code: def __call__(self, /, *args, backend=None, **kwargs):
      if not backends:
          # Fast path if no backends are installed
          return self.orig_func(*args, **kwargs)
  
      # Use `backend_name` in this function instead of `backend`
      backend_name = backend
      if backend_name is not None and backend_name not in backends:
          raise ImportError(f"Unable to load backend: {backend_name}")
  
      graphs_resolved = {}
      for gname, pos in self.graphs.items():
          if pos < len(args):
              if gname in kwargs:
                  raise TypeError(
                      f"{self.name}() got multiple values for {gname!r}"
                  )
              val = args[pos]
          elif gname in kwargs:
              val = kwargs[gname]
          elif gname not in self.optional_graphs:
              raise TypeError(
                  f"{self.name}() missing required graph argument: {gname}"
              )
          else:
              continue
          if val is None:
              if gname not in self.optional_graphs:
                  raise TypeError(
                      f"{self.name}() required graph argument {gname!r} is None; must be a graph"
                  )
          else:
              graphs_resolved[gname] = val
  
      # Alternative to the above that does not check duplicated args or missing required graphs.
      # graphs_resolved = {
      #     val
      #     for gname, pos in self.graphs.items()
      #     if (val := args[pos] if pos < len(args) else kwargs.get(gname)) is not None
      # }
  
      if (
          self._is_testing
          and self._automatic_backends
          and backend_name is None
      ):
          # Special path if we are running networkx tests with a backend.
          return self._convert_and_call_for_tests(
              self._automatic_backends[0],
              args,
              kwargs,
              fallback_to_nx=self._fallback_to_nx,
          )
  
      # Check if any graph comes from a backend
      if self.list_graphs:
          # Make sure we don't lose values by consuming an iterator
          args = list(args)
          for gname in self.list_graphs & graphs_resolved.keys():
              val = list(graphs_resolved[gname])
              graphs_resolved[gname] = val
              if gname in kwargs:
                  kwargs[gname] = val
              else:
                  args[self.graphs[gname]] = val
  
          has_backends = any(
              hasattr(g, "__networkx_backend__")
              if gname not in self.list_graphs
              else any(hasattr(g2, "__networkx_backend__") for g2 in g)
              for gname, g in graphs_resolved.items()
          )
          if has_backends:
              graph_backend_names = {
                  getattr(g, "__networkx_backend__", "networkx")
                  for gname, g in graphs_resolved.items()
                  if gname not in self.list_graphs
              }
              for gname in self.list_graphs & graphs_resolved.keys():
                  graph_backend_names.update(
                      getattr(g, "__networkx_backend__", "networkx")
                      for g in graphs_resolved[gname]
                  )
      else:
          has_backends = any(
              hasattr(g, "__networkx_backend__")
              for g in graphs_resolved.values()
          )
          if has_backends:
              graph_backend_names = {
                  getattr(g, "__networkx_backend__", "networkx")
                  for g in graphs_resolved.values()
              }
      if has_backends:
          # Dispatchable graphs found! Dispatch to backend function.
          # We don't handle calls with different backend graphs yet,
          # but we may be able to convert additional networkx graphs.
          backend_names = graph_backend_names - {"networkx"}
          if len(backend_names) != 1:
              # Future work: convert between backends and run if multiple backends found
              raise TypeError(
                  f"{self.name}() graphs must all be from the same backend, found {backend_names}"
              )
          [graph_backend_name] = backend_names
          if (
              backend_name is not None
              and backend_name != graph_backend_name
          ):
              # Future work: convert between backends to `backend_name` backend
              raise TypeError(
                  f"{self.name}() is unable to convert graph from backend {graph_backend_name!r} "
                  f"to the specified backend {backend_name!r}."
              )
          if graph_backend_name not in backends:
              raise ImportError(
                  f"Unable to load backend: {graph_backend_name}"
              )
          if (
              "networkx" in graph_backend_names
              and graph_backend_name not in self._automatic_backends
          ):
              # Not configured to convert networkx graphs to this backend
              raise TypeError(
                  f"Unable to convert inputs and run {self.name}. "
                  f"{self.name}() has networkx and {graph_backend_name} graphs, but NetworkX is not "
                  f"configured to automatically convert graphs from networkx to {graph_backend_name}."
              )
          backend = _load_backend(graph_backend_name)
          if hasattr(backend, self.name):
              if "networkx" in graph_backend_names:
                  # We need to convert networkx graphs to backend graphs
                  return self._convert_and_call(
                      graph_backend_name,
                      args,
                      kwargs,
                      fallback_to_nx=self._fallback_to_nx,
                  )
              # All graphs are backend graphs--no need to convert!
              return getattr(backend, self.name)(*args, **kwargs)
          # Future work: try to convert and run with other backends in self._automatic_backends
          raise NetworkXNotImplemented(
              f"'{self.name}' not implemented by {graph_backend_name}"
          )
  
      # If backend was explicitly given by the user, so we need to use it no matter what
      if backend_name is not None:
          return self._convert_and_call(
              backend_name, args, kwargs, fallback_to_nx=False
          )
  
      # Only networkx graphs; try to convert and run with a backend with automatic
      # conversion, but don't do this by default for graph generators or loaders.
      if self.graphs:
          for backend_name in self._automatic_backends:
              if self._can_backend_run(backend_name, *args, **kwargs):
                  return self._convert_and_call(
                      backend_name,
                      args,
                      kwargs,
                      fallback_to_nx=self._fallback_to_nx,
                  )
      # Default: run with networkx on networkx inputs
      return self.orig_func(*args, **kwargs)
  
imports: import inspect
  import os
  import sys
  import warnings
  from functools import partial
  from importlib.metadata import entry_points
  import networkx
  from ..exception import NetworkXNotImplemented
label_desc: Use image node_id 5 for calling the _dispatchable obj's underlying member method code with example usage: obj.__call__() and returns: self, self, self, self, getattr, self, self