Is this Dockerfile compatible with sagemaker elastic inference

**What did you find confusing? Please describe.**
This is Dockerfile link:
https://github.com/aws/sagemaker-pytorch-inference-toolkit/blob/master/docker/1.5.0/py3/Dockerfile.cpu
This link https://docs.aws.amazon.com/sagemaker/latest/dg/ei-endpoints.html#ei-endpoints-pytorch
states:
You can download the Elastic Inference enabled binary for PyTorch from the public Amazon S3 bucket at [console.aws.amazon.com/s3/buckets/amazonei-pytorch](https://console.aws.amazon.com/s3/buckets/amazonei-pytorch). For information about building a container that uses the Elastic Inference enabled version of PyTorch, see [Building your image](https://github.com/aws/sagemaker-pytorch-serving-container/#building-your-image).
I am confused. If I use the Dockerfile above, do I still need to download and install https://console.aws.amazon.com/s3/buckets/amazonei-pytorch to build docker container image?
If I want to use customer docker image for Sagemaker elastic inference, do I need to convert pytorch code into torchscript?
This part is not covered.
Can I use it for Python version >=3.7 and PyTorch version >=1.12?

**Describe how documentation can be improved**
A clear and concise description of where documentation was lacking and how it can be improved.

**Additional context**
[Add any other context or screenshots about the documentation request here.](https://docs.aws.amazon.com/elastic-inference/latest/developerguide/ei-pytorch-using.html)

Review docker/1.5.0/py3/Dockerfile.cpu and the linked SageMaker Elastic Inference and PyTorch serving documentation. Determine whether the Dockerfile covers the required binary, whether customer images require TorchScript, and which Python and PyTorch versions are supported. Done means documenting clear answers and linking the relevant build and deployment guidance.

Written by the indexing model from the issue text.