Update documentation for ADO project initialization (#84)

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Scott Donohoo 2023-01-26 21:20:27 -06:00 коммит произвёл GitHub
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@ -1,26 +1,26 @@
trigger: none
parameters:
- name: adoProjectName
displayName: ADO project name
- name: adoProjectName
displayName: Azure DevOps ProjectName
type: string
- name: repoName
displayName: Repo name
- name: repoName
displayName: New Project Repository Name
type: string
- name: mlOpsProjectTemplateAdoProjectName
displayName: MLOps Project Template's ADO project name
type: string
# default: [good idea to put your default here]
#- name: mlOpsProjectTemplateAdoProjectName
# displayName: MLOps Project Template's ADO project name
# type: string
# # default: [good idea to put your default here]
- name: mlOpsProjectRepoName
- name: mlOpsProjectRepoName
displayName: MLOps Project Template's repo
type: string
default: mlops-project-template
- name: projectType
displayName: ML project type
- name: projectType
displayName: ML Project Type
type: string
default: classical
values:
@ -28,13 +28,23 @@ parameters:
- cv
- nlp
- name: mlopsVersion
displayName: MLOps version
- name: mlopsVersion
displayName: MLOps Interface
type: string
default: aml-cli-v2
values:
- python-sdk
- aml-cli-v2
- python-sdk-v1
- python-sdk-v2
- rai-aml-cli-v2
- name: infrastructure_version
displayName: Infrastructure Provider
type: string
default: bicep
values:
- bicep
- terraform
stages:
- stage: InitialiseProject
@ -45,7 +55,9 @@ stages:
steps:
- checkout: self
persistCredentials: false
- checkout: git://${{ parameters.mlOpsProjectTemplateAdoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
#- checkout: git://${{ parameters.mlOpsProjectTemplateAdoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
# persistCredentials: false
- checkout: git://${{ parameters.adoProjectName }}/${{ parameters.mlOpsProjectRepoName }}
persistCredentials: false
- checkout: git://${{ parameters.adoProjectName }}/${{ parameters.repoName }}
persistCredentials: true
@ -53,20 +65,19 @@ stages:
- task: Bash@3
displayName: Run script to initialise your repo
inputs:
targetType: 'filePath'
targetType: "filePath"
filePath: mlops-v2/.azuredevops/scripts/initialise_repo.sh
arguments: >
${{ parameters.repoName }}
${{ parameters.projectType }}
${{ parameters.mlopsVersion }}
${{ parameters.repoName }} ${{ parameters.projectType }} ${{ parameters.mlopsVersion }} ${{ parameters.infrastructure_version}}
- task: Bash@3
displayName: Run script to create pipelines in ADO
inputs:
targetType: 'filePath'
targetType: "filePath"
filePath: mlops-v2/.azuredevops/scripts/create_ado_pipelines.sh
arguments: >
${{ parameters.repoName }}
${{ parameters.adoProjectName }}
${{ parameters.repoName }} ${{ parameters.adoProjectName }}
env:
AZURE_DEVOPS_EXT_PAT: $(System.AccessToken)

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@ -1,7 +1,8 @@
repo_name=$1
project_type=$2
mlops_version=$3
infrastructure_version=bicep #options: terraform / bicep
#infrastructure_version=bicep #options: terraform / bicep
infrastructure_version=$4 #options: terraform / bicep
git config --global user.email "hosted.agent@dev.azure.com"
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
![image](./images/ado-parameters-sparepipeline.png)
- **ADO project name** : This is the name of the Azure DevOps project you created
- **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)
- **MLOps Project Template name**: Name of the shared templates you imported previously (Default is **mlops-project-template**)
- ML Project type:
- **Azure DevOps Project Name** : This is the name of the Azure DevOps project you are running the pipeline from.
- **New Project Repository Name**: The name of your new project repository created in 3.5.1.
- **MLOps Project Template Repo Name**: Name of the shared templates you imported previously (Default is **mlops-project-template**)
- **ML Project type**:
- Choose **classical** for a regression or classification project.
- Choose **cv** for a computer vision project
- Choose **nlp** for natural language projects
- MLOps version
- choose **python-sdk** to use the python SDK for training and deployment of your model
- Choose **aml-cli-v2** to yse the cli tools for training and deployment of your model
- Infrastructure Version:
- Choose **Bicep** to deploy using Azure ARM based templates
- **MLOps Interface**: Select the interface to the ML platform, either CLI or SDK.
- Choose **aml-cli-v2** for the Azure ML CLI v2 interface. This is supported for all ML project types.
- 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.
- 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.
- 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.
- **Infrastructure Provider**: Choose the provider to use to deploy Azure infrastructure for your project.
- Choose **Bicep** to deploy using Azure ARM-based templates
- Choose **terraform** to use terraform based templates.
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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