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Merge pull request #3822 from MicrosoftDocs/repo_sync_working_branch
Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-ai-docs (branch main)
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articles/machine-learning/concept-prebuilt-docker-images-inference.md

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Framework version | CPU/GPU | Pre-installed packages | MCR Path
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--- | --- | --- | --- |
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NA | CPU | NA | `mcr.microsoft.com/azureml/minimal-ubuntu20.04-py38-cpu-inference:latest`
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NA | GPU | NA | `mcr.microsoft.com/azureml/minimal-ubuntu20.04-py38-cuda11.6.2-gpu-inference:latest`
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NA | CPU | NA | `mcr.microsoft.com/azureml/minimal-ubuntu22.04-py39-cpu-inference:latest`
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NA | GPU | NA | `mcr.microsoft.com/azureml/minimal-ubuntu22.04-py39-cuda11.8-gpu-inference:latest`
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NA | CPU | NA | `mcr.microsoft.com/azureml/minimal-py312-inference:latest`
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> [!NOTE]
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> Azure Machine Learning supports [Curated environments](resource-curated-environments.md). You can [browse curated environments](how-to-manage-environments-in-studio.md#browse-curated-environments) and add filter for `Tags: Inferencing`.

articles/machine-learning/how-to-secure-workspace-vnet.md

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> [!IMPORTANT]
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> The compute cluster used to build Docker images needs to be able to access the package repositories that are used to train and deploy your models. You might need to add network security rules that allow access to public repos, [use private Python packages](concept-vulnerability-management.md#using-a-private-package-repository), or use [custom Docker images (SDK v1)](v1/how-to-train-with-custom-image.md?view=azureml-api-1&preserve-view=true) that already include the packages.
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> [!WARNING]
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> If your Azure Container Registry uses a private endpoint or service endpoint to communicate with the virtual network, you cannot use a managed identity with an Azure Machine Learning compute cluster.
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### Azure Monitor
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> [!WARNING]

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