diff --git a/tasks/adding_task.py b/tasks/adding_task.py
index ca0dbd2..ebc8d59 100644
--- a/tasks/adding_task.py
+++ b/tasks/adding_task.py
@@ -99,7 +99,9 @@ def generate_data(length, size):
   sums = np.array(sums)
   sums = sums.reshape(1, 1, 1)
 
-  return cudavec(x_seq_list, gpu_id=args.cuda).float(), cudavec(sums, gpu_id=args.cuda).float(), sums_text
+  return cudavec(x_seq_list.astype(np.float32), gpu_id=args.cuda).float(), \
+          cudavec(sums.astype(np.float32), gpu_id=args.cuda).float(), \
+          sums_text
 
 
 def cross_entropy(prediction, target):
@@ -221,7 +223,7 @@ if __name__ == '__main__':
 
     T.nn.utils.clip_grad_norm_(rnn.parameters(), args.clip)
     optimizer.step()
-    loss_value = loss.data[0]
+    loss_value = loss.item()
 
     # detach memory from graph
     mhx = { k : (v.detach() if isinstance(v, var) else v) for k, v in mhx.items() }
diff --git a/tasks/argmax_task.py b/tasks/argmax_task.py
index 711a017..398c487 100644
--- a/tasks/argmax_task.py
+++ b/tasks/argmax_task.py
@@ -227,7 +227,7 @@ if __name__ == '__main__':
 
     T.nn.utils.clip_grad_norm_(rnn.parameters(), args.clip)
     optimizer.step()
-    loss_value = loss.data[0]
+    loss_value = loss.item()
 
     # detach memory from graph
     mhx = { k : (v.detach() if isinstance(v, var) else v) for k, v in mhx.items() }
diff --git a/tasks/copy_task.py b/tasks/copy_task.py
index 8be5984..0ca5a8c 100755
--- a/tasks/copy_task.py
+++ b/tasks/copy_task.py
@@ -214,7 +214,7 @@ if __name__ == '__main__':
 
     T.nn.utils.clip_grad_norm_(rnn.parameters(), args.clip)
     optimizer.step()
-    loss_value = loss.data[0]
+    loss_value = loss.item()
 
     summarize = (epoch % summarize_freq == 0)
     take_checkpoint = (epoch != 0) and (epoch % check_freq == 0)