Migrate neg's CUDA implementation to ATen. (#23617)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23617
Doesn't seem to cause any performance regression. Performance difference
in the benchmarks is negligible.
Benchmark script:
```python
import timeit
for n, t in [(10, 100000),
(1000, 10000)]:
print('a.neg() (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', 'torch.float', 'torch.double') + (('torch.half',) if device == 'cuda' else ()):
print(f'device: {device}, dtype: {dtype}, {t} times', end='\t\t')
print(timeit.timeit(f'a.neg()\nif "{device}" == "cuda": torch.cuda.synchronize()', setup=f'import torch; a = torch.ones({n}, device="{device}", dtype={dtype})', number=t))
```
Before:
```
a.neg() (a.numel() == 10) for 100000 times
device: cpu, dtype: torch.int8, 100000 times 2.5537249100016197
device: cpu, dtype: torch.uint8, 100000 times 2.512518662999355
device: cpu, dtype: torch.int16, 100000 times 2.548207502000878
device: cpu, dtype: torch.int32, 100000 times 2.5974994509997487
device: cpu, dtype: torch.int64, 100000 times 2.6533011499996064
device: cpu, dtype: torch.float, 100000 times 2.6474813019995054
device: cpu, dtype: torch.double, 100000 times 2.6949866009999823
device: cuda, dtype: torch.int8, 100000 times 5.820120684998983
device: cuda, dtype: torch.uint8, 100000 times 5.732108927997615
device: cuda, dtype: torch.int16, 100000 times 5.791249125999457
device: cuda, dtype: torch.int32, 100000 times 5.816761754998879
device: cuda, dtype: torch.int64, 100000 times 5.935873205999087
device: cuda, dtype: torch.float, 100000 times 6.276509613999224
device: cuda, dtype: torch.double, 100000 times 6.122782447000645
device: cuda, dtype: torch.half, 100000 times 6.161522764999972
a.neg() (a.numel() == 1000) for 10000 times
device: cpu, dtype: torch.int8, 10000 times 0.3766637519984215
device: cpu, dtype: torch.uint8, 10000 times 0.37288786600038293
device: cpu, dtype: torch.int16, 10000 times 0.3485262310023245
device: cpu, dtype: torch.int32, 10000 times 0.41810554200128536
device: cpu, dtype: torch.int64, 10000 times 0.5609612200023548
device: cpu, dtype: torch.float, 10000 times 0.39054008099992643
device: cpu, dtype: torch.double, 10000 times 0.4946578170020075
device: cuda, dtype: torch.int8, 10000 times 0.5843639539998549
device: cuda, dtype: torch.uint8, 10000 times 0.5780841570012853
device: cuda, dtype: torch.int16, 10000 times 0.5819949180004187
device: cuda, dtype: torch.int32, 10000 times 0.5827294059999986
device: cuda, dtype: torch.int64, 10000 times 0.5861426519986708
device: cuda, dtype: torch.float, 10000 times 0.5929420489992481
device: cuda, dtype: torch.double, 10000 times 0.594638443999429
device: cuda, dtype: torch.half, 10000 times 0.5903799709994928
```
After:
```
a.neg() (a.numel() == 10) for 100000 times
device: cpu, dtype: torch.int8, 100000 times 2.4983287129980454
device: cpu, dtype: torch.uint8, 100000 times 2.479393904999597
device: cpu, dtype: torch.int16, 100000 times 2.5382055320005747
device: cpu, dtype: torch.int32, 100000 times 2.5587980189993687
device: cpu, dtype: torch.int64, 100000 times 2.637738788002025
device: cpu, dtype: torch.float, 100000 times 2.602799075997609
device: cpu, dtype: torch.double, 100000 times 2.6648931070012623
device: cuda, dtype: torch.int8, 100000 times 5.793338211999071
device: cuda, dtype: torch.uint8, 100000 times 5.782462584000314
device: cuda, dtype: torch.int16, 100000 times 5.824340334998851
device: cuda, dtype: torch.int32, 100000 times 5.851659068001027
device: cuda, dtype: torch.int64, 100000 times 5.8898071570001775
device: cuda, dtype: torch.float, 100000 times 5.913144636000652
device: cuda, dtype: torch.double, 100000 times 5.963339805999567
device: cuda, dtype: torch.half, 100000 times 5.87889370099947
a.neg() (a.numel() == 1000) for 10000 times
device: cpu, dtype: torch.int8, 10000 times 0.37244726499920944
device: cpu, dtype: torch.uint8, 10000 times 0.36641623199830065
device: cpu, dtype: torch.int16, 10000 times 0.3449854829996184
device: cpu, dtype: torch.int32, 10000 times 0.4127863069988962
device: cpu, dtype: torch.int64, 10000 times 0.5551902160004829
device: cpu, dtype: torch.float, 10000 times 0.38593814199703047
device: cpu, dtype: torch.double, 10000 times 0.48877579500185675
device: cuda, dtype: torch.int8, 10000 times 0.5862828740027908
device: cuda, dtype: torch.uint8, 10000 times 0.5836667540024791
device: cuda, dtype: torch.int16, 10000 times 0.5918155769977602
device: cuda, dtype: torch.int32, 10000 times 0.5961457039993547
device: cuda, dtype: torch.int64, 10000 times 0.5963898690024507
device: cuda, dtype: torch.float, 10000 times 0.5985483309996198
device: cuda, dtype: torch.double, 10000 times 0.6027148480025062
device: cuda, dtype: torch.half, 10000 times 0.5961164370019105
```
Test Plan: Imported from OSS
Differential Revision: D16617574
Pulled By: ezyang
fbshipit-source-id: c90aa410f6385ce94fe6b84ebeceffa5effd0267
