def get_variable_names(self):
    """Returns list of all variable names in this model.

    Returns:
      List of names.
    """
    return [name for name, _ in checkpoints.list_variables(self.model_dir)]

def print_tensors_in_checkpoint_file(file_name, tensor_name):
  """Prints tensors in a checkpoint file.

  If no `tensor_name` is provided, prints the tensor names and shapes
  in the checkpoint file.

  If `tensor_name` is provided, prints the content of the tensor.

  Args:
    file_name: Name of the checkpoint file.
    tensor_name: Name of the tensor in the checkpoint file to print.
  """
  try:
    if not tensor_name:
      variables = checkpoints.list_variables(file_name)
      for name, shape in variables:
        print("%s\t%s" % (name, str(shape)))
    else:
      print("tensor_name: ", tensor_name)
      print(checkpoints.load_variable(file_name, tensor_name))
  except Exception as e:  # pylint: disable=broad-except
    print(str(e))
    if "corrupted compressed block contents" in str(e):
      print("It's likely that your checkpoint file has been compressed "
            "with SNAPPY.")

 def testGetAllVariables(self):
   checkpoint_dir = self.get_temp_dir()
   with self.test_session() as session:
     _create_checkpoints(session, checkpoint_dir)
   self.assertEqual(checkpoints.list_variables(checkpoint_dir),
                    [("useful_scope/var4", [9, 9]),
                     ("var1", [1, 10]),
                     ("var2", [10, 10]),
                     ("var3", [100, 100])])

 def weights_(self):
     values = {}
     optimizer_regex = r".*/" + self._optimizer.get_name() + r"(_\d)?$"
     for name, _ in checkpoints.list_variables(self._model_dir):
         if name.startswith("linear/") and name != "linear/bias_weight" and not re.match(optimizer_regex, name):
             values[name] = checkpoints.load_variable(self._model_dir, name)
     if len(values) == 1:
         return values[list(values.keys())[0]]
     return values

  def get_weights(self, model_dir):
    """Returns weights per feature of the linear part.

    Args:
      model_dir: Directory where model parameters, graph and etc. are saved.

    Returns:
      The weights created by this model (without the optimizer weights).
    """
    all_variables = [name for name, _ in checkpoints.list_variables(model_dir)]
    values = {}
    optimizer_regex = r".*/" + self._get_optimizer().get_name() + r"(_\d)?$"
    for name in all_variables:
      if (name.startswith(self._scope + "/") and
          name != self._scope + "/bias_weight" and
          not re.match(optimizer_regex, name)):
        values[name] = checkpoints.load_variable(model_dir, name)
    if len(values) == 1:
      return values[list(values.keys())[0]]
    return values

 def get_variable_names(self):
   return [name for name, _ in checkpoints.list_variables(self._model_dir)]