code: def barbell_graph(m1, m2, create_using=None):
      # Like two complete graphs and a path_graph
      m1 = _ensure_nonnegative_int(m1)
      if m1 < 2:
          raise nx.NetworkXError(
              "Invalid graph description, m1 should be >=2"
          )
      m2 = _ensure_nonnegative_int(m2)
      graph_class, inplace = _create_using_class(create_using)
      if graph_class.is_directed():
          raise nx.NetworkXError("Directed Graph not supported")
      src_bell1, dst_bell1 = _complete_graph_indices(m1)
      src_bell2 = src_bell1 + (m1 + m2)
      dst_bell2 = dst_bell1 + (m1 + m2)
      if m2 == 0:
          src_bar = cp.array([m1 - 1, m1], index_dtype)
          dst_bar = cp.array([m1, m1 - 1], index_dtype)
      else:
          src_bar = (
              cp.arange(
                  2 * m1 - 1, 2 * m1 + 2 * m2 + 1, dtype=index_dtype
              )
              // 2
          )
          dst_bar = (
              cp.arange(m1 - 1, m1 + m2 + 1, dtype=index_dtype)[:, None]
              + cp.array([-1, 1], index_dtype)
          ).ravel()[1:-1]
      src_indices = cp.hstack((src_bell1, src_bar, src_bell2))
      dst_indices = cp.hstack((dst_bell1, dst_bar, dst_bell2))
      G = graph_class.from_coo(2 * m1 + m2, src_indices, dst_indices)
      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 1 for calling a global function with example usage: barbell_graph(m1, m2, create_using) and returns: G, create_using