code: def forward(self, x: Tensor, batch: Data) -> Tensor:
      # Basic test to ensure that the dataset is not replicated:
      self.trainer.datamodule.train_dataset._data.x.add_(1)
  
      x = self.lin1(x).relu()
      x = global_mean_pool(x, batch)
      x = self.lin2(x)
      return x
  
imports: import math
  import pytest
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.data.lightning import LightningDataset, LightningLinkData, LightningNodeData
  from torch_geometric.nn import global_mean_pool
  from torch_geometric.sampler import BaseSampler, NeighborSampler
  from torch_geometric.testing import MyFeatureStore, MyGraphStore, get_random_edge_index, onlyCUDA, onlyFullTest, onlyNeighborSampler, onlyOnline, withPackage
label_desc: Use image node_id 2 for calling the LinearGraphModule obj's underlying member method code with example usage: obj.forward(x, batch) and returns: x