IUM_06

IUM_05-model.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import tensorflow as tf
+import sys
 
 train_data = pd.read_csv('./beer_reviews_train.csv')
 X_train = train_data[['review_aroma', 'review_appearance', 'review_palate', 'review_taste']]
@@ -22,6 +23,6 @@ model.compile(optimizer='adam',
               loss='binary_crossentropy',
               metrics=['accuracy'])
 
-model.fit(X_train_pad, y_train, epochs=40, batch_size=32, validation_split=0.1)
+model.fit(X_train_pad, y_train, epochs=int(sys.argv[1]), batch_size=int(sys.argv[2]), validation_split=0.1)
 
 model.save('beer_review_sentiment_model.h5')

Jenkinsfile

@@ -1,36 +1,25 @@
 pipeline {
     agent any
 
+    triggers {
+        upstream(upstreamProjects: 'z-s464979-create-dataset', threshold: hudson.model.Result.SUCCESS)
+    }
+
     parameters {
-        string(name: 'CUTOFF', defaultValue: '10000', description: 'Liczba wierszy do obcięcia ze zbioru danych')
-	    string(name: 'KAGGLE_USERNAME', defaultValue: '', description: 'Kaggle username')
-        password(name: 'KAGGLE_KEY', defaultValue: '', description: 'Kaggle API key')
+        string(name: 'EPOCHS', defaultValue: '40', description: 'Number of epochs')
+        string(name: 'BATCH_SIZE', defaultValue: '32', description: 'Batch size')
+        buildSelector(defaultSelector: lastSuccessful(), description: 'Which build to use for copying artifacts', name: 'BUILD_SELECTOR')
     }
 
     stages {
         stage('Clone Repository') {
             steps {
-                git url: "https://git.wmi.amu.edu.pl/s464979/ium_464979"
+                git branch: 'training', url: "https://git.wmi.amu.edu.pl/s464979/ium_464979.git"
             }
         }
-        stage('Download dataset') {
+        stage('Copy Artifacts') {
             steps {
-                 withEnv(["KAGGLE_USERNAME=${env.KAGGLE_USERNAME}", "KAGGLE_KEY=${env.KAGGLE_KEY}"]) {
-                    sh "kaggle datasets download -d thedevastator/1-5-million-beer-reviews-from-beer-advocate --unzip"
-                }
-            }
-        }
-        stage('Process and Split Dataset') {
-            agent {
-                dockerfile {
-                    filename 'Dockerfile'
-                    reuseNode true
-                }
-            }
-            steps {
-                sh "chmod +x ./IUM_05-split.py"
-                sh "python3 ./IUM_05-split.py"
-                archiveArtifacts artifacts: 'beer_reviews.csv,beer_reviews_train.csv,beer_reviews_test.csv', onlyIfSuccessful: true
+                 copyArtifacts filter: 'beer_reviews.csv,beer_reviews_train.csv,beer_reviews_test.csv', projectName: 'z-s464979-create-dataset', selector: buildParameter('BUILD_SELECTOR')
             }
         }
         stage("Run") {
@@ -42,16 +31,9 @@ pipeline {
             }
             steps {
                 sh "chmod +x ./IUM_05-model.py"
-                sh "chmod +x ./IUM_05-predict.py"
-                sh "python3 ./IUM_05-model.py"
-                sh "python3 ./IUM_05-predict.py"
-                archiveArtifacts artifacts: 'beer_review_sentiment_model.h5,beer_review_sentiment_predictions.csv', onlyIfSuccessful: true
+                sh "python3 ./IUM_05-model.py ${params.EPOCHS} ${params.BATCH_SIZE}"
+                archiveArtifacts artifacts: 'beer_review_sentiment_model.h5', onlyIfSuccessful: true
             }
         }
     }
-//     post {
-//         always {
-//              deleteDir()
-//         }
-//     }
 }