ium_444452/Jenkins/Jenkinsfile.training
AdamOsiowy123 b786b7176d
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fix paramteres
2022-05-08 13:57:52 +02:00

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node {
checkout scm
try {
docker.image('s444452/ium:1.3').inside {
stage('Preparation') {
properties([
pipelineTriggers([upstream(threshold: hudson.model.Result.SUCCESS, upstreamProjects: "s444452-create-dataset")]),
parameters([
string(
defaultValue: ".",
description: 'Data path',
name: 'DATA_PATH'
),
string(
defaultValue: "1",
description: 'EPOCHS',
name: 'EPOCHS'
),
string(
defaultValue: "20000",
description: 'Num words',
name: 'NUM_WORDS'
),
string(
defaultValue: "150",
description: 'Batch size',
name: 'BATCH_SIZE'
),
string(
defaultValue: "300",
description: 'Pad length',
name: 'PAD_LENGTH'
)
])
])
}
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'
}
stage('Run script') {
withEnv(["DATA_PATH=${params.DATA_PATH}","EPOCHS=${params.EPOCHS}","NUM_WORDS=${params.NUM_WORDS}",
"BATCH_SIZE=${params.BATCH_SIZE}","PAD_LENGTH=${params.PAD_LENGTH}"]) {
sh "python3 Scripts/train_neural_network.py $DATA_PATH $EPOCHS $NUM_WORDS $BATCH_SIZE $PAD_LENGTH"
}
}
stage('Archive artifacts') {
archiveArtifacts "model/neural_net"
archiveArtifacts "my_runs/**"
}
}
} 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}"
def build_params = "Path: ${params.DATA_PATH}, Epochs: ${params.EPOCHS}, Num_words: ${params.NUM_WORDS}, Batch_size: ${params.BATCH_SIZE}, Pad_length: ${params.PAD_LENGTH}"
def details = "Build nr: ${env.BUILD_NUMBER}, status: ${buildStatus} \n url: ${env.BUILD_URL} \n build params: ${build_params}"
if (buildStatus == 'SUCCESS') {
build (
job: "s444452-evaluation/${env.BRANCH_NAME}",
parameters: [
gitParameter(name: "BRANCH", value: "${env.BRANCH_NAME}"),
string(name: "BUILD_NR", value: "${env.BUILD_NUMBER}"),
string(name: "DATA_PATH", value: "${params.DATA_PATH}"),
string(name: "EPOCHS", value: "${params.EPOCHS}"),
string(name: "NUM_WORDS", value: "${params.NUM_WORDS}"),
string(name: "BATCH_SIZE", value: "${params.BATCH_SIZE}"),
string(name: "PAD_LENGTH", value: "${params.PAD_LENGTH}")
],
wait: false
)
}
emailext (
subject: subject,
body: details,
to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
)
}