63 lines
2.2 KiB
Groovy
63 lines
2.2 KiB
Groovy
pipeline {
|
|
agent any
|
|
parameters {
|
|
string(name: 'KAGGLE_USERNAME', defaultValue: 'alicjaszulecka', description: 'Kaggle username')
|
|
password(name: 'KAGGLE_KEY', defaultValue:'', description: 'Kaggle Key')
|
|
string(name: 'CUTOFF', defaultValue: '100', description: 'cut off number')
|
|
}
|
|
stages {
|
|
stage('Git Checkout') {
|
|
steps {
|
|
checkout scm
|
|
}
|
|
}
|
|
stage('Download dataset') {
|
|
steps {
|
|
withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}"]) {
|
|
sh 'pip install kaggle'
|
|
sh 'kaggle datasets download -d uciml/forest-cover-type-dataset'
|
|
sh 'unzip -o forest-cover-type-dataset.zip'
|
|
sh 'rm forest-cover-type-dataset.zip'
|
|
}
|
|
}
|
|
}
|
|
stage('Build') {
|
|
steps {
|
|
script {
|
|
withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
|
|
"KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
|
|
def customImage = docker.build("custom-image")
|
|
customImage.inside {
|
|
sh 'python3 ./IUM_2.py'
|
|
archiveArtifacts artifacts: 'covtype.csv, forest_train.csv, forest_test.csv, forest_val.csv', onlyIfSuccessful: true
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
stage('Train and Predict') {
|
|
steps {
|
|
script {
|
|
def customImage = docker.build("custom-image")
|
|
customImage.inside {
|
|
sh 'python3 ./model.py'
|
|
sh 'python3 ./prediction.py'
|
|
archiveArtifacts artifacts: 'model.pth, predictions.txt', onlyIfSuccessful: true
|
|
}
|
|
}
|
|
}
|
|
}
|
|
stage('Experiments') {
|
|
steps {
|
|
script {
|
|
def customImage = docker.build("custom-image")
|
|
customImage.inside {
|
|
sh 'python3 ./sacred_model.py'
|
|
archiveArtifacts artifacts: 'experiments', onlyIfSuccessful: true
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
} |