code: def uniform_node_drop(self, data):
      num_nodes = maybe_num_nodes(
          data.edge_index, num_nodes=data.x.shape[0]
      )
      keep_probs = torch.tensor(
          [1.0 - self.magnitude for _ in range(num_nodes)]
      )
      dist = Bernoulli(keep_probs)
      subset = dist.sample().to(torch.bool)
  
      while subset.sum() == 0:
          dist = Bernoulli(keep_probs)
          subset = dist.sample().to(torch.bool)
      edge_index, _ = subgraph(
          subset, data.edge_index, relabel_nodes=True
      )
  
      x = data.x
      if x is not None:
          x = x[subset]
      new_data = Data(x=x, edge_index=edge_index, y=data.y)
      return new_data, None
  
file_path: DIG/dig/auggraph/method/GraphAug/aug/node_drop.py
imports: import torch
  import torch.nn.functional
  from torch.distributions.bernoulli import Bernoulli
  from torch_geometric.data import Data
  from torch_geometric.utils import subgraph
  from torch_geometric.utils.num_nodes import maybe_num_nodes
label_desc: Use image node_id 3 for calling the NodeDrop obj's underlying member method code with example usage: obj.uniform_node_drop(data) and returns: new_data,  None