def setup_saver(self):
if self.execution_type == "<STR_LIT>":<EOL><INDENT>global_variables = self.get_variables(include_submodules=True, include_nontrainable=True)<EOL><DEDENT>else:<EOL><INDENT>global_variables = self.global_model.get_variables(include_submodules=True, include_nontrainable=True)<EOL><DEDENT>for c in self.get_savable_components():<EOL><INDENT>c.register_saver_ops()<EOL><DEDENT>self.saver = tf.train.Saver(<EOL>var_list=global_variables,  <EOL>reshape=False,<EOL>sharded=False,<EOL>max_to_keep=<NUM_LIT:5>,<EOL>keep_checkpoint_every_n_hours=<NUM_LIT>,<EOL>name=None,<EOL>restore_sequentially=False,<EOL>saver_def=None,<EOL>builder=None,<EOL>defer_build=False,<EOL>allow_empty=True,<EOL>write_version=tf.train.SaverDef.V2,<EOL>pad_step_number=False,<EOL>save_relative_paths=True<EOL>)<EOL>
Creates the tf.train.Saver object and stores it in self.saver.