**Apache Airflow version**: 2.0.0


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

**Environment**:

- **Cloud provider or hardware configuration**:
- **OS** (e.g. from /etc/os-release):
- **Kernel** (e.g. `uname -a`):
- **Install tools**:
- **Others**:

**What happened**:

I have the following DAG:

```py
from datetime import datetime, timedelta

from airflow import DAG
from airflow.operators.bash_operator import BashOperator

with DAG(
    dag_id="sla_trigger",
    schedule_interval="* * * * *",
    start_date=datetime(2020, 2, 3),
) as dag:
    BashOperator(
        task_id="bash_task",
        bash_command="sleep 30",
        sla=timedelta(seconds=2),
    )

```

And in my understanding this dag should result in SLA miss every time it is triggered (every minute). However, after few minutes of running I don't see any SLA misses...

**What you expected to happen**:

I expect to see SLA if task takes longer than expected.

**How to reproduce it**:

Use the dag from above.

**Anything else we need to know**:

N/A

airflow/serialization/serialized_objects.py
"""Deserializes a DAG from a JSON object."""
        dag = SerializedDAG(dag_id=encoded_dag['_dag_id'])
        for k, v in encoded_dag.items():
            if k == "_downstream_task_ids":
                v = set(v)
            elif k == "tasks":
                
                SerializedBaseOperator._load_operator_extra_links = cls._load_operator_extra_links
                
                v = {task["task_id"]: SerializedBaseOperator.deserialize_operator(task) for task in v}
                k = "task_dict"
            elif k == "timezone":
                v = cls._deserialize_timezone(v)
            elif k in {"dagrun_timeout"}:
                v = cls._deserialize_timedelta(v)
            elif k.endswith("_date"):
                v = cls._deserialize_datetime(v)
            elif k in cls._decorated_fields:
                v = cls._deserialize(v)
            
            setattr(dag, k, v)
        
        
        if "_task_group" in encoded_dag:
            dag._task_group = SerializedTaskGroup.deserialize_task_group(  
                encoded_dag["_task_group"], None, dag.task_dict
            )
        else: