Missing type hints cause falsely detected return type

[twsl]

🐛 Describe the bug

The return type is automatically assumed as BoundingBoxes | Any by pyright

vision/torchvision/tv_tensors/__init__.py

Lines 14 to 15 in d3beb52

	@torch.compiler.disable
	def wrap(wrappee, *, like, **kwargs):

This could easily be fixed

Versions

Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

OS: Debian GNU/Linux 12 (bookworm) (x86_64)
GCC version: (Debian 12.2.0-14) 12.2.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.36

Python version: 3.11.10 (main, Sep 27 2024, 06:09:18) [GCC 12.2.0] (64-bit runtime)
Python platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.36
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      46 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             12
On-line CPU(s) list:                0-11
Vendor ID:                          GenuineIntel
Model name:                         12th Gen Intel(R) Core(TM) i7-1265U
CPU family:                         6
Model:                              154
Thread(s) per core:                 2
Core(s) per socket:                 6
Socket(s):                          1
Stepping:                           4
BogoMIPS:                           5375.88
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology tsc_reliable nonstop_tsc cpuid pni pclmulqdq vmx ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves avx_vnni umip waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize flush_l1d arch_capabilities
Virtualization:                     VT-x
Hypervisor vendor:                  Microsoft
Virtualization type:                full
L1d cache:                          288 KiB (6 instances)
L1i cache:                          192 KiB (6 instances)
L2 cache:                           7.5 MiB (6 instances)
L3 cache:                           12 MiB (1 instance)
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Not affected
Vulnerability Mds:                  Not affected
Vulnerability Meltdown:             Not affected
Vulnerability Mmio stale data:      Not affected
Vulnerability Retbleed:             Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] numpy==2.2.0
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pytorch-lightning==2.5.0.post0
[pip3] pytorchcocotools==0.0.0
[pip3] torch==2.5.1
[pip3] torchmetrics==1.6.0
[pip3] torchvision==0.20.1
[pip3] triton==3.1.0
[conda] Could not collect

[twsl]

Any chance to get the pr merged soon?

[NicolasHug]

Thanks for the report @twsl - Just pasting my comment from #8830 (comment)

Sorry folks, I don't think I can merge this. Mypy is painful enough to please (and I'll probably have to disable it entirely anyway), but I just really don't have any bandwidth to support all type-checkers out there :/

[twsl]

@NicolasHug I really don't understand your comment tho, cause this would help dealing with mypy, regardless of other type-checkers, as the current implementation is lacking all type hints.

[NicolasHug]

cause this would help dealing with mypy, regardless of other type-checkers

I wish it would be that simple, but it's not. Some type checkers are happy with some annotations, while others are not. For example, mypy fails on your PR: https://github.com/pytorch/vision/actions/runs/13437322523/job/37542714033?pr=8830

I'm really sorry, but I have no bandwidth to deal with different type checkers. In fact I don't recommend rely on torchvision's type annotations at all, because a lot of them are wrong. They exist for torchscript to work, but they are often pretty incorrect.

[twsl]

Well, I do understand and share your frustration with mypy. However, given that my PR provides the correct implementation of the typehints and they are valuable for torchscript and other causes, i think we should still strive to merge it. I'll try to figure out, if mypy's wrong behaviour can be fixed and hope you will reconsider then (edit: at least it passes now)