62 lines
1.5 KiB
Groovy
62 lines
1.5 KiB
Groovy
pipeline {
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agent { dockerfile true }
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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('copy artifacts')
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{
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steps
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{
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copyArtifacts(fingerprintArtifacts: true, projectName: 's434695-create-dataset', selector: buildParameter('WHICH_BUILD'))
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}
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}
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stage('train')
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{
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steps
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{
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sh 'python3 train.py ${BATCH_SIZE} ${EPOCHS}'
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sh 'rm -r my_model'
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sh 'python3 vgsales-mlflow.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 'vgsales_model.h5'
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archiveArtifacts 'my_runs/**/*'
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archiveArtifacts 'my_model/**/*'
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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: 's434695-evaluation/evaluation'
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mail body: 'SUCCESS TRAINING', subject: 's434695', 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: 's434695', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
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}
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}
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}
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