Training mxnet:mx.mlp - r

Question

I am trying to reproduce an example from ND Lewis: Neural Networks for time series forecasting with R. If I include the device argument I get the error:
Error in mx.opt.sgd(...) :
unused argument (device = list(device = "cpu", device_id = 0, device_typeid = 1))
In addition: Warning message:
In mx.model.select.layout.train(X, y) :
Auto detect layout of input matrix, use rowmajor..
If I remove this parameter, I still get this warning:
Warning message:
In mx.model.select.layout.train(X, y) :
Auto detect layout of input matrix, use rowmajor..
The code is:
library(zoo)
library(quantmod)
library(mxnet)
# data
data("ecoli", package = "tscount")
data <- ecoli$cases
data <- as.zoo(ts(data, start = c(2001, 1), end = c(2013, 20), frequency = 52))
xorig <- do.call(cbind, lapply((1:4), function(x) as.zoo(Lag(data, k = x))))
xorig <- cbind(xorig, data)
xorig <- xorig[-(1:4), ]
# normalization
range_data <- function(x) {
(x - min(x))/(max(x) - min(x))
}
xnorm <- data.matrix(xorig)
xnorm <- range_data(xnorm)
# test/train
y <- xnorm[, 5]
x <- xnorm[, -5]
n_train <- 600
x_train <- x[(1:n_train), ]
y_train <- y[(1:n_train)]
x_test <- x[-(1:n_train), ]
y_test <- y[-(1:n_train)]
# mxnet:
mx.set.seed(2018)
model1 <- mx.mlp(x_train,
y_train,
hidden_node = c(10, 2),
out_node = 1,
activation = "sigmoid",
out_activation = "rmse",
num.round = 100,
array.batch.size = 20,
learning.rate = 0.07,
momentum = 0.9
#, device = mx.cpu()
)
pred1_train <- predict(model1, x_train, ctx = mx.cpu())
How can I fix this?

Answer 1

Regarding the second warning message, MXNet is trying to detect the row/column major based on the shape of your inputs: https://github.com/apache/incubator-mxnet/blob/424143ac47ab3a38ae8aedaeb3319379887de0bc/R-package/R/model.R#L329
For the unused argument device = mx.cpu(), should the argument name be corrected to ctx instead of device?