Github user WeichenXu123 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/15051#discussion_r79295910
  
    --- Diff: R/pkg/R/mllib.R ---
    @@ -694,8 +694,14 @@ setMethod("predict", signature(object = "KMeansModel"),
     #' }
     #' @note spark.mlp since 2.1.0
     setMethod("spark.mlp", signature(data = "SparkDataFrame"),
    -          function(data, blockSize = 128, layers = c(3, 5, 2), solver = 
"l-bfgs", maxIter = 100,
    -                   tol = 0.5, stepSize = 1, seed = 1) {
    +          function(data, layers, blockSize = 128, solver = "l-bfgs", 
maxIter = 100,
    +                   tol = 1E-6, stepSize = 0.03, seed = 0x7FFFFFFF) {
    +            if (length(layers) <= 1) {
    +              stop("layers vector require length > 0.")
    +            }
    +            if (any(sapply(layers, function(e) !is.numeric(e)))) {
    --- End diff --
    
    layers should be integer, but in R it seems we can't distinguish numeric or 
integer vector ?
    to `layers<-c(1,2)` or `layers<-c(1.0, 2.0)`, `is.integer(layers[i])` both 
return `false` and `as.integer(layers)` both return `true`,
    so is there some good way to check it is an integer vector but not a 
numeric vector ?



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