試験AI-102J トピック1 問題244 スレッド

Explanation:

You are deploying a Language Understanding (LUIS) container. When running LUIS in Docker, the model must first be exported from the Language Understanding portal, and then provided to the container at runtime.
Step-by-step reasoning:
From the Language Understanding portal, export the solution as a package file.
The trained LUIS model must be exported from the portal into a .json package file.
This is required because the container cannot access the hosted service directly.
From the host computer, move the package file to the Docker input directory.
Containers expect the model to be available locally.
The package file is placed into the input directory that the container maps for models.
From the host computer, run the container and specify the input directory.
When starting the container, you specify --volume < local_input > :/input so the container has access to the package file.
This makes the exported model available inside the container for processing.
Why not the other options?
Retain the model in the portal is not sufficient; the container cannot pull directly from the cloud.
Build the container and specify the output directory is not required; the container image is already available from MCR and is not custom-built for this step.
Correct Answer Order:
Export the solution as a package file.
Move the package file to the Docker input directory.
Run the container and specify the input directory.
Microsoft References
Run LUIS containers
Use containers with Azure AI services