Repository: pytorch
Issue: Segmentation fault (core dumped) in `_fft_r2c`
Labels: module: error checking,triaged,module: edge cases,topic: fuzzer

### 🐛 Describe the bug

Under specific inputs, `_fft_r2c` triggered a crash.
```python
import torch

self = torch.full((10, 10, 10,), 9.0072e+15, dtype=torch.double)
dim = [4194304]
normalization = 4
onesided = False
torch._fft_r2c(self, dim, normalization, onesided)
```
Output:
```
Segmentation fault (core dumped)
```
ASAN report:
```
=================================================================
==1403775==ERROR: AddressSanitizer: SEGV on unknown address 0x61000220ef88 (pc 0x7f91a3c37f93 bp 0x7ffd781d05a0 sp 0x7ffd781d0200 T0)
==1403775==The signal is caused by a READ memory access.
    #0 0x7f91a3c37f93 in at::native::_fft_r2c_mkl(at::Tensor const&, c10::ArrayRef<long>, long, bool) /mnt/pytorch-2.5.0/aten/src/ATen/native/mkl/SpectralOps.cpp:285
    #1 0x7f91a663a691 in wrapper_CPU___fft_r2c /mnt/pytorch-2.5.0/build/aten/src/ATen/RegisterCPU.cpp:6527
    #2 0x7f91a6a85ebe in operator() /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13
    #3 0x7f91a6a85ebe in call /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:468
    #4 0x7f91a4fb3f68 in at::Tensor c10::callUnboxedKernelFunction<at::Tensor, at::Tensor const&, c10::ArrayRef<long>, long, bool>(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>&&, long&&, bool&&) /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/KernelFunction_impl.h:53
    #5 0x7f91a5d58e60 in at::Tensor c10::KernelFunction::call<at::Tensor, at::Tensor const&, c10::ArrayRef<long>, long, bool>(c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, long, bool) const /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/KernelFunction_impl.h:105
    #6 0x7f91a5d58e60 in at::Tensor c10::Dispatcher::redispatch<at::Tensor, at::Tensor const&, c10::ArrayRef<long>, long, bool>(c10::TypedOperatorHandle<at::Tensor (at::Tensor const&, c10::ArrayRef<long>, long, bool)> const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, long, bool) const /mnt/pytorch-2.5.0/aten/src/ATen/core/dispatch/Dispatcher.h:714
    #7 0x7f91a5a88e4b in c10::TypedOperatorHandle<at::Tensor (at::Tensor const&, c10::ArrayRef<long>, long, bool)>::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, long, bool) const /mnt/pytorch-2.5.0/aten/src/ATen/core/dispatch/Dispatcher.h:536
    #8 0x7f91a5a88e4b in at::_ops::_fft_r2c::redispatch(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, long, bool) /mnt/pytorch-2.5.0/build/aten/src/ATen/Operators_3.cpp:3310
    #9 0x7f91aec97302 in at::redispatch::_fft_r2c(c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, long, bool) /mnt/pytorch-2.5.0/build/aten/src/ATen/RedispatchFunctions.h:3717
    #10 0x7f91ae8b7adb in operator() /mnt/pytorch-2.5.0/torch/csrc/autograd/generated/VariableType_3.cpp:727
    #11 0x7f91ae8b855b in _fft_r2c /mnt/pytorch-2.5.0/torch/csrc/autograd/generated/VariableType_3.cpp:728
    #12 0x7f91aebbc6c9 in operator() /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/impl/WrapFunctionIntoFunctor.h:13
    #13 0x7f91aebbc6c9 in call /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/impl/make_boxed_from_unboxed_functor.h:485
    #14 0x7f91a4fb3f68 in at::Tensor c10::callUnboxedKernelFunction<at::Tensor, at::Tensor const&, c10::ArrayRef<long>, long, bool>(void*, c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>&&, long&&, bool&&) /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/KernelFunction_impl.h:53
    #15 0x7f91a5a8862e in at::Tensor c10::KernelFunction::call<at::Tensor, at::Tensor const&, c10::ArrayRef<long>, long, bool>(c10::OperatorHandle const&, c10::DispatchKeySet, at::Tensor const&, c10::ArrayRef<long>, long, bool) const /mnt/pytorch-2.5.0/aten/src/ATen/core/boxing/KernelFunction_impl.h:105
    #16 0x7f91a5a8862e in at::Tensor c10::Dispatcher::call<at::Tensor, at::Tensor const&, c10::ArrayRef<long>, long, bool>(c10::TypedOperatorHandle<at::Tensor (at::Tensor const&, c10::ArrayRef<long>, long, bool)> const&, at::Tensor const&, c10::ArrayRef<long>, long, bool) const /mnt/pytorch-2.5.0/aten/src/ATen/core/dispatch/Dispatcher.h:698
    #17 0x7f91a5a8862e in c10::TypedOperatorHandle<at::Tensor (at::Tensor const&, c10::ArrayRef<long>, long, bool)>::call(at::Tensor const&, c10::ArrayRef<long>, long, bool) const /mnt/pytorch-2.5.0/aten/src/ATen/core/dispatch/Dispatcher.h:531
    #18 0x7f91a5a8862e in at::_ops::_fft_r2c::call(at::Tensor const&, c10::ArrayRef<long>, long, bool) /mnt/pytorch-2.5.0/build/aten/src/ATen/Operators_3.cpp:3303
    #19 0x7f91e92d7be3 in at::_fft_r2c(at::Tensor const&, c10::ArrayRef<long>, long, bool) /mnt/pytorch-2.5.0/build/aten/src/ATen/ops/_fft_r2c.h:27
    #20 0x7f91e91caa19 in operator() /mnt/pytorch-2.5.0/torch/csrc/autograd/generated/python_torch_functions_1.cpp:3710
    #21 0x7f91e91cb38f in THPVariable__fft_r2c /mnt/pytorch-2.5.0/torch/csrc/autograd/generated/python_torch_functions_1.cpp:3712
    #22 0x56abf2 in cfunction_call /usr/local/src/conda/python-3.13.0/Objects/methodobject.c:540
    #23 0x5341f3 in _PyObject_MakeTpCall /usr/local/src/conda/python-3.13.0/Objects/call.c:242
    #24 0x549ece in _PyEval_EvalFrameDefault /usr/local/src/conda/python-3.13.0/Python/generated_cases.c.h:813
    #25 0x60902d in PyEval_EvalCode /usr/local/src/conda/python-3.13.0/Python/ceval.c:596
    #26 0x62eedc in run_eval_code_obj /usr/local/src/conda/python-3.13.0/Python/pythonrun.c:1323
    #27 0x629d9c in run_mod /usr/local/src/conda/python-3.13.0/Python/pythonrun.c:1408
    #28 0x64888f in pyrun_file /usr/local/src/conda/python-3.13.0/Python/pythonrun.c:1241
    #29 0x6473fa in _PyRun_SimpleFileObject /usr/local/src/conda/python-3.13.0/Python/pythonrun.c:490
    #30 0x64711a in _PyRun_AnyFileObject /usr/local/src/conda/python-3.13.0/Python/pythonrun.c:77
    #31 0x640b66 in pymain_run_file_obj /usr/local/src/conda/python-3.13.0/Modules/main.c:409
    #32 0x640b66 in pymain_run_file /usr/local/src/conda/python-3.13.0/Modules/main.c:428
    #33 0x640b66 in pymain_run_python /usr/local/src/conda/python-3.13.0/Modules/main.c:696
    #34 0x640b66 in Py_RunMain /usr/local/src/conda/python-3.13.0/Modules/main.c:775
    #35 0x5f9508 in Py_BytesMain /usr/local/src/conda/python-3.13.0/Modules/main.c:829
    #36 0x7f91f1b6fd8f  (/lib/x86_64-linux-gnu/libc.so.6+0x29d8f)
    #37 0x7f91f1b6fe3f in __libc_start_main (/lib/x86_64-linux-gnu/libc.so.6+0x29e3f)
    #38 0x5f885c  (/mnt/anaconda3/envs/pytorch-2.3-asan/bin/python3.13+0x5f885c)

AddressSanitizer can not provide additional info.
SUMMARY: AddressSanitizer: SEGV /mnt/pytorch-2.5.0/aten/src/ATen/native/mkl/SpectralOps.cpp:285 in at::native::_fft_r2c_mkl(at::Tensor const&, c10::ArrayRef<long>, long, bool)
==1403775==ABORTING
```

### Versions

PyTorch version: 2.5.0a0+git32f585d
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.13.0 | packaged by Anaconda, Inc. | (main, Oct 7 2024, 21:29:38) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
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): 80
On-line CPU(s) list: 0-79
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Gold 5218R CPU @ 2.10GHz
CPU family: 6
Model: 85
Thread(s) per core: 2
Core(s) per socket: 20
Socket(s): 2
Stepping: 7
CPU max MHz: 4000.0000
CPU min MHz: 800.0000
BogoMIPS: 4200.00
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 pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 1.3 MiB (40 instances)
L1i cache: 1.3 MiB (40 instances)
L2 cache: 40 MiB (40 instances)
L3 cache: 55 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78
NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: 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 / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled

Versions of relevant libraries:
[pip3] numpy==2.1.3
[pip3] torch==2.5.0a0+git32f585d
[conda] numpy 2.1.3 pypi_0 pypi
[conda] torch 2.5.0a0+git32f585d pypi_0 pypi

cc @malfet