'For backends which support distributed training, this will distribute
or gather the error or activation tensor depending on the type of
parallelism used to distribute the layer computation. Currently
this is only supported by multi-GPU in Nervana cloud.
Arguments:
tensor: Tensor containing either activations or errors
layer_parallelism: Type of parallelism expected by the layer
Returns:
Tensor which has been altered by this call or None'

def distribute_data(self, tensor, layer_parallelism):

    return None
