**Apache Airflow version**:
1.10.14 and 1.10.8. 

**Environment**:
Python 3.6 and Airflow 1.10.14 on sqllite,

**What happened**:

Nested jinja templates do not consistently render when running tasks. TI run rendering behavior also differs from airflow UI and airflow render cli. 

**What you expected to happen**:

Airflow should render nested jinja templates consistently and completely across each interface. Coming from airflow 1.8.2, this used to be the case.

<!-- What do you think went wrong? -->

This regression may have been introduced in 1.10.6 with a refactor of BaseOperator templating functionality. 
https://github.com/apache/airflow/pull/5461

Whether or not a nested layer renders seems to differ based on which arg is being templated in an operator and perhaps order. Furthermore, it seems like the render cli and airflow ui each apply TI.render_templates() a second time, creating inconsistency in what nested templates get rendered.

There may be bug in the way BaseOperator.render_template() observes/caches templated fields

**How to reproduce it**:
From the most basic airflow setup

nested_template_bug.py


```
from datetime import datetime
from airflow import DAG
from airflow.operators.python_operator import PythonOperator

with DAG("nested_template_bug", start_date=datetime(2021, 1, 1)) as dag:

    arg0 = 'level_0_{{task.task_id}}_{{ds}}'
    kwarg1 = 'level_1_{{task.op_args[0]}}'

    def print_fields(arg0, kwarg1):
        print(f'level 0 arg0: {arg0}')
        print(f'level 1 kwarg1: {kwarg1}') 

    nested_render = PythonOperator(
        task_id='nested_render',
        python_callable=print_fields,
        op_args=[arg0, ],
        op_kwargs={
            'kwarg1': kwarg1,
        },
    )
```

```
> airflow test c

level 0 arg0: level_0_nested_render_2021-01-01
level 1 kwarg1: level_1_level_0_{{task.task_id}}_{{ds}}

> airflow render nested_template_bug nested_render 2021-01-01

# ----------------------------------------------------------
# property: op_args
# ----------------------------------------------------------
['level_0_nested_render_2021-01-01']

# ----------------------------------------------------------
# property: op_kwargs
# ----------------------------------------------------------
{'kwarg1': 'level_1_level_0_nested_render_2021-01-01'}
```
airflow/models/taskinstance.py
"""
        Returns whether or not all the conditions are met for this task instance to be run
        given the context for the dependencies (e.g. a task instance being force run from
        the UI will ignore some dependencies).
        :param dep_context: The execution context that determines the dependencies that
            should be evaluated.
        :type dep_context: DepContext
        :param session: database session
        :type session: sqlalchemy.orm.session.Session
        :param verbose: whether log details on failed dependencies on
            info or debug log level
        :type verbose: bool
        """
        dep_context = dep_context or DepContext()
        failed = False
        verbose_aware_logger = self.log.info if verbose else self.log.debug
        for dep_status in self.get_failed_dep_statuses(dep_context=dep_context, session=session):
            failed = True
            verbose_aware_logger(
                "Dependencies not met for %s, dependency '%s' FAILED: %s",
                self,
                dep_status.dep_name,
                dep_status.reason,
            )
        if failed:
            return False
        verbose_aware_logger("Dependencies all met for %s", self)
        return True
    @provide_session
    def get_failed_dep_statuses(self, dep_context=None, session=None):