ium_444452/Jenkins/Jenkinsfile.evaluation

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node {
checkout scm
try {
docker.image('s444452/ium:1.3').inside {
stage('Preparation') {
properties([
parameters([
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gitParameter(
branchFilter: 'origin/(.*)',
defaultValue: 'master',
description: 'Select branch',
name: 'BRANCH',
type: 'PT_BRANCH'
),
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string(
defaultValue: "0",
description: 'BUILD_NR',
name: 'BUILD_NR'
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),
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string(
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defaultValue: ".,14000,1,50,100",
description: 'Test params: data_path,num_words,epochs,batch_size,pad_length',
name: 'TEST_PARAMS'
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)
])
])
}
stage('Copy artifacts') {
copyArtifacts filter: 'train_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
copyArtifacts filter: 'test_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
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git branch: "${params.BRANCH}", url: 'https://git.wmi.amu.edu.pl/s444452/ium_444452.git'
copyArtifacts filter: 'neural_network_evaluation.csv', projectName: "s444452-evaluation/${BRANCH}/", optional: true
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copyArtifacts filter: 'model/neural_net', projectName: "s444452-training/${BRANCH}/"
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}
stage('Run script') {
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withEnv(["TEST_PARAMS=${params.TEST_PARAMS}"]) {
sh "python3 Scripts/evaluate_neural_network.py ${params.BUILD_NR} $TEST_PARAMS"
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}
}
stage('Archive artifacts') {
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archiveArtifacts "neural_network_evaluation.csv, evaluation.png"
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}
}
} catch (e) {
currentBuild.result = "FAILED"
throw e
} finally {
notifyBuild(currentBuild.result)
}
}
def notifyBuild(String buildStatus = 'STARTED') {
buildStatus = buildStatus ?: 'SUCCESS'
def subject = "Job: ${env.JOB_NAME}"
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def details = "Build nr: ${env.BUILD_NUMBER}, status: ${buildStatus} \n url: ${env.BUILD_URL} \n build params: ${params.TEST_PARAMS}"
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emailext (
subject: subject,
body: details,
to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
)
}