Raises:
         TypeError -- input doesn't contain at least one tensor
  Return type:
     *RRef*

Skip connections
Certain models like ResNeXt are not completely sequential and have
skip connections between layers. Naively implementing as part of
pipeline parallelism would imply that we need to copy outputs for
certain layers through multiple GPUs till we eventually reach the GPU
where the layer for the skip connection resides. To avoid this copy
overhead, we provide APIs below to stash and pop Tensors in different
layers of the model.
torch.distributed.pipeline.sync.skip.skippable.skippable(stash=(), pop=())
The decorator to define a "nn.Module" with skip connections.
   Decorated modules are called "skippable". This functionality works
   perfectly fine even when the module is not wrapped by "Pipe".
Each skip tensor is managed by its name. Before manipulating skip
   tensors, a skippable module must statically declare the names for