Multi-machine-fix

config.ini

@@ -16,7 +16,7 @@ lr = 0.01
 [TRAIN_PARAMS]
 training_package = decentralizepy.training.Training
 training_class = Training
-epochs_per_round = 10
+epochs_per_round = 4
 batch_size = 1024
 shuffle = True
 loss_package = torch.nn

src/decentralizepy/datasets/Femnist.py

@@ -275,7 +275,10 @@ class Femnist(Dataset):
         logging.debug("Predicted on the test set")
 
         for key, value in enumerate(correct_pred):
-            accuracy = 100 * float(value) / total_pred[key]
+            if total_pred[key] != 0:
+                accuracy = 100 * float(value) / total_pred[key]
+            else:
+                accuracy = 100.0
             logging.debug("Accuracy for class {} is: {:.1f} %".format(key, accuracy))
 
         accuracy = 100 * float(total_correct) / total_predicted

testing.py

@@ -42,5 +42,5 @@ if __name__ == "__main__":
     mp.spawn(
         fn=Node,
         nprocs=procs_per_machine,
-        args=[m_id, l, g, my_config, 20, "results", logging.DEBUG],
+        args=[m_id, l, g, my_config, 20, "results", logging.INFO],
     )