55 lines
1.5 KiB
Plaintext
55 lines
1.5 KiB
Plaintext
pipeline {
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agent {
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dockerfile true
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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: 'WHICH_BUILD'
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)
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string(
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defaultValue: '16',
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description: 'batch size',
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name: 'BATCH_SIZE'
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)
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string(
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defaultValue: '15',
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description: 'epochs',
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name: 'EPOCHS'
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)
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}
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stages {
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stage('checkout') {
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steps {
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copyArtifacts fingerprintArtifacts: true, projectName: 's440058-create-dataset', selector: buildParameter('WHICH_BUILD')
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}
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}
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stage('Docker'){
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steps{
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sh 'python3 "./pytorch-example.py" ${BATCH_SIZE} ${EPOCHS} > model.txt'
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sh 'python3 "./sacred-example-file.py"'
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sh 'python3 "./sacred-example-mongo.py"'
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}
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}
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stage('archiveArtifacts') {
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steps{
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archiveArtifacts 'model.txt'
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archiveArtifacts 'diabetes.pkl'
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archiveArtifacts 'diabetes.pth'
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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: 's440058-evaluation/master'
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mail body: 'SUCCESS TRAINING', subject: 's440058', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
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}
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failure {
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mail body: 'FAILURE TRAINING', subject: 's440058', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
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}
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}
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} |