code: def star_graph(n, create_using=None):
      orig_n, orig_nodes = n
      n, nodes = _number_and_nodes(n)
      # star_graph behaves differently whether the input was an int or iterable
      if isinstance(orig_n, Integral):
          if nodes is not None:
              nodes.append(n)
          n += 1
      if n < 3:
          return _common_small_graph(
              n, nodes, create_using, allow_directed=False
          )
      graph_class, inplace = _create_using_class(create_using)
      if graph_class.is_directed():
          raise nx.NetworkXError("Directed Graph not supported")
      flat = cp.zeros(n - 1, index_dtype)
      ramp = cp.arange(1, n, dtype=index_dtype)
      src_indices = cp.hstack((flat, ramp))
      dst_indices = cp.hstack((ramp, flat))
      G = graph_class.from_coo(
          n, src_indices, dst_indices, id_to_key=nodes
      )
      if inplace:
          return create_using._become(G)
      return G
  
imports: import itertools
  from numbers import Integral
  import cupy
  import networkx
  import numpy
  import nx_cugraph
  from ..utils import _get_int_dtype, index_dtype, networkx_algorithm
  from ._utils import _IS_NX32_OR_LESS, _common_small_graph, _complete_graph_indices, _create_using_class, _ensure_int, _ensure_nonnegative_int, _number_and_nodes
label_desc: Use image node_id 12 for calling a global function with example usage: star_graph(n, create_using) and returns: G, _common_small_graph, create_using