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Question 165 - MLS-C01 discussion

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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?

A.
Modify the bash_profile file in the container and add a bash command to start the training program
Answers
A.
Modify the bash_profile file in the container and add a bash command to start the training program
B.
Use CMD config in the Dockerfile to add the training program as a CMD of the image
Answers
B.
Use CMD config in the Dockerfile to add the training program as a CMD of the image
C.
Configure the training program as an ENTRYPOINT named train
Answers
C.
Configure the training program as an ENTRYPOINT named train
D.
Copy the training program to directory /opt/ml/train
Answers
D.
Copy the training program to directory /opt/ml/train
Suggested answer: C

Explanation:

To use a custom algorithm in Amazon SageMaker, the Docker container image must have an executable file namedtrainthat acts as theENTRYPOINTfor the container. This file is responsible for running the training code and communicating with the Amazon SageMaker service. Thetrainfile must be in thePATHof the container and haveexecute permissions. The other options are not valid ways to package the Docker container for Amazon SageMaker.References:

Use Docker containers to build models - Amazon SageMaker

Create a container with your own algorithms and models - Amazon SageMaker

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asked 16/09/2024
Jorge Fontes
44 questions
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