Repository: pytorch
Issue: ONNX export error when exporting Vision Transformer model from PyTorch to ONNX format
Labels: module: onnx,triaged

### 🐛 Describe the bug

Hello, I've been trying to export the dinov2 vision transformer model to onnx format and have been getting an error:
```
torch.onnx.errors.UnsupportedOperatorError: Exporting the operator 'aten::_upsample_bicubic2d_aa' to ONNX opset version 15 is not supported.
```
I've tried with different versions of pytorch (previously with 2.0.0 and currently with the nightly build 2.3.0) and getting the same issue. I've inspected onnxscript and see that the `aten_bicubic_2d` function seems to be present ([link here](https://github.com/microsoft/onnxscript/blob/main/onnxscript/function_libs/torch_lib/ops/nn.py#L2200)).

Thanks for your help :)

Steps to reproduce issue:
1. Run this script:
```
import torch
import onnx
import onnxscript

dinov2_vits14_reg = torch.hub.load('facebookresearch/dinov2', 'dinov2_vits14_reg')

dummy_input = torch.randn(1,3,224,224)

torch.onnx.export(dinov2_vits14_reg, dummy_input, export_params=True, "model.onnx")

```


### Versions

PyTorch version: 2.3.0.dev20231221+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.26.3
Libc version: glibc-2.31

Python version: 3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:26:04) [GCC 10.4.0] (64-bit runtime)
Python platform: Linux-4.14.327-246.539.amzn2.x86_64-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 11.8.89
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla T4
Nvidia driver version: 470.57.02
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
Byte Order:                         Little Endian
Address sizes:                      46 bits physical, 48 bits virtual
CPU(s):                             8
On-line CPU(s) list:                0-7
Thread(s) per core:                 2
Core(s) per socket:                 4
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              85
Model name:                         Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz
Stepping:                           7
CPU MHz:                            3098.932
BogoMIPS:                           5000.00
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          128 KiB
L1i cache:                          128 KiB
L2 cache:                           4 MiB
L3 cache:                           35.8 MiB
NUMA node0 CPU(s):                  0-7
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit:        KVM: Vulnerable
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:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             Vulnerable
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
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
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 aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves ida arat pku ospke avx512_vnni

Versions of relevant libraries:
[pip3] numpy==1.24.1
[pip3] onnx==1.15.0
[pip3] onnxscript==0.1.0.dev20231213
[pip3] pytorch-triton==2.2.0+e28a256d71
[pip3] torch==2.3.0.dev20231221+cu118
[pip3] torchaudio==2.2.0.dev20231221+cu118
[pip3] torchvision==0.18.0.dev20231221+cu118
[conda] blas                      1.0                         mkl    conda-forge
[conda] mkl                       2023.1.0         h84fe81f_48680    conda-forge
[conda] mkl-include               2023.1.0         h84fe81f_48680    conda-forge
[conda] numpy                     1.23.5          py310h53a5b5f_0    conda-forge
[conda] pytorch-cuda              11.8                 h7e8668a_3    https://aws-ml-conda-pre-prod-ec2.s3.us-west-2.amazonaws.com
[conda] pytorch-lightning         1.9.5                    pypi_0    pypi
[conda] pytorch-mutex             1.0                        cuda    https://aws-ml-conda-pre-prod-ec2.s3.us-west-2.amazonaws.com
[conda] sagemaker-pytorch-training 2.8.0                    pypi_0    pypi
[conda] torch                     2.0.0                    pypi_0    pypi
[conda] torchaudio                2.0.1               py310_cu118    https://aws-ml-conda-pre-prod-ec2.s3.us-west-2.amazonaws.com
[conda] torchdata                 0.6.0                     py310    https://aws-ml-conda-pre-prod-ec2.s3.us-west-2.amazonaws.com
[conda] torchmetrics              0.10.3                   pypi_0    pypi
[conda] torchnet                  0.0.4                    pypi_0    pypi
[conda] torchtext                 0.15.1                    py310    https://aws-ml-conda-pre-prod-ec2.s3.us-west-2.amazonaws.com
[conda] torchvision               0.15.1                   pypi_0    pypi
[conda] triton                    2.0.0                    pypi_0    pypi
```[tasklist]
### Tasks
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