The worker_module argument fails with unexpected keyword error

**What happened**:
Using the `worker_module` argument when starting a cluster causes an unexpected argument failure.

**Minimal Complete Verifiable Example**:
This is a piece of code from the Dask cloud provider docs (https://cloudprovider.dask.org/en/latest/gpus.html):

```python
cluster = EC2Cluster(ami="ami-0c7c7d78f752f8f17", # Example Deep Learning AMI (Ubuntu 18.04)
docker_image="rapidsai/rapidsai:cuda10.1-runtime-ubuntu18.04",
instance_type="p3.2xlarge",
worker_module="dask_cuda.cli.dask_cuda_worker",
bootstrap=False,
filesystem_size=120)
```
returns
```python
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
in
----> 1 cluster = EC2Cluster(ami="ami-0c7c7d78f752f8f17", # Example Deep Learning AMI (Ubuntu 18.04)
2 docker_image="rapidsai/rapidsai:cuda10.1-runtime-ubuntu18.04",
3 instance_type="p3.2xlarge",
4 worker_module="dask_cuda.cli.dask_cuda_worker",
5 bootstrap=False,

~/anaconda3/envs/rapids-gpu-bdb/lib/python3.8/site-packages/dask_cloudprovider/aws/ec2.py in __init__(self, region, availability_zone, bootstrap, auto_shutdown, ami, instance_type, vpc, subnet_id, security_groups, filesystem_size, key_name, iam_instance_profile, docker_image, debug, **kwargs)
476 self.scheduler_options = {**self.options}
477 self.worker_options = {**self.options}
--> 478 super().__init__(debug=debug, **kwargs)

~/anaconda3/envs/rapids-gpu-bdb/lib/python3.8/site-packages/dask_cloudprovider/generic/vmcluster.py in __init__(self, n_workers, worker_class, worker_options, scheduler_options, docker_image, docker_args, env_vars, security, protocol, debug, **kwargs)
287 self.uuid = str(uuid.uuid4())[:8]
288
--> 289 super().__init__(**kwargs, security=self.security)
290
291 async def call_async(self, f, *args, **kwargs):

TypeError: __init__() got an unexpected keyword argument 'worker_module'
```

**Environment**:

- Dask version: 2021.04.0
- Python version: 3.8
- Operating System: Ubuntu 18.04
- Install method (conda, pip, source): pip