Use SMP rank and size when applicable

[rahul003]

Description of changes:

When SMP is used together with Horovod, there'll be multiple horovod 'groups'. Rank and size need to be queried from SMP in such cases.

This is not a problem for Pytorch as there is a single torch.distributed group there or MXNet as SMP doesn't support MXNet.

[codecov-io]

Codecov Report

Merging #411 (42d300b) into master (9d2d0c3) will decrease coverage by 1.57%. The diff coverage is 62.96%.

@@            Coverage Diff             @@
##           master     #411      +/-   ##
==========================================
- Coverage   77.70%   76.13%   -1.58%     
==========================================
  Files         113      113              
  Lines       10139    10165      +26     
==========================================
- Hits         7879     7739     -140     
- Misses       2260     2426     +166     

Impacted Files	Coverage Δ
smdebug/tensorflow/base_hook.py	70.28% <18.18%> (-5.75%)	:arrow_down:
smdebug/core/utils.py	79.72% <74.41%> (+1.98%)	:arrow_up:
smdebug/tensorflow/callable_cache.py	52.17% <0.00%> (-26.09%)	:arrow_down:
smdebug/tensorflow/utils.py	64.59% <0.00%> (-23.45%)	:arrow_down:
smdebug/tensorflow/singleton_utils.py	83.33% <0.00%> (-16.67%)	:arrow_down:
smdebug/profiler/tf_profiler_parser.py	54.54% <0.00%> (-11.58%)	:arrow_down:
smdebug/tensorflow/collection.py	84.53% <0.00%> (-11.35%)	:arrow_down:
smdebug/tensorflow/keras.py	79.21% <0.00%> (-11.00%)	:arrow_down:
smdebug/rules/action/stop_training_action.py	56.45% <0.00%> (-9.68%)	:arrow_down:
smdebug/core/logger.py	66.12% <0.00%> (-8.07%)	:arrow_down:
... and 31 more

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[rahul003]

ok, will do