checkpoint: List. This must be a loaded vaeac save object. That is, torch::torch_load('vaeac_save_path').
cuda: Logical (default is FALSE). If TRUE, then the vaeac model will be trained using cuda/GPU. If torch::cuda_is_available() is FALSE, the we fall back to use CPU. If FALSE, we use the CPU. Using a GPU for smaller tabular dataset often do not improve the efficiency. See vignette("installation", package = "torch") fo help to enable running on the GPU (only Linux and Windows).
mode_train: Logical. If TRUE, the returned vaeac model is set to be in training mode. If FALSE, the returned vaeac model is set to be in evaluation mode.
Returns
A vaeac model with the correct state (based on checkpoint), sent to the desired hardware (based on cuda), and in the right mode (based on mode_train).