**Apache Airflow version**:
2.0.0dev

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

**Environment**:
```
./breeze --python=3.8 --backend=postgres --db-reset restart
```

**What happened**:

Sensors in reschedule mode are not rescheduled by scheduler.

**What you expected to happen**:

Sensors in both poke and reschedule mode should work.

**How to reproduce it**:

```
from airflow import DAG
from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.utils.dates import days_ago

class DummySensor(BaseSensorOperator):
    def poke(self, context):
        return False

with DAG(
    "other_dag",
    start_date=days_ago(1),
    schedule_interval="*/5 * * * *",
    catchup=False
) as dag3:
    DummySensor(
        task_id='wait-task',
        poke_interval=60 * 5,
        mode='reschedule'
    )
```

Then:
```
root@053f6ca34e24: /opt/airflow# airflow dags unpause other_dag
Dag: other_dag, paused: False
root@053f6ca34e24: /opt/airflow# airflow scheduler
  ____________       _____________
 ____    |__( )_________  __/__  /________      __
____  /| |_  /__  ___/_  /_ __  /_  __ \_ | /| / /
___  ___ |  / _  /   _  __/ _  / / /_/ /_ |/ |/ /
 _/_/  |_/_/  /_/    /_/    /_/  \____/____/|__/
[2020-12-03 14:18:58,404] {scheduler_job.py:1247} INFO - Starting the scheduler
[2020-12-03 14:18:58,404] {scheduler_job.py:1252} INFO - Processing each file at most -1 times
[2020-12-03 14:18:58,571] {dag_processing.py:250} INFO - Launched DagFileProcessorManager with pid: 63835
[2020-12-03 14:18:58,576] {scheduler_job.py:1757} INFO - Resetting orphaned tasks for active dag runs
[2020-12-03 14:18:58,660] {settings.py:52} INFO - Configured default timezone Timezone('UTC')
[2020-12-03 14:18:58,916] {scheduler_job.py:944} INFO - 1 tasks up for execution:
	<TaskInstance: other_dag.wait-task 2020-12-03 14:10:00+00:00 [scheduled]>
[2020-12-03 14:18:58,920] {scheduler_job.py:973} INFO - Figuring out tasks to run in Pool(name=default_pool) with 128 open slots and 1 task instances ready to be queued
[2020-12-03 14:18:58,921] {scheduler_job.py:1001} INFO - DAG other_dag has 0/16 running and queued tasks
[2020-12-03 14:18:58,921] {scheduler_job.py:1066} INFO - Setting the following tasks to queued state:
	<TaskInstance: other_dag.wait-task 2020-12-03 14:10:00+00:00 [scheduled]>
[2020-12-03 14:18:58,925] {scheduler_job.py:1108} INFO - Sending TaskInstanceKey(dag_id='other_dag', task_id='wait-task', execution_date=datetime.datetime(2020, 12, 3, 14, 10, tzinfo=Timezone('UTC')), try_number=1) to executor with priority 1 and queue default
[2020-12-03 14:18:58,926] {base_executor.py:79} INFO - Adding to queue: ['airflow', 'tasks', 'run', 'other_dag', 'wait-task', '2020-12-03T14:10:00+00:00', '--local', '--pool', 'default_pool', '--subdir', '/files/dags/the_old_issue.py']
[2020-12-03 14:18:58,935] {local_executor.py:80} INFO - QueuedLocalWorker running ['airflow', 'tasks', 'run', 'other_dag', 'wait-task', '2020-12-03T14:10:00+00:00', '--local', '--pool', 'default_pool', '--subdir', '/files/dags/the_old_issue.py']
[2020-12-03 14:18:59,063] {dagbag.py:440} INFO - Filling up the DagBag from /files/dags/the_old_issue.py
Running <TaskInstance: other_dag.wait-task 2020-12-03T14:10:00+00:00 [queued]> on host 053f6ca34e24
[2020-12-03 14:19:00,022] {scheduler_job.py:944} INFO - 1 tasks up for execution:
	<TaskInstance: other_dag.wait-task 2020-12-03 14:10:00+00:00 [scheduled]>
[2020-12-03 14:19:00,029] {scheduler_job.py:973} INFO - Figuring out tasks to run in Pool(name=default_pool) with 128 open slots and 1 task instances ready to be queued
[2020-12-03 14:19:00,029] {scheduler_job.py:1001} INFO - DAG other_dag has 0/16 running and queued tasks
[2020-12-03 14:19:00,029] {scheduler_job.py:1066} INFO - Setting the following tasks to queued state:
	<TaskInstance: other_dag.wait-task 2020-12-03 14:10:00+00:00 [scheduled]>
[2020-12-03 14:19:00,033] {scheduler_job.py:1108} INFO - Sending TaskInstanceKey(dag_id='other_dag', task_id='wait-task', execution_date=datetime.datetime(2020, 12, 3, 14, 10, tzinfo=Timezone('UTC')), try_number=1) to executor with priority 1 and queue default
[2020-12-03 14:19:00,033] {base_executor.py:82} ERROR - could not queue task TaskInstanceKey(dag_id='other_dag', task_id='wait-task', execution_date=datetime.datetime(2020, 12, 3, 14, 10, tzinfo=Timezone('UTC')), try_number=1)
[2020-12-03 14:19:00,038] {scheduler_job.py:1199} INFO - Executor reports execution of other_dag.wait-task execution_date=2020-12-03 14:10:00+00:00 exited with status success for try_number 1
[2020-12-03 14:19:00,045] {scheduler_job.py:1235} ERROR - Executor reports task instance <TaskInstance: other_dag.wait-task 2020-12-03 14:10:00+00:00 [queued]> finished (success) although the task says its queued. (Info: None) Was the task killed externally?
[2020-12-03 14:19:01,173] {dagrun.py:429} ERROR - Marking run <DagRun other_dag @ 2020-12-03 14:10:00+00:00: scheduled__2020-12-03T14:10:00+00:00, externally triggered: False> failed
```


**Anything else we need to know**:

Discovered when working on #10790 

Thank @nathadfield for helping discover this issue!

tests/serialization/test_dag_serialization.py
CustomOperator(task_id='simple_task', dag=dag, bash_command="true")
        serialized_dag = SerializedDAG.to_dict(dag)
        self.assertIn("bash_command", serialized_dag["dag"]["tasks"][0])
        dag = SerializedDAG.from_dict(serialized_dag)
        simple_task = dag.task_dict["simple_task"]
        self.assertEqual(getattr(simple_task, "bash_command"), "true")
        
        
        
        
        self.assertEqual(
            serialized_dag["dag"]["tasks"][0]["_operator_extra_links"],
            [{'tests.test_utils.mock_operators.CustomOpLink': {}}],
        )
        
        self.assertCountEqual(simple_task.extra_links, ['Google Custom', 'airflow', 'github', 'google'])
        ti = TaskInstance(task=simple_task, execution_date=test_date)
        ti.xcom_push('search_query', "dummy_value_1")
        
        custom_inbuilt_link = simple_task.get_extra_links(test_date, CustomOpLink.name)
        self.assertEqual('http://google.com/custom_base_link?search=dummy_value_1', custom_inbuilt_link)
        
        google_link_from_plugin = simple_task.get_extra_links(test_date, GoogleLink.name)
        self.assertEqual("https://www.google.com", google_link_from_plugin)
    def test_extra_operator_links_logs_error_for_non_registered_extra_links(self):
        """
        Assert OperatorLinks not registered via Plugins and if it is not an inbuilt Operator Link,
        it can still deserialize the DAG (does not error) but just logs an error
        """
        class TaskStateLink(BaseOperatorLink):