code: def shardable_parameters(
      self, module: FusedEmbeddingBagCollection
  ) -> Dict[str, nn.Parameter]:
      params = {
          name.split(".")[-2]: param
          for name, param in module.state_dict().items()
          if name.endswith(".weight")
      }
      return params
  
file_path: torchrec/torchrec/distributed/fused_embeddingbag.py
imports: from typing import Dict, List, Optional, Type
  import torch
  from torch import nn
  from torch.nn.parallel import DistributedDataParallel
  from torchrec.distributed.embedding_types import BaseEmbeddingSharder, EmbeddingComputeKernel
  from torchrec.distributed.embeddingbag import ShardedEmbeddingBagCollection
  from torchrec.distributed.sharding.dp_sharding import DpPooledEmbeddingSharding
  from torchrec.distributed.types import ParameterSharding, QuantizedCommCodecs, ShardingEnv, ShardingType
  from torchrec.modules.fused_embedding_modules import convert_optimizer_type_and_kwargs, FusedEmbeddingBagCollection
label_desc: Use image node_id 2 for calling the FusedEmbeddingBagCollectionSharder obj's underlying member method code with example usage: obj.shardable_parameters(module) and returns: params