IUM_06 - add epochs, learning_rate and weight_decay parameters models/Jenkinsfile, update create_model.py script

create_model.py

@@ -5,6 +5,7 @@ import torch.nn as nn
 import torch.optim as optim
 
 import os
+import sys
 
 from sklearn.metrics import classification_report
 
@@ -34,10 +35,18 @@ y_test = torch.FloatTensor(y_test).view(-1, 1)
 # Parameters
 input_size = X_train.shape[1]
 hidden_size = 128
+
+# Default parameters
 learning_rate = 0.001
 weight_decay = 0.001
 num_epochs = 1000
 
+# Parameters from sys.argv
+if len(sys.argv) > 1:
+    num_epochs = int(sys.argv[1])
+    learning_rate = float(sys.argv[2])
+    weight_decay = float(sys.argv[3])
+
 # Model initialization
 model = NeuralNetwork(input_size, hidden_size)
 

models/Jenkinsfile

@@ -1,6 +1,10 @@
 pipeline {
     agent any
 
+    parameters {
+
+    }
+
     stages {
         stage('Clone repository') {
             steps {