CML-EC2-Runner #69
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| name: CML-EC2-Runner | |
| on: | |
| workflow_dispatch: | |
| jobs: | |
| launch-runner: | |
| runs-on: ubuntu-latest | |
| steps: | |
| - uses: actions/checkout@v3 | |
| - uses: iterative/setup-cml@v2 | |
| - name: Deploy runner on AWS EC2 | |
| env: | |
| REPO_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }} | |
| AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} | |
| AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} | |
| run: | | |
| cml runner launch \ | |
| --cloud=aws \ | |
| --name=session-08 \ | |
| --cloud-region=ap-south-1 \ | |
| --cloud-type=g4dn.xlarge \ | |
| --cloud-hdd-size=64 \ | |
| --cloud-spot \ | |
| --single \ | |
| --labels=cml-gpu \ | |
| --idle-timeout=100 | |
| train-and-report: | |
| runs-on: [self-hosted, cml-gpu] | |
| needs: launch-runner | |
| timeout-minutes: 20 | |
| # container: | |
| # image: docker://pytorch/pytorch:2.4.0-cuda12.4-cudnn9-runtime | |
| # options: --gpus all | |
| # runs-on: ubuntu-latest | |
| steps: | |
| # - name: Set node environment | |
| # run: | | |
| # apt-get remove nodejs | |
| # apt-get remove npm | |
| # curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.1/install.sh | bash | |
| # chmod +x ~/.nvm/nvm.sh | |
| # ls -a ~ | |
| # nvm -v | |
| # nvm install 20 | |
| # node -v | |
| # npm -v | |
| # - uses: actions/setup-node@v4 | |
| # with: | |
| # node-version: 20 | |
| # - run: npm ci | |
| # - run: npm test | |
| # - uses: actions/checkout@v2 | |
| - name: Display CUDA Version | |
| run: | | |
| echo "CUDA Version:" | |
| nvcc --version || true | |
| - name: Display cuDNN Version | |
| run: | | |
| echo "cuDNN Version:" | |
| cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2 || true | |
| - name: Verify EC2 Instance | |
| run: | | |
| echo "Checking instance information..." | |
| # Check if we're on EC2 | |
| TOKEN=$(curl -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 21600") | |
| curl -H "X-aws-ec2-metadata-token: $TOKEN" http://169.254.169.254/latest/meta-data/instance-type | |
| echo "Checking system resources..." | |
| lscpu | |
| free -h | |
| df -h | |
| nvidia-smi # This will show GPU if available | |
| echo "Checking environment..." | |
| env | grep AWS || true | |
| hostname | |
| whoami | |
| pwd | |
| # Install the AWS CLI if not already available | |
| if ! command -v aws &> /dev/null; then | |
| apt-get update | |
| apt-get install -y awscli | |
| fi | |
| # Get ECR login command and execute it | |
| $(aws ecr get-login --no-include-email --region ap-south-1) | |
| aws ecr get-login-password --region ap-south-1 | docker login --username AWS --password-stdin 306093656765.dkr.ecr.ap-south-1.amazonaws.com | |
| - name: Set up AWS CLI credentials | |
| env: | |
| AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} | |
| AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} | |
| AWS_DEFAULT_REGION: ap-south-1 # Change to your desired region | |
| run: | | |
| # Create the AWS config and credentials files | |
| mkdir -p ~/.aws | |
| echo "[default]" > ~/.aws/config | |
| echo "region=${AWS_DEFAULT_REGION}" >> ~/.aws/config | |
| echo "[default]" > ~/.aws/credentials | |
| echo "aws_access_key_id=${AWS_ACCESS_KEY_ID}" >> ~/.aws/credentials | |
| echo "aws_secret_access_key=${AWS_SECRET_ACCESS_KEY}" >> ~/.aws/credentials | |
| - name: Test AWS CLI | |
| run: | | |
| # Now you can run any AWS CLI command | |
| aws s3 ls # Example command to list S3 buckets | |
| # - name: Authenticate with AWS ECR | |
| # uses: aws-actions/configure-aws-credentials@v4 | |
| # with: | |
| # aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }} | |
| # aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }} | |
| # aws-region: ${{ secrets.AWS_REGION }} | |
| # - name: AWS ECR | |
| # run: | | |
| # aws configure aws_access_key_id=${{ secrets.AWS_ACCESS_KEY_ID }} aws_secret_access_key=${{ secrets.AWS_SECRET_ACCESS_KEY }} | |
| # - name: Install Docker | |
| # run: | | |
| # curl -fsSL https://get.docker.com -o get-docker.sh | |
| # sh get-docker.sh | |
| # - name: Login to Amazon ECR | |
| # id: login-ecr | |
| # uses: aws-actions/amazon-ecr-login@v2 | |
| # - name: CUDA Check | |
| # run: | | |
| # docker run --gpus all -it pytorch/pytorch:2.3.1-cuda11.8-cudnn8-runtime python3 -c " | |
| # import torch; | |
| # print(f'CUDA Available: {torch.cuda.is_available()}'); | |
| # if torch.cuda.is_available(): | |
| # print(f'Device: {torch.cuda.get_device_name(0)}')" | |
| - name: Pull Docker image from ECR | |
| run: | | |
| docker pull ${{secrets.AWS_ECR_LOGIN_URI}}/${{ secrets.ECR_REPOSITORY_NAME }}:latest | |
| ls -a | |
| - name: Run DVC commands in container | |
| run: | | |
| mkdir -p model_storage | |
| docker run --gpus=all \ | |
| -v "$(pwd)/model_storage:/workspace/model_storage" \ | |
| -e AWS_ACCESS_KEY_ID=${{ secrets.AWS_ACCESS_KEY_ID }} \ | |
| -e AWS_SECRET_ACCESS_KEY=${{ secrets.AWS_SECRET_ACCESS_KEY }} \ | |
| -e AWS_DEFAULT_REGION=${{ secrets.AWS_REGION }} \ | |
| ${{ secrets.AWS_ECR_LOGIN_URI }}/${{ secrets.ECR_REPOSITORY_NAME }}:latest \ | |
| /bin/bash -c " | |
| dvc pull -r myremote && \ | |
| mkdir -p model_storage && \ | |
| dvc repro -f | |
| " | |
| # # Wait a moment to ensure the container has started | |
| # sleep 5 | |
| ls model_storage/ | |
| # # Print logs from the container | |
| # docker logs $CONTAINER_ID | |
| # # Stop the container after retrieving logs | |
| # docker stop $CONTAINER_ID | |
| - name: List files in folder | |
| run: | | |
| ls -l ./ | |
| - name: Install jq | |
| run: | | |
| sudo apt-get update | |
| sudo apt-get install -y jq | |
| - name: Get latest commit ID from the repository | |
| id: get_commit_id | |
| env: | |
| REPO_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }} | |
| run: | | |
| repo="ajithvcoder/emlo4-session-08-ajithvcoder" | |
| latest_commit=$(curl -s -H "Authorization: token $REPO_TOKEN" \ | |
| "https://api.github.com/repos/$repo/commits?per_page=1" | \ | |
| jq -r '.[0].sha') | |
| echo "COMMIT_ID=$latest_commit" >> $GITHUB_ENV | |
| - name: List files in folder | |
| run: | | |
| ls -l ./model_storage | |
| - name: Read best checkpoint file name | |
| id: read_checkpoint | |
| run: | | |
| checkpoint_file=$(head -n 1 ./model_storage/best_model_checkpoint.txt) | |
| echo "CHECKPOINT_FILE=$checkpoint_file" >> $GITHUB_ENV | |
| - name: Upload checkpoint to S3 | |
| run: | | |
| checkpoint_path="${{ env.CHECKPOINT_FILE }}" # Use the checkpoint path from the file | |
| bucket_name="mybucket-emlo-mumbai/session-08-checkpoint/" # Change to your S3 bucket name | |
| s3_key="session-08-checkpoint/${{ env.COMMIT_ID }}/$(basename "$checkpoint_path")" # Define S3 key | |
| echo "Uploading $checkpoint_path to s3://$bucket_name/$s3_key" | |
| aws s3 cp "$checkpoint_path" "s3://$bucket_name/$s3_key" --recursive | |
| - name: Clean previous images and containers | |
| run: | | |
| docker system prune -f | |