code: def forward(
      self,
      dense: torch.Tensor,
      sparse: torch.Tensor,
  ) -> torch.Tensor:
      return self.linear(torch.cat([dense, sparse], dim=1))
  
imports: from typing import cast, Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn
  from torchrec.distributed.embedding import EmbeddingCollectionSharder
  from torchrec.distributed.fbgemm_qcomm_codec import get_qcomm_codecs_registry, QCommsConfig
  from torchrec.distributed.test_utils.test_model import ModelInput, TestDenseArch, TestSparseNNBase
  from torchrec.modules.embedding_configs import BaseEmbeddingConfig, EmbeddingConfig
  from torchrec.modules.embedding_modules import EmbeddingCollection
  from torchrec.modules.embedding_tower import EmbeddingTower
  from torchrec.sparse.jagged_tensor import JaggedTensor, KeyedJaggedTensor
label_desc: Use image node_id 2 for calling the TestSequenceOverArch obj's underlying member method code with example usage: obj.forward(dense, sparse) and returns: self