`predict.MXFeedForwardModel`¶

Description¶

Predict the outputs given a model and dataset.

predict.MXFeedForwardModel(

  model,

  X,

  ctx = NULL,

  array.batch.size = 128,

  array.layout = "auto",

  allow.extra.params = FALSE

)

Argument	Description
`model`	The MXNet Model.
`X`	The dataset to predict.
`ctx`	mx.cpu() or mx.gpu(). The device used to generate the prediction.
`array.batch.size`	The batch size used in batching. Only used when X is R’s array.
`array.layout`	can be “auto”, “colmajor”, “rowmajor”, (detault=auto). The layout of array. “rowmajor” is only supported for two dimensional array. For matrix, “rowmajor” means dim(X) = c(nexample, nfeatures), “colmajor” means dim(X) = c(nfeatures, nexample) “auto” will auto detect the layout by match the feature size, and will report error when X is a square matrix to ask user to explicitly specify layout.
`allow.extra.params`	Whether allow extra parameters that are not needed by symbol. If this is TRUE, no error will be thrown when arg_params or aux_params contain extra parameters that is not needed by the executor.