diff --git a/generic_trainer/trainer.py b/generic_trainer/trainer.py
index 601fee2..9f2987b 100644
--- a/generic_trainer/trainer.py
+++ b/generic_trainer/trainer.py
@@ -5,6 +5,7 @@
 import copy
 import re
 import warnings
+from contextlib import ExitStack
 
 try:
     from mpi4py import MPI
@@ -170,7 +171,7 @@ def clear_classification_results_and_labels(self):
     def update_classification_results_and_labels(self, preds, labels):
         """
         Update the classification results recorded for the current epoch with the predictions and labels of
-        the current iteration.
+        the current iteration.testtr
 
         :param preds: list[torch.tensor]. Each tensor should be of shape [n_batch, n_classes].
         :param labels: list[torch.tensor]. Each tensor should be of shape [n_batch, n_classes].
@@ -610,7 +611,11 @@ def load_data_and_get_loss(self, data_and_labels, loss_buffer, *args, **kwargs):
         :return: loss_buffer, total_loss_tensor, preds, labels
         """
         data, labels = self.process_data_loader_yield(data_and_labels)
-        with torch.autocast(device_type=self.device.type, dtype=torch.float16, enabled=self.use_torch_amp):
+        with ExitStack() as es:
+            # torch.autocast would raise an exception about CPU data type even when enabled == False, so
+            # we use ExitStack to control the entrance of this context on a higher level.
+            if self.use_torch_amp:
+                es.enter_context(torch.autocast(device_type=self.device.type, dtype=torch.float16))
             preds = self.model(*data)
             losses, total_loss_tensor = self.compute_losses(loss_buffer, preds, labels)
         return loss_buffer, total_loss_tensor, preds, labels