code: def create_input_dist(
      self, device: Optional[torch.device] = None
  ) -> BaseSparseFeaturesDist[KJTList]:
      return InferTwSparseFeaturesDist(
          self.features_per_rank(),
          self._world_size,
          device if device is not None else self._device,
      )
  
imports: from typing import Any, Callable, Dict, List, Optional, Set, Tuple, TypeVar
  import torch
  import torch.distributed
  from fbgemm_gpu.permute_pooled_embedding_modules_split import PermutePooledEmbeddingsSplit
  from torchrec.distributed.dist_data import EmbeddingsAllToOne
  from torchrec.distributed.embedding_lookup import GroupedPooledEmbeddingsLookup, InferGroupedPooledEmbeddingsLookup
  from torchrec.distributed.embedding_sharding import BaseEmbeddingDist, BaseEmbeddingLookup, BaseSparseFeaturesDist, EmbeddingShardingContext, EmbeddingShardingInfo
  from torchrec.distributed.embedding_types import BaseGroupedFeatureProcessor, EmbeddingComputeKernel, KJTList, ShardedEmbeddingTable
  from torchrec.distributed.sharding.tw_sharding import BaseTwEmbeddingSharding, InferTwSparseFeaturesDist, TwPooledEmbeddingDist, TwSparseFeaturesDist
  from torchrec.distributed.types import NullShardingContext, QuantizedCommCodecs, ShardedTensorMetadata, ShardingEnv, ShardMetadata
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
  from torchrec.streamable import Multistreamable
label_desc: Use image node_id 1 for calling the InferCwPooledEmbeddingSharding obj's underlying member method code with example usage: obj.create_input_dist(device) and returns: InferTwSparseFeaturesDist