Convert data to torch format — matrix_to

For an x/y interface, matrix_to_dataset() converts the data to proper encodings then formats the results for consumption by torch.

Usage

matrix_to_dataset(x, y, device = NULL)

Arguments

x: A numeric matrix of predictors.
y: A vector. If regression than y is numeric. For classification, it is a factor.
device: A single character string for the device to use (e.g., "cpu" or "cuda"). The default of NULL uses the CPU. See training_efficiency.

Value

An R6 index sampler object with classes "training_set", "dataset", and "R6".

Details

Missing values should be removed before passing data to this function.

Examples

if (torch::torch_is_installed()) {
  matrix_to_dataset(as.matrix(mtcars[, -1]), mtcars$mpg)
}
#> <tensor_dataset>
#>   Inherits from: <dataset>
#>   Public:
#>     .getbatch: function (index) 
#>     .getitem: function (index, ..., drop = TRUE) 
#>     .length: function () 
#>     clone: function (deep = FALSE) 
#>     initialize: function (...) 
#>     load_state_dict: function (x, ..., .refer_to_state_dict = FALSE) 
#>     state_dict: function () 
#>     tensors: list