class_docstr: Redistributes sequence embedding tensor in hierarchical fashion with an AlltoOne
  operation.
  
  Args:
      device (torch.device): device on which the tensors will be communicated to.
      world_size (int): number of devices in the topology.
class_docstr_tok: ["Redistributes","sequence","embedding","tensor","in","hierarchical","fashion","with","an","AlltoOne","operation",".","Args",":","device","(","torch.device",")",":","device","on","which","the","tensors","will","be","communicated","to",".","world_size","(","int",")",":","number","of","devices","in","the","topology","."]
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.sequence_sharding import InferSequenceShardingContext, SequenceShardingContext
  from torchrec.distributed.sharding.tw_sharding import BaseTwEmbeddingSharding, InferTwSparseFeaturesDist, TwSparseFeaturesDist
  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 InferTwSequenceEmbeddingDist object from inherited base classes: BaseEmbeddingDist with example: obj = InferTwSequenceEmbeddingDist(device, world_size)