code: def _get_conv_slices(
      size, k, s, p, cover_all=False, d=1, include_pad=True, dtype="l"
  ):
      """Returns the patch slices.
  
      Returns:
          A tuple of two 1-D :class:`numpy.ndarrays`\\ s.
          Each represents starting and ending indices of the patches.
      """
      n = conv.get_conv_outsize(size, k, s, p, cover_all, d)
      starts = -p + numpy.arange(n, dtype=dtype) * s
      ends = starts + k
      if not include_pad:
          starts = numpy.maximum(starts, 0)
          ends = numpy.minimum(ends, size)
      return starts, ends
  
imports: import functools
  import operator
  import numpy
  import six
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.functions.pooling import average_pooling_nd_kernel
  from chainer.functions.pooling import pooling_nd
  from chainer.utils import conv
  from chainer.utils import conv_nd
  import chainerx
label_desc: Use image node_id 1 for calling a global function with example usage: _get_conv_slices(size, k, s, p, cover_all, d, include_pad, dtype) and returns: starts,  ends