code: def store(self, exp):
      idx = self.idx % self.size
      self.memory[idx] = exp
      self.sum_tree[idx] = self.max_value
      self.min_tree[idx] = self.max_value
      self.idx += 1
  
file_path: dynet/examples/reinforcement-learning/memory.py
imports: import numpy
  from math import log, ceil
  from reduce_tree import ReduceTree, SumTree
label_desc: Use image node_id 2 for calling the PrioritizedMemory obj's underlying member method code with example usage: obj.store(exp) without return types