code: def alltoall(comm, xs):
      """Differentiable all-to-all communication between workers.
  
      This function invokes all-to-all communications among processes specified
      by the communicator. Backward will be invoked as well as the ordinary
      chainer functions, just passing input gradients back.
      Unlike point-to-point communication such as ``chainermn.functions.send``
      and ``chainermn.functions.recv``, users need not to care about
      delegate variables, since ``backward()`` will not be invoked until
      all gradients from output direction arrive.
      Please refer to ``chainermn.functions.pseudo_connect`` about the detail
      of delegate variables.
  
      The received array will be on the current CUDA device on the invoking
      process if ``xs`` is on GPU. Please be aware that the current CUDA device
      is intended one.
      (``https://docs-cupy.chainer.org/en/stable/tutorial/basic.html#current-device``)
  
      Args:
          comm: ChainerMN communicator.
          xs (list of chainer.Variables): Variables to send.
  
      Returns:
          ys (list of chainer.Variables): Received variables.
      """
      chainer.utils.experimental("chainermn.functions.all_to_all")
  
      if len(xs) != comm.size:
          raise ValueError(
              "The length of xs must be same as communicator size."
          )
  
      return AllToAll(comm)(*xs)
  
imports: import chainer
  from chainer import backend
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: alltoall(comm, xs) and returns: AllToAll