【发布时间】:2018-08-07 00:35:27
【问题描述】:
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,我希望启用 GPU 加速来加快训练速度。请让我知道使用 GPU 而不是 CPU 的代码 sn-p。 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()
【问题讨论】: