code: def __init__(
      self,
      device: torch.device,
      world_size: int,
  ) -> None:
      super().__init__()
      self._dist: SeqEmbeddingsAllToOne = SeqEmbeddingsAllToOne(
          device, world_size
      )
  
imports: from typing import Any, Dict, List, Optional
  import torch
  import torch.distributed
  from torchrec.distributed.dist_data import SeqEmbeddingsAllToOne, SequenceEmbeddingsAllToAll
  from torchrec.distributed.embedding_lookup import GroupedEmbeddingsLookup, InferGroupedEmbeddingsLookup
  from torchrec.distributed.embedding_sharding import BaseEmbeddingDist, BaseEmbeddingLookup, BaseSparseFeaturesDist
  from torchrec.distributed.embedding_types import BaseGroupedFeatureProcessor, KJTList
  from torchrec.distributed.sharding.rw_sharding import BaseRwEmbeddingSharding, InferRwSparseFeaturesDist, RwSparseFeaturesDist
  from torchrec.distributed.sharding.sequence_sharding import InferSequenceShardingContext, SequenceShardingContext
  from torchrec.distributed.types import Awaitable, CommOp, QuantizedCommCodecs
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 1 to create a new InferRwSequenceEmbeddingDist object from inherited base classes: BaseEmbeddingDist with example: obj = InferRwSequenceEmbeddingDist(device, world_size)