code: def output_dist(
      self,
      ctx: EmbeddingBagCollectionContext,
      output: List[torch.Tensor],
  ) -> LazyAwaitable[KeyedTensor]:
      lazy_awaitable_kt = self._embedding_bag_collection.output_dist(
          ctx, output
      )
      return self.add_fp_params_grad_sync_callback(lazy_awaitable_kt)
  
imports: from functools import partial
  from typing import Any, Dict, Iterator, List, Optional, Type, Union
  import torch
  from torch import nn
  from torchrec.distributed.embedding_types import BaseEmbeddingSharder, KJTList, ShardedEmbeddingModule
  from torchrec.distributed.embeddingbag import EmbeddingBagCollectionContext, EmbeddingBagCollectionSharder, ShardedEmbeddingBagCollection
  from torchrec.distributed.types import Awaitable, LazyAwaitable, ParameterSharding, QuantizedCommCodecs, ShardingEnv, ShardingType
  from torchrec.distributed.utils import append_prefix, init_parameters
  from torchrec.modules.feature_processor_ import FeatureProcessorsCollection
  from torchrec.modules.fp_embedding_modules import apply_feature_processors_to_kjt, FeatureProcessedEmbeddingBagCollection
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor, KeyedTensor
label_desc: Use image node_id 5 for calling the ShardedFeatureProcessedEmbeddingBagCollection obj's underlying member method code with example usage: obj.output_dist(ctx, output) and returns: self