python之如何在 Python 中对 H2O 启用 GPU 加速

我正在尝试使用 Python 和 H2O 在我的 AWS 服务器上训练深度学习神经网络，我想启用 GPU 加速来加速训练。请让我知道使用 GPU 而不是 CPU 的代码片段。 AWS 使用 OpenGL。弹性 GPU 类型为 eg1.xlarge，内存为 4 GB。

我的模型的代码是:

nn = H2OGridSearch(model=H2ODeepLearningEstimator, 
                               hyper_params = { 
        'activation' :[ "Rectifier","Tanh","Maxout","RectifierWithDropout","TanhWithDropout","MaxoutWithDropout"], 
        'hidden':[[20,20],[50,50],[30,30,30],[25,25,25,25]],            ## small network, runs faster 
#        'rate' :[0.0005,0.001,0.0015,0.002,0.0025,0.003,0.0035,0.0040,0.0045,0.005], 
         'l1':[0,1e-4,1e-6], 
         'l2':[0,1e-4,1e-6] 
        }) 
 
start_time = time.time() 
 
nn.train( 
        train1_x, train1_y,train1, 
        score_validation_samples = 10000,      ## sample the validation dataset (faster) 
        stopping_rounds = 2, 
        stopping_metric ="MSE", ## alternatives: "MSE","logloss","r2" 
        epochs=1000000,   
        stopping_tolerance = 0.01, 
        max_w2 = 10 
        ) 
end_time = time.time() 

请您参考如下方法:

如果您有兴趣运行支持 GPU 的 H2O.ai 产品，H2O-3 仅支持 CPU，请参阅 H2O4GPU或 Driverless AI(注意:后者是闭源的)