code: def shard(
      self,
      module: FusedEmbeddingCollection,
      params: Dict[str, ParameterSharding],
      env: ShardingEnv,
      device: Optional[torch.device] = None,
  ) -> ShardedFusedEmbeddingCollection:
      return ShardedFusedEmbeddingCollection(
          module, params, env, device
      )
  
imports: from typing import Dict, Iterator, List, Optional, Type
  import torch
  from torch import nn
  from torch.nn.parallel import DistributedDataParallel
  from torchrec.distributed.embedding import ShardedEmbeddingCollection
  from torchrec.distributed.embedding_types import BaseEmbeddingSharder, EmbeddingComputeKernel
  from torchrec.distributed.sharding.dp_sharding import DpPooledEmbeddingSharding
  from torchrec.distributed.types import ParameterSharding, ShardingEnv, ShardingType
  from torchrec.distributed.utils import append_prefix
  from torchrec.modules.fused_embedding_modules import convert_optimizer_type_and_kwargs, FusedEmbeddingCollection
  from torchrec.optim.fused import FusedOptimizerModule
label_desc: Use image node_id 1 for calling the FusedEmbeddingCollectionSharder obj's underlying member method code with example usage: obj.shard(module, params, env, device) and returns: ShardedFusedEmbeddingCollection