s434766
49038cd155
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47 lines
1.3 KiB
Groovy
47 lines
1.3 KiB
Groovy
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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stages {
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stage('checkout') {
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steps {
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copyArtifacts(fingerprintArtifacts: true, projectName: 's434766-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 "./stroke-pytorch.py" ${BATCH_SIZE} ${EPOCHS} > pred.txt'
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}
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}
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stage('archiveArtifacts') {
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steps {
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archiveArtifacts 'pred.txt'
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archiveArtifacts 'stroke.pkl'
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}
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post {
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success {
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emailext body: 'Training of stroke predictions is finished',
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subject: 's434766 training finished',
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to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
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}
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}
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}
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}
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} |