**Apache Airflow version**:
2.0.0

**Kubernetes version (if you are using kubernetes)** (use `kubectl version`):
1.15
**Environment**:

- **Cloud provider or hardware configuration**: 
GKE
- **OS** (e.g. from /etc/os-release):
Ubuntu 18.04

**What happened**:
I just migrated from 1.10.14 to 2.0.0. When I turn on some random dags, the scheduler crashes with the following error:

```python
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1275, in _execute
    self._run_scheduler_loop()
  File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1377, in _run_scheduler_loop
    num_queued_tis = self._do_scheduling(session)
  File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1533, in _do_scheduling
    num_queued_tis = self._critical_section_execute_task_instances(session=session)
  File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1132, in _critical_section_execute_task_instances
    queued_tis = self._executable_task_instances_to_queued(max_tis, session=session)
  File "/usr/local/lib/python3.6/dist-packages/airflow/utils/session.py", line 62, in wrapper
    return func(*args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1034, in _executable_task_instances_to_queued
    if task_instance.pool_slots > open_slots:
TypeError: '>' not supported between instances of 'NoneType' and 'int'
```
**What you expected to happen**:

I expected those dags would have their tasks scheduled without problems.

**How to reproduce it**:

Can't reproduce it yet. Still trying to figure out if this happens only with specific dags or not.

**Anything else we need to know**:

I couldn't find in which context `task_instance.pool_slots` could be None

airflow/models/taskinstance.py
if task_copy.is_smart_sensor_compatible():
                
                registered = False
                try:
                    registered = task_copy.register_in_sensor_service(self, context)
                except Exception as e:
                    self.log.warning(
                        "Failed to register in sensor service.Continue to run task in non smart sensor mode."
                    )
                    self.log.exception(e, exc_info=True)
                if registered:
                    
                    self._update_ti_state_for_sensing()
            
            with set_current_context(context):
                result = self._execute_task(context, task_copy)
            
            task_copy.post_execute(context=context, result=result)
        Stats.incr(f'operator_successes_{self.task.task_type}', 1, 1)
        Stats.incr('ti_successes')
    @provide_session
    def _update_ti_state_for_sensing(self, session=None):
        self.log.info('Submitting %s to sensor service', self)
        self.state = State.SENSING
        self.start_date = timezone.utcnow()
        session.merge(self)
        session.commit()
        
        raise AirflowSmartSensorException("Task successfully registered in smart sensor.")
    def _execute_task(self, context, task_copy):