Splits a dataset into a left half and a right half (e.g. train / test).

Usage

split_dataset(
  dataset,
  left_size = NULL,
  right_size = NULL,
  shuffle = FALSE,
  seed = NULL
)

dataset: A tf$data$Dataset, a torch$utils$data$Dataset object, or a list of arrays with the same length.
left_size: If float (in the range [0, 1]), it signifies the fraction of the data to pack in the left dataset. If integer, it signifies the number of samples to pack in the left dataset. If NULL, defaults to the complement to right_size. Defaults to NULL.
right_size: If float (in the range [0, 1]), it signifies the fraction of the data to pack in the right dataset. If integer, it signifies the number of samples to pack in the right dataset. If NULL, defaults to the complement to left_size. Defaults to NULL.
shuffle: Boolean, whether to shuffle the data before splitting it.
seed: A random seed for shuffling.

A list of two tf$data$Dataset objects: the left and right splits.

data <- random_uniform(c(1000, 4))
c(left_ds, right_ds) %<-% split_dataset(list(data$numpy()), left_size = 0.8)
left_ds$cardinality()

## tf.Tensor(800, shape=(), dtype=int64)

right_ds$cardinality()

## tf.Tensor(200, shape=(), dtype=int64)