Comments (1)
@NarcissaMorton There isn't anything specific to GitHub in the repositories unless you are working with GitHub Actions. The accelerator requires two main repos:
- Main Repo: https://github.com/Azure/mlops-project-template
- Template Repo: https://github.com/Azure/mlops-templates
The main repo holds your main data science code and the overall pipeline. The template repo contains the individual reusable pipeline steps. To work with Azure repos will be the same as the current step, except your repositories will now be in Azure Repos.
To use them you will need to clone the two repositories into Azure Repos. Configure the required pipeline files to run the pipelines for the required area (CV/Classical/NLP).
What to edit in Pipeline:
Each of the pipeline script has a connection that you can potentially modify to allow for:
repositories:
- repository: mlops-templates # Template Repo --> Use your Azure Repo name here.
name: Azure/mlops-templates # need to change org name from "Azure" to your own org
endpoint: github-connection # need to set up and hardcode. You will need to configure the connection in Azure DevOps
type: github # git for Azure Repos
You can also refer to this documentation to add appropriate repo in the pipeline. Reference: https://docs.microsoft.com/en-us/azure/devops/pipelines/repos/multi-repo-checkout?view=azure-devops
Let us know if you run into specific issues, you can ask them here.
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Related Issues (20)
- No deploy-model-training-pipeline.yml or other examples for Python SDK v2 HOT 2
- Unexpected parameter "build_type" when running deploy-model-training-pipeline in CV pattern HOT 9
- Update documentation for Github Action deployment HOT 1
- run the model-deploy-pipeline github action workflow automatically on completion of model-training-pipeline gha workflow
- Python SDK v2 option is not working
- Environments are not created automatically (Prod &Dev) on Azure DevOps Pipelines HOT 2
- When "config-infra-prod.yml" file is changed, 3 pipelines are automatically triggered and failed. HOT 2
- Review added
- Repository mlops-templates references endpoint github-connection which does not exist or is not authorized for use HOT 4
- Missing /mlops/azureml/train/data.yml (ADO/classical) HOT 1
- Using sweep in the train pipeline errors out HOT 1
- Azure DevOps - Error Deploying Online Endpoint - ResourceNotReady: User container has crashed or terminated: Liveness probe failed: HTTP probe failed with statuscode: 502 HOT 1
- RAI Insights Dashboard Constructor step fails
- Any support or suggestion of initializing a ML repo with your codes locally and create related pipelines? HOT 5
- Model Training ADO pipeline FAILS after over an hour HOT 8
- For free/VS MCT subscriptions vcore quota limit of 6 in eastus causes endpoint deployment failure HOT 2
- Jenkins Pipeline HOT 1
- Accelerator Azure Devops instructions steps 3.5.2 & 3.5.3 misleading HOT 3
- Deploying Infrastructure via Azure DevOps HOT 6
- Accelerator guide ADO with Terraform misses creation of dev AML environment HOT 5
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from mlops-v2.