code: def _uniform_sample_indices_and_probabilities(
      self, n: int
  ) -> Tuple[List[int], List[float]]:
      indices = list(sample_n_k(len(self.data), n))
      probabilities = [1 / len(self)] * len(indices)
      return indices, probabilities
  
imports: import collections
  from typing import Any, Callable, Deque, Generic, List, Optional, Sequence, Tuple, TypeVar
  import numpy
  from pfrl.utils.random import sample_n_k
label_desc: Use image node_id 8 for calling the PrioritizedBuffer obj's underlying member method code with example usage: obj._uniform_sample_indices_and_probabilities(n) and returns: indices,  probabilities