DEBUG:Divide by zero

config.ini

@@ -16,7 +16,7 @@ lr = 0.01
 [TRAIN_PARAMS]
 training_package = decentralizepy.training.Training
 training_class = Training
-epochs_per_round = 1
+epochs_per_round = 5
 batch_size = 1024
 shuffle = True
 loss_package = torch.nn

src/decentralizepy/datasets/Femnist.py

@@ -116,6 +116,8 @@ class Femnist(Dataset):
         self.train_y = np.array(my_train_data["y"], dtype=np.dtype("int64")).reshape(-1)
         logging.debug("train_x.shape: %s", str(self.train_x.shape))
         logging.debug("train_y.shape: %s", str(self.train_y.shape))
+        assert self.train_x.shape[0] == self.train_y.shape[0]
+        assert self.train_x.shape[0] > 0
 
     def load_testset(self):
         logging.info("Loading testing set.")
@@ -135,6 +137,8 @@ class Femnist(Dataset):
         self.test_y = np.array(test_y, dtype=np.dtype("int64")).reshape(-1)
         logging.debug("test_x.shape: %s", str(self.test_x.shape))
         logging.debug("test_y.shape: %s", str(self.test_y.shape))
+        assert self.test_x.shape[0] == self.test_y.shape[0]
+        assert self.test_x.shape[0] > 0
 
     def __init__(
         self,

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],
     )