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: 's440058-create-dataset', selector: buildParameter('WHICH_BUILD')
            }
        }
      stage('Docker'){
         steps{
            sh 'python3 "./pytorch-example.py" ${BATCH_SIZE} ${EPOCHS} > model.txt'
            sh 'python3 "./sacred-example-file.py"'
            sh 'python3 "./sacred-example-mongo.py"'
         }
      }
      stage('archiveArtifacts') {
			steps{
				archiveArtifacts 'model.txt'
                archiveArtifacts 'diabetes.pkl'
                archiveArtifacts 'diabetes.pth'
			}
		}
    }
    post {
        success {
            build job: 's440058-evaluation/master'
            mail body: 'SUCCESS TRAINING', subject: 's440058', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
        }

        failure {
            mail body: 'FAILURE TRAINING', subject: 's440058', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
        }

   }
}