def export_compact(self, filename, optimize=True, toco_compatible=False):
        """Create a self-contained inference-only graph and write final graph (in pb format) to disk.

        Args:
            filename (str): path to the output graph
            optimize (bool): whether to use TensorFlow's `optimize_for_inference`
                to prune and optimize the graph. This does not work on all types of graphs.
            toco_compatible (bool): See TensorFlow's
                `optimize_for_inference
                <https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/optimize_for_inference.py>`_
                for details. Only available after TF 1.8.
        """
        if toco_compatible:
            assert optimize, "toco_compatible is only effective when optimize=True!"
        self.graph = self.config._maybe_create_graph()
        with self.graph.as_default():
            input = PlaceholderInput()
            input.setup(self.config.input_signature)
            with PredictTowerContext(''):
                self.config.tower_func(*input.get_input_tensors())

            input_tensors = get_tensors_by_names(self.config.input_names)
            output_tensors = get_tensors_by_names(self.config.output_names)

            self.config.session_init._setup_graph()
            # we cannot use "self.config.session_creator.create_session()" here since it finalizes the graph
            sess = tfv1.Session(config=tfv1.ConfigProto(allow_soft_placement=True))
            self.config.session_init._run_init(sess)

            dtypes = [n.dtype for n in input_tensors]

            # freeze variables to constants
            frozen_graph_def = graph_util.convert_variables_to_constants(
                sess,
                self.graph.as_graph_def(),
                [n.name[:-2] for n in output_tensors],
                variable_names_whitelist=None,
                variable_names_blacklist=None)

            # prune unused nodes from graph
            if optimize:
                toco_args = () if get_tf_version_tuple() < (1, 8) else (toco_compatible, )
                frozen_graph_def = optimize_for_inference_lib.optimize_for_inference(
                    frozen_graph_def,
                    [n.name[:-2] for n in input_tensors],
                    [n.name[:-2] for n in output_tensors],
                    [dtype.as_datatype_enum for dtype in dtypes],
                    *toco_args)

            with gfile.FastGFile(filename, "wb") as f:
                f.write(frozen_graph_def.SerializeToString())
                logger.info("Output graph written to {}.".format(filename))
Create a self-contained inference-only graph and write final graph (in pb format) to disk.

        Args:
            filename (str): path to the output graph
            optimize (bool): whether to use TensorFlow's `optimize_for_inference`
                to prune and optimize the graph. This does not work on all types of graphs.
            toco_compatible (bool): See TensorFlow's
                `optimize_for_inference
                <https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/optimize_for_inference.py>`_
                for details. Only available after TF 1.8.
        
tensorpack/tfutils/export.py