code: def sample_test_batch(self, batch_size):
      batch_idx = np.random.randint(
          int(self.max_size * 0.2) - self.context_len - 1,
          size=batch_size,
      ) + int(self.max_size * 0.8)
      # batch_idx = (self._curr_pos + batch_idx) % self._curr_size
      batch_exp = [self.sample(i) for i in batch_idx]
      return self._process_batch(batch_exp)
  
file_path: PARL/benchmark/fluid/offline-Q-learning/replay_memory.py
imports: import numpy
  import copy
  import os
  from collections import deque, namedtuple
  from parl.utils import logger
label_desc: Use image node_id 9 for calling the ReplayMemory obj's underlying member method code with example usage: obj.sample_test_batch(batch_size) and returns: self