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b47e9b97a2
Summary: Refer to https://github.com/pytorch/pytorch/pull/25665, add `bitwise_and` operator. Benchmark script : ``` import timeit #for __and__ for n, t in [(10, 100000),(1000, 10000)]: print('__and__ (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 __iand__ for n, t in [(10, 100000),(1000, 10000)]: print('__iand__ (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: ``` __and__ (a.numel() == 10) for 100000 times device: cpu, dtype: torch.int8, 100000 times 0.1766007635742426 device: cpu, dtype: torch.uint8, 100000 times 0.17322628945112228 device: cpu, dtype: torch.int16, 100000 times 0.17650844901800156 device: cpu, dtype: torch.int32, 100000 times 0.17711848113685846 device: cpu, dtype: torch.int64, 100000 times 0.18240160401910543 device: cuda, dtype: torch.int8, 100000 times 1.273967768996954 device: cuda, dtype: torch.uint8, 100000 times 1.2778537990525365 device: cuda, dtype: torch.int16, 100000 times 1.2753686187788844 device: cuda, dtype: torch.int32, 100000 times 1.2797665279358625 device: cuda, dtype: torch.int64, 100000 times 1.2933144550770521 __and__ (a.numel() == 1000) for 10000 times device: cpu, dtype: torch.int8, 10000 times 0.031139614060521126 device: cpu, dtype: torch.uint8, 10000 times 0.03091452084481716 device: cpu, dtype: torch.int16, 10000 times 0.022756479680538177 device: cpu, dtype: torch.int32, 10000 times 0.025045674294233322 device: cpu, dtype: torch.int64, 10000 times 0.024164282716810703 device: cuda, dtype: torch.int8, 10000 times 0.12820732593536377 device: cuda, dtype: torch.uint8, 10000 times 0.12775669433176517 device: cuda, dtype: torch.int16, 10000 times 0.12697868794202805 device: cuda, dtype: torch.int32, 10000 times 0.12832533661276102 device: cuda, dtype: torch.int64, 10000 times 0.1280576130375266 __iand__ (a.numel() == 10) for 100000 times device: cpu, dtype: torch.int8, 100000 times 0.3687064303085208 device: cpu, dtype: torch.uint8, 100000 times 0.36253443732857704 device: cpu, dtype: torch.int16, 100000 times 0.362891579978168 device: cpu, dtype: torch.int32, 100000 times 0.37680106051266193 device: cpu, dtype: torch.int64, 100000 times 0.3689364707097411 device: cuda, dtype: torch.int8, 100000 times 1.419940729625523 device: cuda, dtype: torch.uint8, 100000 times 1.4247053815051913 device: cuda, dtype: torch.int16, 100000 times 1.4191444097086787 device: cuda, dtype: torch.int32, 100000 times 1.4305962566286325 device: cuda, dtype: torch.int64, 100000 times 1.4567416654899716 __iand__ (a.numel() == 1000) for 10000 times device: cpu, dtype: torch.int8, 10000 times 0.06224383972585201 device: cpu, dtype: torch.uint8, 10000 times 0.06205617543309927 device: cpu, dtype: torch.int16, 10000 times 0.05016433447599411 device: cpu, dtype: torch.int32, 10000 times 0.05216377507895231 device: cpu, dtype: torch.int64, 10000 times 0.06139362137764692 device: cuda, dtype: torch.int8, 10000 times 0.14827249851077795 device: cuda, dtype: torch.uint8, 10000 times 0.14801877550780773 device: cuda, dtype: torch.int16, 10000 times 0.14952312968671322 device: cuda, dtype: torch.int32, 10000 times 0.14999118447303772 device: cuda, dtype: torch.int64, 10000 times 0.14951884001493454 ``` After: ``` __and__ (a.numel() == 10) for 100000 times device: cpu, dtype: torch.int8, 100000 times 0.23157884553074837 device: cpu, dtype: torch.uint8, 100000 times 0.23063660878688097 device: cpu, dtype: torch.int16, 100000 times 0.23005440644919872 device: cpu, dtype: torch.int32, 100000 times 0.23748818412423134 device: cpu, dtype: torch.int64, 100000 times 0.24106105230748653 device: cuda, dtype: torch.int8, 100000 times 1.4394256137311459 device: cuda, dtype: torch.uint8, 100000 times 1.4436759827658534 device: cuda, dtype: torch.int16, 100000 times 1.4631587155163288 device: cuda, dtype: torch.int32, 100000 times 1.459101552143693 device: cuda, dtype: torch.int64, 100000 times 1.4784048134461045 __and__ (a.numel() == 1000) for 10000 times device: cpu, dtype: torch.int8, 10000 times 0.028442862443625927 device: cpu, dtype: torch.uint8, 10000 times 0.028130197897553444 device: cpu, dtype: torch.int16, 10000 times 0.025318274274468422 device: cpu, dtype: torch.int32, 10000 times 0.02519288007169962 device: cpu, dtype: torch.int64, 10000 times 0.028299466706812382 device: cuda, dtype: torch.int8, 10000 times 0.14342594426125288 device: cuda, dtype: torch.uint8, 10000 times 0.145280827768147 device: cuda, dtype: torch.int16, 10000 times 0.14673697855323553 device: cuda, dtype: torch.int32, 10000 times 0.14499565307050943 device: cuda, dtype: torch.int64, 10000 times 0.14582364354282618 __iand__ (a.numel() == 10) for 100000 times device: cpu, dtype: torch.int8, 100000 times 0.25548241566866636 device: cpu, dtype: torch.uint8, 100000 times 0.2552562616765499 device: cpu, dtype: torch.int16, 100000 times 0.25905191246420145 device: cpu, dtype: torch.int32, 100000 times 0.26635489892214537 device: cpu, dtype: torch.int64, 100000 times 0.26269810926169157 device: cuda, dtype: torch.int8, 100000 times 1.485458506271243 device: cuda, dtype: torch.uint8, 100000 times 1.4742380809038877 device: cuda, dtype: torch.int16, 100000 times 1.507783885113895 device: cuda, dtype: torch.int32, 100000 times 1.4926990242674947 device: cuda, dtype: torch.int64, 100000 times 1.519851053133607 __iand__ (a.numel() == 1000) for 10000 times device: cpu, dtype: torch.int8, 10000 times 0.03425929415971041 device: cpu, dtype: torch.uint8, 10000 times 0.03293587639927864 device: cpu, dtype: torch.int16, 10000 times 0.029559112153947353 device: cpu, dtype: torch.int32, 10000 times 0.030915481969714165 device: cpu, dtype: torch.int64, 10000 times 0.03292469773441553 device: cuda, dtype: torch.int8, 10000 times 0.15792148280888796 device: cuda, dtype: torch.uint8, 10000 times 0.16000914946198463 device: cuda, dtype: torch.int16, 10000 times 0.1600684942677617 device: cuda, dtype: torch.int32, 10000 times 0.16162546630948782 device: cuda, dtype: torch.int64, 10000 times 0.1629159888252616 ``` Fix https://github.com/pytorch/pytorch/issues/24508, https://github.com/pytorch/pytorch/issues/24509, https://github.com/pytorch/pytorch/issues/24655, https://github.com/pytorch/pytorch/issues/24656. Pull Request resolved: https://github.com/pytorch/pytorch/pull/31104 Differential Revision: D18938930 Pulled By: VitalyFedyunin fbshipit-source-id: a77e805a0b84e8ace16c6e648c2f67dad44f2e44 |
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| .. | ||
| _static | ||
| _templates | ||
| community | ||
| notes | ||
| org/pytorch | ||
| scripts | ||
| __config__.rst | ||
| autograd.rst | ||
| bottleneck.rst | ||
| checkpoint.rst | ||
| conf.py | ||
| cpp_extension.rst | ||
| cuda_deterministic_backward.rst | ||
| cuda_deterministic.rst | ||
| cuda.rst | ||
| cudnn_deterministic.rst | ||
| cudnn_persistent_rnn.rst | ||
| data.rst | ||
| distributed.rst | ||
| distributions.rst | ||
| dlpack.rst | ||
| hub.rst | ||
| index.rst | ||
| jit_builtin_functions.rst | ||
| jit_language_reference.rst | ||
| jit_python_reference.rst | ||
| jit_unsupported.rst | ||
| jit.rst | ||
| math-quantizer-equation.png | ||
| model_zoo.rst | ||
| multiprocessing.rst | ||
| name_inference.rst | ||
| named_tensor.rst | ||
| nn.functional.rst | ||
| nn.init.rst | ||
| nn.rst | ||
| onnx.rst | ||
| optim.rst | ||
| packages.rst | ||
| quantization.rst | ||
| random.rst | ||
| rpc.rst | ||
| sparse.rst | ||
| storage.rst | ||
| tensor_attributes.rst | ||
| tensorboard.rst | ||
| tensors.rst | ||
| torch.rst | ||
| type_info.rst | ||
