[SR] Add runtime check to correct bad schema alias info (#67825)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67825
The comment explains how it works.
Test Plan:
A small regression to local and local_ro if we only enable it for fallback ops.
```
## local_ro
# before
I1103 21:25:05.250440 2636751 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.22213. Iters per second: 818.247
I1103 21:25:08.629221 2636751 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.22351. Iters per second: 817.319
I1103 21:25:12.005179 2636751 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.22285. Iters per second: 817.759
I1103 21:25:12.005236 2636751 PyTorchPredictorBenchLib.cpp:285] Mean milliseconds per iter: 1.22283, standard deviation: 0.000693619
# after
# # only enable for fall back ops: 0.7%
I1103 21:26:40.190436 2644597 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.22928. Iters per second: 813.481
I1103 21:26:43.590443 2644597 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.23265. Iters per second: 811.262
I1103 21:26:46.992928 2644597 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.23379. Iters per second: 810.51
I1103 21:26:46.992980 2644597 PyTorchPredictorBenchLib.cpp:285] Mean milliseconds per iter: 1.23191, standard deviation: 0.0023424
# enable for all (no clone): 4.7%
I1103 21:27:55.291216 2649780 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.28204. Iters per second: 780.005
I1103 21:27:58.822347 2649780 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.27854. Iters per second: 782.14
I1103 21:28:02.354184 2649780 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 1.27958. Iters per second: 781.506
I1103 21:28:02.354240 2649780 PyTorchPredictorBenchLib.cpp:285] Mean milliseconds per iter: 1.28006, standard deviation: 0.00179765
# local
# before
I1103 21:52:00.784718 2765168 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.676. Iters per second: 50.8233
I1103 21:52:28.985873 2765168 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.699. Iters per second: 50.7641
I1103 21:52:57.200223 2765168 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.6953. Iters per second: 50.7735
I1103 21:52:57.200273 2765168 PyTorchPredictorBenchLib.cpp:285] Mean milliseconds per iter: 19.6901, standard deviation: 0.0123206
# after
# # only enable for fall back ops: 0.1%
I1103 21:45:25.514535 2734440 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.7103. Iters per second: 50.7349
I1103 21:45:53.773594 2734440 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.7005. Iters per second: 50.7601
I1103 21:46:21.955680 2734440 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.7398. Iters per second: 50.659
I1103 21:46:21.955729 2734440 PyTorchPredictorBenchLib.cpp:285] Mean milliseconds per iter: 19.7169, standard deviation: 0.0204658
# enable for all (no clone): 0.9%
I1103 21:43:22.162272 2723868 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.8893. Iters per second: 50.2783
I1103 21:43:50.651847 2723868 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.8566. Iters per second: 50.3611
I1103 21:44:19.068519 2723868 PyTorchPredictorBenchLib.cpp:274] PyTorch run finished. Milliseconds per iter: 19.8793. Iters per second: 50.3037
I1103 21:44:19.068570 2723868 PyTorchPredictorBenchLib.cpp:285] Mean milliseconds per iter: 19.875, standard deviation: 0.0167498
```
Reviewed By: d1jang
Differential Revision: D32124812
fbshipit-source-id: 0f60c26f8fb338d347e4ca7a70b23e5a386fc9aa