Hi,
I’m trying to build an auto-encoder. I am using the following data construct:
tl = TabularList.from_df(df, cat_names=cat_names, cont_names=cont_names, procs=procs)
def get_y_fn(i):
return tl[i]
data = tl\
.split_by_idx(valid_idx)\
.label_from_func(get_y_fn, label_cls=FloatList)\
.databunch()
This works nicely, but when training, the i
passed into get_y_fn
always starts from 0, no matter whether the training or validation set is being used. So return tl[i]
always returns data from the training set, because the indices for the validation set start from for example 50000.
Is there any way to determine in get_y_fn
whether we’re working with the training or the validation set?
Thank you.