code: def test_create_slices():
      """Test checking the create of time create_slices."""
      # Test that create_slices default provide an empty list
      assert create_slices(0, 0) == []
      # Test that create_slice return correct number of slices
      assert len(create_slices(0, 100)) == 100
      # Test with non-zero start parameters
      assert len(create_slices(50, 100)) == 50
      # Test slices' length with non-zero start and window_width=2
      assert len(create_slices(0, 100, length=2)) == 50
      # Test slices' length with manual slice separation
      assert len(create_slices(0, 100, step=10)) == 10
      # Test slices' within length for non-consecutive samples
      assert len(create_slices(0, 500, length=50, step=10)) == 46
      # Test that slices elements start, stop and step correctly
      slices = create_slices(0, 10)
      assert slices[0].start == 0
      assert slices[0].step == 1
      assert slices[0].stop == 1
      assert slices[-1].stop == 10
      # Same with larger window width
      slices = create_slices(0, 9, length=3)
      assert slices[0].start == 0
      assert slices[0].step == 1
      assert slices[0].stop == 3
      assert slices[-1].stop == 9
      # Same with manual slices' separation
      slices = create_slices(0, 9, length=3, step=1)
      assert len(slices) == 7
      assert slices[0].step == 1
      assert slices[0].stop == 3
      assert slices[-1].start == 6
      assert slices[-1].stop == 9
  
imports: from copy import deepcopy
  from datetime import datetime, timezone
  from io import StringIO
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from scipy import sparse
  from mne import pick_types, read_cov, read_evokeds
  from mne._fiff.pick import _picks_by_type
  from mne.epochs import make_fixed_length_epochs
  from mne.io import read_raw_fif
  from mne.time_frequency import tfr_morlet
  from mne.utils import _PCA, _apply_scaling_array, _apply_scaling_cov, _array_equal_nan, _cal_to_julian, _custom_lru_cache, _dt_to_julian, _freq_mask, _get_inst_data, _julian_to_cal, _julian_to_dt, _reg_pinv, _ReuseCycle, _time_mask, _undo_scaling_array, _undo_scaling_cov, compute_corr, create_slices, grand_average, hashfunc, numerics, object_diff, object_hash, object_size, random_permutation, sum_squared
  from mne.utils.numerics import _LRU_CACHE_MAXSIZES, _LRU_CACHES
label_desc: Use image node_id 5 for calling a global function with example usage: test_create_slices() without return types