class_docstr: Description
  -----------
  The unpooling module for graph
  
  Parameters
  ----------
  hidden_dim : int
      The number of channels of node features.
class_docstr_tok: ["Description","--","--","--","--","--","-","The","unpooling","module","for","graph","Parameters","--","--","--","--","--","hidden_dim",":","int","The","number","of","channels","of","node","features","."]
code: def __init__(self, hidden_dim: int):
      super(GraphUnpool, self).__init__()
      self.up_sample_gcn = GraphConvWithDropout(hidden_dim, hidden_dim)
  
imports: from typing import Optional
  import dgl
  import torch
  import torch.nn
  from dgl import DGLGraph
  from dgl.nn import GraphConv
  from torch import Tensor
label_desc: Use image node_id 1 to create a new GraphUnpool object from inherited base classes: torch.nn with example: obj = GraphUnpool(hidden_dim)