class_docstr: Experience Replay Buffer
  
  As described in
  https://storage.googleapis.com/deepmind-media/dqn/DQNNaturePaper.pdf.
  
  Args:
      capacity (int): capacity in terms of number of transitions
      num_steps (int): Number of timesteps per stored transition
          (for N-step updates)
class_docstr_tok: ["Experience","Replay","Buffer","As","described","in","https",":","\/\/storage.googleapis.com\/deepmind-media\/dqn\/DQNNaturePaper.pdf",".","Args",":","capacity","(","int",")",":","capacity","in","terms","of","number","of","transitions","num_steps","(","int",")",":","Number","of","timesteps","per","stored","transition","(","for","N-step","updates",")"]
code: def load(self, filename):
      with open(filename, "rb") as f:
          self.memory = pickle.load(f)
      if isinstance(self.memory, collections.deque):
          # Load v0.2
          self.memory = RandomAccessQueue(
              self.memory, maxlen=self.memory.maxlen
          )
  
file_path: pfrl/pfrl/replay_buffers/replay_buffer.py
imports: import collections
  import pickle
  from typing import Optional
  from pfrl import replay_buffer
  from pfrl.collections.random_access_queue import RandomAccessQueue
label_desc: Use image node_id 7 for calling the ReplayBuffer obj's underlying member method code with example usage: obj.load(filename) without return types