a nightly update

README.md

@@ -120,9 +120,9 @@ The link will give some basic usage.
 
 ## Contributors
 
-**[GAMMA LAB](https://github.com/BUPT-GAMMA) [BUPT]**: [Tianyu Zhao](https://github.com/Theheavens), Cheng Yang, Xiao Wang, [Chuan Shi](http://shichuan.org/)
+**[GAMMA LAB](https://github.com/BUPT-GAMMA) [BUPT]**: [Tianyu Zhao](https://github.com/Theheavens), Yaoqi Liu, Fengqi Liang, Yibo Li, Yanhu Mo, Donglin Xia, Xinlong Zhai, Siyuan Zhang, Qi Zhang, [Chuan Shi](http://shichuan.org/), Cheng Yang, Xiao Wang
 
-**BUPT**: Jiahang Li
+**BUPT**: Jiahang Li, Anke Hu
 
 **DGL Team**: Quan Gan, [Jian Zhang](https://github.com/zhjwy9343)
 

openhgnn/output/RHGNN/README.md

@@ -29,7 +29,7 @@ Node classification
 
 | |accuracy|
 |----|----|
-|imdb4GTN|xxx|
+|imdb4GTN|0.5883|
 
 
 ## TrainerFlow: node_classification

openhgnn/trainerflow/node_classification.py

@@ -13,9 +13,9 @@ class NodeClassification(BaseFlow):
     r"""
     Node classification flow means
 
-    The task is to classify the nodes of HIN(Heterogeneous Information Network).
+    The task is to classify the nodes of Heterogeneous graph.
     
-    Note: If the output dim is not equal the number of classes, a MLP will follow the gnn model.
+    Note: If the output dim is not equal the number of classes, we will modify the output dim with the number of classes.
     """
 
     def __init__(self, args):
@@ -53,6 +53,12 @@ def __init__(self, args):
                 batch_size=self.args.batch_size, device=self.device, shuffle=True, num_workers=0)
 
     def preprocess(self):
+        r"""
+        Preprocess for different models, e.g.: different optimizer for GTN.
+        And prepare the dataloader foe train validation and test.
+        Last, we will call preprocess_feature.
+
+        """
         if self.args.model == 'GTN':
             if hasattr(self.args, 'adaptive_lr_flag') and self.args.adaptive_lr_flag == True:
                 self.optimizer = torch.optim.Adam([{'params': self.model.gcn.parameters()},