pipeline {
    agent {
	    docker {
	        image 'agakul/ium:mlflow'
	        args '-v /mlruns:/mlruns'
	    }
    }
    	parameters {
    			buildSelector(
			defaultSelector: lastSuccessful(),
			description: 'Which build to use for copying artifacts',
			name: 'BUILD_SELECTOR'
		)
		string(
			defaultValue: '1000',
            		description: 'Number of epochs',
            		name: 'EPOCHS'
		)
	}
    stages {
		stage('Check out from version control') {
			steps {
				checkout([$class: 'GitSCM', branches: [[name: '*/training_and_evaluation']], extensions: [], userRemoteConfigs: [[credentialsId: 's444421', url: 'https://git.wmi.amu.edu.pl/s444421/ium_444421.git']]])
			}
		}
        stage('Training') {
            steps {
            	copyArtifacts filter: '*', projectName:'s444421-create-dataset', selector: buildParameter('BUILD_SELECTOR')
            	sh 'python training_mlflow.py $EPOCHS'
            	archiveArtifacts artifacts: 'mlruns/**'
            }
        }
    }
}