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This template creates an Azure Machine Learning service.
Bu Azure Resource Manager (ARM) şablonu Microsoft tarafından değil bir topluluk üyesi tarafından oluşturulmuştur. Her bir ARM şablonu size Microsoft tarafından değil, bir lisans sözleşmesi altında sahibi tarafından lisanslanmıştır. Microsoft, topluluk üyeleri tarafından sağlanan ve lisanslanan ARM şablonlarından sorumlu değildir ve güvenlik, uyumluluk ve performans denetimi yapmaz. Topluluk ARM şablonları herhangi bir Microsoft destek programı veya hizmeti altında desteklenmez ve herhangi bir garanti olmaksızın OLDUĞU GİBİ kullanıma sunulur.
Parametreler
Parametre Adı | Açıklama |
---|---|
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. |
Şablonu kullanın
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 deploymentAzure PowerShell'i yükleme ve yapılandırma
New-AzResourceGroupDeployment -ResourceGroupName <resource-group-name> -TemplateUri https://raw.githubusercontent.com/Azure/azure-quickstart-templates/master/101-machine-learning-service-create-aci/azuredeploy.json
Komut satırı
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 deploymentAzure Platformlar Arası Komut Satırı Arabirimini Yükleme ve Yapılandırma
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