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Create an Azure Machine Learning Service.

Última actualización: 16/12/2020

This template creates an Azure Machine Learning service.

Esta plantilla de Azure Resource Manager (ARM) la creó un miembro de la comunidad, no Microsoft. Su propietario (no Microsoft) le permite usar las plantillas de ARM con arreglo a un contrato de licencia. Microsoft no se responsabiliza de ninguna plantilla de ARM que le proporcionen los miembros de la comunidad (o cuya licencia le otorguen) en cuanto a su seguridad, compatibilidad ni rendimiento. Las plantillas de ARM de la comunidad no reciben ningún tipo de soporte en ningún servicio ni programa de soporte de Microsoft. Dichas plantillas se proporcionan TAL CUAL, sin garantía de ningún tipo.

Parámetros

Nombre del parámetro Descripción
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.

Uso de la plantilla

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/101-machine-learning-service-create-aci/azuredeploy.json
Instalar y configurar PowerShell de Azure

Línea de comandos

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/101-machine-learning-service-create-aci/azuredeploy.json
Instalación y configuración de la interfaz de línea de comandos multiplataforma de Azure