parameters: (solver_prototxt, roidb, output_dir,
                pretrained_model=None, max_iters=40000)
return_statement: return model_paths
docstring: Train a Fast R-CNN network.
docstring_summary: Train a Fast R-CNN network.
docstring_tokens: Train a Fast R - CNN network .
function: def train_net(solver_prototxt, roidb, output_dir,
                pretrained_model=None, max_iters=40000):
      """Train a Fast R-CNN network."""
  
      roidb = filter_roidb(roidb)
      sw = SolverWrapper(solver_prototxt, roidb, output_dir,
                         pretrained_model=pretrained_model)
  
      print 'Solving...'
      model_paths = sw.train_model(max_iters)
      print 'done solving'
      return model_paths
function_tokens: def train_net ( solver_prototxt , roidb , output_dir , pretrained_model = None , max_iters = 40000 ) : roidb = filter_roidb ( roidb ) sw = SolverWrapper ( solver_prototxt , roidb , output_dir , pretrained_model = pretrained_model ) print 'Solving...' model_paths = sw . train_model ( max_iters ) print 'done solving' return model_paths