99 lines
3.7 KiB
Plaintext
99 lines
3.7 KiB
Plaintext
node {
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checkout scm
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try {
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docker.image('s444452/ium:1.3').inside {
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stage('Preparation') {
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properties([
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parameters([
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gitParameter(
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branchFilter: 'origin/(.*)',
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defaultValue: 'master',
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description: 'Select branch',
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name: 'BRANCH',
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type: 'PT_BRANCH'
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),
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buildSelector(
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defaultSelector: upstream(),
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description: 'Which build to use for copying artifacts',
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name: 'BUILD_SELECTOR'
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),
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string(
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defaultValue: "0",
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description: 'Build number',
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name: 'BUILD_NR'
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),
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string(
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defaultValue: ".",
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description: 'Data path',
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name: 'DATA_PATH'
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),
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string(
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defaultValue: "1",
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description: 'EPOCHS',
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name: 'EPOCHS'
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),
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string(
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defaultValue: "20000",
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description: 'Num words',
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name: 'NUM_WORDS'
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),
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string(
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defaultValue: "150",
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description: 'Batch size',
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name: 'BATCH_SIZE'
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),
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string(
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defaultValue: "300",
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description: 'Pad length',
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name: 'PAD_LENGTH'
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)
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])
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])
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}
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stage('Copy artifacts') {
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copyArtifacts filter: 'train_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
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copyArtifacts filter: 'test_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
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copyArtifacts filter: 'neural_network_evaluation.csv', projectName: "s444452-evaluation/${params.BRANCH}", optional: true
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copyArtifacts filter: 'model/neural_net', projectName: "s444452-training/${params.BRANCH}", selector: buildParameter('BUILD_SELECTOR')
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}
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stage('Run script') {
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withEnv(["BUILD_NR=${params.BUILD_NR}","DATA_PATH=${params.DATA_PATH}","EPOCHS=${params.EPOCHS}",
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"NUM_WORDS=${params.NUM_WORDS}", "BATCH_SIZE=${params.BATCH_SIZE}","PAD_LENGTH=${params.PAD_LENGTH}"]) {
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sh "python3 Scripts/evaluate_neural_network.py $BUILD_NR $DATA_PATH $EPOCHS $NUM_WORDS $BATCH_SIZE $PAD_LENGTH"
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}
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}
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stage('Archive artifacts') {
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archiveArtifacts "neural_network_evaluation.csv, evaluation.png"
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archiveArtifacts "my_runs/**"
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}
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}
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} catch (e) {
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currentBuild.result = "FAILED"
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throw e
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} finally {
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notifyBuild(currentBuild.result)
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}
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}
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def notifyBuild(String buildStatus = 'STARTED') {
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buildStatus = buildStatus ?: 'SUCCESS'
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def subject = "Job: ${env.JOB_NAME}"
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def lastline = ""
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try {
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def filePath = readFile "${WORKSPACE}/neural_network_evaluation.csv"
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def lines = filePath.readLines()
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lastline = lines.get(lines.size()-1)
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}
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catch (e) {
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println(e.toString())
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}
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def build_params = "Path: ${params.DATA_PATH}, Epochs: ${params.EPOCHS}, Num_words: ${params.NUM_WORDS}, Batch_size: ${params.BATCH_SIZE}, Pad_length: ${params.PAD_LENGTH}"
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def details = "Build nr: ${env.BUILD_NUMBER}, status: ${buildStatus} \n url: ${env.BUILD_URL} \n build params: ${build_params} \n metrics: ${lastline}"
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emailext (
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subject: subject,
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body: details,
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to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
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)
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} |