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120 lines
3.5 KiB
YAML
120 lines
3.5 KiB
YAML
name: Register the model for the given pipeline branch
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# on:
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# push:
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# branches:
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# - "model-**"
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on:
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pull_request:
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types:
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- closed
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branches:
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- "master"
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permissions: write-all
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jobs:
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Promote-Model-To-Dev:
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if: github.event.pull_request.merged == true
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Install packages to retrieve artifacts
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run: |
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pip install --upgrade pip
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pip install -r modules/ml-pipeline/src/pipeline/src/requirements/version_control/requirements.txt
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- name: Retrieve artifacts (dvc.lock)
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env:
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AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
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run: |
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cd modules/ml-pipeline/src/pipeline/src
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dvc pull -r experiments
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- name: Push artifacts to Dev
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env:
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AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
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run: |
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cd modules/ml-pipeline/src/pipeline/src
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dvc push -r dev
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Register-New-Model:
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if: github.event.pull_request.merged == true
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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with:
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fetch-depth: 0
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- name: Install packages to register model
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env:
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AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
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run: |
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pip install --upgrade pip
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pip install -r modules/ml-pipeline/src/pipeline/src/requirements/version_control/requirements.txt
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- name: Register Model
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env:
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REPO_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: |
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REGISTER_MODEL_NAME=$(echo ${{ github.event.pull_request.head.ref }} | awk -F"-" '{print $1}')
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# REGISTER_MODEL_NAME=$(echo ${{github.ref_name}} | awk -F"-" '{print $1}')
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git config user.name "Github-Bot"
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git config user.email "Github-Bot"
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git fetch origin
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git merge origin/master
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git pull
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gto register ${REGISTER_MODEL_NAME}
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gto assign ${REGISTER_MODEL_NAME} --stage dev
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gto show
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Register-Prediction-Image-Dev:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Install packages to retrieve artifacts
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env:
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AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
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run: |
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pip install --upgrade pip
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pip install -r modules/ml-pipeline/src/pipeline/src/requirements/version_control/requirements.txt
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- name: Retrieve artifacts (dvc.lock)
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env:
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AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
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run: |
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cd modules/ml-pipeline/src/pipeline/src
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dvc pull -r dev
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- name: Build Prediction docker image (TODO - NEED LAMBDA IMAGE)
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run: |
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cd modules/ml-pipeline/src/pipeline/
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docker build . --file Prediction.Dockerfile --tag prediction_test
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- name: ECR Login - Dev
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env:
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AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
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run: |
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echo "LOGIN TO ECR"
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- name: Push Prediction image to ECR - Dev
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env:
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AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
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run: |
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echo "PUSH TO ECR"
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