.

biblioteki_ml.py

@@ -1,3 +1,4 @@
+import sys
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -5,6 +6,14 @@ from sklearn.preprocessing import LabelEncoder
 import pandas as pd
 
 
+# Parametry z konsoli
+try:
+    epochs = sys.argv[1]
+except:
+    print('No epoch number passed. Defaulting to 100')
+    epochs = 100
+
+
 # Model
 class Model(nn.Module):
     def __init__(self, input_features=2, hidden_layer1=60, hidden_layer2=90, output_features=3):
@@ -64,7 +73,6 @@ optimizer = torch.optim.Adam(model.parameters(), lr=0.01)
 
 
 # Trening
-epochs = 100
 losses = []
 for i in range(epochs):
     y_pred = model.forward(X_train)

training.Jenkinsfile

@@ -9,9 +9,9 @@ pipeline {
 			name: 'BUILD_SELECTOR'
 		)
 		string(
-            defaultValue: '10',
-            description: 'some training parameter',
-            name: 'TRAINING_PARAM'
+            defaultValue: '100',
+            description: 'number of epochs',
+            name: 'EPOCH'
         )
 	}
     stages {
@@ -23,7 +23,9 @@ pipeline {
 		}
         stage('Train model') {
             steps {
-				sh 'python biblioteki_ml.py ${params.TRAINING_PARAM}'
+                withEnv(["EPOCH=${params.EPOCH}"]) {
+				    sh 'python biblioteki_ml.py $EPOCH'
+				}
 			}
 		}
 		stage('Archive model') {