Repository: pytorch
Issue: `torch.onnx.dynamo_export` provides wrong output shape for `torch.fft.irfft`
Labels: module: onnx,triaged,onnx-triaged

### 🐛 Describe the bug

I'm experiencing a torch.fft.irfft shape mismatch when exporting a model using torch.onnx.dynamo_export. Details below

### Error logs

I've got shapes for repro below
```
torch shape: torch.Size([960])
onnx shape: (481,)
```

But they should match

### Minified repro

```python
import torch
import onnxruntime as ort

from torch import nn


class iRFFTModel(nn.Module):
  def __init__(self):
      super().__init__()

  def forward(self, x):
    return torch.fft.irfft(torch.view_as_complex(x), n=960)

example_tensor = torch.rand(481, 2)
irfft_model = iRFFTModel()
irfft_model_onnx_path = "irfft_model.onnx"
out_torch = irfft_model(example_tensor)
print("torch shape:", out_torch.shape)

torch.onnx.dynamo_export(
    irfft_model,
    example_tensor
).save(irfft_model_onnx_path)

# rfft
irfft_ort_session = ort.InferenceSession(
    irfft_model_onnx_path,
    providers=["CPUExecutionProvider"]
)

def run_onnx_irfft():
    return irfft_ort_session.run(
        ['_fft_c2r'],
         {
             "arg0": example_tensor.detach().cpu().numpy()
         }
    )

out_onnx = run_onnx_irfft()[0]
print("onnx shape:", out_onnx.shape)
```

### Versions

It reproduces both in Colab and on my local machine.

```
Collecting environment information...
PyTorch version: 2.1.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.27.9
Libc version: glibc-2.35

Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.1.58+-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.6
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):                             2
On-line CPU(s) list:                0,1
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) CPU @ 2.20GHz
CPU family:                         6
Model:                              79
Thread(s) per core:                 2
Core(s) per socket:                 1
Socket(s):                          1
Stepping:                           0
BogoMIPS:                           4399.99
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 nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat md_clear arch_capabilities
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          32 KiB (1 instance)
L1i cache:                          32 KiB (1 instance)
L2 cache:                           256 KiB (1 instance)
L3 cache:                           55 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0,1
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Mitigation; PTE Inversion
Vulnerability Mds:                  Vulnerable; SMT Host state unknown
Vulnerability Meltdown:             Vulnerable
Vulnerability Mmio stale data:      Vulnerable
Vulnerability Retbleed:             Vulnerable
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:           Vulnerable, IBPB: disabled, STIBP: disabled, PBRSB-eIBRS: Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Vulnerable

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] onnx==1.15.0
[pip3] onnxruntime==1.17.0
[pip3] onnxscript==0.1.0.dev20240207
[pip3] torch==2.1.0+cu121
[pip3] torchaudio==2.1.0+cu121
[pip3] torchdata==0.7.0
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.16.0
[pip3] torchvision==0.16.0+cu121
[pip3] triton==2.1.0
[conda] Could not collect
```

cc @ezyang @msaroufim @bdhirsh @anijain2305 @zou3519