code: def load_model(
      keras,
      wrap_optimizer,
      optimizer_modules,
      filepath,
      custom_optimizers,
      custom_objects,
  ):
      byteps_objects = {
          subclass.__name__.lower(): wrap_optimizer(subclass)
          for subclass in keras.optimizers.Optimizer.__subclasses__()
          if subclass.__module__ in optimizer_modules
      }
  
      if custom_optimizers is not None:
          byteps_objects.update(
              {
                  cls.__name__: wrap_optimizer(cls)
                  for cls in custom_optimizers
              }
          )
  
      if custom_objects is not None:
          byteps_objects.update(custom_objects)
  
      return keras.models.load_model(
          filepath, custom_objects=byteps_objects
      )
  
imports: import byteps.tensorflow
  import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: load_model(keras, wrap_optimizer, optimizer_modules, filepath, custom_optimizers, custom_objects) and returns: keras