code: def test_correctness(self) -> None:
      D = 4
      B = 3
      # multi-head attentions
      nhead = 4
      ntransformer_layers = 4
      keys = [
          "f1",
          "f2",
          "f3",
          "f4",
      ]
      F = len(keys)
      # place the manual_seed before the InteractionTransformerArch object to generate the same initialization random values in the Transformer
      torch.manual_seed(0)
      inter_arch = InteractionTransformerArch(
          num_sparse_features=F,
          embedding_dim=D,
          nhead=nhead,
          ntransformer_layers=ntransformer_layers,
      )
      dense_features = torch.rand((B, D))
      sparse_features = torch.rand((B, F, D))
      concat_dense = inter_arch(dense_features, sparse_features)
      self.assertEqual(concat_dense.size(), (B, D * (F + 1)))
      expected = torch.tensor(
          [
              [
                  -0.4411,
                  0.2487,
                  -1.2685,
                  1.4610,
                  1.3110,
                  0.5152,
                  -0.4960,
                  -1.3303,
                  -0.3962,
                  -0.0623,
                  -1.1371,
                  1.5956,
                  0.2431,
                  -1.6820,
                  0.5242,
                  0.9148,
                  1.3033,
                  0.6409,
                  -0.9577,
                  -0.9866,
              ],
              [
                  -1.0850,
                  -0.0366,
                  -0.4862,
                  1.6078,
                  1.1254,
                  -0.9989,
                  -0.9927,
                  0.8661,
                  -0.1704,
                  1.0223,
                  -1.5580,
                  0.7060,
                  -0.3081,
                  -1.3686,
                  0.2788,
                  1.3979,
                  0.0328,
                  1.5470,
                  -0.3670,
                  -1.2128,
              ],
              [
                  -1.5917,
                  -0.0995,
                  0.7302,
                  0.9609,
                  0.6606,
                  1.0238,
                  -0.1017,
                  -1.5827,
                  -0.6761,
                  -1.0771,
                  0.2262,
                  1.5269,
                  -0.5671,
                  -1.2114,
                  1.4503,
                  0.3281,
                  -0.6540,
                  -1.2925,
                  0.9134,
                  1.0331,
              ],
          ]
      )
      self.assertTrue(
          torch.allclose(
              concat_dense,
              expected,
              rtol=1e-4,
              atol=1e-4,
          )
      )
  
imports: import unittest
  import torch
  from torchrec.datasets.utils import Batch
  from torchrec.models.dlrm import DLRMTrain
  from torchrec.models.experimental.transformerdlrm import DLRM_Transformer, InteractionTransformerArch
  from torchrec.modules.embedding_configs import EmbeddingBagConfig
  from torchrec.modules.embedding_modules import EmbeddingBagCollection
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 3 for calling the InteractionArchTransformerTest obj's underlying member method code with example usage: obj.test_correctness() without return types