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Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-use-batch-endpoint-sdk-v2.md
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@@ -50,6 +50,7 @@ The [workspace](concept-workspace.md) is the top-level resource for Azure Machin
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# import required libraries
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from azure.ai.ml import MLClient, Input
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from azure.ai.ml.entities import (
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AmlCompute,
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BatchEndpoint,
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BatchDeployment,
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Model,
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ml_client.begin_create_or_update(endpoint)
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```
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## Create batch compute
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Batch endpoint runs only on cloud computing resources, not locally. The cloud computing resource is a reusable virtual computer cluster. Run the following code to create an Azure Machine Learning compute cluster. The following examples in this article use the compute created here named `cpu-cluster`.
A deployment is a set of resources required for hosting the model that does the actual inferencing. We'll create a deployment for our endpoint using the `BatchDeployment` class. This class allows user to configure the following key aspects.
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