Add torch.utils.flop_counter to TorchBench
Summary:
## context
task 1.5 https://fburl.com/gdoc/65hluw97
FLOPS counting can measure how much computation a model involves and is important to estimate model performance. The torch.utils.flops_counter proposed by Horace He is by far the most ideal tool to measure the FLOPS of a model. It covers both forward and backward pass, and captures all operators.
TorchBench already includes hardware flops measurements for some models but that is different from the model flops. The goal is to replace the theoretical flops calculated via fvcore, which only counts the forward pass.
## this diff
Integrate `FlopCounterMode` in TorchBench, so that users can measure the model flops with the run.py command line tool.
Reviewed By: xuzhao9
Differential Revision: D47610528
fbshipit-source-id: fdc616e9c424f8930543fd89995420c256011143
