hi i want to use bayesianoptimization in h2o.deeplearning.
so i try this code.
`initial_weight_distribution = c("UniformAdaptive","Uniform", "Normal")
loss = c("Automatic", "CrossEntropy", "Huber" , "Absolute" , "Quadratic")
activation = c("RectifierWithDropout" , "MaxoutWithDropout" ,"TanhWithDropout")
acq <- c("ucb" , "ei" , "poi")
library(rlist)
source("./deep_source.R")
for ( init in initial_weight_distribution){
for (loss_1 in loss){
for( act in activation){
for (acq_1 in acq){
print(paste("-----",init ,loss_1 , act , acq_1,"-----",sep="-"))
aa <- tryCatch( select(h2o_bayes , parameter) , error = function(e){ list(print(e)) } )
time <- Sys.time()
file_name <- paste(substr(time,3,4),substr(time,6,7),substr(time,9,10),substr(time,12,13)
,init ,loss_1 , act , acq1, sep="")
list.save(aa , file = paste0("./loop_para/",file_name,".rds") )
print("==============================")
}
}
}
}`
but An error occurs in the middle. " <simpleError: DistributedException from localhost/127.0.0.1:54321: '> "
hi i want to use bayesianoptimization in h2o.deeplearning. so i try this code. `initial_weight_distribution = c("UniformAdaptive","Uniform", "Normal") loss = c("Automatic", "CrossEntropy", "Huber" , "Absolute" , "Quadratic") activation = c("RectifierWithDropout" , "MaxoutWithDropout" ,"TanhWithDropout") acq <- c("ucb" , "ei" , "poi") library(rlist)
source("./deep_source.R")
for ( init in initial_weight_distribution){ for (loss_1 in loss){ for( act in activation){ for (acq_1 in acq){ print(paste("-----",init ,loss_1 , act , acq_1,"-----",sep="-")) aa <- tryCatch( select(h2o_bayes , parameter) , error = function(e){ list(print(e)) } ) time <- Sys.time() file_name <- paste(substr(time,3,4),substr(time,6,7),substr(time,9,10),substr(time,12,13) ,init ,loss_1 , act , acq1, sep="") list.save(aa , file = paste0("./loop_para/",file_name,".rds") ) print("==============================") } } } }`
but An error occurs in the middle. " <simpleError: DistributedException from localhost/127.0.0.1:54321: '> "
thanks :)