docstr: Sample n unique samples from this replay buffer
docstr_tok: ["Sample","n","unique","samples","from","this","replay","buffer"]
code: def sample_episodes(self, n_episodes, max_len=None):
      """Sample n unique samples from this replay buffer"""
      assert len(self.episodic_memory) >= n_episodes
      episodes, probabilities, min_prob = self.episodic_memory.sample(
          n_episodes, uniform_ratio=self.uniform_ratio
      )
      if max_len is not None:
          episodes = [random_subseq(ep, max_len) for ep in episodes]
      if self.return_sample_weights:
          weights = self.weights_from_probabilities(
              probabilities, min_prob
          )
          return episodes, weights
      else:
          return episodes
  
file_path: chainerrl/chainerrl/replay_buffers/prioritized_episodic.py
imports: import collections
  from chainerrl.misc.collections import RandomAccessQueue
  from chainerrl.misc.prioritized import PrioritizedBuffer
  from chainerrl.replay_buffer import random_subseq
  from chainerrl.replay_buffers import EpisodicReplayBuffer
  from chainerrl.replay_buffers import PriorityWeightError
label_desc: Use image node_id 2 for calling the PrioritizedEpisodicReplayBuffer obj's underlying member method code with example usage: obj.sample_episodes(n_episodes, max_len) and returns: episodes,  weights, episodes