77 lines
2.3 KiB
Groovy
77 lines
2.3 KiB
Groovy
pipeline {
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agent any
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parameters {
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string(
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name: 'epochs',
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defaultValue: '1000',
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description: 'Number of epochs for training'
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)
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string(
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name: 'learning_rate',
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defaultValue: '0.001',
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description: 'Learning rate for training'
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)
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string(
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name: 'weight_decay',
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defaultValue: '0.001',
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description: 'Regularization parameter for training'
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)
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}
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stages {
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stage('Clone repository') {
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steps {
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checkout scm
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}
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}
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stage('Copy artifacts') {
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agent {
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dockerfile {
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filename 'Dockerfile'
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reuseNode true
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}
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}
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steps {
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copyArtifacts(projectName: 'z-s464863-create-dataset', filter: 'datasets/*', selector: lastSuccessful())
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}
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}
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stage('Create model') {
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agent {
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dockerfile {
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filename 'Dockerfile'
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reuseNode true
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}
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}
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steps {
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script {
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sh "chmod +x ./create_model.py"
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sh "python3 ./create_model.py with 'num_epochs=${params.epochs}' 'learning_rate=${params.learning_rate}' 'weight_decay=${params.weight_decay}'"
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archiveArtifacts artifacts: "models/model.pth", onlyIfSuccessful: true
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def experiment_id = readFile('experiment_id.txt').trim()
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archiveArtifacts artifacts: "my_runs/${experiment_id}/*", onlyIfSuccessful: true
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def sources = readFile('sources.txt').split('\n')
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for (def source in sources) {
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archiveArtifacts artifacts: "my_runs/${source}", onlyIfSuccessful: true
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}
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def resources = readFile('resources.txt').split('\n')
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for (def resource in resources) {
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archiveArtifacts artifacts: "${resource}", onlyIfSuccessful: true
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}
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build job: 's464863-evaluation/main', wait: false
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}
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}
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}
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}
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} |