class_docstr: Distributes sparse features (input) to be data-parallel.
class_docstr_tok: ["Distributes","sparse","features","(","input",")","to","be","data-parallel","."]
code: def __init__(self) -> None:
      super().__init__()
  
imports: from typing import Any, cast, Dict, List, Optional, TypeVar
  import torch
  from torchrec.distributed.embedding_lookup import GroupedPooledEmbeddingsLookup
  from torchrec.distributed.embedding_sharding import BaseEmbeddingDist, BaseEmbeddingLookup, BaseSparseFeaturesDist, EmbeddingSharding, EmbeddingShardingContext, EmbeddingShardingInfo, group_tables
  from torchrec.distributed.embedding_types import BaseGroupedFeatureProcessor, EmbeddingComputeKernel, GroupedEmbeddingConfig, ShardedEmbeddingTable
  from torchrec.distributed.types import Awaitable, NoWait, ShardingEnv, ShardMetadata
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
  from torchrec.streamable import Multistreamable
label_desc: Use image node_id 1 to create a new DpSparseFeaturesDist object from inherited base classes: BaseSparseFeaturesDist with example: obj = DpSparseFeaturesDist()