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pipeline {
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agent any
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environment {
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PATH = "/path/to/your/python/bin:${env.PATH}"
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SACRED_IGNORE_GIT = 'TRUE'
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}
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parameters {
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string(name: 'EPOCHS', defaultValue: '10', description: 'Liczba Epok')
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}
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stages {
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stage('Przygotowanie') {
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steps {
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sh 'pip install pandas tensorflow scikit-learn imbalanced-learn sacred pymongo mlflow'
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}
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}
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stage('Pobierz dane') {
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steps {
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script {
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copyArtifacts(projectName: 's487187-create-dataset', fingerprintArtifacts: true)
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}
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}
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}
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stage('Trenuj model') {
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steps {
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script {
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sh 'mlflow run . -P epochs=$EPOCHS'
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}
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}
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}
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stage('Zarchiwizuj model') {
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steps {
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sh '''
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mkdir -p model
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cp -r mlruns/* model/
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'''
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archiveArtifacts artifacts: 'model/**', fingerprint: true
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}
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}
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}
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}
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