**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
"""Remake the key by subtracting 1 from try number to match in memory information"""
        return TaskInstanceKey(self.dag_id, self.task_id, self.execution_date, max(1, self.try_number - 1))
    def with_try_number(self, try_number: int) -> 'TaskInstanceKey':
        """Returns TaskInstanceKey with provided ``try_number``"""
        return TaskInstanceKey(self.dag_id, self.task_id, self.execution_date, try_number)
class TaskInstance(Base, LoggingMixin):  
    """
    Task instances store the state of a task instance. This table is the
    authority and single source of truth around what tasks have run and the
    state they are in.
    The SqlAlchemy model doesn't have a SqlAlchemy foreign key to the task or
    dag model deliberately to have more control over transactions.
    Database transactions on this table should insure double triggers and
    any confusion around what task instances are or aren't ready to run
    even while multiple schedulers may be firing task instances.
    """
    __tablename__ = "task_instance"
    task_id = Column(String(ID_LEN, **COLLATION_ARGS), primary_key=True)
    dag_id = Column(String(ID_LEN, **COLLATION_ARGS), primary_key=True)
    execution_date = Column(UtcDateTime, primary_key=True)
    start_date = Column(UtcDateTime)
    end_date = Column(UtcDateTime)
    duration = Column(Float)
    state = Column(String(20))
    _try_number = Column('try_number', Integer, default=0)
    max_tries = Column(Integer)
    hostname = Column(String(1000))