Add op bitwise_or (#31559)
Summary:
ezyang , this PR add bitwise_or operator as https://github.com/pytorch/pytorch/pull/31104 .
Benchmark script :
```
import timeit
import torch
torch.manual_seed(1)
for n, t in [(10, 100000),(1000, 10000)]:
print('__or__ (a.numel() == {}) for {} times'.format(n, t))
for device in ('cpu', 'cuda'):
for dtype in ('torch.int8', 'torch.uint8', 'torch.int16', 'torch.int32', 'torch.int64'):
print(f'device: {device}, dtype: {dtype}, {t} times', end='\t\t')
print(timeit.timeit(f'a | b\nif "{device}" == "cuda": torch.cuda.synchronize()', setup=f'import torch; a = torch.randint(0, 10, ({n},), dtype = {dtype}, device="{device}"); b = torch.randint(0, 10, ({n},), dtype = {dtype}, device="{device}")', number=t))
for n, t in [(10, 100000),(1000, 10000)]:
print('__ior__ (a.numel() == {}) for {} times'.format(n, t))
for device in ('cpu', 'cuda'):
for dtype in ('torch.int8', 'torch.uint8', 'torch.int16', 'torch.int32', 'torch.int64'):
print(f'device: {device}, dtype: {dtype}, {t} times', end='\t\t')
print(timeit.timeit(f'a | b\nif "{device}" == "cuda": torch.cuda.synchronize()', setup=f'import torch; a = torch.randint(0, 10, ({n},), dtype = {dtype}, device="{device}"); b = torch.tensor(5, dtype = {dtype}, device="{device}")', number=t))
```
Device: **Tesla P100, skx-8180**
Cuda verison: **9.0.176**
Before:
```
__or__ (a.numel() == 10) for 100000 times
device: cpu, dtype: torch.int8, 100000 times 0.17616272252053022
device: cpu, dtype: torch.uint8, 100000 times 0.17148233391344547
device: cpu, dtype: torch.int16, 100000 times 0.17616403382271528
device: cpu, dtype: torch.int32, 100000 times 0.17717823758721352
device: cpu, dtype: torch.int64, 100000 times 0.1801931718364358
device: cuda, dtype: torch.int8, 100000 times 1.270583058707416
device: cuda, dtype: torch.uint8, 100000 times 1.2636413089931011
device: cuda, dtype: torch.int16, 100000 times 1.2839747751131654
device: cuda, dtype: torch.int32, 100000 times 1.2548385225236416
device: cuda, dtype: torch.int64, 100000 times 1.2650810535997152
__or__ (a.numel() == 1000) for 10000 times
device: cpu, dtype: torch.int8, 10000 times 0.031136621721088886
device: cpu, dtype: torch.uint8, 10000 times 0.030786747112870216
device: cpu, dtype: torch.int16, 10000 times 0.02391665056347847
device: cpu, dtype: torch.int32, 10000 times 0.024147341027855873
device: cpu, dtype: torch.int64, 10000 times 0.024414129555225372
device: cuda, dtype: torch.int8, 10000 times 0.12741921469569206
device: cuda, dtype: torch.uint8, 10000 times 0.1249831635504961
device: cuda, dtype: torch.int16, 10000 times 0.1283819805830717
device: cuda, dtype: torch.int32, 10000 times 0.12591975275427103
device: cuda, dtype: torch.int64, 10000 times 0.12655890546739101
__ior__ (a.numel() == 10) for 100000 times
device: cpu, dtype: torch.int8, 100000 times 0.3908365070819855
device: cpu, dtype: torch.uint8, 100000 times 0.38267823681235313
device: cpu, dtype: torch.int16, 100000 times 0.38239253498613834
device: cpu, dtype: torch.int32, 100000 times 0.3817988149821758
device: cpu, dtype: torch.int64, 100000 times 0.3901665909215808
device: cuda, dtype: torch.int8, 100000 times 1.4211318120360374
device: cuda, dtype: torch.uint8, 100000 times 1.4215159295126796
device: cuda, dtype: torch.int16, 100000 times 1.4307750314474106
device: cuda, dtype: torch.int32, 100000 times 1.4123614141717553
device: cuda, dtype: torch.int64, 100000 times 1.4480243818834424
__ior__ (a.numel() == 1000) for 10000 times
device: cpu, dtype: torch.int8, 10000 times 0.06468924414366484
device: cpu, dtype: torch.uint8, 10000 times 0.06442475505173206
device: cpu, dtype: torch.int16, 10000 times 0.05267547257244587
device: cpu, dtype: torch.int32, 10000 times 0.05286940559744835
device: cpu, dtype: torch.int64, 10000 times 0.06211103219538927
device: cuda, dtype: torch.int8, 10000 times 0.15332304500043392
device: cuda, dtype: torch.uint8, 10000 times 0.15353196952492
device: cuda, dtype: torch.int16, 10000 times 0.15300503931939602
device: cuda, dtype: torch.int32, 10000 times 0.15274472255259752
device: cuda, dtype: torch.int64, 10000 times 0.1512152962386608
```
After:
```
__or__ (a.numel() == 10) for 100000 times
device: cpu, dtype: torch.int8, 100000 times 0.2465507509186864
device: cpu, dtype: torch.uint8, 100000 times 0.2472386620938778
device: cpu, dtype: torch.int16, 100000 times 0.2469814233481884
device: cpu, dtype: torch.int32, 100000 times 0.2535214088857174
device: cpu, dtype: torch.int64, 100000 times 0.24855613708496094
device: cuda, dtype: torch.int8, 100000 times 1.4351346511393785
device: cuda, dtype: torch.uint8, 100000 times 1.4434308474883437
device: cuda, dtype: torch.int16, 100000 times 1.4520929995924234
device: cuda, dtype: torch.int32, 100000 times 1.4456610176712275
device: cuda, dtype: torch.int64, 100000 times 1.4580101007595658
__or__ (a.numel() == 1000) for 10000 times
device: cpu, dtype: torch.int8, 10000 times 0.029985425993800163
device: cpu, dtype: torch.uint8, 10000 times 0.03024935908615589
device: cpu, dtype: torch.int16, 10000 times 0.026356655173003674
device: cpu, dtype: torch.int32, 10000 times 0.027377349324524403
device: cpu, dtype: torch.int64, 10000 times 0.029163731262087822
device: cuda, dtype: torch.int8, 10000 times 0.14540370367467403
device: cuda, dtype: torch.uint8, 10000 times 0.1456305105239153
device: cuda, dtype: torch.int16, 10000 times 0.1450125053524971
device: cuda, dtype: torch.int32, 10000 times 0.1472016740590334
device: cuda, dtype: torch.int64, 10000 times 0.14709716010838747
__ior__ (a.numel() == 10) for 100000 times
device: cpu, dtype: torch.int8, 100000 times 0.27195510920137167
device: cpu, dtype: torch.uint8, 100000 times 0.2692424338310957
device: cpu, dtype: torch.int16, 100000 times 0.27726674638688564
device: cpu, dtype: torch.int32, 100000 times 0.2815811652690172
device: cpu, dtype: torch.int64, 100000 times 0.2852728571742773
device: cuda, dtype: torch.int8, 100000 times 1.4743850827217102
device: cuda, dtype: torch.uint8, 100000 times 1.4766502184793353
device: cuda, dtype: torch.int16, 100000 times 1.4774163831025362
device: cuda, dtype: torch.int32, 100000 times 1.4749693805351853
device: cuda, dtype: torch.int64, 100000 times 1.5772947426885366
__ior__ (a.numel() == 1000) for 10000 times
device: cpu, dtype: torch.int8, 10000 times 0.03614502027630806
device: cpu, dtype: torch.uint8, 10000 times 0.03619729354977608
device: cpu, dtype: torch.int16, 10000 times 0.0319912089034915
device: cpu, dtype: torch.int32, 10000 times 0.03319283854216337
device: cpu, dtype: torch.int64, 10000 times 0.0343862259760499
device: cuda, dtype: torch.int8, 10000 times 0.1581476852297783
device: cuda, dtype: torch.uint8, 10000 times 0.15974601730704308
device: cuda, dtype: torch.int16, 10000 times 0.15957212820649147
device: cuda, dtype: torch.int32, 10000 times 0.16002820804715157
device: cuda, dtype: torch.int64, 10000 times 0.16129320487380028
```
Fix https://github.com/pytorch/pytorch/issues/24511, https://github.com/pytorch/pytorch/issues/24515, https://github.com/pytorch/pytorch/issues/24658, https://github.com/pytorch/pytorch/issues/24662.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31559
Differential Revision: D19315875
Pulled By: ezyang
fbshipit-source-id: 4a3ca88fdafbeb796079687e676228111eb44aad
