🐛 Describe the bug

As discussed in #114755 , torch script has added support for the union type introduced in python 3.10, however, I find when "-O" added to the python command line, it fails sometimes, for example:

import torch


class B(torch.nn.Module):

    def __init__(self) -> None:
        super().__init__()

    def forward(
        self,
        x: torch.Tensor,
        cache: list[tuple[torch.Tensor, torch.Tensor]] | None,
    ) -> tuple[torch.Tensor, list[tuple[torch.Tensor, torch.Tensor]]]:
        return x, []


class C(torch.nn.Module):

    def __init__(self,) -> None:
        super().__init__()
        self.b: torch.nn.Module = B()

    @torch.jit.export
    def forward(self, x: torch.Tensor) -> torch.Tensor:
        result, _ = self.b(x, None)
        return result


c1 = C()
c2 = torch.jit.script(c1)

Save the above code to a file named test.py, and run python test.py works well, but python -O test.py failed with error message:

Traceback (most recent call last):
  File "/home/hzhangxyz/Cloud/Desktop/qmb/test.py", line 30, in <module>
    c2 = torch.jit.script(c1)
  File "/home/hzhangxyz/Cloud/Desktop/qmb/env/lib/python3.13/site-packages/torch/jit/_script.py", line 1429, in script
    ret = _script_impl(
        obj=obj,
    ...<3 lines>...
        example_inputs=example_inputs,
    )
  File "/home/hzhangxyz/Cloud/Desktop/qmb/env/lib/python3.13/site-packages/torch/jit/_script.py", line 1147, in _script_impl
    return torch.jit._recursive.create_script_module(
           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
        obj, torch.jit._recursive.infer_methods_to_compile
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/hzhangxyz/Cloud/Desktop/qmb/env/lib/python3.13/site-packages/torch/jit/_recursive.py", line 557, in create_script_module
    return create_script_module_impl(nn_module, concrete_type, stubs_fn)
  File "/home/hzhangxyz/Cloud/Desktop/qmb/env/lib/python3.13/site-packages/torch/jit/_recursive.py", line 634, in create_script_module_impl
    create_methods_and_properties_from_stubs(
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
        concrete_type, method_stubs, property_stubs
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/hzhangxyz/Cloud/Desktop/qmb/env/lib/python3.13/site-packages/torch/jit/_recursive.py", line 466, in create_methods_and_properties_from_stubs
    concrete_type._create_methods_and_properties(
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
        property_defs, property_rcbs, method_defs, method_rcbs, method_defaults
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
RuntimeError:

forward(__torch__.B self, Tensor x, (Tensor, Tensor)[] cache) -> ((Tensor, (Tensor, Tensor)[])):
Expected a value of type 'Tuple[Tensor, Tensor]' for argument '<varargs>' but instead found type 'NoneType'.
:
  File "/home/hzhangxyz/Cloud/Desktop/qmb/test.py", line 25
    @torch.jit.export
    def forward(self, x: torch.Tensor) -> torch.Tensor:
        result, _ = self.b(x, None)
                    ~~~~~~ <--- HERE
        return result

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: Arch Linux (x86_64)
GCC version: (GCC) 14.2.1 20250207
Clang version: 19.1.7
CMake version: version 3.31.6
Libc version: glibc-2.41

Python version: 3.13.2 (main, Feb 5 2025, 08:05:21) [GCC 14.2.1 20250128] (64-bit runtime)
Python platform: Linux-6.6.59-1-lts-x86_64-with-glibc2.41
Is CUDA available: True
CUDA runtime version: 12.8.61
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3060
Nvidia driver version: 565.57.01
cuDNN version: Could not collect
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: 39 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) i5-12400F
CPU family: 6
Model: 151
Thread(s) per core: 2
Core(s) per socket: 6
Socket(s): 1
Stepping: 5
CPU(s) scaling MHz: 89%
CPU max MHz: 4400.0000
CPU min MHz: 800.0000
BogoMIPS: 4993.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr ibt flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 288 KiB (6 instances)
L1i cache: 192 KiB (6 instances)
L2 cache: 7.5 MiB (6 instances)
L3 cache: 18 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-11
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 Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] mypy==1.14.1
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[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] torch==2.5.1
[conda] Could not collect

cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel