code: def get_wiki_cs(transform=RowFeatNormalizer(subtract_min=True)):
      dataset = WikiCSDataset(transform=transform)
      g = dataset[0]
      std, mean = torch.std_mean(g.ndata["feat"], dim=0, unbiased=False)
      g.ndata["feat"] = (g.ndata["feat"] - mean) / std
  
      return [g]
  
file_path: dgl/examples/pytorch/bgrl/utils.py
imports: import copy
  import numpy
  import torch
  from dgl.data import AmazonCoBuyComputerDataset, AmazonCoBuyPhotoDataset, CoauthorCSDataset, CoauthorPhysicsDataset, PPIDataset, WikiCSDataset
  from dgl.dataloading import GraphDataLoader
  from dgl.transforms import Compose, DropEdge, FeatMask, RowFeatNormalizer
label_desc: Use image node_id 2 for calling a global function with example usage: get_wiki_cs(transform) and returns: list