ium_444452/Jenkins/Jenkinsfile.training

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node {
checkout scm
docker.image('s444452/ium:1.3').inside {
stage('Preparation') {
properties([
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pipelineTriggers([upstream(threshold: hudson.model.Result.SUCCESS, upstreamProjects: "s444452-create-dataset")]),
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parameters([
string(
defaultValue: ".",
description: 'Arguments for model training: arg1,arg2,arg3',
name: 'TRAIN_ARGS'
)
])
])
}
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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'
copyArtifacts filter: 'dev_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
}
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stage('Run script') {
withEnv(["TRAIN_ARGS=${params.TRAIN_ARGS}"]) {
sh "python3 Scripts/train_neural_network.py $TRAIN_ARGS"
}
}
}
}