Fixes

Author: emsal0

docs/src/manual/conv.md

@@ -127,7 +127,7 @@ Reference: [How Powerful are Graph Neural Networks?](https://arxiv.org/pdf/1810.
 \textbf{x}_i' = \textbf{x}_i + \sum_{j \in \mathcal{N}(i)} \sigma\left( \textbf{z}_{i,j} \textbf{W}_f + \textbf{b}_f \right) \odot \text{softplus}\left(\textbf{z}_{i,j} \textbf{W}_s + \textbf{b}_s \right)
 ```
 
-where ``\textbf{z}_{i,j} = [\textbf{x}_i, \textbf{x}_j}, \textbf{e}_{i,j}]`` denotes the concatenation of node features, neighboring node features, and edge features.
+where ``\textbf{z}_{i,j} = [\textbf{x}_i, \textbf{x}_j}, \textbf{e}_{i,j}]`` denotes the concatenation of node features, neighboring node features, and edge features. The operation ``\odot`` represents elementwise multiplication, and ``\sigma`` denotes the sigmoid function.
 
 ```@docs
 CGConv

src/layers/conv.jl

@@ -499,10 +499,10 @@ end
 (l::CGConv)(fg::FeaturedGraph) = FeaturedGraph(fg, nf=l(fg, node_feature(fg),
                                                         edge_feature(fg)),
                                                ef=edge_feature(fg))
-(l::CGConv)(M::AbstractMatrix; edge=false) =
-    if !edge
-        l(l.fg, M, edge_feature(l.fg))
-    else
+(l::CGConv)(M::AbstractMatrix; as_edge=false) =
+    if as_edge
         l(l.fg, node_feature(l.fg), M)
+    else
+        l(l.fg, M, edge_feature(l.fg))
     end
 (l::CGConv)(X::AbstractMatrix, E::AbstractMatrix) = l(l.fg, X, E)