Multibranch pipeline training

Dockerfile

@@ -9,11 +9,11 @@ RUN python3 -m pip install --upgrade tensorflow
 
 WORKDIR app
 
-ARG CUTOFF
-ENV CUTOFF=${CUTOFF}
+ARG EPOCHS
+ENV EPOCHS=${EPOCHS}
 
 COPY ml_training.py ./
 COPY heart_2020_cleaned.csv ./
 
 
-CMD ["python3", "./ml_training.py"]
+CMD ["python3", "./ml_training.py", EPOCHS]

Jenkinsfile.train

@@ -0,0 +1,27 @@
+pipeline {
+    agent {
+        dockerfile true
+    }
+    parameters {
+        string(
+            defaultValue: "10",
+            description: 'How many epochs during training?',
+            name: 'epochs'
+        )
+    }
+    stages {
+        stage("Git clone") {
+            steps {
+              checkout([$class: 'GitSCM', branches: [[name: '*/master']], extensions: [], userRemoteConfigs: [[credentialsId: 's444465', url: 'https://git.wmi.amu.edu.pl/s444465/ium_444465']]])
+            }
+        }
+        stage("Training") {
+            steps {
+                withEnv(["EPOCHS=${params.EPOCHS}"]) {
+                    sh "chmod 777 ml_training.py"
+                    sh "python3 ml_training.py $EPOCHS"
+                }
+            }
+        }
+    }
+}

ml_training.py

@@ -3,9 +3,13 @@ import pandas as pd
 import tensorflow as tf
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
-
+import sys
 
 def main():
+    no_of_epochs = 10
+    if len(sys.argv) == 2:
+        no_of_epochs = int(sys.argv[1])
+
     scaler = StandardScaler()
     feature_names = ["BMI", "SleepTime", "Sex", "Diabetic", "PhysicalActivity", "Smoking", "AlcoholDrinking"]
 
@@ -54,7 +58,7 @@ def main():
     test_X = tf.convert_to_tensor(test_X)
     test_Y = tf.convert_to_tensor(test_Y)
 
-    model.fit(train_X, train_Y, epochs=10)
+    model.fit(train_X, train_Y, epochs=no_of_epochs)
     model.save("trained_model")
 
     test_loss, test_acc, test_rec = model.evaluate(test_X, test_Y, verbose=1)