ium_444452/Jenkins/Jenkinsfile.evaluation

node {
    checkout scm
    try {
        docker.image('s444452/ium:1.3').inside {
        stage('Preparation') {
            properties([
                parameters([
                gitParameter(
                    branchFilter: 'origin/(.*)',
                    defaultValue: 'master',
                    description: 'Select branch',
                    name: 'BRANCH',
                    type: 'PT_BRANCH'
                ),
                buildSelector(
                    defaultSelector: upstream(),
                    description: 'Which build to use for copying artifacts',
                    name: 'BUILD_SELECTOR'
                ),
                string(
                    defaultValue: ".,14000,1,50,100",
                    description: 'Test params: data_path,num_words,epochs,batch_size,pad_length',
                    name: 'TEST_PARAMS'
                ),
                string(
                    defaultValue: "0",
                    description: 'Build number',
                    name: 'BUILD_NR'
                )
                ])
            ])
        }
        stage('Copy artifacts') {
            copyArtifacts filter: 'train_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
            copyArtifacts filter: 'test_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
            git branch: "${params.BRANCH}", url: 'https://git.wmi.amu.edu.pl/s444452/ium_444452.git'
            copyArtifacts filter: 'neural_network_evaluation.csv', projectName: "s444452-evaluation/${BRANCH}/", optional: true
            copyArtifacts filter: 'model/neural_net', projectName: "s444452-training/${BRANCH}/", selector: buildParameter('BUILD_SELECTOR')
        }
        stage('Run script') {
            withEnv(["TEST_PARAMS=${params.TEST_PARAMS}", "BUILD_NR=${params.BUILD_NR}"]) {
                sh "python3 Scripts/evaluate_neural_network.py $BUILD_NR $TEST_PARAMS"
            }
        }
        stage('Archive artifacts') {
            archiveArtifacts "neural_network_evaluation.csv, evaluation.png"
        }
        }
    } catch (e) {
        currentBuild.result = "FAILED"
        throw e
    } finally {
        notifyBuild(currentBuild.result)
    }
}
def notifyBuild(String buildStatus = 'STARTED') {
    buildStatus = buildStatus ?: 'SUCCESS'

    def subject = "Job: ${env.JOB_NAME}"
    def lines= new File("./neural_network_evaluation.csv").readLines()
    def lastline=lines.get(lines.size()-1)
    def details = "Build nr: ${env.BUILD_NUMBER}, status: ${buildStatus} \n url: ${env.BUILD_URL} \n build params: ${params.TEST_PARAMS} \n metrics: ${lastline}"

    emailext (
        subject: subject,
        body: details,
        to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
    )
}