code: def _yield_estimators(model):
      
      yield from _yield_preproc_steps(model)
  
      net_prefixes = []
      module_prefixes = []
  
      if isinstance(model, Pipeline):
          name = model.steps[-1][0]
          net_prefixes.append(name)
          module_prefixes.append(name)
          net = model.steps[-1][1]
      else:
          net = model
  
      yield '__'.join(net_prefixes), net
  
      module = net.module
      module_prefixes.append('module')
      yield '__'.join(module_prefixes), module
docs: Yield estimator and its prefix from the model.
  
      First, pipeline preprocessing steps are yielded (if there are
      any). Next the neural net is yielded. Finally, the module is
      yielded.