code: def __init__(
      self, in_channels, hidden_channels, out_channels, num_relations
  ):
      super().__init__()
      self.conv1 = RGATConv(in_channels, hidden_channels, num_relations)
      self.conv2 = RGATConv(
          hidden_channels, hidden_channels, num_relations
      )
      self.lin = torch.nn.Linear(hidden_channels, out_channels)
  
file_path: pytorch_geometric/examples/rgat.py
imports: import os.path
  import time
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Entities
  from torch_geometric.nn import RGATConv
label_desc: Use image node_id 1 to create a new RGAT object from inherited base classes: torch.nn with example: obj = RGAT(in_channels, hidden_channels, out_channels, num_relations)