vaeac
modelConvert a the data into a torch::dataset()
which the vaeac model creates batches from.
vaeac_dataset(X, one_hot_max_sizes)
A torch_tensor contain the data of shape N x p, where N and p are the number of observations and features, respectively.
A torch tensor of dimension n_features
containing the one hot sizes of the n_features
features. That is, if the i
th feature is a categorical feature with 5 levels, then one_hot_max_sizes[i] = 5
.
While the size for continuous features can either be 0
or 1
.
Lars Henry Berge Olsen
This function creates a torch::dataset()
object that represent a map from keys to data samples.
It is used by the torch::dataloader()
to load data which should be used to extract the
batches for all epochs in the training phase of the neural network. Note that a dataset object
is an R6 instance, see https://r6.r-lib.org/articles/Introduction.html, which is classical
object-oriented programming, with self reference. I.e, vaeac_dataset()
is a subclass
of type torch::dataset()
.