Panoptic Segmentation Can Not be Exported to ONNX

## Instructions To Reproduce the 🐛 Bug:

1. Full runnable code or full changes you made:
```
I use the original repo and do not change anything.
```

2. What exact command do you run:
```bash
export DETECTRON2_DATASETS=/data/datasets/

python3 export_model.py \
--config-file ../../configs/COCO-PanopticSegmentation/panoptic_fpn_R_50_1x.yaml \
--output /data/output/ \
--export-method caffe2_tracing \
--format onnx \
MODEL.WEIGHTS /data/model/COCO-PanopticSegmentation/panoptic_fpn_R_50_1x/139514544/model_final_dbfeb4.pkl \
MODEL.DEVICE cpu
```

I have already prepared the COCO dataset in `/data/datasets/`.

3. __Full logs__ or other relevant observations:
```
[06/23 06:22:33 detectron2]: Command line arguments: Namespace(format='onnx', export_method='caffe2_tracing', config_file='../../configs/COCO-PanopticSegmentation/panoptic_fpn_R_50_1x.yaml', sample_image=None, run_eval=False, output='/data/output/', opts=['MODEL.WEIGHTS', '/data/model/COCO-PanopticSegmentation/panoptic_fpn_R_50_1x/139514544/model_final_dbfeb4.pkl', 'MODEL.DEVICE', 'cpu'])
[W init.cpp:759] Warning: Use _jit_set_fusion_strategy, bailout depth is deprecated. Setting to (STATIC, 1) (function operator())
[06/23 06:22:35 d2.data.datasets.coco]: Loaded 5000 images in COCO format from /data/datasets/coco/annotations/instances_val2017.json
[06/23 06:22:35 d2.data.datasets.coco]: Loaded 5000 images with semantic segmentation from /data/datasets/coco/val2017
[06/23 06:22:35 d2.data.build]: Distribution of instances among all 80 categories:
| category | #instances | category | #instances | category | #instances |
|:-------------:|:-------------|:------------:|:-------------|:-------------:|:-------------|
| person | 10777 | bicycle | 314 | car | 1918 |
| motorcycle | 367 | airplane | 143 | bus | 283 |
| train | 190 | truck | 414 | boat | 424 |
| traffic light | 634 | fire hydrant | 101 | stop sign | 75 |
| parking meter | 60 | bench | 411 | bird | 427 |
| cat | 202 | dog | 218 | horse | 272 |
| sheep | 354 | cow | 372 | elephant | 252 |
| bear | 71 | zebra | 266 | giraffe | 232 |
| backpack | 371 | umbrella | 407 | handbag | 540 |
| tie | 252 | suitcase | 299 | frisbee | 115 |
| skis | 241 | snowboard | 69 | sports ball | 260 |
| kite | 327 | baseball bat | 145 | baseball gl.. | 148 |
| skateboard | 179 | surfboard | 267 | tennis racket | 225 |
| bottle | 1013 | wine glass | 341 | cup | 895 |
| fork | 215 | knife | 325 | spoon | 253 |
| bowl | 623 | banana | 370 | apple | 236 |
| sandwich | 177 | orange | 285 | broccoli | 312 |
| carrot | 365 | hot dog | 125 | pizza | 284 |
| donut | 328 | cake | 310 | chair | 1771 |
| couch | 261 | potted plant | 342 | bed | 163 |
| dining table | 695 | toilet | 179 | tv | 288 |
| laptop | 231 | mouse | 106 | remote | 283 |
| keyboard | 153 | cell phone | 262 | microwave | 55 |
| oven | 143 | toaster | 9 | sink | 225 |
| refrigerator | 126 | book | 1129 | clock | 267 |
| vase | 274 | scissors | 36 | teddy bear | 190 |
| hair drier | 11 | toothbrush | 57 | | |
| total | 36335 | | | | |
[06/23 06:22:35 d2.data.dataset_mapper]: [DatasetMapper] Augmentations used in inference: [ResizeShortestEdge(short_edge_length=(800, 800), max_size=1333, sample_style='choice')]
[06/23 06:22:35 d2.data.common]: Serializing 5000 elements to byte tensors and concatenating them all ...
[06/23 06:22:35 d2.data.common]: Serialized dataset takes 19.52 MiB
Traceback (most recent call last):
File "/data/detectron2/tools/deploy/export_model.py", line 217, in
exported_model = export_caffe2_tracing(cfg, torch_model, sample_inputs)
File "/data/detectron2/tools/deploy/export_model.py", line 36, in export_caffe2_tracing
from detectron2.export import Caffe2Tracer
ImportError: cannot import name 'Caffe2Tracer' from 'detectron2.export' (/usr/local/lib/python3.10/dist-packages/detectron2-0.6-py3.10-linux-x86_64.egg/detectron2/export/__init__.py)
```

4. please simplify the steps as much as possible so they do not require additional resources to
run, such as a private dataset.

## Expected behavior:

I expected that the official code [export_model.py](https://github.com/facebookresearch/detectron2/blob/main/tools/deploy/export_model.py) can help me to export onnx model.

## Environment:

Provide your environment information using the following command:
```
--------------------- ----------------------------------------------------------------------------------------------
sys.platform linux
Python 3.10.4 (main, Apr 2 2022, 09:04:19) [GCC 11.2.0]
numpy 1.22.4
detectron2 0.6 @/usr/local/lib/python3.10/dist-packages/detectron2-0.6-py3.10-linux-x86_64.egg/detectron2
Compiler GCC 11.2
CUDA compiler not available
DETECTRON2_ENV_MODULE
PyTorch 1.11.0+cpu @/usr/local/lib/python3.10/dist-packages/torch
PyTorch debug build False
GPU available No: torch.cuda.is_available() == False
Pillow 9.1.1
torchvision 0.12.0+cpu @/usr/local/lib/python3.10/dist-packages/torchvision
fvcore 0.1.5.post20220512
iopath 0.1.9
cv2 4.6.0
--------------------- ----------------------------------------------------------------------------------------------
PyTorch built with:
- GCC 7.3
- C++ Version: 201402
- Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=0, USE_CUDNN=OFF, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,
```

If your issue looks like an installation issue / environment issue,
please first try to solve it yourself with the instructions in
https://detectron2.readthedocs.io/tutorials/install.html#common-installation-issues

Finally, thanks to your effects that contribute such excellent repo!