The Azure Quickstart templates are currently available in English

Create an Azure Machine Learning Service.

Última atualização: 16/12/2020

This template creates an Azure Machine Learning service.

Este modelo de Gestor de Recursos do Azure (Azure Resource Manager, ARM) foi criado por um membro da comunidade e não pela Microsoft. Cada modelo de ARM está licenciado para si ao abrigo de um contrato de licença pelo respetivo proprietário e não pela Microsoft. A Microsoft não é responsável por modelos de ARM fornecidos e licenciados por membros da comunidade e não os analisa quanto a a segurança, compatibilidade ou desempenho. Os modelos de ARM da comunidade não são suportados ao abrigo de nenhum programa de suporte ou serviço da Microsoft e são disponibilizados TAL COMO ESTÃO sem qualquer tipo de garantia.

Parâmetros

Nome do Parâmetro Descrição
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.

Utilizar o modelo

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 e configurar o PowerShell para Azure

Linha 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
Instalar e Configurar a Interface de Linha de Comandos para Várias Plataformas do Azure