code: def test_4d_input(self, N: int, C: int, W: int, H: int):
      x = torch.randn([N, C, H, W])
      norm = nn.InstanceNorm2d(
          num_features=C, affine=True, track_running_stats=False
      )
      self.run_test(x, norm, batch_first=True)
  
file_path: opacus/opacus/tests/grad_samples/instance_norm2d_test.py
imports: import hypothesis.strategies
  import torch
  import torch.nn
  from hypothesis import given, settings
  from .common import GradSampleHooks_test
label_desc: Use image node_id 1 for calling the InstanceNorm2d_test obj's underlying member method code with example usage: obj.test_4d_input(N, C, W, H) without return types