63 lines
2.1 KiB
Groovy
63 lines
2.1 KiB
Groovy
pipeline {
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agent {
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dockerfile true
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}
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triggers {
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upstream(upstreamProjects: 's464979-training/training', threshold: hudson.model.Result.SUCCESS)
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}
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parameters {
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buildSelector(defaultSelector: lastSuccessful(), description: 'Which build to use for copying artifacts', name: 'BUILD_SELECTOR')
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gitParameter branchFilter: 'origin/(.*)', defaultValue: 'training', name: 'BRANCH', type: 'PT_BRANCH'
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}
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stages {
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stage('Clone Repository') {
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steps {
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git branch: 'evaluation', url: "https://git.wmi.amu.edu.pl/s464979/ium_464979"
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}
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}
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stage('Copy Dataset Artifacts') {
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steps {
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copyArtifacts filter: 'beer_reviews.csv,beer_reviews_train.csv,beer_reviews_test.csv', projectName: 'z-s464979-create-dataset', selector: buildParameter('BUILD_SELECTOR')
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}
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}
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stage('Copy Training Artifacts') {
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steps {
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copyArtifacts filter: 'beer_review_sentiment_model.h5', projectName: 's464979-training/' + params.BRANCH, selector: buildParameter('BUILD_SELECTOR')
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}
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}
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stage('Copy Evaluation Artifacts') {
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steps {
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copyArtifacts filter: 'beer_metrics.txt', projectName: '_s464979-evaluation/evaluation', selector: buildParameter('BUILD_SELECTOR'), optional: true
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}
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}
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stage("Run predictions") {
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steps {
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sh "chmod +x ./IUM_05-predict.py"
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sh "python3 ./IUM_05-predict.py"
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archiveArtifacts artifacts: 'beer_review_sentiment_predictions.csv', onlyIfSuccessful: true
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}
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}
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stage('Run metrics') {
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steps {
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sh 'chmod +x ./IUM_06-metrics.py'
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sh "python3 ./IUM_06-metrics.py ${currentBuild.number}"
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}
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}
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stage('Run plot') {
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steps {
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sh 'chmod +x ./IUM_06-plot.py'
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sh 'python3 ./IUM_06-plot.py'
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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: '*', onlyIfSuccessful: true
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}
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}
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}
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}
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