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[Model] Add dgl.nn.CuGraphGATConv
model
#5168
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dgl.nn.CuGraphGATConv
modeldgl.nn.CuGraphGATConv
model
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How about model accuracy? |
If not None, applies an activation function to the updated node features. | ||
Default: ``None``. | ||
bias : bool, optional | ||
If True, learns a bias term. Defaults: ``True``. |
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What if the graph has zero-degree nodes?
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Their output features would be zero.
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Is this consistent with the behavior of GATConv
?
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Yes, GATConv
also outputs zeros for zero-degree nodes.
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done a pass
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
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Co-authored-by: Mufei Li <mufeili1996@gmail.com>
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We get the same accuracy number as the DGL in those examples. |
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I'm good.
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* add CuGraphGATConv model * lintrunner * update model to reflect changes in make_mfg_csr(), move max_in_degree to forward() * simplify pytest markers * fall back to FG option for large fanout * update error msg * add feat_drop and activation options * add residual option * Update python/dgl/nn/pytorch/conv/cugraph_gatconv.py Co-authored-by: Mufei Li <mufeili1996@gmail.com> * Update python/dgl/nn/pytorch/conv/cugraph_gatconv.py Co-authored-by: Mufei Li <mufeili1996@gmail.com> * reset res_fc --------- Co-authored-by: Mufei Li <mufeili1996@gmail.com>
Description
This PR adds a GATConv model Add
dgl.nn.CuGraphGATConv
that uses the accelerated sparse aggregation primitives in cugraph-ops. It requirespylibcugraphops >= 23.02
.Checklist
Please feel free to remove inapplicable items for your PR.
Changes
CuGraphGATConv
CuGraphGATConv
Notes
Fixes rapidsai/cugraph-ops#181.