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Create an Azure Machine Learning Service.

Data ultimo aggiornamento: 11/05/2021

This template creates an Azure Machine Learning service.

Questo modello di Azure Resource Manager è stato creato da un membro della community e non da Microsoft. Ogni modello di Azure Resource Manager viene concesso in licenza ai sensi di un contratto di licenza a cura del proprietario e non di Microsoft. Microsoft non è responsabile dei modelli di Azure Resource Manager forniti e concessi in licenza da membri della community e non ne verifica la sicurezza, la compatibilità o le prestazioni. I modelli di Azure Resource Manager della community non sono supportati nell'ambito di alcun programma o servizio di supporto tecnico Microsoft e vengono resi disponibili COSÌ COME SONO senza garanzie di alcun tipo.

Parametri

Nome parametro Descrizione
webserviceName The name of the Azure Machine Learning Web Service. This resource will be created in the same resource group as the workspace.
workspaceName The name of the Azure Machine Learning Workspace.
location The location of the Azure Machine Learning Workspace.
environmentName Name of Azure Machine Learning Environment for deployment. See https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-environments and https://docs.microsoft.com/en-us/azure/machine-learning/resource-curated-environments .
environmentVersion Version of Azure Machine Learning Environment for deployment.
cpu The default number of CPU cores to allocate for this Webservice. Can be a decimal.
cpuLimit The max number of CPU cores this Webservice is allowed to use. Can be a decimal.
gpu The number of gpu cores to allocate for this Webservice
memoryInGB The amount of memory (in GB) to allocate for this Webservice. Can be a decimal.
driverProgram Relative path of a file from storage account that contains the code to run for service.
models Details of the models to be deployed. Each model must have the following properties: 'name'(name of the model), 'path'(relative path of a file from storage account linked to Workspace), 'mimeType'(MIME type of Model content. For more details about MIME type, please open https://www.iana.org/assignments/media-types/media-types.xhtml), 'framework'(framework of the model, use Custom if unsure) and 'frameworkVersion'(framework version of the model).
authEnabled Whether or not to enable key auth for this Webservice.
tokenAuthEnabled Whether or not to enable token auth for this Webservice. Only applicable when deploying to AKS.
primaryKey A primary auth key to use for this Webservice.
secondaryKey A secondary auth key to use for this Webservice.
scoringTimeoutMilliSeconds A timeout to enforce for scoring calls to this Webservice.
appInsightsEnabled Whether or not to enable AppInsights for this Webservice.

Usa il modello

PowerShell

New-AzResourceGroup -Name <resource-group-name> -Location <resource-group-location> #use this command when you need to create a new resource group for your deployment
New-AzResourceGroupDeployment -ResourceGroupName <resource-group-name> -TemplateUri https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/quickstarts/microsoft.machinelearningservices/machine-learning-service-create-aci/azuredeploy.json
Installare e configurare Azure PowerShell

Riga di comando

az group create --name <resource-group-name> --location <resource-group-location> #use this command when you need to create a new resource group for your deployment
az group deployment create --resource-group <my-resource-group> --template-uri https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/quickstarts/microsoft.machinelearningservices/machine-learning-service-create-aci/azuredeploy.json
Installare e configurare l'interfaccia della riga di comando multipiattaforma di Azure