47 lines
1.3 KiB
Groovy
47 lines
1.3 KiB
Groovy
pipeline {
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agent any
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parameters {
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buildSelector(
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name: 'BUILD_SELECTOR',
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defaultSelector: lastSuccessful(),
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description: 'A build to take the artifacts from'
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)
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string(
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name: 'EPOCHS',
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description: 'Number of epochs',
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defaultValue: '10'
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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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script {
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copyArtifacts(
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projectName: 'z-s487179-create-dataset',
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selector: buildParameter('BUILD_SELECTOR'),
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target: './MLTrain'
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)
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}
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}
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}
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stage('Run training and save model') {
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steps {
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script {
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sh 'ls -l'
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docker.image('docker-image').inside {
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dir('./MLTrain') {
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sh 'ls -l'
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sh 'python3 ./model_train.py'
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archiveArtifacts 'model.pt'
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}
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}
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}
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}
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}
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}
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post {
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success {
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build job: 'z-s487179-evaluation.eg/main', wait: false
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}
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}
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} |