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@ -3,6 +3,7 @@ node {
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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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pipelineTriggers([upstream(threshold: hudson.model.Result.SUCCESS, upstreamProjects: "s444452-create-dataset")]),
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parameters([
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string(
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defaultValue: ".",
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@ -12,6 +13,11 @@ node {
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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: 'dev_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
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}
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stage('Run script') {
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withEnv(["TRAIN_ARGS=${params.TRAIN_ARGS}"]) {
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sh "python3 Scripts/train_neural_network.py $TRAIN_ARGS"
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