class_docstr: An out-of-graph Replay Buffer for Prioritized Experience Replay.
  See circular_replay_buffer.py for details.
docstr: Sets the priority of the given elements according to Schaul et al.
  Args:
    indices: np.array with dtype int32, of indices in range
      [0, replay_capacity).
    priorities: float, the corresponding priorities.
code: def set_priority(self, indices, priorities) -> None:
      """Sets the priority of the given elements according to Schaul et al.
      Args:
        indices: np.array with dtype int32, of indices in range
          [0, replay_capacity).
        priorities: float, the corresponding priorities.
      """
      assert (
          indices.dtype == np.int32
      ), "Indices must be integers, " "given: {}".format(indices.dtype)
      for index, priority in zip(indices, priorities):
          self.sum_tree.set(index, priority)
  
file_path: ReAgent/reagent/replay_memory/prioritized_replay_buffer.py
imports: import numpy
  import torch
  from reagent.replay_memory import circular_replay_buffer, sum_tree
label_desc: Use image node_id 5 for calling the PrioritizedReplayBuffer obj's underlying member method code with example usage: obj.set_priority(indices, priorities) without return types