code: def test_step(self, data: HeteroData, batch_idx: int):
      y_hat = self(data["paper"].x)[data["paper"].test_mask]
      y = data["paper"].y[data["paper"].test_mask]
      self.test_acc(y_hat.softmax(dim=-1), y)
      self.log("test_acc", self.test_acc, batch_size=y.size(0))
  
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 5 for calling the LinearHeteroNodeModule obj's underlying member method code with example usage: obj.test_step(data, batch_idx) without return types