code: def test_composability(self) -> None:
      device = torch.device("cpu")
      eb1_config = EmbeddingBagConfig(
          name="t1",
          embedding_dim=4,
          num_embeddings=10,
          feature_names=["f1"],
      )
      eb2_config = EmbeddingBagConfig(
          name="t2",
          embedding_dim=4,
          num_embeddings=10,
          feature_names=["f2"],
      )
      eb3_config = EmbeddingBagConfig(
          name="t3",
          embedding_dim=4,
          num_embeddings=10,
          feature_names=["f3"],
      )
  
      ebc = EmbeddingBagCollection(
          tables=[eb1_config, eb2_config, eb3_config],
      )
      test_model = TestModel(ebc).to(device)
      original_named_buffers = dict(test_model.named_buffers())
      original_named_modules = dict(test_model.named_modules())
      original_named_parameters = dict(test_model.named_parameters())
  
      fuse_embedding_optimizer(
          test_model,
          optimizer_type=torch.optim.SGD,
          optimizer_kwargs={"lr": 0.02},
          device=device,
      )
  
      fused_named_buffers = dict(test_model.named_buffers())
      fused_named_modules = dict(test_model.named_modules())
      fused_named_parameters = dict(test_model.named_parameters())
  
      self.assertEqual(
          original_named_buffers.keys(), fused_named_buffers.keys()
      )
      for buffer_key in original_named_buffers.keys():
          original_buffer, fused_buffer = (
              original_named_buffers[buffer_key],
              fused_named_buffers[buffer_key],
          )
          self.assertEqual(original_buffer.shape, fused_buffer.shape)
  
      self.assertEqual(
          original_named_modules.keys(), fused_named_modules.keys()
      )
  
      self.assertEqual(
          original_named_parameters.keys(),
          fused_named_parameters.keys(),
      )
      for param_key in original_named_parameters.keys():
          original_param, fused_param = (
              original_named_parameters[param_key],
              fused_named_parameters[param_key],
          )
          self.assertEqual(original_param.shape, fused_param.shape)
  
imports: import unittest
  from collections import OrderedDict
  from typing import Any, Dict, List, Optional, Tuple, Type
  import hypothesis.strategies
  import torch
  import torch.fx
  import torchrec
  from fbgemm_gpu.split_table_batched_embeddings_ops_training import EmbeddingLocation
  from hypothesis import given, settings
  from torchrec.modules.embedding_configs import EmbeddingBagConfig, EmbeddingConfig
  from torchrec.modules.embedding_modules import EmbeddingBagCollection, EmbeddingCollection
  from torchrec.modules.fused_embedding_modules import fuse_embedding_optimizer, FusedEmbeddingBagCollection, FusedEmbeddingCollection
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 15 for calling the FusedEmbeddingBagCollectionTest obj's underlying member method code with example usage: obj.test_composability() without return types