code: def gen_single_dim_tables(self) -> List[ShardedEmbeddingTable]:
      num_tables = 47
      embeddings: List[ShardedEmbeddingTable] = []
      for i in range(num_tables):
          embeddings.append(
              ShardedEmbeddingTable(
                  name=f"table_{i}",
                  embedding_dim=16,
                  num_embeddings=random.randint(100, 500000),
                  data_type=DataType.FP16,
              )
          )
      return embeddings
  
file_path: torchrec/torchrec/distributed/tests/test_emb_dim_bucketer.py
imports: import random
  import unittest
  from typing import List, Tuple
  from torchrec.distributed.embedding_dim_bucketer import EmbDimBucketer, EmbDimBucketerPolicy, should_do_dim_bucketing
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel, ShardedEmbeddingTable
  from torchrec.modules.embedding_configs import DataType
label_desc: Use image node_id 3 for calling the TestEmbDimBucketer obj's underlying member method code with example usage: obj.gen_single_dim_tables() and returns: embeddings