Zaktualizuj 'Jenkinsfile_training'
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Add mount mlflow folder
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@ -1,5 +1,8 @@
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pipeline {
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pipeline {
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agent {dockerfile true}
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agent {dockerfile true}
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environment {
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img = docker.build('s430705/ium:4')
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}
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parameters {
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parameters {
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buildSelector(
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buildSelector(
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defaultSelector: lastSuccessful(),
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defaultSelector: lastSuccessful(),
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@ -13,11 +16,17 @@ pipeline {
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}
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}
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stages {
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stages {
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stage('MLFLOW mounted'){
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img.inside('-v /tmp/mlruns:/tmp/mlruns -v /mlruns:/mlruns ') {
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sh "export MLFLOW_TRACKING_URI=http://172.17.0.1:5000"
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sh "python3 lab08_mfl.py"
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}
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}
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stage('copyArtifacts') {
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stage('copyArtifacts') {
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steps {
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steps {
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copyArtifacts fingerprintArtifacts: true, projectName: 's430705-create-dataset', selector: buildParameter('BUILD_SELECTOR')
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copyArtifacts fingerprintArtifacts: true, projectName: 's430705-create-dataset', selector: buildParameter('BUILD_SELECTOR')
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sh "python3 lab08_mfl.py"
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sh "rm -rf movies_imdb"
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sh "export MLFLOW_TRACKING_URI=http://172.17.0.1:5000"
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sh "python3 lab08_mfl.py"
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sh "python3 lab08_mfl.py"
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sh "python3 lab06_training.py ${epochs}"
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sh "python3 lab06_training.py ${epochs}"
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}
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}
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