**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
"""Prepare Task for Execution"""
        from airflow.models.renderedtifields import RenderedTaskInstanceFields
        task_copy = task.prepare_for_execution()
        self.task = task_copy
        def signal_handler(signum, frame):  
            self.log.error("Received SIGTERM. Terminating subprocesses.")
            task_copy.on_kill()
            raise AirflowException("Task received SIGTERM signal")
        signal.signal(signal.SIGTERM, signal_handler)
        
        self.clear_xcom_data()
        with Stats.timer(f'dag.{task_copy.dag_id}.{task_copy.task_id}.duration'):
            self.render_templates(context=context)
            RenderedTaskInstanceFields.write(RenderedTaskInstanceFields(ti=self, render_templates=False))
            RenderedTaskInstanceFields.delete_old_records(self.task_id, self.dag_id)
            
            airflow_context_vars = context_to_airflow_vars(context, in_env_var_format=True)
            self.log.info(
                "Exporting the following env vars:\n%s",
                '\n'.join([f"{k}={v}" for k, v in airflow_context_vars.items()]),
            )
            os.environ.update(airflow_context_vars)
            
            task_copy.pre_execute(context=context)
            
            self._run_execute_callback(context, task)