Add accuracy metrics to e2e models (#1356)
Summary:
This PR makes two changes to E2E models:
1. Turn on accuracy validation in train by default
2. Store the accuracy metrics in the result json file
For example:
```
$ python run_e2e.py hf_bert -t train
{"device": "cuda", "device_num": 1, "test": "train", "num_examples": 8576, "num_epochs": 3, "batch_size": 32, "result": {"latency": 8.417137417, "qps": 3056.6211201491665, "accuracy": 0.4213272367274183}}
```
```
$ python run_e2e.py hf_t5 -t train
{"device": "cuda", "device_num": 1, "test": "train", "num_examples": 610336, "num_epochs": 3, "batch_size": 32, "result": {"latency": 141.87018556799998, "qps": 12906.221223784734, "accuracy": 27.662052905235683}}
```
Pull Request resolved: https://github.com/pytorch/benchmark/pull/1356
Reviewed By: yanboliang
Differential Revision: D42348124
Pulled By: xuzhao9
fbshipit-source-id: 9064751bb6cbd01d133c12bcbfd142b255ac078b
