code: def __init__(
      self,
      training=False,
      uniform=False,
      hid_dim=128,
      magnitude=None,
      temperature=1.0,
  ):
      super(NodeDrop, self).__init__()
      self.uniform = uniform
      self.magnitude = magnitude
      if not uniform:
          self.node_drop_mlp = torch.nn.Sequential(
              torch.nn.Linear(hid_dim, 2 * hid_dim),
              torch.nn.ReLU(),
              torch.nn.Linear(2 * hid_dim, 1),
          )
          self.training = training
          self.temperature = temperature
      else:
          assert magnitude is not 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 1 to create a new NodeDrop object from inherited base classes: torch.nn with example: obj = NodeDrop(training, uniform, hid_dim, magnitude, temperature)