48 lines
1.2 KiB
Plaintext
48 lines
1.2 KiB
Plaintext
pipeline {
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agent {
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docker {image 'zadanie'}
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}
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parameters {
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buildSelector(
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defaultSelector: lastSuccessful(),
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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: '100',
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description: 'number of epochs',
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name: 'EPOCH'
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)
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}
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stages {
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stage('Copy artifacts') {
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steps {
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copyArtifacts fingerprintArtifacts: true, projectName: 's444501-create-dataset', selector: buildParameter('BUILD_SELECTOR')
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}
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}
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stage('Train model') {
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steps {
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withEnv(["EPOCH=${params.EPOCH}"]) {
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sh 'python biblioteki_ml.py with "epochs=$EPOCH"'
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}
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}
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}
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stage('Archive artifacts') {
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steps {
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archiveArtifacts artifacts: 'model.pkl, neural_network_prediction_results.csv'
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archiveArtifacts artifacts: 'my_runs/**'
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}
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}
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stage ('Model - evaluation') {
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steps {
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build job: 's444501-evaluation/master', wait: false
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}
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}
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}
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post {
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always {
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emailext body: "${currentBuild.currentResult}", subject: 's444501-training', to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
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}
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}
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} |