code: def _min_index(shape, strides, storage_offset):
      """Returns the leftest index in the array (in the unit-steps)
  
      Args:
          shape (tuple of int): The shape of output.
          strides (tuple of int):
              The strides of output, given in the unit of steps.
          storage_offset (int):
              The offset between the head of allocated memory and the pointer of
              first element, given in the unit of steps.
  
      Returns:
          int: The leftest pointer in the array
      """
      sh_st_neg = [
          sh_st for sh_st in zip(shape, strides) if sh_st[1] < 0
      ]
      if not sh_st_neg:
          return storage_offset
      else:
          return storage_offset + six.moves.reduce(
              lambda base, sh_st: base + (sh_st[0] - 1) * sh_st[1],
              sh_st_neg,
              0,
          )
  
imports: import numpy
  import six
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling a global function with example usage: _min_index(shape, strides, storage_offset) and returns: storage_offset, unknown