ium_444409/Jenkinsfile-train

59 lines
1.5 KiB
Plaintext
Raw Normal View History

2022-05-05 21:40:34 +02:00
pipeline {
2022-05-05 22:11:32 +02:00
parameters {
string(
defaultValue: '64',
description: 'Batch size used in ADAM',
name: 'BATCHSIZE',
trim: true
)
string(
defaultValue: '5',
description: 'Number of iterations',
name: 'EPOCHS',
trim: true
)
}
2022-05-05 21:40:34 +02:00
agent {
docker {
image 's444409-create-dataset'
}
}
stages {
stage('Train model') {
steps {
2022-05-05 22:11:32 +02:00
sh "python train_model.py -e ${params.EPOCHS} -b ${params.BATCHSIZE}"
2022-05-05 21:40:34 +02:00
}
}
2022-05-05 23:02:43 +02:00
stage('Archive model and evaluate it') {
steps {
archiveArtifacts artifacts: 'model_out', onlyIfSuccessful: true
2022-05-05 23:09:09 +02:00
build job: 's444409-evaluation'
2022-05-05 23:02:43 +02:00
}
}
2022-05-05 21:40:34 +02:00
}
2022-05-05 21:53:00 +02:00
environment {
NOTIFICATION_ADDRESS = 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
}
2022-05-05 21:40:34 +02:00
post {
2022-05-05 21:53:00 +02:00
success {
emailext body: 'SUCCESS', subject: "${env.JOB_NAME}", to: "${env.NOTIFICATION_ADDRESS}"
}
failure {
emailext body: 'FAILURE', subject: "${env.JOB_NAME}", to: "${env.NOTIFICATION_ADDRESS}"
}
unstable {
emailext body: 'UNSTABLE', subject: "${env.JOB_NAME}", to: "${env.NOTIFICATION_ADDRESS}"
}
changed {
emailext body: 'CHANGED', subject: "${env.JOB_NAME}", to: "${env.NOTIFICATION_ADDRESS}"
}
2022-05-05 21:40:34 +02:00
}
}