class_docstr: Hypergraph Attention module as in the paper
  `Hypergraph Convolution and Hypergraph Attention
  <https://arxiv.org/pdf/1901.08150.pdf>`_.
class_docstr_tok: ["Hypergraph","Attention","module","as","in","the","paper","`","Hypergraph","Convolution","and","Hypergraph","Attention","<","https",":","\/\/arxiv.org\/pdf\/1901.08150.pdf",">","`","_","."]
code: def __init__(self, in_size, out_size):
      super().__init__()
  
      self.P = nn.Linear(in_size, out_size)
      self.a = nn.Linear(2 * out_size, 1)
  
imports: import argparse
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  import tqdm
  from dgl.data import CoraGraphDataset
  from torchmetrics.functional import accuracy
label_desc: Use image node_id 1 to create a new HypergraphAttention object from inherited base classes: nn with example: obj = HypergraphAttention(in_size, out_size)