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('copy artifacts')
            {
                steps
                {
                    copyArtifacts(fingerprintArtifacts: true, projectName: 's434695-create-dataset', selector: buildParameter('WHICH_BUILD'))
                }
            }
            stage('train')
            {
                steps
                {
                       sh 'python3 train.py ${BATCH_SIZE} ${EPOCHS}'
                       sh 'rm -r my_model'
                       sh 'python3 vgsales-mlflow.py'
                }
            }


		stage('Archive artifacts') {
			steps{
				archiveArtifacts 'vgsales_model.h5'
            archiveArtifacts 'my_runs/**/*'
            archiveArtifacts 'my_model/**/*'

			}
		}
	}
    post {
        success {
            build job: 's434695-evaluation/evaluation'
            mail body: 'SUCCESS TRAINING', subject: 's434695', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
        }

        failure {
            mail body: 'FAILURE TRAINING', subject: 's434695', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
        }

   }
}