86 lines
2.0 KiB
Plaintext
86 lines
2.0 KiB
Plaintext
pipeline {
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agent {
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dockerfile {
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filename 'Dockerfile'
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label 'docker'
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}
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}
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triggers {
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upstream(upstreamProjects: 's123456-create-dataset', threshold: hudson.model.Result.SUCCESS)
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}
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parameters {
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string(
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defaultValue: '--epochs 100 --batch_size 32 --learning_rate 0.01',
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description: 'Parametry trenowania',
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name: 'TRAINING_PARAMS'
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)
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}
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environment {
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DATASET_PROJECT = 's123456-create-dataset'
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DATA_DIR = 'data'
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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 Dataset') {
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steps {
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script {
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copyArtifacts(
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projectName: "${env.DATASET_PROJECT}",
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selector: lastSuccessful(),
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target: "${env.DATA_DIR}"
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)
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}
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}
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}
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stage('Set execute permission') {
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steps {
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script {
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sh 'chmod +x data_processing.sh'
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}
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}
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}
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stage('Run shell script') {
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steps {
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script {
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sh './data_processing.sh'
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}
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}
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post {
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success {
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archiveArtifacts artifacts: 'results.txt', allowEmptyArchive: true
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}
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}
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}
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stage('Train Model') {
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steps {
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sh "python3 model.py ${params.TRAINING_PARAMS}"
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}
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}
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stage('Archive Model') {
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steps {
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archiveArtifacts artifacts: 'orange_quality_model_tf.h5', allowEmptyArchive: true
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archiveArtifacts artifacts: 'predictions_tf.json', allowEmptyArchive: true
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}
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}
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}
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post {
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always {
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cleanWs()
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}
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}
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}
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