After training my dataset which has a number of categorical data using fastai's tabular model, I wish to read out the entity embedding and use it to map to my original data values. I can see the embedding weights. The number of input don't seem to match anything, but maybe it is based on the unique categorical values in the train_ds.
To get that map, I would like to get the self.categories dictionary from the Categorify transform class. Is there anyway to get that from the data variable obtained by calling TabularList.from_df? Or maybe someone can tell me a better way to get this map. I know the input df into the TabularList.from_df() is not it, because the number of rows are wrong. Most likely because df is splitted into train and valid subsets. But there is no easy way to obtain the train part of the TabularList to check just the train part.
It's strange I can't find any code example that shows this. Doesn't anyone else care to map the entity embedding value back to its original categorical value?
