code: def get_tbes_to_register_from_iterable(
      iterable: Iterable[torch.nn.Module],
  ) -> Dict[
      IntNBitTableBatchedEmbeddingBagsCodegen, GroupedEmbeddingConfig
  ]:
      tbes: Dict[
          IntNBitTableBatchedEmbeddingBagsCodegen,
          GroupedEmbeddingConfig,
      ] = {}
      for m in iterable:
          if isinstance(m, TBEToRegisterMixIn):
              tbes.update(m.get_tbes_to_register())
      return tbes
  
file_path: torchrec/torchrec/distributed/fused_params.py
imports: from typing import Any, Dict, Iterable, Optional
  import torch
  from fbgemm_gpu.split_table_batched_embeddings_ops_inference import IntNBitTableBatchedEmbeddingBagsCodegen
  from torchrec.distributed.embedding_types import GroupedEmbeddingConfig
label_desc: Use image node_id 1 for calling a global function with example usage: get_tbes_to_register_from_iterable(iterable) and returns: tbes