code: def les_miserables_graph():
      # fmt: off
      src_indices = cp.array(
          [
              0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
              2, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6,
              6, 6, 6, 6, 6, 6, 6, 7, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 10, 10,
              10, 10, 10, 10, 11, 12, 12, 12, 12, 12, 12, 13, 13, 14, 14, 15, 15, 15,
              15, 15, 15, 15, 15, 15, 15, 16, 16, 16, 16, 16, 16, 17, 17, 17, 17, 17,
              17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 19,
              20, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 22, 23, 23, 23,
              23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
              24, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 26, 26, 26, 26, 26,
              26, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 27, 28, 28,
              28, 28, 29, 29, 29, 29, 29, 29, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30,
              30, 30, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31,
              31, 31, 31, 31, 31, 31, 32, 33, 34, 34, 34, 34, 34, 34, 34, 35, 35, 35,
              35, 35, 35, 35, 35, 35, 35, 36, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37,
              38, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39,
              40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 42, 42, 42, 42, 42,
              42, 43, 44, 44, 44, 44, 44, 44, 44, 45, 45, 45, 45, 46, 46, 46, 46, 46,
              46, 46, 46, 46, 46, 46, 47, 47, 48, 48, 49, 49, 49, 49, 49, 49, 49, 49,
              49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 50, 50, 50, 51, 51, 51, 51,
              51, 51, 51, 52, 53, 53, 54, 55, 55, 55, 55, 55, 55, 55, 56, 56, 56, 57,
              57, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 59, 59, 59, 59, 59, 59,
              59, 59, 59, 60, 60, 61, 62, 62, 62, 62, 62, 62, 62, 62, 62, 62, 63, 64,
              65, 65, 66, 66, 66, 67, 67, 67, 67, 67, 67, 67, 67, 67, 68, 69, 69, 69,
              69, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 71,
              71, 71, 71, 71, 71, 71, 71, 71, 72, 72, 72, 73, 73, 73, 73, 73, 73, 73,
              73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73,
              73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 73, 74, 74, 75, 75, 75, 76, 76,
              76, 76, 76, 76, 76,
          ],
          index_dtype,
      )
      dst_indices = cp.array(
          [
              25, 58, 70, 9, 15, 25, 31, 37, 39, 58, 59, 70, 73, 6, 17, 21, 24, 30, 31,
              35, 40, 46, 49, 55, 67, 8, 10, 12, 16, 27, 39, 42, 73, 34, 49, 23, 26,
              27, 29, 44, 71, 76, 2, 17, 21, 24, 30, 31, 35, 40, 46, 49, 55, 67, 73,
              70, 3, 10, 12, 16, 42, 73, 1, 15, 25, 31, 37, 59, 70, 3, 8, 12, 16, 42,
              73, 62, 3, 8, 10, 16, 42, 73, 14, 31, 13, 31, 1, 9, 24, 25, 37, 39, 58,
              59, 70, 73, 3, 8, 10, 12, 42, 73, 2, 6, 21, 24, 30, 31, 35, 40, 46, 49,
              67, 34, 39, 45, 49, 51, 58, 70, 71, 72, 73, 75, 62, 62, 2, 6, 17, 24, 25,
              30, 31, 35, 40, 46, 49, 55, 67, 62, 5, 26, 27, 29, 44, 71, 76, 2, 6, 15,
              17, 21, 30, 31, 35, 39, 40, 46, 49, 55, 67, 73, 0, 1, 9, 15, 21, 37, 46,
              49, 58, 59, 70, 5, 23, 27, 29, 44, 71, 76, 3, 5, 23, 26, 29, 39, 44, 48,
              58, 65, 69, 70, 71, 73, 76, 36, 39, 60, 73, 5, 23, 26, 27, 44, 71, 76, 2,
              6, 17, 21, 24, 31, 35, 40, 46, 49, 67, 1, 2, 6, 9, 13, 14, 17, 21, 24,
              30, 35, 37, 39, 40, 46, 49, 53, 55, 59, 67, 70, 73, 62, 73, 4, 18, 45,
              47, 49, 51, 73, 2, 6, 17, 21, 24, 30, 31, 40, 55, 67, 28, 1, 9, 15, 25,
              31, 39, 58, 59, 70, 73, 73, 1, 3, 15, 18, 24, 27, 28, 31, 37, 58, 59, 69,
              70, 72, 73, 74, 75, 2, 6, 17, 21, 24, 30, 31, 35, 46, 49, 55, 67, 53, 3,
              8, 10, 12, 16, 73, 73, 5, 23, 26, 27, 29, 71, 76, 18, 34, 49, 51, 2, 6,
              17, 21, 24, 25, 30, 31, 40, 49, 61, 34, 58, 27, 73, 2, 4, 6, 17, 18, 21,
              24, 25, 30, 31, 34, 40, 45, 46, 51, 66, 70, 71, 73, 56, 62, 73, 18, 34,
              45, 49, 52, 57, 73, 51, 31, 41, 73, 2, 6, 21, 24, 31, 35, 40, 50, 62, 73,
              51, 66, 0, 1, 15, 18, 25, 27, 37, 39, 47, 70, 73, 1, 9, 15, 25, 31, 37,
              39, 70, 73, 28, 73, 46, 11, 19, 20, 22, 32, 50, 56, 63, 64, 73, 62, 62,
              27, 69, 49, 57, 70, 2, 6, 17, 21, 24, 30, 31, 35, 40, 73, 27, 39, 65, 73,
              0, 1, 7, 9, 15, 18, 25, 27, 31, 37, 39, 49, 58, 59, 66, 73, 5, 18, 23,
              26, 27, 29, 44, 49, 76, 18, 39, 73, 1, 3, 6, 8, 10, 12, 15, 16, 18, 24,
              27, 28, 31, 33, 34, 37, 38, 39, 42, 43, 48, 49, 50, 51, 54, 56, 58, 59,
              60, 62, 68, 69, 70, 72, 74, 75, 39, 73, 18, 39, 73, 5, 23, 26, 27, 29,
              44, 71,
          ],
          index_dtype,
      )
      weights = cp.array(
          [
              2, 1, 2, 3, 4, 1, 1, 6, 2, 1, 2, 6, 1, 4, 5, 6, 4, 3, 5, 1, 5, 2, 1, 1,
              2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 3, 4, 3, 4, 4, 4, 3, 4, 9, 12, 10, 6, 5,
              3, 7, 1, 5, 1, 2, 1, 1, 1, 2, 2, 2, 2, 2, 3, 1, 1, 1, 3, 1, 3, 2, 2, 2,
              2, 3, 3, 1, 1, 2, 2, 2, 2, 2, 3, 2, 3, 2, 4, 1, 1, 1, 4, 1, 1, 2, 4, 1,
              1, 2, 2, 2, 2, 2, 5, 9, 13, 15, 5, 6, 1, 5, 2, 5, 2, 3, 1, 1, 21, 2, 4,
              1, 1, 2, 31, 1, 2, 1, 6, 12, 13, 17, 1, 6, 7, 2, 5, 2, 9, 1, 3, 1, 3, 3,
              4, 5, 3, 3, 4, 4, 10, 1, 15, 17, 6, 7, 3, 6, 5, 1, 7, 1, 4, 4, 2, 1, 1,
              1, 1, 1, 1, 5, 2, 1, 3, 4, 3, 3, 3, 4, 4, 3, 1, 3, 4, 3, 4, 5, 3, 2, 2,
              1, 2, 1, 3, 9, 4, 2, 1, 3, 8, 4, 5, 3, 4, 3, 3, 4, 3, 6, 5, 6, 6, 2, 1,
              5, 1, 1, 2, 1, 5, 5, 1, 2, 2, 6, 7, 7, 2, 1, 1, 1, 3, 1, 4, 2, 1, 1, 1,
              1, 1, 1, 1, 1, 3, 1, 1, 12, 9, 2, 1, 3, 1, 2, 3, 1, 1, 2, 1, 1, 2, 6, 3,
              4, 1, 1, 1, 1, 2, 5, 1, 1, 2, 1, 1, 1, 6, 5, 1, 1, 1, 1, 1, 1, 5, 1, 17,
              1, 1, 5, 7, 5, 5, 5, 5, 3, 2, 1, 2, 1, 2, 1, 2, 2, 3, 2, 2, 3, 1, 4, 3,
              4, 3, 3, 4, 3, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 3, 1, 1, 2, 1,
              1, 1, 5, 5, 21, 9, 7, 5, 1, 4, 12, 2, 1, 1, 6, 1, 2, 1, 19, 6, 8, 3, 2,
              9, 2, 6, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 6, 10, 3, 1, 1, 1, 1,
              1, 4, 2, 2, 1, 1, 1, 13, 7, 2, 1, 2, 1, 1, 2, 1, 1, 1, 3, 1, 3, 1, 2, 1,
              1, 1, 8, 10, 1, 1, 5, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 3, 4, 2, 1, 1, 2, 1,
              2, 1, 2, 3, 2, 6, 1, 3, 4, 1, 3, 1, 1, 5, 5, 2, 13, 1, 1, 12, 4, 1, 3, 4,
              3, 3, 4, 1, 3, 2, 1, 1, 1, 2, 1, 2, 3, 2, 1, 2, 31, 4, 9, 8, 1, 1, 2, 1,
              1, 17, 3, 1, 1, 19, 3, 2, 1, 3, 7, 1, 1, 5, 1, 3, 12, 1, 2, 3, 1, 2, 1,
              1, 3, 3, 4, 3, 4, 4, 3, 3,
          ],
          np.int8,
      )
      nodes = [
          "Anzelma", "Babet", "Bahorel", "Bamatabois", "BaronessT", "Blacheville",
          "Bossuet", "Boulatruelle", "Brevet", "Brujon", "Champmathieu",
          "Champtercier", "Chenildieu", "Child1", "Child2", "Claquesous",
          "Cochepaille", "Combeferre", "Cosette", "Count", "CountessDeLo",
          "Courfeyrac", "Cravatte", "Dahlia", "Enjolras", "Eponine", "Fameuil",
          "Fantine", "Fauchelevent", "Favourite", "Feuilly", "Gavroche", "Geborand",
          "Gervais", "Gillenormand", "Grantaire", "Gribier", "Gueulemer", "Isabeau",
          "Javert", "Joly", "Jondrette", "Judge", "Labarre", "Listolier",
          "LtGillenormand", "Mabeuf", "Magnon", "Marguerite", "Marius",
          "MlleBaptistine", "MlleGillenormand", "MlleVaubois", "MmeBurgon", "MmeDeR",
          "MmeHucheloup", "MmeMagloire", "MmePontmercy", "MmeThenardier",
          "Montparnasse", "MotherInnocent", "MotherPlutarch", "Myriel", "Napoleon",
          "OldMan", "Perpetue", "Pontmercy", "Prouvaire", "Scaufflaire", "Simplice",
          "Thenardier", "Tholomyes", "Toussaint", "Valjean", "Woman1", "Woman2",
          "Zephine",
      ]
      # fmt: on
      return nxcg.Graph.from_coo(
          77,
          src_indices,
          dst_indices,
          edge_values={"weight": weights},
          id_to_key=nodes,
      )
  
file_path: cugraph/python/nx-cugraph/nx_cugraph/generators/social.py
imports: import cupy
  import numpy
  import nx_cugraph
  from ..utils import index_dtype, networkx_algorithm
label_desc: Use image node_id 4 for calling a global function with example usage: les_miserables_graph() and returns: nxcg