Update google_solver/scratch.py

google_solver/scratch.py

@@ -1,27 +1,33 @@
-
-
 from just_time_windows.google_solver.google_model import evaluate_google_model
 from just_time_windows.Actor.actor import Actor as NN_Actor
 from just_time_windows.build_data import Raw_VRP_Data
 from just_time_windows.dataloader import VRP_Dataset
 
+def main():
+    # إعداد مجموعة بيانات صغيرة للاختبار
+    dataset = VRP_Dataset(dataset_size=10, num_depots=1, num_nodes=12)
 
-dataset = VRP_Dataset(dataset_size=10, num_depots=1, num_nodes=12)
-
-batch = dataset.get_batch(0, 10)
-
-nn_actor = NN_Actor(model=None, num_movers=10, num_neighbors_action=1)
+    # استخراج دفعة واحدة للاختبار
+    batch = dataset.get_batch(start_index=0, batch_size=10)
 
+    # تهيئة نموذج الشبكة العصبية
+    nn_actor = NN_Actor(model=None, num_movers=10, num_neighbors_action=1)
 
-nn_output = nn_actor(batch)
-time = nn_output['total_time']
-arrival_times = nn_output['arrival_times']
+    # حساب مخرجات NN
+    nn_output = nn_actor(batch)
+    total_time_nn = nn_output['total_time']
+    arrival_times_nn = nn_output['arrival_times']
 
+    # استخدام Google OR-Tools لتقييم نفس البيانات
+    google_output = evaluate_google_model(dataset)
 
-output = evaluate_google_model(dataset)
+    # طباعة النتائج للمقارنة
+    print("Arrival times (NN):")
+    print(arrival_times_nn)
 
+    print("\nAverage Total Time (NN Actor):", total_time_nn.mean().item())
+    print("Average Total Time (Google OR-Tools):", google_output.mean().item())
 
 
-print(arrival_times)
-print(time.mean().item())
-print(output.mean().item())
+if __name__ == '__main__':
+    main()