pytorch

b10761d8 - fix type stub errors (#33762)

fix type stub errors (#33762) Summary: I've been using pytorch with type hintings, and I found errors that can be easily fixed. So I'm creating this PR to fix type bugs. I expected below code should be type-checked without any errors. ```python import torch from torch.nn import Linear from torch.autograd import Variable from torch.optim import AdamW from torch.utils import hooks # nn.Module should have training attribute module = Linear(10, 20) module.training # torch should have dtype bfloat16 tensor2 = torch.tensor([1,2,3], dtype=torch.bfloat16) # torch.Tensor.cuda should accept int or str value torch.randn(5).cuda(1) torch.tensor(5).cuda('cuda:0') # optimizer should have default attribute module = Linear(10, 20) print(AdamW(module.weight).default) # torch.Tensor should have these boolean attributes torch.tensor([1]).is_sparse torch.tensor([1]).is_quantized torch.tensor([1]).is_mkldnn # Size class should tuple of int a, b = torch.tensor([[1,2,3]]).size() # check modules can be accessed torch.nn.parallel torch.autograd.profiler torch.multiprocessing torch.sparse torch.onnx torch.jit torch.hub torch.random torch.distributions torch.quantization torch.__config__ torch.__future__ torch.ops torch.classes # Variable class's constructor should return Tensor def fn_to_test_variable(t: torch.Tensor): return None v = Variable(torch.tensor(1)) fn_to_test_variable(v) # check RemovableHandle attributes can be accessed handle = hooks.RemovableHandle({}) handle.id handle.next_id # check torch function hints torch.is_grad_enabled() ``` But current master branch raises errors. (I checked with pyright) ``` $ pyright test.py Searching for source files Found 1 source file test.py 12:45 - error: 'bfloat16' is not a known member of module 15:21 - error: Argument of type 'Literal[1]' cannot be assigned to parameter 'device' of type 'Optional[device]' 'int' is incompatible with 'device' Cannot assign to 'None' 16:22 - error: Argument of type 'Literal['cuda:0']' cannot be assigned to parameter 'device' of type 'Optional[device]' 'str' is incompatible with 'device' Cannot assign to 'None' 23:19 - error: Cannot access member 'is_sparse' for type 'Tensor' Member 'is_sparse' is unknown 24:19 - error: Cannot access member 'is_quantized' for type 'Tensor' Member 'is_quantized' is unknown 25:19 - error: Cannot access member 'is_mkldnn' for type 'Tensor' Member 'is_mkldnn' is unknown 32:7 - error: 'autograd' is not a known member of module 33:7 - error: 'multiprocessing' is not a known member of module 34:7 - error: 'sparse' is not a known member of module 35:7 - error: 'onnx' is not a known member of module 36:7 - error: 'jit' is not a known member of module 37:7 - error: 'hub' is not a known member of module 38:7 - error: 'random' is not a known member of module 39:7 - error: 'distributions' is not a known member of module 40:7 - error: 'quantization' is not a known member of module 41:7 - error: '__config__' is not a known member of module 42:7 - error: '__future__' is not a known member of module 44:7 - error: 'ops' is not a known member of module 45:7 - error: 'classes' is not a known member of module 60:7 - error: 'is_grad_enabled' is not a known member of module 20 errors, 0 warnings Completed in 1.436sec ``` and below list is not checked as errors, but I think these are errors too. * `nn.Module.training` is not boolean * return type of `torch.Tensor.size()` is `Tuple[Unknown]`. --- related issues. https://github.com/pytorch/pytorch/issues/23731, https://github.com/pytorch/pytorch/issues/32824, https://github.com/pytorch/pytorch/issues/31753 Pull Request resolved: https://github.com/pytorch/pytorch/pull/33762 Differential Revision: D20118884 Pulled By: albanD fbshipit-source-id: 41557d66674a11b8e7503a48476d4cdd0f278eab