compute function in neuralnet R package not working when reproduced - r

Question

I trained a model in neuralnet and I am trying to figure out how to compute results in Excel. Using the compute function that you call from the package everything works fine. But I went into the source code using F2 in Rstudio and the github page and the function is not working and stops on the relist() function and gives the error: Error in relist(weights, nrow.weights, ncol.weights) :
unused argument (ncol.weights)
I think the problem is the relist() function but I do not know how to transform the weights without it. And the neuralnet package does not come with its own version of relist(). If you ignore the relist line you get the following error: Error in neurons[[i]] %*% weights[[i]] : non-conformable arguments because the weights wasn't transformed correctly. I tried the same thing on my own data and got the same error.
library(neuralnet)
normalize <-function(x) {
return((x - min(x))/(max(x) - min(x)))
}
newdf <- Cars93
newdf = na.omit(newdf)
newdf <- newdf[complete.cases(newdf),]
newdf$Cylinders <- as.numeric(levels(newdf$Cylinders))[newdf$Cylinders]
newdf$Horsepower <- normalize(newdf$Horsepower)
newdf$EngineSize <- normalize(newdf$EngineSize)
newdf$Cylinders <- normalize(newdf$Cylinders)
smp_size <- floor(0.75 * nrow(newdf))
set.seed(12)
train_ind <- sample(seq_len(nrow(newdf)), size = smp_size)
train <- newdf[train_ind, ]
test <- newdf[-train_ind, ]
carsNN <- neuralnet(Horsepower ~ Cylinders+EngineSize,
data = train,hidden = c(1))
cars_results = compute(carsNN,test[11:12])
#this is the source code using F2 in RStudio and on github
sourceCodeCompute = function (x, covariate, rep = 1)
{
nn <- x
linear.output <- nn$linear.output
weights <- nn$weights[[rep]]
nrow.weights <- sapply(weights, nrow)
ncol.weights <- sapply(weights, ncol)
weights <- unlist(weights)
if (any(is.na(weights)))
weights[is.na(weights)] <- 0
weights <- relist(weights, nrow.weights, ncol.weights)
length.weights <- length(weights)
covariate <- as.matrix(cbind(1, covariate))
act.fct <- nn$act.fct
neurons <- list(covariate)
if (length.weights > 1)
for (i in 1:(length.weights - 1)) {
temp <- neurons[[i]] %*% weights[[i]]
act.temp <- act.fct(temp)
neurons[[i + 1]] <- cbind(1, act.temp)
}
temp <- neurons[[length.weights]] %*% weights[[length.weights]]
if (linear.output)
net.result <- temp
else net.result <- act.fct(temp)
list(neurons = neurons, net.result = net.result)
}
sourceCodeCompute(carsNN,test[11:12])

Answer 1

You use the wrong relist function. Try explicitly calling neuralnet:::relist, which is the (unexported) function used automatically within the package namespace.
(I don't know how this question relates to Excel.)