code: def test_network(self):
      if resnet18 is None:
          self.skipTest("no torchvision")
      rn = resnet18(
          norm_layer=lambda x: torch.nn.BatchNorm2d(
              x, track_running_stats=False
          )
      )
      rn.train()
      img = torch.rand(1, 1, 2, 3, 224, 224)
      imgf = img.view(2, 3, 224, 224)
  
      i, j = dims()
      r = rn(img[i, j])
      r = r.order(i, j).view(2, 1000)
      r2 = rn(imgf)
      assert torch.allclose(r2, r, atol=1e-06)
  
imports: from functorch.dim import Tensor, Dim, dims, dimlists, stack, DimensionBindError, DimList
  from attn_ft import BertSelfAttention, Linear
  from attn_positional import BertSelfAttention
  from torch.testing._internal.common_utils import TestCase, run_tests, TEST_CUDA
  from unittest import skip, skipIf
  import torch
  import gc
  from functorch._C import dim
  from contextlib import contextmanager
  from time import perf_counter
label_desc: Use image node_id 22 for calling the TestMin obj's underlying member method code with example usage: obj.test_network() without return types