Update documentation for ADO project initialization (#84)
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@ -1,26 +1,26 @@
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trigger: none
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parameters:
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- name: adoProjectName
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displayName: ADO project name
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- name: adoProjectName
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displayName: Azure DevOps ProjectName
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type: string
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- name: repoName
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displayName: Repo name
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- name: repoName
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displayName: New Project Repository Name
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type: string
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- name: mlOpsProjectTemplateAdoProjectName
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displayName: MLOps Project Template's ADO project name
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type: string
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# default: [good idea to put your default here]
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#- name: mlOpsProjectTemplateAdoProjectName
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# displayName: MLOps Project Template's ADO project name
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# type: string
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# # default: [good idea to put your default here]
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- name: mlOpsProjectRepoName
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- name: mlOpsProjectRepoName
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displayName: MLOps Project Template's repo
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type: string
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default: mlops-project-template
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- name: projectType
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displayName: ML project type
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- name: projectType
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displayName: ML Project Type
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type: string
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default: classical
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values:
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@ -28,13 +28,23 @@ parameters:
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- cv
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- nlp
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- name: mlopsVersion
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displayName: MLOps version
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- name: mlopsVersion
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displayName: MLOps Interface
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type: string
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default: aml-cli-v2
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values:
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- python-sdk
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- aml-cli-v2
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- python-sdk-v1
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- python-sdk-v2
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- rai-aml-cli-v2
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- name: infrastructure_version
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displayName: Infrastructure Provider
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type: string
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default: bicep
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values:
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- bicep
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- terraform
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stages:
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- stage: InitialiseProject
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@ -45,7 +55,9 @@ stages:
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steps:
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- checkout: self
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persistCredentials: false
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- checkout: git://${{ parameters.mlOpsProjectTemplateAdoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
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#- checkout: git://${{ parameters.mlOpsProjectTemplateAdoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
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# persistCredentials: false
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- checkout: git://${{ parameters.adoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
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persistCredentials: false
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- checkout: git://${{ parameters.adoProjectName }}/${{ parameters.repoName }}
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persistCredentials: true
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@ -53,20 +65,19 @@ stages:
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- task: Bash@3
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displayName: Run script to initialise your repo
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inputs:
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targetType: 'filePath'
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targetType: "filePath"
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filePath: mlops-v2/.azuredevops/scripts/initialise_repo.sh
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arguments: >
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${{ parameters.repoName }}
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${{ parameters.projectType }}
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${{ parameters.mlopsVersion }}
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${{ parameters.repoName }} ${{ parameters.projectType }} ${{ parameters.mlopsVersion }} ${{ parameters.infrastructure_version}}
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- task: Bash@3
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displayName: Run script to create pipelines in ADO
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inputs:
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targetType: 'filePath'
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targetType: "filePath"
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filePath: mlops-v2/.azuredevops/scripts/create_ado_pipelines.sh
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arguments: >
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${{ parameters.repoName }}
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${{ parameters.adoProjectName }}
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${{ parameters.repoName }} ${{ parameters.adoProjectName }}
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env:
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AZURE_DEVOPS_EXT_PAT: $(System.AccessToken)
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@ -1,7 +1,8 @@
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repo_name=$1
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project_type=$2
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mlops_version=$3
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infrastructure_version=bicep #options: terraform / bicep
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#infrastructure_version=bicep #options: terraform / bicep
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infrastructure_version=$4 #options: terraform / bicep
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git config --global user.email "hosted.agent@dev.azure.com"
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git config --global user.name "Azure Pipeline"
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@ -184,18 +184,21 @@ This document will guide you through deploying the MLOps V2 project generator an
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![image](./images/ado-parameters-sparepipeline.png)
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- **ADO project name** : This is the name of the Azure DevOps project you created
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- **Project repo name**: This is the name of the mlops-v2 accelerator project you imported from GitHub (Default is **mlops-v2** unless you changed it during import)
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- **MLOps Project Template name**: Name of the shared templates you imported previously (Default is **mlops-project-template**)
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- ML Project type:
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- **Azure DevOps Project Name** : This is the name of the Azure DevOps project you are running the pipeline from.
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- **New Project Repository Name**: The name of your new project repository created in 3.5.1.
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- **MLOps Project Template Repo Name**: Name of the shared templates you imported previously (Default is **mlops-project-template**)
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- **ML Project type**:
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- Choose **classical** for a regression or classification project.
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- Choose **cv** for a computer vision project
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- Choose **nlp** for natural language projects
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- MLOps version
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- choose **python-sdk** to use the python SDK for training and deployment of your model
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- Choose **aml-cli-v2** to yse the cli tools for training and deployment of your model
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- Infrastructure Version:
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- Choose **Bicep** to deploy using Azure ARM based templates
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- **MLOps Interface**: Select the interface to the ML platform, either CLI or SDK.
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- Choose **aml-cli-v2** for the Azure ML CLI v2 interface. This is supported for all ML project types.
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- Choose **python-sdk-v1** to use the Azure ML python SDK v1 for training and deployment of your model. This is supported for Classical and CV project types.
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- Choose **python-sdk-v1** to use the Azure ML python SDK v2 for training and deployment of your model. This is supported for Classical and NLP project types.
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- Choose **rai-aml-cli-v2** to use the Responsible AI cli tools for training and deployment of your model. This is supported only for Classical project types at this time.
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- **Infrastructure Provider**: Choose the provider to use to deploy Azure infrastructure for your project.
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- Choose **Bicep** to deploy using Azure ARM-based templates
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- Choose **terraform** to use terraform based templates.
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3.8.1 The first run of the pipeline will require you to grant access to the repositories you created. Click **View**
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