### Apache Airflow version

2.5.1

### What happened

If an Operator specifies a template_field with `execution_timeout` then the DAG will serialize correctly but throw an error during deserialization. This causes the entire scheduler to crash and breaks the application.

### What you think should happen instead

The scheduler should never go down because of some code someone wrote, this should probably throw an error during serialization.

### How to reproduce

Define an operator like this
```
class ExecutionTimeoutOperator(BaseOperator):
    template_fields = ("execution_timeout", )

    def __init__(self, execution_timeout: timedelta, **kwargs):
        super().__init__(**kwargs)
        self.execution_timeout = execution_timeout
```
then make a dag like this
```
dag = DAG(
    "serialize_with_default",
    schedule_interval="0 12 * * *",
    start_date=datetime(2023, 2, 28),
    catchup=False,
    default_args={
        "execution_timeout": timedelta(days=4),
    },
)

with dag:
    execution = ExecutionTimeoutOperator(task_id="execution", execution_timeout=timedelta(hours=1))
```
that will break the scheduler, you can force the stack trace by doing this
```
from airflow.models import DagBag
db = DagBag('dags/', read_dags_from_db=True)
db.get_dag('serialize_with_default')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.9/site-packages/airflow/utils/session.py", line 75, in wrapper
    return func(*args, session=session, **kwargs)
  File "/usr/local/lib/python3.9/site-packages/airflow/models/dagbag.py", line 190, in get_dag
    self._add_dag_from_db(dag_id=dag_id, session=session)
  File "/usr/local/lib/python3.9/site-packages/airflow/models/dagbag.py", line 265, in _add_dag_from_db
    dag = row.dag
  File "/usr/local/lib/python3.9/site-packages/airflow/models/serialized_dag.py", line 218, in dag
    dag = SerializedDAG.from_dict(self.data)
  File "/usr/local/lib/python3.9/site-packages/airflow/serialization/serialized_objects.py", line 1287, in from_dict
    return cls.deserialize_dag(serialized_obj["dag"])
  File "/usr/local/lib/python3.9/site-packages/airflow/serialization/serialized_objects.py", line 1194, in deserialize_dag
    v = {task["task_id"]: SerializedBaseOperator.deserialize_operator(task) for task in v}
  File "/usr/local/lib/python3.9/site-packages/airflow/serialization/serialized_objects.py", line 1194, in <dictcomp>
    v = {task["task_id"]: SerializedBaseOperator.deserialize_operator(task) for task in v}
  File "/usr/local/lib/python3.9/site-packages/airflow/serialization/serialized_objects.py", line 955, in deserialize_operator
    cls.populate_operator(op, encoded_op)
  File "/usr/local/lib/python3.9/site-packages/airflow/serialization/serialized_objects.py", line 864, in populate_operator
    v = cls._deserialize_timedelta(v)
  File "/usr/local/lib/python3.9/site-packages/airflow/serialization/serialized_objects.py", line 513, in _deserialize_timedelta
    return datetime.timedelta(seconds=seconds)
TypeError: unsupported type for timedelta seconds component: str
```

### Operating System

Mac 13.1 (22C65)

### Versions of Apache Airflow Providers

apache-airflow-providers-amazon==5.1.0
apache-airflow-providers-apache-hdfs==3.2.0
apache-airflow-providers-apache-hive==5.1.1
apache-airflow-providers-apache-spark==4.0.0
apache-airflow-providers-celery==3.1.0
apache-airflow-providers-cncf-kubernetes==5.1.1
apache-airflow-providers-common-sql==1.3.3
apache-airflow-providers-datadog==3.1.0
apache-airflow-providers-ftp==3.3.0
apache-airflow-providers-http==4.1.1
apache-airflow-providers-imap==3.1.1
apache-airflow-providers-jdbc==3.3.0
apache-airflow-providers-jenkins==3.2.0
apache-airflow-providers-mysql==4.0.0
apache-airflow-providers-pagerduty==3.1.0
apache-airflow-providers-postgres==5.4.0
apache-airflow-providers-presto==4.2.1
apache-airflow-providers-slack==7.2.0
apache-airflow-providers-sqlite==3.3.1
apache-airflow-providers-ssh==3.4.0

### Deployment

Docker-Compose

### Deployment details

I could repro this with docker-compose and in a helm backed deployment so I don't think it's really related to the deployment details

### Anything else

In the serialization code there are two pieces of logic that are in
direct conflict with each other. The first dictates how template fields
are serialized, from the code

```
# Store all template_fields as they are if there are JSON Serializable
# If not, store them as strings
```

and the second special cases a few names of arguments that need to be
deserialized in a specific way

```
elif k in {"retry_delay", "execution_timeout", "sla", "max_retry_delay"}:
    v = cls._deserialize_timedelta(v)
```

so during serialization airflow sees that execution_timeout is a
template field, serializes it as a string, then during deserialization
it is a special name that forces the deserialization as timedelta and BOOM!

### Are you willing to submit PR?

- [ ] 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)

#
#
"""Serialized DAG and BaseOperator."""
from __future__ import annotations
import collections.abc
import datetime
import enum
import logging
import warnings
import weakref
from dataclasses import dataclass
from inspect import Parameter, signature
from typing import TYPE_CHECKING, Any, Collection, Iterable, Mapping, NamedTuple, Union
import cattr
import lazy_object_proxy
import pendulum
from dateutil import relativedelta
from pendulum.tz.timezone import FixedTimezone, Timezone
from airflow.compat.functools import cache
from airflow.configuration import conf
from airflow.datasets import Dataset
from airflow.exceptions import AirflowException, RemovedInAirflow3Warning, SerializationError
from airflow.models.baseoperator import BaseOperator, BaseOperatorLink
from airflow.models.connection import Connection
from airflow.models.dag import DAG, create_timetable
from airflow.models.expandinput import EXPAND_INPUT_EMPTY, ExpandInput, create_expand_input, get_map_type_key
from airflow.models.mappedoperator import MappedOperator
from airflow.models.operator import Operator