def setup_keyring(keyring_name):
    '''Setup the keyring'''
    keyring_path = os.path.join("test", "outputdata", keyring_name)
    # Delete the entire keyring
    shutil.rmtree(keyring_path, ignore_errors=True)
    os.makedirs(keyring_path)
    gpg = GPG(gnupghome=keyring_path, gpgbinary="gpg")
    for key_name in ["key1_private", "key1_public"]:
        with open(os.path.join("test", "inputdata", key_name + ".txt"), "r") as keyfile:
            key_str = "".join(keyfile.readlines())
        import_result = gpg.import_keys(key_str)
        print("Import result:", type(import_result))
        print(import_result.__dict__)
        if import_result.count == 1 and len(set(import_result.fingerprints)) == 1:
            print("Got one import result")
    return gpg
def _restore_checkpoint_and_maybe_run_saved_model_initializers(
    sess, saver, path):
  """Restores checkpoint values and SavedModel initializers if found."""
  # NOTE: All references to SavedModel refer to SavedModels loaded from the
  # load_v2 API (which does not require the `sess` argument).

  # If the graph contains resources loaded from a SavedModel, they are not
  # restored when calling `saver.restore`. Thus, the SavedModel initializer must
  # be called with `saver.restore` to properly initialize the model.

  # The SavedModel init is stored in the "saved_model_initializers" collection.
  # This collection is part of the MetaGraph's default_init_op, so it is already
  # called by MonitoredSession as long as the saver doesn't restore any
  # checkpoints from the working dir.
  saved_model_init_ops = ops.get_collection("saved_model_initializers")
  if saved_model_init_ops:
    sess.run(saved_model_init_ops)

  # The saver must be called *after* the SavedModel init, because the SavedModel
  # init will restore the variables from the SavedModel variables directory.
  # Initializing/restoring twice is not ideal but there's no other way to do it.
  saver.restore(sess, path)