GitLab

add a clip gradients util, equivalent to torch's but aware of the sharded states. Add a corresponding unit test

Adds support for:
* Reused layers (e.g. for weight sharing)
* Lazily-constructed layers
* Single-process control via PipeRPCWrapper
* PipelineStyle.AsyncScheudle, which lays the foundation for asynchronous pipeline work by introducing an event loop for each rank/worker to process either activations or gradients as they arrive

Also added examples for multi-process and PipeRPCWrapper

* small refactor, getting rid of the while loop

- Aurick noticed this bug and I ran into it yesterday
- after the fix, our cifar training shows same gain values from
  different replics now:

```
20-Oct-20 16:00:19 - DEBUG - rank1 - scale 2, gain ratio 1.3512124098087777
20-Oct-20 16:00:19 - DEBUG - rank0 - scale 2, gain ratio 1.3512124098087777
20-Oct-20 16:00:19 - DEBUG - rank1 - timing: data 0:00:00.000600 fwd 0:00:00.003678 loss 0:00:00.000086 bwd 0:00:00.314158 update 0:00:00.002132 rest 0:00:00.000399
20-Oct-20 16:00:19 - DEBUG - rank0 - timing: data 0:00:00.000643 fwd 0:00:00.003460 loss 0:00:00.000084 bwd 0:00:00.314678 update 0:00:00.002001 rest 0:00:00.000408
20-Oct-20 16:00:19 - DEBUG - rank1 - scale 2, gain ratio 1.3514997779980324
20-Oct-20 16:00:19 - DEBUG - rank0 - scale 2, gain ratio 1.3514997779980324
20-Oct-20 16:00:19 - DEBUG - rank1 - timing: data 0:00:00.000732 fwd 0:00:00.003689 loss 0:00:00.000086 bwd 0:00:00.314176 update 0:00:00.002146 rest 0:00:00.000397
20-Oct-20 16:00:19 - DEBUG - rank0 - timing: data 0:00:00.000646 fwd 0:00:00.003542 loss 0:00:00.000089 bwd 0:00:00.314549 update 0:00:00.001956 rest 0:00:00.000392
20-Oct-20 16:00:19 - DEBUG - rank1 - scale 2, gain ratio 1.352149646693932
20-Oct-20 16:00:19 - DEBUG - rank0 - scale 2, gain ratio 1.352149646693932
```

Adds support for distributing pipeline stages across multiple processes (and therefore multiple machines)
* Adds a style argument to the Pipe constructor, defaulting to PipelineStyle.SingleProcess, but also supporting PipelineStyle.MultiProcess
* Added support for lazy construction of modules (see lazy_construction for an example)
* Added two implementations of inter-process communication: one based on rpc with globally visible queues, one based on send/recv
* Copied all the relevant tests from tests/pipe to tests/pipe_process and modified them to exercise PipelineStyle.MultiProcess