code: def test_3d_input(self, N: int, C: int, W: int):
      x = torch.randn([N, C, W])
      norm = nn.InstanceNorm1d(
          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_norm1d_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 InstanceNorm1d_test obj's underlying member method code with example usage: obj.test_3d_input(N, C, W) without return types