model's parameters afterwards, gradient reduction functions no
     longer match the correct set of parameters.
Warning:
 Using "DistributedDataParallel" in conjunction with the
 Distributed RPC Framework is experimental and subject to change.

Parameters:
      * module (Module) -- module to be parallelized
  * **device_ids** (*list of python:int** or **torch.device*) --

    CUDA devices. 1) For single-device modules, "device_ids" can
    contain exactly one device id, which represents the only CUDA
    device where the input module corresponding to this process
    resides. Alternatively, "device_ids" can also be "None". 2)
    For multi-device modules and CPU modules, "device_ids" must be
    "None".

    When "device_ids" is "None" for both cases, both the input
    data for the forward pass and the actual module must be placed
    on the correct device. (default: "None")

  * **output_device** (*int** or **torch.device*) -- Device
