**Description**

For a DAG that looks like this:

```
A >> B
```

If A fails, B goes into "upstream_failed" state. If a user then marks A "success", B will remain in "upstream_failed" state. It will not automatically start running. This scenario often happens if the failure of A is dealt with outside of Airflow and the user does not want Airflow to run A again. But he usually expect Airflow to run B after A is marked "success".

**Use case / motivation**

After A is marked "success", its downstream tasks B should be cleared automatically and get ready to be scheduled. To avoid changing this behaviour completely, there can be a toggle button next to "Success" that lets the user decide if he wants Airflow to automatically clear downstream tasks that are in "upstream_failed" state.
airflow/www/views.py
html_dict = {}
        renderers = wwwutils.get_attr_renderer()
        for template_field in task.template_fields:
            content = getattr(task, template_field)
            renderer = task.template_fields_renderers.get(template_field, template_field)
            if renderer in renderers:
                html_dict[template_field] = renderers[renderer](content)
            else:
                html_dict[template_field] = Markup("<pre><code>{}</pre></code>").format(
                    pformat(content)
                )  
        return self.render_template(
            'airflow/ti_code.html',
            html_dict=html_dict,
            dag=dag,
            task_id=task_id,
            execution_date=execution_date,
            form=form,
            root=root,
            title=title,
        )
    @expose('/rendered-k8s')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
        ]
    )
    @action_logging
    def rendered_k8s(self):