3_h2o_deeplearning.py 文件源码

def run_all_dl(csvfile = saving_fp, 
                space = [hp.quniform('h1', 100, 550, 1), 
                        hp.quniform('h2', 100, 550, 1),
                        hp.quniform('h3', 100, 550, 1),
                        #hp.choice('activation', ["RectifierWithDropout", "TanhWithDropout"]),
                        hp.uniform('hdr1', 0.001, 0.3),
                        hp.uniform('hdr2', 0.001, 0.3),
                        hp.uniform('hdr3', 0.001, 0.3),
                        hp.uniform('rho', 0.9, 0.999), 
                        hp.uniform('epsilon', 1e-10, 1e-4)]):
          # maxout works well with dropout (Goodfellow et al 2013), and rectifier has worked well with image recognition (LeCun et al 1998)
          start_save(csvfile = csvfile)
          trials = Trials()
          print "Deep learning..."
          best = fmin(objective,
                      space = space,
                      algo=tpe.suggest,
                      max_evals=evals,
                      trials=trials)
          print best
          print trials.losses()
          with open('output/dlbest.pkl', 'w') as output:
            pickle.dump(best, output, -1)
          with open('output/dltrials.pkl', 'w') as output:
            pickle.dump(trials, output, -1)