Os modelos de Início Rápido do Azure estão atualmente disponíveis em inglês
This template creates an Azure Machine Learning service.
Este modelo do ARM (Azure Resource Manager) foi criado por um membro da comunidade, e não pela Microsoft. Cada modelo do ARM é licenciado para você de acordo com o contrato de licença de seu proprietário, e não da Microsoft. A Microsoft não é responsável por modelos do ARM fornecidos e licenciado por membros da comunidade e não avalia sua segurança, compatibilidade ou desempenho. Modelos do ARM da comunidade não têm suporte de nenhum programa ou serviço de suporte da Microsoft e são disponibilizados DA FORMA COMO ESTÃO, sem nenhum 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. |
Usar 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 deploymentInstale e configure o PowerShell do Azure
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
Linha de 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 deploymentInstalar e configurar a Interface de Linha de Comando de Plataforma Cruzada do Azure
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