code: def roll(a, shift, axis=None):
      """Roll array elements along a given axis.
  
      Elements that roll beyond the last position are re-introduced at the first.
  
      Args:
          a (~cupy.ndarray): Array to be rolled.
          shift (int or tuple of int): The number of places by which elements are
              shifted. If a tuple, then `axis` must be a tuple of the same size,
              and each of the given axes is shifted by the corresponding number.
              If an int while `axis` is a tuple of ints, then the same value is
              used for all given axes.
          axis (int or tuple of int or None): The axis along which elements are
              shifted. By default, the array is flattened before shifting, after
              which the original shape is restored.
  
      Returns:
          ~cupy.ndarray: Output array.
  
      .. seealso:: :func:`numpy.roll`
  
      """
      if axis is None:
          return roll(a.ravel(), shift, 0).reshape(a.shape)
  
      axes = (axis,) if numpy.isscalar(axis) else axis
      axes = tuple(
          [  # allow_duplicate
              internal._normalize_axis_index(ax, a.ndim) for ax in axes
          ]
      )
      if isinstance(shift, cupy.ndarray):
          shift = shift.ravel()
          n_axes = max(len(axes), shift.size)
          axes = numpy.broadcast_to(axes, (n_axes,))
          shift = cupy.broadcast_to(shift, (n_axes,))
  
          # TODO(asi1024): Improve after issue #4799 is resolved.
          indices = []
          for ax in range(a.ndim):
              ind_shape = [1] * a.ndim
              ind_shape[ax] = a.shape[ax]
              indices.append(
                  cupy.arange(a.shape[ax]).reshape(ind_shape)
              )
  
          for ax, s in zip(axes, shift):
              indices[ax] -= s
              indices[ax] %= a.shape[ax]
  
          for ax in range(a.ndim):
              indices[ax] = cupy.broadcast_to(indices[ax], a.shape)
  
          return a[tuple(indices)]
      else:
          broadcasted = numpy.broadcast(shift, axes)
          if broadcasted.nd > 1:
              raise ValueError(
                  "'shift' and 'axis' should be scalars or 1D sequences"
              )
          shifts = {ax: 0 for ax in range(a.ndim)}
          for sh, ax in broadcasted:
              shifts[ax] += sh
  
          rolls = [((slice(None), slice(None)),)] * a.ndim
          for ax, offset in shifts.items():
              offset %= (
                  a.shape[ax] or 1
              )  # If `a` is empty, nothing matters.
              if offset:
                  # (original, result), (original, result)
                  rolls[ax] = (
                      (slice(None, -offset), slice(offset, None)),
                      (slice(-offset, None), slice(None, offset)),
                  )
  
          result = cupy.empty_like(a)
          for indices in itertools.product(*rolls):
              arr_index, res_index = zip(*indices)
              result[res_index] = a[arr_index]
  
          return result
  
file_path: cupy/cupy/_manipulation/rearrange.py
imports: import itertools
  import numpy
  import cupy
  from cupy._core import internal
label_desc: Use image node_id 4 for calling a global function with example usage: roll(a, shift, axis) and returns: roll, a, result