code: def test_skip_batch_sampler():
      skip = 2
      sampler = torch.utils.data.SequentialSampler(range(15))
      batch_sampler = torch.utils.data.BatchSampler(
          sampler, batch_size=2, drop_last=False
      )
      skip_batch_sampler = samplers.SkipBatchSampler(
          batch_sampler, skip
      )
  
      assert len(skip_batch_sampler) == 8
  
      iterator = iter(batch_sampler)
  
      # Advance the iterator by skip batches.
      for _ in range(skip):
          next(iterator)
  
      for samp, skip_samp in zip(iterator, iter(skip_batch_sampler)):
          assert samp == skip_samp
  
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 4 for calling a global function with example usage: test_skip_batch_sampler() without return types