pipeline {
    agent {
        docker { 
            image 's444507_create_dataset_image:latest' 
            args '-v /mlruns:/mlruns'
        }
    }
    parameters {
        string(name: 'epoch', defaultValue: '100', description: 'Number of epochs to train model.')
    }
    stages {
        stage('Get artifacts') {
            steps {
                copyArtifacts fingerprintArtifacts: true, projectName: 's444507-create-dataset', selector: lastSuccessful()
                archiveArtifacts artifacts: 'CarPrices_pytorch_model.pkl'
                archiveArtifacts artifacts: 'mlruns/**'
                archiveArtifacts artifacts: 'my_model/**'
                sh 'rm -r mlruns'
                sh 'rm -r my_model'
            }
        }
        stage('Run mlflow script and save artifacts') {
            steps {
                sh "python3 lab08_deepLearining_mlflow.py $epoch"

            }
        }
    }
    post {
        always {
            emailext body: "${currentBuild.currentResult}", subject: 's444507-training', to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
        }
    }
}