Add all the edges in ebunch.

        Parameters
        ----------
        ebunch : container of edges
            Each edge given in the container will be added to the
            graph. The edges can be:

                - 3-tuples (u,v,d) for an edge attribute dict d, or
                - 4-tuples (u,v,k,d) for an edge identified by key k

            Each edge must have a layers attribute (set of str).
        attr_dict : dictionary, optional  (default= no attributes)
            Dictionary of edge attributes.  Key/value pairs will
            update existing data associated with each edge.
        attr : keyword arguments, optional
            Edge data (or labels or objects) can be assigned using
            keyword arguments.


        See Also
        --------
        add_edge : add a single edge

        Notes
        -----
        Adding the same edge twice has no effect but any edge data
        will be updated when each duplicate edge is added.

        An edge can only be added if the source and target nodes are
        already present in the graph. This decision was taken to ensure
        that all edges are associated with at least one (meaningful)
        layer.

        Edge attributes specified in edges as a tuple (in ebunch) take
        precedence over attributes specified otherwise (in attr_dict or
        attr). Layers can only be added (via a 'layers' edge attribute),
        but not overwritten.

        Examples
        --------
        >>> d = DiscourseDocumentGraph()
        >>> d.add_node(1, {'int'})
        >>> d.add_node(2, {'int'})

        >>> d.add_edges_from([(1, 2, {'layers': {'int'}, 'weight': 23})])
        >>> d.add_edges_from([(1, 2, {'layers': {'int'}, 'weight': 42})])

        >>> d.edges(data=True) # multiple edges between the same nodes
        [(1, 2, {'layers': {'int'}, 'weight': 23}),
         (1, 2, {'layers': {'int'}, 'weight': 42})]

        Associate data to edges

        We update the existing edge (key=0) and overwrite its 'weight'
        value. Note that we can't overwrite the 'layers' value, though.
        Instead, they are added to the set of existing layers

        >>> d.add_edges_from([(1, 2, 0, {'layers':{'number'}, 'weight':66})])
        [(1, 2, {'layers': {'int', 'number'}, 'weight': 66}),
         (1, 2, {'layers': {'int'}, 'weight': 42})]

def add_edges_from(self, ebunch, attr_dict=None, **attr):
        """Add all the edges in ebunch.

        Parameters
        ----------
        ebunch : container of edges
            Each edge given in the container will be added to the
            graph. The edges can be:

                - 3-tuples (u,v,d) for an edge attribute dict d, or
                - 4-tuples (u,v,k,d) for an edge identified by key k

            Each edge must have a layers attribute (set of str).
        attr_dict : dictionary, optional  (default= no attributes)
            Dictionary of edge attributes.  Key/value pairs will
            update existing data associated with each edge.
        attr : keyword arguments, optional
            Edge data (or labels or objects) can be assigned using
            keyword arguments.


        See Also
        --------
        add_edge : add a single edge

        Notes
        -----
        Adding the same edge twice has no effect but any edge data
        will be updated when each duplicate edge is added.

        An edge can only be added if the source and target nodes are
        already present in the graph. This decision was taken to ensure
        that all edges are associated with at least one (meaningful)
        layer.

        Edge attributes specified in edges as a tuple (in ebunch) take
        precedence over attributes specified otherwise (in attr_dict or
        attr). Layers can only be added (via a 'layers' edge attribute),
        but not overwritten.

        Examples
        --------
        >>> d = DiscourseDocumentGraph()
        >>> d.add_node(1, {'int'})
        >>> d.add_node(2, {'int'})

        >>> d.add_edges_from([(1, 2, {'layers': {'int'}, 'weight': 23})])
        >>> d.add_edges_from([(1, 2, {'layers': {'int'}, 'weight': 42})])

        >>> d.edges(data=True) # multiple edges between the same nodes
        [(1, 2, {'layers': {'int'}, 'weight': 23}),
         (1, 2, {'layers': {'int'}, 'weight': 42})]

        Associate data to edges

        We update the existing edge (key=0) and overwrite its 'weight'
        value. Note that we can't overwrite the 'layers' value, though.
        Instead, they are added to the set of existing layers

        >>> d.add_edges_from([(1, 2, 0, {'layers':{'number'}, 'weight':66})])
        [(1, 2, {'layers': {'int', 'number'}, 'weight': 66}),
         (1, 2, {'layers': {'int'}, 'weight': 42})]
        """
        # set up attribute dict
        if attr_dict is None:
            attr_dict = attr
        else:
            try:
                attr_dict.update(attr)
            except AttributeError as e:
                raise AttributeError("The attr_dict argument must be "
                                     "a dictionary: ".format(e))
        # process ebunch
        for e in ebunch:
            ne = len(e)
            if ne == 4:
                u, v, key, dd = e
            elif ne == 3:
                u, v, dd = e
                key = None
            else:
                raise AttributeError(
                    "Edge tuple {0} must be a 3-tuple (u,v,attribs) "
                    "or 4-tuple (u,v,key,attribs).".format(e))

            if not 'layers' in dd:
                dd['layers'] = {self.ns}

            layers = dd['layers']
            assert isinstance(layers, set), \
                "'layers' must be specified as a set of strings."
            assert all((isinstance(layer, str)
                        for layer in layers)), \
                "All elements of the 'layers' set must be strings."
            additional_layers = attr_dict.get('layers', {})
            if additional_layers:
                assert isinstance(additional_layers, set), \
                    "'layers' must be specified as a set of strings."
                assert all((isinstance(layer, str)
                            for layer in additional_layers)), \
                    "'layers' set must only contain strings."
            # union of layers specified in ebunch tuples,
            # attr_dict and **attr
            new_layers = layers.union(additional_layers)

            if u in self.adj:  # edge with u as source already exists
                keydict = self.adj[u].get(v, {})
            else:
                keydict = {}
            if key is None:
                # find a unique integer key
                # other methods might be better here?
                key = len(keydict)
                while key in keydict:
                    key += 1
            datadict = keydict.get(key, {})  # existing edge attribs
            existing_layers = datadict.get('layers', set())
            datadict.update(attr_dict)
            datadict.update(dd)
            updated_attrs = {k: v for (k, v) in datadict.items()
                             if k != 'layers'}

            all_layers = existing_layers.union(new_layers)
            # add_edge() checks if u and v exist, so we don't need to
            self.add_edge(u, v, layers=all_layers, key=key,
                          attr_dict=updated_attrs)