Repository: pytorch
Issue: [ONNX] Support for `aten.istft`
Labels: module: onnx,triaged

### 🐛 Describe the bug

When I run [this](https://github.com/tuna2134/f5-tts/blob/master/onnx/convert_vocos.py), it failed.

### Versions

Collecting environment information...
PyTorch version: 2.6.0.dev20241024+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.1 LTS (x86_64)
GCC version: (Ubuntu 13.2.0-23ubuntu4) 13.2.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.39

Python version: 3.12.7 (main, Oct 23 2024, 01:45:22) [GCC 13.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-47-generic-x86_64-with-glibc2.39
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:                        40 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               6
On-line CPU(s) list:                  0-5
Vendor ID:                            GenuineIntel
Model name:                           QEMU Virtual CPU version 2.5+
CPU family:                           15
Model:                                107
Thread(s) per core:                   1
Core(s) per socket:                   6
Socket(s):                            1
Stepping:                             1
BogoMIPS:                             4794.41
Flags:                                fpu de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx lm constant_tsc nopl xtopology cpuid tsc_known_freq pni ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c hypervisor lahf_lm abm cpuid_fault pti bmi1 avx2 bmi2
Hypervisor vendor:                    KVM
Virtualization type:                  full
L1d cache:                            192 KiB (6 instances)
L1i cache:                            192 KiB (6 instances)
L2 cache:                             24 MiB (6 instances)
L3 cache:                             16 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-5
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          KVM: Mitigation: VMX unsupported
Vulnerability L1tf:                   Mitigation; PTE Inversion
Vulnerability Mds:                    Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Meltdown:               Mitigation; PTI
Vulnerability Mmio stale data:        Unknown: No mitigations
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Retpoline
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] onnx==1.17.0
[pip3] onnxscript==0.1.0.dev20241023
[pip3] torch==2.6.0.dev20241024+cpu
[pip3] torchaudio==2.5.0.dev20241024+cpu
[pip3] torchvision==0.20.0.dev20241024+cpu