Record Caffe2's current stream ID in c10_cuda. (#15174)

Record Caffe2's current stream ID in c10_cuda. (#15174)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15174

Previously, Caffe2 maintained a separate per-thread per-device
current logical CUDA stream ID.  In this PR, we switch Caffe2 over
to using c10::Stream to manage the current stream, and also
manage the allocation of cudaStream_t objects.

This results in a slight behavior change: previously, Caffe2
would have been willing to allocate an arbitrary number of
CUDA streams, depending on how high the logical stream IDs
went.  The c10::Stream pool has a fixed number of streams, once
you exceed it, it wraps around.

Reviewed By: dzhulgakov

Differential Revision: D13451550

fbshipit-source-id: da6cf33ee026932a2d873835f6e090f7b8a7d8dc