code: def test_batch_norm(device, conf):
      x = torch.randn(100, 16, device=device)
  
      norm = BatchNorm(16, affine=conf, track_running_stats=conf).to(
          device
      )
      norm.reset_running_stats()
      norm.reset_parameters()
      assert str(norm) == "BatchNorm(16)"
  
      if is_full_test():
          torch.jit.script(norm)
  
      out = norm(x)
      assert out.size() == (100, 16)
  
imports: import pytest
  import torch
  from torch_geometric.nn import BatchNorm, HeteroBatchNorm
  from torch_geometric.testing import is_full_test, withCUDA
label_desc: Use image node_id 1 for calling a global function with example usage: test_batch_norm(device, conf) without return types