custom containers for training in sagemaker?

Hello Fam!

Kindly go through the documentation below https://docs.aws.amazon.com/sagemaker/latest/dg/docker-containers.html and follow the notebook for the solution here -> https://github.com/aws/amazon-sagemaker-examples/tree/main/advanced_functionality/scikit_bring_your_own.

Dockerfile for training
# Set the environment variables
ENV PYTHONUNBUFFERED=TRUE
ENV PYTHONDONTWRITEBYTECODE=TRUE
ENV PATH="/opt/program:${PATH}"

# Copy the model and inference code
COPY train / opt/program

# Set the working directory
WORKDIR /opt/program

RUN chmod +x /opt/program/serve 

RUN chmod +x /opt/program/train
# Set the default command to run when the container starts

ENTRYPOINT [ "python3" ]

Test locally docker run -v your path to folder/local_test:/opt/ml --rm training_container:latest train

You can then scan with trivy or Amazon Inspector for vulnerability fixes and patch them accordingly

Hope it helps!

Cheers & Best Regards, Ashlin Gabriel