class_docstr: ## Cache
  
  This maintains a key-value cache and queues push values and pop them in the same order.
  The queues are useful since we have multiple attention layers.
class_docstr_tok: ["#","#","Cache","This","maintains","a","key-value","cache","and","queues","push","values","and","pop","them","in","the","same","order",".","The","queues","are","useful","since","we","have","multiple","attention","layers","."]
docstr: ### Clear cache
docstr_tok: ["#","#","#","Clear","cache"]
code: def clear_all(self):
      """
      ### Clear cache
      """
      self._cache = {}
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/neox/utils/cache.py
imports: from typing import Any
label_desc: Use image node_id 2 for calling the Cache obj's underlying member method code with example usage: obj.clear_all() without return types