docstr: Can be used to perform inference for multiple tasks (i.e., adapters) in parallel (for the same input).
  
  See AdapterDrop https://arxiv.org/abs/2010.11918
docstr_tok: ["Can","be","used","to","perform","inference","for","multiple","tasks","(","i.e.",",","adapters",")","in","parallel","(","for","the","same","input",")",".","See","AdapterDrop","https",":","\/\/arxiv.org\/abs\/2010.11918"]
code: def __init__(self, *parallel_adapters: List[str]):
      """
      Can be used to perform inference for multiple tasks (i.e., adapters) in parallel (for the same input).
  
      See AdapterDrop https://arxiv.org/abs/2010.11918
      """
      super().__init__(*parallel_adapters)
  
imports: import itertools
  from collections.abc import Sequence
  from typing import List, Optional, Set, Tuple, Union
  import torch
label_desc: Use image node_id 1 to create a new Parallel object from inherited base classes: AdapterCompositionBlock with example: obj = Parallel()