except

train_model.py

@@ -18,13 +18,19 @@ import sys
 from tqdm import tqdm
 from Levenshtein import distance as levenshtein_distance
 from sacred import Experiment
+import traceback
 
 ex = Experiment("CNN")
 ex.observers.append(FileStorageObserver('sacred_file_observer'))
+try:
     ex.observers.append(MongoObserver(url='mongodb://mongo_user:mongo_password_IUM_2021@localhost:27017',
                                       db_name='sacred'))
+except Exception as e:
+    traceback.print_exc()
+    
 device = torch.device('cuda:0') if torch.cuda.is_available() else torch.device('cpu')
 
+
 class CNN(nn.Module):
     def __init__(self, kernel_size, hidden_layers, channels, embedding_size, in_alphabet, max_len):
         super(CNN, self).__init__()
@@ -206,4 +212,3 @@ def run(kernel_size, hidden_layers, data_file, epochs, teacher_forcing_probabili
     if mode == 'eval':
         cnn.eval()
         evaluate_monte_carlo(cnn, 1, data, batch_size, in_alphabet, max_len)
-