(self, checkpoint_dir)
Loads model weights from a saved checkpoint.

    Args:
      checkpoint_dir: Directory which contains a saved checkpoint of the
        model.
Loads model weights from a saved checkpoint.
Loads model weights from a saved checkpoint .
def restore_vars_from_checkpoint(self, checkpoint_dir):
    """Loads model weights from a saved checkpoint.

    Args:
      checkpoint_dir: Directory which contains a saved checkpoint of the
        model.
    """
    tf.logging.info('Restoring variables from checkpoint')

    var_dict = self.get_variable_name_dict()
    with self.graph.as_default():
      saver = tf.train.Saver(var_list=var_dict)

    tf.logging.info('Checkpoint dir: %s', checkpoint_dir)
    checkpoint_file = tf.train.latest_checkpoint(checkpoint_dir)
    if checkpoint_file is None:
      tf.logging.warn("Can't find checkpoint file, using %s",
                      self.checkpoint_file)
      checkpoint_file = self.checkpoint_file
    tf.logging.info('Checkpoint file: %s', checkpoint_file)

    saver.restore(self.session, checkpoint_file)
def restore_vars_from_checkpoint ( self , checkpoint_dir ) : tf . logging . info ( 'Restoring variables from checkpoint' ) var_dict = self . get_variable_name_dict ( ) with self . graph . as_default ( ) : saver = tf . train . Saver ( var_list = var_dict ) tf . logging . info ( 'Checkpoint dir: %s' , checkpoint_dir ) checkpoint_file = tf . train . latest_checkpoint ( checkpoint_dir ) if checkpoint_file is None : tf . logging . warn ( "Can't find checkpoint file, using %s" , self . checkpoint_file ) checkpoint_file = self . checkpoint_file tf . logging . info ( 'Checkpoint file: %s' , checkpoint_file ) saver . restore ( self . session , checkpoint_file )