class_docstr: ManagedCollisionEmbeddingCollection represents a EmbeddingCollection module and a set of managed collision modules.
  The inputs into the MC-EC will first be modified by the managed collision module before being passed into the embedding collection.
  
  For details of input and output types, see EmbeddingCollection
  
  Args:
      embedding_module: EmbeddingCollection to lookup embeddings
      managed_collision_modules: Dict of managed collision modules
      return_remapped_features (bool): whether to return remapped input features
          in addition to embeddings
class_docstr_tok: ["ManagedCollisionEmbeddingCollection","represents","a","EmbeddingCollection","module","and","a","set","of","managed","collision","modules",".","The","inputs","into","the","MC-EC","will","first","be","modified","by","the","managed","collision","module","before","being","passed","into","the","embedding","collection",".","For","details","of","input","and","output","types",",","see","EmbeddingCollection","Args",":","embedding_module",":","EmbeddingCollection","to","lookup","embeddings","managed_collision_modules",":","Dict","of","managed","collision","modules","return_remapped_features","(","bool",")",":","whether","to","return","remapped","input","features","in","addition","to","embeddings"]
code: def __init__(
      self,
      embedding_collection: EmbeddingCollection,
      managed_collision_collection: ManagedCollisionCollection,
      return_remapped_features: bool = False,
  ) -> None:
      super().__init__(
          embedding_collection,
          managed_collision_collection,
          return_remapped_features,
      )
  
      # For consistency with embedding bag collection
      self._embedding_collection: EmbeddingCollection = (
          embedding_collection
      )
  
file_path: torchrec/torchrec/modules/mc_embedding_modules.py
imports: from typing import Dict, Optional, Tuple, Union
  import torch
  import torch.nn
  from torchrec.modules.embedding_modules import EmbeddingBagCollection, EmbeddingCollection
  from torchrec.modules.mc_modules import ManagedCollisionCollection
  from torchrec.sparse.jagged_tensor import JaggedTensor, KeyedJaggedTensor, KeyedTensor
label_desc: Use image node_id 1 to create a new ManagedCollisionEmbeddingCollection object from inherited base classes: BaseManagedCollisionEmbeddingCollection with example: obj = ManagedCollisionEmbeddingCollection(embedding_collection, managed_collision_collection, return_remapped_features)