this one a lot
c) we could add "disable_template_ext_pattern"  (str) parameter where we could specify list of regexp's where we could filter out only specific values <- this one will allow to disable template_ext much more "selectively" - only for certain parameters.


UPDATE: It only affects Kubenernetes Pod Operator due to it's recursive behaviour and should be fixed there.

airflow/providers/cncf/kubernetes/operators/kubernetes_pod.py
and limit_gpu, which will be used to generate airflow.kubernetes.pod.Resources.
        See also kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
    :type resources: k8s.V1ResourceRequirements
    :param affinity: A dict containing a group of affinity scheduling rules.
    :type affinity: k8s.V1Affinity
    :param config_file: The path to the Kubernetes config file. (templated)
        If not specified, default value is ``~/.kube/config``
    :type config_file: str
    :param node_selectors: A dict containing a group of scheduling rules.
    :type node_selectors: dict
    :param image_pull_secrets: Any image pull secrets to be given to the pod.
        If more than one secret is required, provide a
        comma separated list: secret_a,secret_b
    :type image_pull_secrets: List[k8s.V1LocalObjectReference]
    :param service_account_name: Name of the service account
    :type service_account_name: str
    :param is_delete_operator_pod: What to do when the pod reaches its final
        state, or the execution is interrupted.
        If False (default): do nothing, If True: delete the pod
    :type is_delete_operator_pod: bool
    :param hostnetwork: If True enable host networking on the pod.
    :type hostnetwork: bool
    :param tolerations: A list of kubernetes tolerations.
    :type tolerations: List[k8s.V1Toleration]
    :param security_context: security options the pod should run with (PodSecurityContext).
    :type security_context: dict
    :param dnspolicy: dnspolicy for the pod.
    :type dnspolicy: str
    :param schedulername: Specify a schedulername for the pod
    :type schedulername: str