Merge pull request #1 from jermainewang/cpp

Cpp

examples/pytorch/gcn/gcn_spmv.py

@@ -55,7 +55,7 @@ class GCN(nn.Module):
             if self.dropout:
                 val = F.dropout(self.g.get_n_repr(), p=self.dropout)
                 self.g.set_n_repr(val)
-            self.g.update_all(fn.copy_src(), fn.sum(), layer, batchable=True)
+            self.g.update_all(fn.copy_src(), fn.sum(), layer)
         return self.g.pop_n_repr()
 
 def main(args):

examples/pytorch/line_graph/README.md

+Community Detection with Graph Neural Networks (CDGNN)
+============
+
+Paper link: [https://arxiv.org/abs/1705.08415](https://arxiv.org/abs/1705.08415)
+
+Author's code repo: [https://github.com/joanbruna/GNN_community](https://github.com/joanbruna/GNN_community)
+
+This folder contains a DGL implementation of the CDGNN model.
+
+An experiment on the Stochastic Block Model in default settings can be run with
+
+```bash
+python train.py
+```
+
+An experiment on the Stochastic Block Model in customized settings can be run with
+```bash
+python train.py --batch-size BATCH_SIZE --gpu GPU --n-communities N_COMMUNITIES --n-features N_FEATURES --n-graphs N_GRAPH --n-iterations N_ITERATIONS --n-layers N_LAYER --n-nodes N_NODE --model-path MODEL_PATH --radius RADIUS
+```

examples/pytorch/line_graph/data.py

-import torch.utils as utils

examples/pytorch/line_graph/utils.py

+def cycle(loader):
+    while True:
+        for x in loader:
+            yield x