MLS-C01 · Question #96
MLS-C01 Question #96: Real Exam Question with Answer & Explanation
The correct answer is C: Configure the training program as an ENTRYPOINT named train. To configure a Docker container to run as an executable, use an ENTRYPOINT instruction in a SageMaker overrides any default CMD statement in a container by specifying the train argument after the image name. https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training
Question
A Machine Learning Specialist wants to bring a custom algorithm to Amazon SageMaker. The Specialist implements the algorithm in a Docker container supported by Amazon SageMaker. How should the Specialist package the Docker container so that Amazon SageMaker can launch the training correctly?
Options
- AModify the bash_profile file in the container and add a bash command to start the training
- BUse CMD config in the Dockerfile to add the training program as a CMD of the image
- CConfigure the training program as an ENTRYPOINT named train
- DCopy the training program to directory /opt/ml/train
Explanation
To configure a Docker container to run as an executable, use an ENTRYPOINT instruction in a SageMaker overrides any default CMD statement in a container by specifying the train argument after the image name. https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html
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