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Fix typo (dmlc#2235)
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Co-authored-by: Chao Ma <[email protected]>
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cafeal and aksnzhy authored Sep 25, 2020
1 parent 36daf66 commit 6b0d42d
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Showing 3 changed files with 3 additions and 3 deletions.
2 changes: 1 addition & 1 deletion python/dgl/nn/pytorch/conv/gatconv.py
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ class GATConv(nn.Module):
----------
in_feats : int, or pair of ints
Input feature size; i.e, the number of dimensions of :math:`h_i^{(l)}`.
ATConv can be applied on homogeneous graph and unidirectional
GATConv can be applied on homogeneous graph and unidirectional
`bipartite graph <https://docs.dgl.ai/generated/dgl.bipartite.html?highlight=bipartite>`__.
If the layer is to be applied to a unidirectional bipartite graph, ``in_feats``
specifies the input feature size on both the source and destination nodes. If
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2 changes: 1 addition & 1 deletion python/dgl/nn/pytorch/conv/nnconv.py
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ class NNConv(nn.Module):
----------
in_feats : int
Input feature size; i.e, the number of dimensions of :math:`h_j^{(l)}`.
NN can be applied on homogeneous graph and unidirectional
NNConv can be applied on homogeneous graph and unidirectional
`bipartite graph <https://docs.dgl.ai/generated/dgl.bipartite.html?highlight=bipartite>`__.
If the layer is to be applied on a unidirectional bipartite graph, ``in_feats``
specifies the input feature size on both the source and destination nodes. If
Expand Down
2 changes: 1 addition & 1 deletion python/dgl/nn/pytorch/conv/sageconv.py
Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@ class SAGEConv(nn.Module):
in_feats : int, or pair of ints
Input feature size; i.e, the number of dimensions of :math:`h_i^{(l)}`.
GATConv can be applied on homogeneous graph and unidirectional
SAGEConv can be applied on homogeneous graph and unidirectional
`bipartite graph <https://docs.dgl.ai/generated/dgl.bipartite.html?highlight=bipartite>`__.
If the layer applies on a unidirectional bipartite graph, ``in_feats``
specifies the input feature size on both the source and destination nodes. If
Expand Down

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