pipeline {
   agent {
      dockerfile true
   }
   parameters{
      buildSelector(
            defaultSelector: lastSuccessful(),
            description: 'Which build to use for copying artifacts',
            name: 'WHICH_BUILD'
        )
        string(
            defaultValue: '16',
            description: 'batch size',
            name: 'BATCH_SIZE'
        )
        string(
            defaultValue: '15', 
            description: 'epochs',
            name: 'EPOCHS'
        )
   stages {
      stage('checkout') {
            steps {
                copyArtifacts(fingerprintArtifacts: true, projectName: 's434766-create-dataset', selector: buildParameter('WHICH_BUILD'))
            }
        }
      stage('Docker'){
         steps{
            sh 'python3 "./stroke-pytorch.py" ${BATCH_SIZE} ${EPOCHS} > pred.txt'
         }
      }
      stage('archiveArtifacts') {
         steps {
            archiveArtifacts 'pred.txt'
            archiveArtifacts 'stroke.pkl'
         }
                     post {
                        success {
                           emailext body: 'Training of stroke predictions is finished',
                           subject: 's434766 training finished',
                           to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
                }
            }
      }
   }
}