Support device mapping for tensor libraries

[fabawi]

Add argument to tensor data structures with direct GPU/TPU mapping to support re-mapping on mirrored node e.g.,

@PluginRegistrar.register
class MXNetTensor(Plugin):
    def __init__(self, load_mxnet_device=None, map_mxnet_devices=None, **kwargs):

where map_mxnet_devices should be {'all': mxnet.gpu(0) when load_mxnet_device=mxnet.gpu(0) and map_mxnet_devices=None.
For instance, when load_mxnet_device=mxnet.gpu(0) or load_mxnet_device="cuda:0", map_mxnet_devices can be set manually as a dictionary representing the source device as key and the target device as value for non-default device maps.

Suppose we have the following wrapified function:

@MiddlewareCommunicator.register("NativeObject", args.mware, "Notify", "/notify/test_native_exchange",
                                         carrier="tcp", should_wait=True, load_mxnet_device=mxnet.cpu(0), 
                                         map_mxnet_devices={"cuda:0": "cuda:1", mxnet.gpu(1): "cuda:0", "cuda:3": "cpu:0", 
                                                                              mxnet.gpu(2):  mxnet.gpu(0)})
        def exchange_object(self):
            msg = input("Type your message: ")
            ret = {"message": msg,
                   "mx_ones": mxnet.nd.ones((2, 4)),
                   "mxnet_zeros_cuda1": mxnet.nd.zeros((2, 3), ctx=mxnet.gpu(1)),
                   "mxnet_zeros_cuda0": mxnet.nd.zeros((2, 3), ctx=mxnet.gpu(0)),
                   "mxnet_zeros_cuda2": mxnet.nd.zeros((2, 3), ctx=mxnet.gpu(2)),
                   "mxnet_zeros_cuda3": mxnet.nd.zeros((2, 3), ctx=mxnet.gpu(3))}
            return ret,

then the source and target gpus 1 & 0 would be flipped, gpu 3 would be placed on cpu 0, and gpu 2 would be placed on gpu 0. Defining mxnet.gpu(1): mxnet.gpu(0) and cuda:1: cuda:2 in the same mapping should raise an error since the same device is mapped to two different targets.

[fabawi]

Resolved but needs to be more consistent e.g., pytorch does not accept "gpu:0" mapping whereas mxnet and paddle accept "gpu:0" and "cuda:0"

[fabawi]

Closing for now as resolved with #24 but needs improvement