code: def forward(self, x, pe, edge_index, edge_attr, batch):
      x_pe = self.pe_norm(pe)
      x = torch.cat(
          (self.node_emb(x.squeeze(-1)), self.pe_lin(x_pe)), 1
      )
      edge_attr = self.edge_emb(edge_attr)
  
      for conv in self.convs:
          x = conv(x, edge_index, batch, edge_attr=edge_attr)
      x = global_add_pool(x, batch)
      return self.mlp(x)
  
file_path: pytorch_geometric/examples/graph_gps.py
imports: import argparse
  import os.path
  from typing import Any, Dict, Optional
  import torch
  from torch.nn import BatchNorm1d, Embedding, Linear, ModuleList, ReLU, Sequential
  from torch.optim.lr_scheduler import ReduceLROnPlateau
  import torch_geometric.transforms
  from torch_geometric.datasets import ZINC
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import GINEConv, GPSConv, global_add_pool
  from torch_geometric.nn.attention import PerformerAttention
label_desc: Use image node_id 2 for calling the GPS obj's underlying member method code with example usage: obj.forward(x, pe, edge_index, edge_attr, batch) and returns: self