Finally, to accommodate the fixed input dimension of the discriminator D, we can simply select a subset P e ⊆ Ω E with the top N occurrence frequency, where N is normally much smaller than |Ω E |.
as for the longer paths, despite their potential utility values, they are more likely to contain worthless or even noisy inference steps, thus we learn them only in the training phase.