code: def test_no_sparse(self) -> None:
      ebc = EmbeddingBagCollection(tables=[])
      D_unused = 1
      with self.assertRaises(AssertionError):
          DLRM(
              embedding_bag_collection=ebc,
              dense_in_features=100,
              dense_arch_layer_sizes=[20, D_unused],
              over_arch_layer_sizes=[5, 1],
          )
  
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 3 for calling the DLRMTest obj's underlying member method code with example usage: obj.test_no_sparse() without return types