* local_rank and install cuda version fix

- resume() is a nested function and when it loads best_prec1
  it creates a local variable that hides the one from the parent
  function (which refers to the global one). This PR adds `global`
  to modify the global variable as intended

Signed-off-by: Janusz Lisiecki <jlisiecki@nvidia.com>

* remove unused tens tensor in example/imagenet/main_amp.py

* remove unused tens tensor in deprecated examples and tests/L1

* [syncBN]
  added syncBN in native pure python apex
  added fused cuda kernels used for sync BN. Using welford for mean/var
    optional installation using 'python setup.py install --cuda_ext'
  added unit test with side to side comparison between apex sync BN with
    PyTorch BN. Notice that for pytorch BN implementation, because of
    numerical issue for mean/var, the output will be slightly off.

* [syncBN PR]
  added fp16 support
  addressing review comments on:
    1. updating last pow 2
    2. look for import error when importing syncBN kernel

* [syncBN PR]
  added convert function to insert SyncBatchNorm
  refactored some kernel code

* fixing type issue (fp16/fp32/fp64)
added Kahan summation
editing unit test to use pytorch primitive ops with double, passing reasonable tests now

* updating tensor creation calls

* fixing the all_reduce contiguous tensor

* transposed all reduce results

* [syncBN]
support fp16 input & fp32 layer for apex fp16
partia...

Fixes to validation in imagenet example scripts. Precision and loss reporting modified to be consistent with train.