code: def test_reproducible_shuffle_batch_sampler():
      sampler = torch.utils.data.SequentialSampler(range(10))
      batch_sampler = torch.utils.data.BatchSampler(
          sampler, batch_size=2, drop_last=False
      )
      shuffle_batch_sampler = samplers.ReproducibleShuffleSampler(
          batch_sampler, 777
      )
  
      assert list(shuffle_batch_sampler) == [
          [0, 1],
          [8, 9],
          [2, 3],
          [4, 5],
          [6, 7],
      ]
      assert list(shuffle_batch_sampler) == [
          [4, 5],
          [0, 1],
          [2, 3],
          [6, 7],
          [8, 9],
      ]
  
imports: import logging
  import queue
  import typing
  from logging import handlers
  import numpy
  import pytest
  import torch
  import determined
  from determined.pytorch import data_length, samplers, to_device
label_desc: Use image node_id 10 for calling a global function with example usage: test_reproducible_shuffle_batch_sampler() without return types