class_docstr: Serializable data structure for holding data for blocks --
  embeddings and necessary metadata for Retriever
class_docstr_tok: ["Serializable","data","structure","for","holding","data","for","blocks","--","embeddings","and","necessary","metadata","for","Retriever"]
docstr: Clear the embedding data structures to save memory.
  The metadata ends up getting used, and is also much smaller in
  dimensionality so it isn't really worth clearing.
docstr_tok: ["Clear","the","embedding","data","structures","to","save","memory",".","The","metadata","ends","up","getting","used",",","and","is","also","much","smaller","in","dimensionality","so","it","is","n't","really","worth","clearing","."]
code: def clear(self):
      """
      Clear the embedding data structures to save memory.
      The metadata ends up getting used, and is also much smaller in
      dimensionality so it isn't really worth clearing.
      """
      self.embed_data = dict()
  
imports: import itertools
  import os
  import pickle
  import shutil
  import numpy
  import torch
  from megatron import get_args
  from megatron.core import mpu
label_desc: Use image node_id 3 for calling the OpenRetreivalDataStore obj's underlying member method code with example usage: obj.clear() without return types