hyerarchical model training is not considering the ancestor matrix

[cregouby]

current situation

according to the hardhat.R code :

tabnet/R/hardhat.R

Lines 166 to 175 in 34e143a

	ancestor <- data.tree::ToDataFrameNetwork(x) %>%
	mutate_if(is.character, ~.x %>% as.factor %>% as.numeric)
	# TODO check correctness
	# embed the M matrix in the config$ancestor variable
	dims <- c(max(ancestor), max(ancestor))
	ancestor_m <- Matrix::sparseMatrix(ancestor$from, ancestor$to, dims = dims, x = 1)
	check_type(processed$outcomes)
	config <- merge_config_and_dots(config, ...)
	tabnet_bridge(processed, config = config, tabnet_model, from_epoch, task = "supervised")

ancestor matrix is computed but not passed to the tabnet model to be fitted.

Expected situation

ancestor matrix is passed through via a config attribute to the model