code: def forward(
      self,
      local_embs: List[torch.Tensor],
      sharding_ctx: Optional[NullShardingContext] = None,
  ) -> torch.Tensor:
      return self._permute(self._dist(local_embs))
  
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 2 for calling the InferCwPooledEmbeddingDistWithPermute obj's underlying member method code with example usage: obj.forward(local_embs, sharding_ctx) and returns: self