code: def test_fx_and_shape(self) -> None:
      B = 20
      D = 3
      in_features = 10
      dense_arch = DenseArch(
          in_features=in_features, layer_sizes=[10, D]
      )
      gm = symbolic_trace(dense_arch)
      dense_embedded = gm(torch.rand((B, in_features)))
      self.assertEqual(dense_embedded.size(), (B, D))
  
imports: import unittest
  import torch
  from torch import nn
  from torch.testing import FileCheck
  from torchrec.datasets.utils import Batch
  from torchrec.fx import symbolic_trace
  from torchrec.models.dlrm import choose, DenseArch, DLRM, DLRM_DCN, DLRM_Projection, DLRMTrain, InteractionArch, InteractionDCNArch, InteractionProjectionArch, SparseArch
  from torchrec.modules.crossnet import LowRankCrossNet
  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 2 for calling the DenseArchTest obj's underlying member method code with example usage: obj.test_fx_and_shape() without return types