diff --git a/tensorflow/python/training/checkpoint_management.py b/tensorflow/python/training/checkpoint_management.py
index 32b9c023aae..e2dbde57a18 100644
--- a/tensorflow/python/training/checkpoint_management.py
+++ b/tensorflow/python/training/checkpoint_management.py
@@ -347,6 +347,30 @@ def latest_checkpoint(checkpoint_dir, latest_filename=None):
   return None
 
 
+def checkpoint_exists_internal(checkpoint_prefix):
+  """Checks whether a V1 or V2 checkpoint exists with the specified prefix.
+
+  This is an internal function to check if a checkpoint exists,
+  since it takes into account the naming difference between V1 and V2 formats.
+
+  Args:
+    checkpoint_prefix: the prefix of a V1 or V2 checkpoint, with V2 taking
+      priority.  Typically the result of `Saver.save()` or that of
+      `tf.train.latest_checkpoint()`, regardless of sharded/non-sharded or
+      V1/V2.
+  Returns:
+    A bool, true if a checkpoint referred to by `checkpoint_prefix` exists.
+  """
+  pathname = _prefix_to_checkpoint_path(checkpoint_prefix,
+                                        saver_pb2.SaverDef.V2)
+  if file_io.get_matching_files(pathname):
+    return True
+  elif file_io.get_matching_files(checkpoint_prefix):
+    return True
+  else:
+    return False
+
+
 @deprecation.deprecated(
     date=None,
     instructions="Use standard file APIs to check for files with this prefix.")
@@ -362,17 +386,11 @@ def checkpoint_exists(checkpoint_prefix):
       priority.  Typically the result of `Saver.save()` or that of
       `tf.train.latest_checkpoint()`, regardless of sharded/non-sharded or
       V1/V2.
+
   Returns:
-    A bool, true iff a checkpoint referred to by `checkpoint_prefix` exists.
+    A bool, true if a checkpoint referred to by `checkpoint_prefix` exists.
   """
-  pathname = _prefix_to_checkpoint_path(checkpoint_prefix,
-                                        saver_pb2.SaverDef.V2)
-  if file_io.get_matching_files(pathname):
-    return True
-  elif file_io.get_matching_files(checkpoint_prefix):
-    return True
-  else:
-    return False
+  return checkpoint_exists_internal(checkpoint_prefix)
 
 
 @deprecation.deprecated(
diff --git a/tensorflow/python/training/saver.py b/tensorflow/python/training/saver.py
index 7b502bffa38..d65297fb30d 100644
--- a/tensorflow/python/training/saver.py
+++ b/tensorflow/python/training/saver.py
@@ -1276,11 +1276,12 @@ class Saver(object):
     if save_path is None:
       raise ValueError("Can't load save_path when it is None.")
 
-    if not checkpoint_management.checkpoint_exists(compat.as_text(save_path)):
+    checkpoint_prefix = compat.as_text(save_path)
+    if not checkpoint_management.checkpoint_exists_internal(checkpoint_prefix):
       raise ValueError("The passed save_path is not a valid checkpoint: " +
-                       compat.as_text(save_path))
+                       checkpoint_prefix)
 
-    logging.info("Restoring parameters from %s", compat.as_text(save_path))
+    logging.info("Restoring parameters from %s", checkpoint_prefix)
     try:
       if context.executing_eagerly():
         self._build_eager(save_path, build_save=False, build_restore=True)