code: def test_cross_net_numercial_forward(self) -> None:
      torch.manual_seed(0)
  
      batch_size = 3
      num_layers = 20
      in_features = 2
      input = torch.randn(batch_size, in_features)
  
      # test using vector for crossing
      dcn = LowRankCrossNet(
          in_features=in_features, num_layers=num_layers, low_rank=10
      )
      output = dcn(input)
      expected_output = torch.Tensor(
          [
              [-11.5000, -3.4863],
              [-0.2742, -0.3330],
              [249.6694, 117.3466],
          ]
      )
      self.assertTrue(
          torch.allclose(output, expected_output, rtol=1e-4, atol=1e-4)
      )
  
imports: import unittest
  import torch
  from torch.fx import GraphModule, Tracer
  from torchrec.modules.crossnet import CrossNet, LowRankCrossNet, LowRankMixtureCrossNet, VectorCrossNet
label_desc: Use image node_id 1 for calling the TestLowRankCrossNet obj's underlying member method code with example usage: obj.test_cross_net_numercial_forward() without return types