**Apache Airflow version**: v2.0.0 and up
**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): not tested with K8
**Environment**:
all

**What happened**:

Executing the unit test included below, or create an infinite pool ( `-1` slots ) and tasks that should be executed in that pool.
```
INFO     airflow.jobs.scheduler_job.SchedulerJob:scheduler_job.py:991 Not scheduling since there are -1 open slots in pool test_scheduler_verify_infinite_pool
```

**What you expected to happen**:

To schedule tasks, or to drop support for infinite slots pools?

**How to reproduce it**:
easiest one is this unit test:
```
def test_scheduler_verify_infinite_pool(self):
    """
    Test that TIs are still scheduled if we only have one infinite pool.
    """
    dag = DAG(dag_id='test_scheduler_verify_infinite_pool', start_date=DEFAULT_DATE)
    BashOperator(
        task_id='test_scheduler_verify_infinite_pool_t0',
        dag=dag,
        owner='airflow',
        pool='test_scheduler_verify_infinite_pool',
        bash_command='echo hi',
    )

    dagbag = DagBag(
        dag_folder=os.path.join(settings.DAGS_FOLDER, "no_dags.py"),
        include_examples=False,
        read_dags_from_db=True,
    )
    dagbag.bag_dag(dag=dag, root_dag=dag)
    dagbag.sync_to_db()

    session = settings.Session()
    pool = Pool(pool='test_scheduler_verify_infinite_pool', slots=-1)
    session.add(pool)
    session.commit()

    dag = SerializedDAG.from_dict(SerializedDAG.to_dict(dag))

    scheduler = SchedulerJob(executor=self.null_exec)
    scheduler.processor_agent = mock.MagicMock()

    dr = dag.create_dagrun(
        run_type=DagRunType.SCHEDULED,
        execution_date=DEFAULT_DATE,
        state=State.RUNNING,
    )
    scheduler._schedule_dag_run(dr, {}, session)

    task_instances_list = scheduler._executable_task_instances_to_queued(max_tis=32, session=session)

    # Let's make sure we don't end up with a `max_tis` == 0
    assert len(task_instances_list) >= 1
```

**Anything else we need to know**:

Overall I'm not sure whether it's worth fixing in those various spots:
https://github.com/bperson/airflow/blob/master/airflow/jobs/scheduler_job.py#L908
https://github.com/bperson/airflow/blob/master/airflow/jobs/scheduler_job.py#L971
https://github.com/bperson/airflow/blob/master/airflow/jobs/scheduler_job.py#L988
https://github.com/bperson/airflow/blob/master/airflow/jobs/scheduler_job.py#L1041
https://github.com/bperson/airflow/blob/master/airflow/jobs/scheduler_job.py#L1056

Or whether to restrict `-1` ( infinite ) slots in pools:
https://github.com/bperson/airflow/blob/master/airflow/models/pool.py#L49
tests/jobs/test_scheduler_job.py
from airflow.jobs.backfill_job import BackfillJob
from airflow.jobs.scheduler_job import DagFileProcessor, SchedulerJob
from airflow.models import DAG, DagBag, DagModel, Pool, SlaMiss, TaskInstance, errors
from airflow.models.dagrun import DagRun
from airflow.models.serialized_dag import SerializedDagModel
from airflow.models.taskinstance import SimpleTaskInstance, TaskInstanceKey
from airflow.operators.bash import BashOperator
from airflow.operators.dummy import DummyOperator
from airflow.serialization.serialized_objects import SerializedDAG
from airflow.utils import timezone
from airflow.utils.callback_requests import DagCallbackRequest, TaskCallbackRequest
from airflow.utils.dag_processing import DagFileProcessorAgent
from airflow.utils.dates import days_ago
from airflow.utils.file import list_py_file_paths
from airflow.utils.session import create_session, provide_session
from airflow.utils.state import State
from airflow.utils.types import DagRunType
from tests.test_utils.asserts import assert_queries_count
from tests.test_utils.config import conf_vars, env_vars
from tests.test_utils.db import (
    clear_db_dags,
    clear_db_import_errors,
    clear_db_jobs,
    clear_db_pools,
    clear_db_runs,
    clear_db_serialized_dags,
    clear_db_sla_miss,
    set_default_pool_slots,
)
from tests.test_utils.mock_executor import MockExecutor