cleanup

Author: CarloLucibello

Project.toml

@@ -4,7 +4,6 @@ authors = ["Carlo Lucibello and contributors"]
 version = "0.1.0"
 
 [deps]
-Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
@@ -34,6 +33,7 @@ NNlibCUDA = "0.1"
 julia = "1.6"
 
 [extras]
+Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

src/layers/conv.jl

@@ -412,7 +412,7 @@ where ``f_\Theta`` typically denotes a learnable function, e.g. a linear layer o
 
 # Arguments
 
-- ``f``: A (possibly learnable) function acting on node features. 
+- `f`: A (possibly learnable) function acting on node features. 
 - `eps`: Weighting factor.
 """
 struct GINConv{R<:Real} <: GNNLayer
@@ -460,7 +460,7 @@ For convenience, also functions returning a single `(out*in, num_edges)` matrix
 
 - `in`: The dimension of input features.
 - `out`: The dimension of output features.
-- ``f``: A (possibly learnable) function acting on edge features.
+- `f`: A (possibly learnable) function acting on edge features.
 - `aggr`: Aggregation operator for the incoming messages (e.g. `+`, `*`, `max`, `min`, and `mean`).
 - `σ`: Activation function.
 - `bias`: Add learnable bias.