class_docstr: BaseManagedCollisionEmbeddingCollection represents a EC/EBC module and a set of managed collision modules.
  The inputs into the MC-EC/EBC will first be modified by the managed collision module before being passed into the embedding collection.
  
  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: ["BaseManagedCollisionEmbeddingCollection","represents","a","EC\/EBC","module","and","a","set","of","managed","collision","modules",".","The","inputs","into","the","MC-EC\/EBC","will","first","be","modified","by","the","managed","collision","module","before","being","passed","into","the","embedding","collection",".","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_module: Union[
          EmbeddingBagCollection, EmbeddingCollection
      ],
      managed_collision_collection: ManagedCollisionCollection,
      return_remapped_features: bool = False,
  ) -> None:
      super().__init__()
      self._managed_collision_collection = managed_collision_collection
      self._return_remapped_features = return_remapped_features
      self._embedding_module: Union[
          EmbeddingBagCollection, EmbeddingCollection
      ] = embedding_module
  
      if isinstance(embedding_module, EmbeddingBagCollection):
          assert (
              self._embedding_module.embedding_bag_configs()
              == self._managed_collision_collection.embedding_configs()
          ), "Embedding Bag Collection and Managed Collision Collection must contain the Embedding Configs"
  
      else:
          assert (
              self._embedding_module.embedding_configs()
              == self._managed_collision_collection.embedding_configs()
          ), "Embedding Collection and Managed Collision Collection must contain the Embedding Configs"
  
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 BaseManagedCollisionEmbeddingCollection object from inherited base classes: nn with example: obj = BaseManagedCollisionEmbeddingCollection(embedding_module, managed_collision_collection, return_remapped_features)