**Apache Airflow version**: 2.0.0

**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): n/a

**Environment**: Linux

- **Cloud provider or hardware configuration**: amd64
- **OS** (e.g. from /etc/os-release): Centos 7
- **Kernel** (e.g. `uname -a`):
- **Install tools**: pip
- **Others**:

**What happened**:

The field `sql` is rendered as a serialized json `["select 1 from dual", "select 2 from dual"]` instead of a list of syntax-highlighted SQL statements.

![image](https://user-images.githubusercontent.com/5377410/106365382-2f8a1e80-6370-11eb-981a-43bf71e7b396.png)

**What you expected to happen**:

`lists` and `dicts` should be rendered as lists and dicts rather than serialized json unless the `template_field_renderer` is `json`

![image](https://user-images.githubusercontent.com/5377410/106365216-f3a28980-636e-11eb-9c48-15deb1fbe0d7.png)


**How to reproduce it**:

```
from airflow import DAG
from airflow.providers.oracle.operators.oracle import OracleOperator

with DAG("demo", default_args={owner='airflow'}, start_date= pendulum.yesterday(), schedule_interval='@daily',) as dag:
    OracleOperator(task_id='single', sql='select 1 from dual')
    OracleOperator(task_id='list', sql=['select 1 from dual', 'select 2 from dual'])
```

**Anything else we need to know**:

Introduced by #11061, .

A quick and dirty work-around:

Edit file [airflow/www/views.py](https://github.com/PolideaInternal/airflow/blob/13ba1ec5494848d4a54b3291bd8db5841bfad72e/airflow/www/views.py#L673)

```
            if renderer in renderers:
-                if isinstance(content, (dict, list)):
+               if isinstance(content, (dict, list)) and renderer is renderers['json']:
                    content = json.dumps(content, sort_keys=True, indent=4)
                html_dict[template_field] = renderers[renderer](content)
```
airflow/www/views.py
y_points[task_instance.task_id].append(float(task_instance.duration))
                fails_dict_key = (task_instance.dag_id, task_instance.task_id, task_instance.execution_date)
                fails_total = fails_totals[fails_dict_key]
                cumulative_y[task_instance.task_id].append(float(task_instance.duration + fails_total))
        
        
        y_unit = infer_time_unit([d for t in y_points.values() for d in t])
        cum_y_unit = infer_time_unit([d for t in cumulative_y.values() for d in t])
        
        chart.create_y_axis('yAxis', format='.02f', custom_format=False, label=f'Duration ({y_unit})')
        chart.axislist['yAxis']['axisLabelDistance'] = '-15'
        cum_chart.create_y_axis('yAxis', format='.02f', custom_format=False, label=f'Duration ({cum_y_unit})')
        cum_chart.axislist['yAxis']['axisLabelDistance'] = '-15'
        for task_id in x_points:
            chart.add_serie(
                name=task_id,
                x=x_points[task_id],
                y=scale_time_units(y_points[task_id], y_unit),
            )
            cum_chart.add_serie(
                name=task_id,
                x=x_points[task_id],
                y=scale_time_units(cumulative_y[task_id], cum_y_unit),
            )
        dates = sorted({ti.execution_date for ti in task_instances})
        max_date = max([ti.execution_date for ti in task_instances]) if dates else None
        session.commit()
        form = DateTimeWithNumRunsForm(
            data={
                'base_date': max_date or timezone.utcnow(),