class_docstr: This class is used to add vertex degree based node features to graphs.
  This is usually used to preprocess the graph datasets that do not have
  node features.
docstr: This is the main function that adds vertex degree based node
  features to the given graph.
  
  Args:
      data (:class:`torch_geometric.data.data.Data`): The graph
      with vertex degrees as node features.
docstr_tok: ["This","is","the","main","function","that","adds","vertex","degree","based","node","features","to","the","given","graph",".","Args",":","data","(",":","class",":","`","torch_geometric.data.data.Data","`",")",":","The","graph","with","vertex","degrees","as","node","features","."]
code: def __call__(self, data):
      r"""
      This is the main function that adds vertex degree based node
      features to the given graph.
  
      Args:
          data (:class:`torch_geometric.data.data.Data`): The graph
          with vertex degrees as node features.
      """
      if data.x is not None:
          return data
      if self.max_degree < 1000:
          idx = data.edge_index[1 if self.in_degree else 0]
          deg = torch.clamp(
              degree(idx, data.num_nodes, dtype=torch.long),
              min=0,
              max=self.max_degree,
          )
          deg = F.one_hot(deg, num_classes=self.max_degree + 1).to(
              torch.float
          )
          data.x = deg
      else:
          deg = degree(data.edge_index[0], dtype=torch.float)
          deg = (deg - self.mean) / self.std
          data.x = deg.view(-1, 1)
      return data
  
imports: import random
  import torch
  import torch.nn.functional
  from torch.utils.data import Dataset
  from torch_geometric.utils import degree
label_desc: Use image node_id 3 for calling the DegreeTrans obj's underlying member method code with example usage: obj.__call__(data) and returns: data, data