【发布时间】:2018-01-14 05:48:42
【问题描述】:
data1.dl.r2 = vector()
for (i in 1:100) {
if (i==1) {
data1.hex = as.h2o(data1)
} else {
data1.hex = nextdata
}
data1.dl = h2o.deeplearning (x=2:1000,y=1,training_frame=data1.hex,nfolds=5,activation="Tanh",hidden=30,seed=5,reproducible=TRUE)
data1.dl.pred = h2o.predict(data1.dl,data1.hex)
data1.dl.r2[i] = sum((as.matrix(data1.dl.pred)-mean(as.matrix(data1.hex[,1])))^2)/
sum((as.matrix(data1.hex[,1])-mean(as.matrix(data1.hex[,1])))^2) # R-squared
prevdata = as.matrix(data1.hex)
nextpred = as.matrix(h2o.predict(data1.dl,as.h2o(data0[i,])))
colnames(nextpred) = "response"
nextdata = as.h2o(rbind(prevdata,cbind(nextpred,data0[i,-1])))
print(i)
}
这是我的代码,其中包含 100 个观察值和 1000 个特征的数据集 (data1)。 当我运行它时,它在第 50~60 次迭代时给了我一条错误消息 "
Error in .h2o.doSafeREST(h2oRestApiVersion = h2oRestApiVersion, urlSuffix = page, :
ERROR MESSAGE:
Total input file size of 87.5 KB is much larger than total cluster memory of Zero , please use either a larger cluster or smaller data.
当我运行“h20.init()”时,它告诉我集群总内存为零。
H2O cluster total nodes: 1
H2O cluster total memory: 0.00 GB
H2O cluster total cores: 8
H2O cluster allowed cores: 8
H2O cluster healthy: TRUE
所以我想知道为什么集群总内存为零, 以及为什么它在早期的迭代中没有出错。
【问题讨论】:
-
当我关闭 R Studio 并再次打开时,它显示集群总内存为 3.56GB。
标签: memory memory-management deep-learning cluster-computing h2o