[Example] Fix GIN Example (#826)

* Add serialization

* fix gin

* Add serialization

* fix gin

* fix

examples/pytorch/gin/README.md

@@ -20,12 +20,12 @@ How to run
 An experiment on the GIN in default settings can be run with
 
 ```bash
-python3 main.py
+python main.py
 ```
 
 An experiment on the GIN in customized settings can be run with
 ```bash
-python3 main.py [--device 0 | --disable-cuda] --dataset COLLAB \
+python main.py [--device 0 | --disable-cuda] --dataset COLLAB \
                --graph_pooling_type max --neighbor_pooling_type sum
 ```
 
@@ -35,7 +35,7 @@ Results
 Run with following with the double SUM pooling way:
 (tested dataset: "MUTAG"(default), "COLLAB", "IMDBBINARY", "IMDBMULTI")
 ```bash
-python3 train.py --dataset MUTAB --device 0  \
+python main.py --dataset MUTAG --device 0  \
                 --graph_pooling_type sum --neighbor_pooling_type sum
 ```
 

examples/pytorch/gin/gin.py

@@ -156,6 +156,8 @@ class GIN(nn.Module):
 
         for layer in range(self.num_layers - 1):
             h = self.ginlayers[layer](g, h)
+            h = self.batch_norms[layer](h)
+            h = F.relu(h)
             hidden_rep.append(h)
 
         score_over_layer = 0

examples/pytorch/gin/main.py

@@ -147,8 +147,8 @@ def main(args):
                 f.write("\n")
 
         lrbar.set_description(
-            "the learning eps with learn_eps={} is: {}".format(
-                args.learn_eps, [layer.eps.data for layer in model.ginlayers]))
+            "Learning eps with learn_eps={}: {}".format(
+                args.learn_eps, [layer.eps.data.item() for layer in model.ginlayers]))
 
     tbar.close()
     vbar.close()