main.yml

name: Wine Quality Machine Learning Pipeline

on: [push]
#  push:
#    branches:    
#      - master

jobs:
  train:
    runs-on: ubuntu-18.04
    env:
      DATABRICKS_HOST: https://westeurope.azuredatabricks.net
      DATABRICKS_TOKEN: ${{ secrets.DATABRICKS_TOKEN }}
      DATABRICKS_NOTEBOOK_PATH: /Shared/MLFlow
      DATABRICKS_CLUSTER_NAME: ML
      DATABRICKS_CLUSTER_SPARK_VERSION: 7.3.x-cpu-ml-scala2.12
      DATABRICKS_CLUSTER_NODE_TYPE_ID: Standard_DS3_v2
      DATABRICKS_CLUSTER_DRIVER_NODE_TYPE_ID: Standard_DS3_v2
      DATABRICKS_CLUSTER_AUTOTERMINATION_MINUTES: 15
      DATABRICKS_CLUSTER_WORKERS_MIN: 1
      DATABRICKS_CLUSTER_WORKERS_MAX: 4
      AZUREML_SDK: azureml-sdk[databricks]==1.23.0
      DATABRICKS_JOB_TRAIN_NAME: Wine Quality (Train)
      DATABRICKS_JOB_BUILDIMAGE_NAME: Wine Quality (Build Container Image)
    steps:
    - uses: actions/checkout@v1
    - name: Set up Python 3.6
      uses: actions/setup-python@v1
      with:
        python-version: 3.6
    - name: Install Databricks CLI
      run: |
        python -m pip install --upgrade pip
        pip install -U databricks-cli
    - name: Configure Databricks CLI
      run: |
        # We need to write the pipe the conf into databricks configure --token since
        # that command only takes inputs from stdin. 
        conf=`cat << EOM
        $DATABRICKS_HOST
        $DATABRICKS_TOKEN
        EOM`
        
        # For password auth there are three lines expected
        # hostname, username, password
        echo "$conf" | databricks configure --token
    - name: Create Notebook Path
      run: 'databricks workspace mkdirs "$DATABRICKS_NOTEBOOK_PATH"'
    - name: Import Notebooks
      run: 'databricks workspace import_dir --overwrite notebooks "$DATABRICKS_NOTEBOOK_PATH"'
    - name: Create / Get Cluster
      run: |
        DATABRICKS_CLUSTER_ID=$(databricks clusters list | grep "$DATABRICKS_CLUSTER_NAME" | awk '{print $1}')
        if [ -z "$DATABRICKS_CLUSTER_ID" ]
        then
        echo "Creating new Databricks Cluster..."
        JSON=`cat << EOM
        {
          "cluster_name": "$DATABRICKS_CLUSTER_NAME",
          "spark_version": "$DATABRICKS_CLUSTER_SPARK_VERSION",
          "spark_conf": {
            "spark.databricks.delta.preview.enabled": "true"
          },
          "node_type_id": "$DATABRICKS_CLUSTER_NODE_TYPE_ID",
          "driver_node_type_id": "$DATABRICKS_CLUSTER_DRIVER_NODE_TYPE_ID",
          "spark_env_vars": {
            "PYSPARK_PYTHON": "/databricks/python3/bin/python3"
          },
          "autotermination_minutes": $DATABRICKS_CLUSTER_AUTOTERMINATION_MINUTES,
          "enable_elastic_disk": true,
          "autoscale": {
            "min_workers": $DATABRICKS_CLUSTER_WORKERS_MIN,
            "max_workers": $DATABRICKS_CLUSTER_WORKERS_MAX
          },
          "init_scripts_safe_mode": false
        }
        EOM`
        DATABRICKS_CLUSTER_ID=$(databricks clusters create --json "$JSON" | jq -r ".cluster_id")
        sleep 10
        else
        echo "Existing Databricks Cluster found (Cluster ID: $DATABRICKS_CLUSTER_ID)"
        fi
        echo "DATABRICKS_CLUSTER_ID=${DATABRICKS_CLUSTER_ID}" >> $GITHUB_ENV
    - name: Start Cluster
      run: |
        echo "Checking Cluster State (Cluster ID: $DATABRICKS_CLUSTER_ID)..."
        DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
        echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        
        if [ $DATABRICKS_CLUSTER_STATE == "TERMINATED" ]
        then
          echo "Starting Databricks Cluster..."
          databricks clusters start --cluster-id "$DATABRICKS_CLUSTER_ID"
          sleep 30
          DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
          echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        fi
        
        while [ $DATABRICKS_CLUSTER_STATE == "PENDING" ]
        do
          sleep 30
          DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
          echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        done
        
        if [ $DATABRICKS_CLUSTER_STATE == "RUNNING" ]
        then
          exit 0
        else
          exit 1
        fi
    - name: Install Azure ML SDK
      run: |
        library_status=$(databricks libraries list --cluster-id $DATABRICKS_CLUSTER_ID | jq -c ".library_statuses[] | select( .library.pypi.package == \"$AZUREML_SDK\" ) | .status" -r)
        if [ -z "$library_status" ]
        then
          echo "Installing $AZUREML_SDK library to $DATABRICKS_CLUSTER_ID..."
          databricks libraries install --cluster-id "$DATABRICKS_CLUSTER_ID" --pypi-package "$AZUREML_SDK"
          sleep 10
          library_status=$(databricks libraries list --cluster-id $DATABRICKS_CLUSTER_ID | jq -c ".library_statuses[] | select( .library.pypi.package == \"$AZUREML_SDK\" ) | .status" -r)
          echo "Library Status: $library_status"
        fi
        
        while [ $library_status == "PENDING" -o $library_status == "INSTALLING" ]
        do
          sleep 30
          library_status=$(databricks libraries list --cluster-id $DATABRICKS_CLUSTER_ID | jq -c ".library_statuses[] | select( .library.pypi.package == \"$AZUREML_SDK\" ) | .status" -r)
          echo "Library Status: $library_status"
        done
        
        if [ $library_status == "INSTALLED" ]
        then
          exit 0
        else
          exit 1
        fi
    - name: Create / Get Training Job
      run: |
        DATABRICKS_JOB_TRAIN_ID=$(databricks jobs list | grep "$DATABRICKS_JOB_TRAIN_NAME" | awk '{print $1}')
        if [ -z "$DATABRICKS_JOB_TRAIN_ID" ]
        then
        echo "Creating $DATABRICKS_JOB_TRAIN_NAME job..."
        JSON=`cat << EOM
        {
          "notebook_task": {
            "notebook_path": "$DATABRICKS_NOTEBOOK_PATH/train",
            "base_parameters": {
              "alpha": "0.5",
              "l1_ratio": "0.5"
            }
          },
          "existing_cluster_id": "$DATABRICKS_CLUSTER_ID",
          "name": "$DATABRICKS_JOB_TRAIN_NAME",
          "max_concurrent_runs": 3,
          "timeout_seconds": 86400,
          "libraries": [],
          "email_notifications": {}
        }
        EOM`
        DATABRICKS_JOB_TRAIN_ID=$(databricks jobs create --json "$JSON" | jq ".job_id")
        else
        echo "Existing $DATABRICKS_JOB_TRAIN_NAME job found (Job ID: $DATABRICKS_JOB_TRAIN_ID)."
        fi
        echo "DATABRICKS_JOB_TRAIN_ID=$DATABRICKS_JOB_TRAIN_ID" >> $GITHUB_ENV
    - name: Run Training Jobs
      run: |
        echo "Running job with ID $DATABRICKS_JOB_TRAIN_ID with alpha=0.5, l1_ratio=0.5..."
        run_id1=$(databricks jobs run-now --job-id $DATABRICKS_JOB_TRAIN_ID --notebook-params '{ "alpha": "0.5", "l1_ratio": "0.5" }' | jq ".run_id")
        echo "  Run ID: $run_id1"
        
        run_state=$(databricks runs get --run-id $run_id1 | jq -r ".state.life_cycle_state")
        echo "Run State (ID $run_id1): $run_state"
        while [ $run_state == "RUNNING" -o $run_state == "PENDING" ]
        do
          sleep 30
          run_state=$(databricks runs get --run-id $run_id1 | jq -r ".state.life_cycle_state")
          echo "Run State (ID $run_id1): $run_state"
        done
        result_state1=$(databricks runs get --run-id $run_id1 | jq -r ".state.result_state")
        state_message1=$(databricks runs get --run-id $run_id1 | jq -r ".state.state_message")
        echo "Result State (ID $run_id1): $result_state1, Message: $state_message1"
        
        echo "Running job with ID $DATABRICKS_JOB_TRAIN_ID with alpha=0.3, l1_ratio=0.3..."
        run_id2=$(databricks jobs run-now --job-id $DATABRICKS_JOB_TRAIN_ID --notebook-params '{ "alpha": "0.3", "l1_ratio": "0.3" }' | jq ".run_id")
        echo "  Run ID: $run_id2"
        
        echo "Running job with ID $DATABRICKS_JOB_TRAIN_ID with alpha=0.1, l1_ratio=0.1..."
        run_id3=$(databricks jobs run-now --job-id $DATABRICKS_JOB_TRAIN_ID --notebook-params '{ "alpha": "0.1", "l1_ratio": "0.1" }' | jq ".run_id")
        echo "  Run ID: $run_id3"
        
        run_state=$(databricks runs get --run-id $run_id2 | jq -r ".state.life_cycle_state")
        echo "Run State (ID $run_id2): $run_state"
        while [ $run_state == "RUNNING" -o $run_state == "PENDING" ]
        do
          sleep 30
          run_state=$(databricks runs get --run-id $run_id2 | jq -r ".state.life_cycle_state")
          echo "Run State (ID $run_id2): $run_state"
        done
        result_state2=$(databricks runs get --run-id $run_id2 | jq -r ".state.result_state")
        state_message2=$(databricks runs get --run-id $run_id2 | jq -r ".state.state_message")
        echo "Result State (ID $run_id2): $result_state2, Message: $state_message2"
        
        run_state=$(databricks runs get --run-id $run_id3 | jq -r ".state.life_cycle_state")
        echo "Run State (ID $run_id3): $run_state"
        while [ $run_state == "RUNNING" -o $run_state == "PENDING" ]
        do
          sleep 30
          run_state=$(databricks runs get --run-id $run_id3 | jq -r ".state.life_cycle_state")
          echo "Run State (ID $run_id3): $run_state"
        done
        result_state3=$(databricks runs get --run-id $run_id3 | jq -r ".state.result_state")
        state_message3=$(databricks runs get --run-id $run_id3 | jq -r ".state.state_message")
        echo "Result State (ID $run_id3): $result_state3, Message: $state_message3"
        
        if [ $result_state1 == "SUCCESS" -a $result_state2 == "SUCCESS" -a $result_state3 == "SUCCESS" ]
        then
          exit 0
        else
          exit 1
        fi
    - name: Build Container Image
      run: |    
        JSON=`cat << EOM
        {
          "notebook_task": {
            "notebook_path": "$DATABRICKS_NOTEBOOK_PATH/serving_build_container_image"
          },
          "existing_cluster_id": "$DATABRICKS_CLUSTER_ID",
          "run_name": "$DATABRICKS_JOB_BUILDIMAGE_NAME",
          "max_concurrent_runs": 1,
          "timeout_seconds": 86400,
          "libraries": [],
          "email_notifications": {}
        }
        EOM`
        
        echo "Building Container Image ..."
        run_id=$(databricks runs submit --json "$JSON" | jq ".run_id")
        echo "  Run ID: $run_id"
        
        run_state=$(databricks runs get --run-id $run_id | jq -r ".state.life_cycle_state")
        echo "Run State (ID $run_id): $run_state"
        while [ $run_state == "RUNNING" -o $run_state == "PENDING" ]
        do
          sleep 30
          run_state=$(databricks runs get --run-id $run_id | jq -r ".state.life_cycle_state")
          echo "Run State (ID $run_id): $run_state"
        done
        result_state=$(databricks runs get --run-id $run_id | jq -r ".state.result_state")
        state_message=$(databricks runs get --run-id $run_id | jq -r ".state.state_message")
        echo "Result State (ID $run_id): $result_state, Message: $state_message"
        
        if [ $result_state == "SUCCESS" ]
        then
          mkdir -p metadata
          databricks runs get-output --run-id $run_id | jq -r .notebook_output.result | tee image.json
          exit 0
        else
          exit 1
        fi
    - name: Upload Model Image ID
      uses: actions/upload-artifact@v1
      with:
        name: model_image_id
        path: image.json
  staging:
    needs: train
    runs-on: ubuntu-18.04
    env:
      DATABRICKS_HOST: https://westeurope.azuredatabricks.net
      DATABRICKS_TOKEN: ${{ secrets.DATABRICKS_TOKEN }}
      DATABRICKS_NOTEBOOK_PATH: /Shared/MLFlow
      DATABRICKS_CLUSTER_NAME: ML
      DATABRICKS_JOB_DEPLOYTOACI_NAME: Wine Quality (Deploy To ACI)
    steps:
    - name: Download Model Image ID
      uses: actions/download-artifact@v1
      with:
        name: model_image_id
    - name: Set up Python 3.6
      uses: actions/setup-python@v1
      with:
        python-version: 3.6
    - name: Install Databricks CLI
      run: |
        python -m pip install --upgrade pip
        pip install -U databricks-cli
    - name: Configure Databricks CLI
      run: |
        # We need to write the pipe the conf into databricks configure --token since
        # that command only takes inputs from stdin. 
        conf=`cat << EOM
        $DATABRICKS_HOST
        $DATABRICKS_TOKEN
        EOM`
        
        # For password auth there are three lines expected
        # hostname, username, password
        echo "$conf" | databricks configure --token
    - name: Get Cluster ID
      run: |
        DATABRICKS_CLUSTER_ID=$(databricks clusters list | grep "$DATABRICKS_CLUSTER_NAME" | awk '{print $1}')
        if [ -z "$DATABRICKS_CLUSTER_ID" ]
        then
          echo "ERROR: Unable to get Cluster ID"
          exit 1
        fi
        echo "DATABRICKS_CLUSTER_ID=$DATABRICKS_CLUSTER_ID" >> $GITHUB_ENV
    - name: Start Cluster
      run: |
        echo "Checking Cluster State (Cluster ID: $DATABRICKS_CLUSTER_ID)..."
        DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
        echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        
        if [ $DATABRICKS_CLUSTER_STATE == "TERMINATED" ]
        then
          echo "Starting Databricks Cluster..."
          databricks clusters start --cluster-id "$DATABRICKS_CLUSTER_ID"
          sleep 30
          DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
          echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        fi
        
        while [ $DATABRICKS_CLUSTER_STATE == "PENDING" ]
        do
          sleep 30
          DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
          echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        done
        
        if [ $DATABRICKS_CLUSTER_STATE == "RUNNING" ]
        then
          exit 0
        else
          exit 1
        fi
    - name: Create / Get Deploy ACI Job
      run: |
        job_id=$(databricks jobs list | grep "$DATABRICKS_JOB_DEPLOYTOACI_NAME" | awk '{print $1}')
        if [ -z "$job_id" ]
        then
        echo "Creating $DATABRICKS_JOB_DEPLOYTOACI_NAME job..."
        JSON=`cat << EOM
        {
          "notebook_task": {
            "notebook_path": "$DATABRICKS_NOTEBOOK_PATH/serving_deploy_to_aci",
            "base_parameters": {
              "model_image_id": ""
            }
          },
          "existing_cluster_id": "$DATABRICKS_CLUSTER_ID",
          "name": "$DATABRICKS_JOB_DEPLOYTOACI_NAME",
          "max_concurrent_runs": 1,
          "timeout_seconds": 86400,
          "libraries": [],
          "email_notifications": {}
        }
        EOM`
        job_id=$(databricks jobs create --json "$JSON" | jq ".job_id")
        else
        echo "Existing $DATABRICKS_JOB_DEPLOYTOACI_NAME job found (Job ID: $job_id)."
        fi
        echo "DATABRICKS_JOB_DEPLOYTOACI_ID=$job_id" >> $GITHUB_ENV
    - name: Get Image ID
      run: |
        echo "Retrieving Image ID..."
        model_image_id=$(cat model_image_id/image.json | jq -r ".model_image_id")
        if [ -z "$model_image_id" ]
        then
          echo "ERROR: Unable to get Image ID"
          exit 1
        fi
        echo "  Image ID: $model_image_id"
        echo "AZUREML_IMAGE_ID=$model_image_id" >> $GITHUB_ENV
    - name: Deploy To ACI
      run: |
        echo "Running job (Job ID: $DATABRICKS_JOB_DEPLOYTOACI_ID) with model_image_id=$AZUREML_IMAGE_ID..."
        notebook_params=$( jq -n --arg imgid "$AZUREML_IMAGE_ID" '{ model_image_id: $imgid }' )
        run_id=$(databricks jobs run-now --job-id $DATABRICKS_JOB_DEPLOYTOACI_ID --notebook-params "$notebook_params" | jq ".run_id")
        echo "  Run ID: $run_id"
        
        run_state=$(databricks runs get --run-id $run_id | jq -r ".state.life_cycle_state")
        echo "Run State (ID $run_id): $run_state"
        while [ $run_state == "RUNNING" -o $run_state == "PENDING" ]
        do
          sleep 30
          run_state=$(databricks runs get --run-id $run_id | jq -r ".state.life_cycle_state")
          echo "Run State (ID $run_id): $run_state"
        done
        result_state=$(databricks runs get --run-id $run_id | jq -r ".state.result_state")
        state_message=$(databricks runs get --run-id $run_id | jq -r ".state.state_message")
        echo "Result State (ID $run_id): $result_state, Message: $state_message"
        
        if [ $result_state == "SUCCESS" ]
        then
          exit 0
        else
          exit 1
        fi
  production:
    needs: [train, staging]
    runs-on: ubuntu-18.04
    env:
      DATABRICKS_HOST: https://westeurope.azuredatabricks.net
      DATABRICKS_TOKEN: ${{ secrets.DATABRICKS_TOKEN }}
      DATABRICKS_NOTEBOOK_PATH: /Shared/MLFlow
      DATABRICKS_CLUSTER_NAME: ML
      DATABRICKS_JOB_DEPLOYTOAKS_NAME: Wine Quality (Deploy To AKS)
    steps:
    - name: Download Model Image ID
      uses: actions/download-artifact@v1
      with:
        name: model_image_id
    - name: Set up Python 3.6
      uses: actions/setup-python@v1
      with:
        python-version: 3.6
    - name: Install Databricks CLI
      run: |
        python -m pip install --upgrade pip
        pip install -U databricks-cli
    - name: Configure Databricks CLI
      run: |
        # We need to write the pipe the conf into databricks configure --token since
        # that command only takes inputs from stdin. 
        conf=`cat << EOM
        $DATABRICKS_HOST
        $DATABRICKS_TOKEN
        EOM`
        
        # For password auth there are three lines expected
        # hostname, username, password
        echo "$conf" | databricks configure --token
    - name: Get Cluster ID
      run: |
        DATABRICKS_CLUSTER_ID=$(databricks clusters list | grep "$DATABRICKS_CLUSTER_NAME" | awk '{print $1}')
        if [ -z "$DATABRICKS_CLUSTER_ID" ]
        then
          echo "ERROR: Unable to get Cluster ID"
          exit 1
        fi
        echo "DATABRICKS_CLUSTER_ID=$DATABRICKS_CLUSTER_ID" >> $GITHUB_ENV
    - name: Start Cluster
      run: |
        echo "Checking Cluster State (Cluster ID: $DATABRICKS_CLUSTER_ID)..."
        DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
        echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        
        if [ $DATABRICKS_CLUSTER_STATE == "TERMINATED" ]
        then
          echo "Starting Databricks Cluster..."
          databricks clusters start --cluster-id "$DATABRICKS_CLUSTER_ID"
          sleep 30
          DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
          echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        fi
        
        while [ $DATABRICKS_CLUSTER_STATE == "PENDING" ]
        do
          sleep 30
          DATABRICKS_CLUSTER_STATE=$(databricks clusters get --cluster-id "$DATABRICKS_CLUSTER_ID" | jq -r ".state")
          echo "Cluster State: $DATABRICKS_CLUSTER_STATE"
        done
        
        if [ $DATABRICKS_CLUSTER_STATE == "RUNNING" ]
        then
          exit 0
        else
          exit 1
        fi
    - name: Create / Get Deploy AKS Job
      run: |
        job_id=$(databricks jobs list | grep "$DATABRICKS_JOB_DEPLOYTOAKS_NAME" | awk '{print $1}')
        if [ -z "$job_id" ]
        then
        echo "Creating $DATABRICKS_JOB_DEPLOYTOAKS_NAME job..."
        JSON=`cat << EOM
        {
          "notebook_task": {
            "notebook_path": "$DATABRICKS_NOTEBOOK_PATH/serving_deploy_to_aks",
            "base_parameters": {
              "model_image_id": ""
            }
          },
          "existing_cluster_id": "$DATABRICKS_CLUSTER_ID",
          "name": "$DATABRICKS_JOB_DEPLOYTOAKS_NAME",
          "max_concurrent_runs": 1,
          "timeout_seconds": 86400,
          "libraries": [],
          "email_notifications": {}
        }
        EOM`
        job_id=$(databricks jobs create --json "$JSON" | jq ".job_id")
        else
        echo "Existing $DATABRICKS_JOB_DEPLOYTOAKS_NAME job found (Job ID: $job_id)."
        fi
        echo "DATABRICKS_JOB_DEPLOYTOAKS_ID=$job_id" >> $GITHUB_ENV
    - name: Get Image ID
      run: |
        echo "Retrieving Image ID..."
        model_image_id=$(cat model_image_id/image.json | jq -r ".model_image_id")
        if [ -z "$model_image_id" ]
        then
          echo "ERROR: Unable to get Image ID"
          exit 1
        fi
        echo "  Image ID: $model_image_id"
        echo "AZUREML_IMAGE_ID=$model_image_id" >> $GITHUB_ENV
    - name: Deploy To AKS
      run: |
        echo "Running job (Job ID: $DATABRICKS_JOB_DEPLOYTOAKS_ID) with model_image_id=$AZUREML_IMAGE_ID..."
        notebook_params=$( jq -n --arg imgid "$AZUREML_IMAGE_ID" '{ model_image_id: $imgid }' )
        run_id=$(databricks jobs run-now --job-id $DATABRICKS_JOB_DEPLOYTOAKS_ID --notebook-params "$notebook_params" | jq ".run_id")
        echo "  Run ID: $run_id"
        
        run_state=$(databricks runs get --run-id $run_id | jq -r ".state.life_cycle_state")
        echo "Run State (ID $run_id): $run_state"
        while [ $run_state == "RUNNING" -o $run_state == "PENDING" ]
        do
          sleep 30
          run_state=$(databricks runs get --run-id $run_id | jq -r ".state.life_cycle_state")
          echo "Run State (ID $run_id): $run_state"
        done
        result_state=$(databricks runs get --run-id $run_id | jq -r ".state.result_state")
        state_message=$(databricks runs get --run-id $run_id | jq -r ".state.state_message")
        echo "Result State (ID $run_id): $result_state, Message: $state_message"
        
        if [ $result_state == "SUCCESS" ]
        then
          exit 0
        else
          exit 1
        fi