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- #
- # Copyright (C) Stanislaw Adaszewski, 2020
- # License: GPLv3
- #
-
-
- #
- # This module implements a single layer of the Decagon
- # model. This is going to be already quite complex, as
- # we will be using all the graph convolutional building
- # blocks.
- #
- # h_{i}^(k+1) = ϕ(∑_r ∑_{j∈N{r}^{i}} c_{r}^{ij} * \
- # W_{r}^(k) h_{j}^{k} + c_{r}^{i} h_{i}^(k))
- #
- # N{r}^{i} - set of neighbors of node i under relation r
- # W_{r}^(k) - relation-type specific weight matrix
- # h_{i}^(k) - hidden state of node i in layer k
- # h_{i}^(k)∈R^{d(k)} where d(k) is the dimensionality
- # of the representation in k-th layer
- # ϕ - activation function
- # c_{r}^{ij} - normalization constants
- # c_{r}^{ij} = 1/sqrt(|N_{r}^{i}| |N_{r}^{j}|)
- # c_{r}^{i} - normalization constants
- # c_{r}^{i} = 1/|N_{r}^{i}|
- #
-
-
- from .layer import *
- from .input import *
- from .convolve import *
- from .decode import *
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