Function that checks for access to CUDA
vaeac_check_cuda(cuda, verbose)The function does not return anything.
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).
String vector or NULL.
Specifies the verbosity (printout detail level) through one or more of strings "basic", "progress",
"convergence", "shapley" and "vS_details".
"basic" (default) displays basic information about the computation which is being performed,
in addition to some messages about parameters being sets or checks being unavailable due to specific input.
"progress displays information about where in the calculation process the function currently is.
#' "convergence" displays information on how close to convergence the Shapley value estimates are
(only when iterative = TRUE) .
"shapley" displays intermediate Shapley value estimates and standard deviations (only when iterative = TRUE)
and the final estimates.
"vS_details" displays information about the v_S estimates.
This is most relevant for approach %in% c("regression_separate", "regression_surrogate", "vaeac").
NULL means no printout.
Note that any combination of four strings can be used.
E.g. verbose = c("basic", "vS_details") will display basic information + details about the v(S)-estimation process.
Lars Henry Berge Olsen