You create a multi-class image classification deep learning model. You train the model by using PyTorch version 1.2. You need to ensure that the correct version of PyTorch can be identified for the…

Question

Options

• ASave the model locally as a.pt file, and deploy the model as a local web service.
• BDeploy the model on computer that is configured to use the default Azure Machine Learning
• CRegister the model with a .pt file extension and the default version property.
• DRegister the model, specifying the model_framework and model_framework_version properties.

• A
  5% (2)
• B
  8% (3)
• C
  15% (6)
• D
  72% (28)

Explanation

When registering a model in Azure ML, you can specify model_framework (e.g., Model.Framework.PYTORCH) and model_framework_version (e.g., '1.2') properties. Azure ML uses these metadata values to automatically configure the correct inferencing environment with the right framework version when deploying. Saving as a local .pt file or deploying locally (A) does not address environment version tracking. The default Azure ML environment (B) may not match the specific version used for training. Registering with only a .pt extension and default version (C) does not capture framework version metadata.

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