--- a
+++ b/common/pytorch.py
@@ -0,0 +1,23 @@
+import torch
+
+
+def save_model(path, model):
+    # Save a trained model
+    print("** ** * Saving fine - tuned model ** ** * ")
+    model_to_save = model.module if hasattr(model, 'module') else model  # Only save the model it-self
+    output_model_file = path
+    torch.save(model_to_save.state_dict(), output_model_file)
+
+
+def load_model(path, model):
+    # load pretrained model and update weights
+    pretrained_dict = torch.load(path, map_location='cpu')
+    model_dict = model.state_dict()
+    # 1. filter out unnecessary keys
+    pretrained_dict = {k: v for k, v in pretrained_dict.items() if k in model_dict}
+    # 2. overwrite entries in the existing state dict
+    model_dict.update(pretrained_dict)
+    # 3. load the new state dict
+    model.load_state_dict(model_dict)
+    return model
+