Excluding AdamWeightDecayOptimizer internal variables from restoring

convert_tf_checkpoint_to_pytorch.py

@@ -68,11 +68,17 @@ def convert():
         arrays.append(array)
 
     for name, array in zip(names, arrays):
-        name = name[5:]  # skip "bert/"
+        if not name.startswith("bert"):
+            print("Skipping {}".format(name))
+            continue
+        else:
+            name = name.replace("bert/", "")  # skip "bert/"
         print("Loading {}".format(name))
         name = name.split('/')
-        if name[0] in ['redictions', 'eq_relationship']:
-            print("Skipping")
+        # adam_v and adam_m are variables used in AdamWeightDecayOptimizer to calculated m and v
+        # which are not required for using pretrained model
+        if name[0] in ['redictions', 'eq_relationship'] or name[-1] == "adam_v" or  name[-1] == "adam_m":
+            print("Skipping {}".format("/".join(name)))
             continue
         pointer = model
         for m_name in name: