code: def multi_source_dijkstra_path_length(
      G, sources, cutoff=None, weight="weight"
  ):
      """Find shortest weighted path lengths in G from a given set of
      source nodes.
  
      Compute the shortest path length between any of the source nodes and
      all other reachable nodes for a weighted graph.
  
      Parameters
      ----------
      G : NetworkX graph
  
      sources : non-empty set of nodes
          Starting nodes for paths. If this is just a set containing a
          single node, then all paths computed by this function will start
          from that node. If there are two or more nodes in the set, the
          computed paths may begin from any one of the start nodes.
  
      cutoff : integer or float, optional
          Length (sum of edge weights) at which the search is stopped.
          If cutoff is provided, only return paths with summed weight <= cutoff.
  
      weight : string or function
          If this is a string, then edge weights will be accessed via the
          edge attribute with this key (that is, the weight of the edge
          joining `u` to `v` will be ``G.edges[u, v][weight]``). If no
          such edge attribute exists, the weight of the edge is assumed to
          be one.
  
          If this is a function, the weight of an edge is the value
          returned by the function. The function must accept exactly three
          positional arguments: the two endpoints of an edge and the
          dictionary of edge attributes for that edge. The function must
          return a number or None to indicate a hidden edge.
  
      Returns
      -------
      length : dict
          Dict keyed by node to shortest path length to nearest source.
  
      Examples
      --------
      >>> G = nx.path_graph(5)
      >>> length = nx.multi_source_dijkstra_path_length(G, {0, 4})
      >>> for node in [0, 1, 2, 3, 4]:
      ...     print(f"{node}: {length[node]}")
      0: 0
      1: 1
      2: 2
      3: 1
      4: 0
  
      Notes
      -----
      Edge weight attributes must be numerical.
      Distances are calculated as sums of weighted edges traversed.
  
      The weight function can be used to hide edges by returning None.
      So ``weight = lambda u, v, d: 1 if d['color']=="red" else None``
      will find the shortest red path.
  
      Raises
      ------
      ValueError
          If `sources` is empty.
      NodeNotFound
          If any of `sources` is not in `G`.
  
      See Also
      --------
      multi_source_dijkstra
  
      """
      if not sources:
          raise ValueError("sources must not be empty")
      for s in sources:
          if s not in G:
              raise nx.NodeNotFound(f"Node {s} not found in graph")
      weight = _weight_function(G, weight)
      return _dijkstra_multisource(G, sources, weight, cutoff=cutoff)
  
imports: from collections import deque
  from heapq import heappop, heappush
  from itertools import count
  import networkx
  from networkx.algorithms.shortest_paths.generic import _build_paths_from_predecessors
label_desc: Use image node_id 8 for calling a global function with example usage: multi_source_dijkstra_path_length(G, sources, cutoff, weight) and returns: _dijkstra_multisource