A/libc: Fatal signal 6 (SIGABRT), code -6 in tid 11742 (objectdetection) 
Labels: oncall: jit, oncall: mobile

### 🐛 Describe the bug

I trained a D2Go model and converted to torchscript_int8. When I tried to run on an android device, it raised the following error.

E/libc++abi: terminating with uncaught exception of type c10::Error: isTuple()INTERNAL ASSERT FAILED at "../../../../src/main/cpp/libtorch_include/arm64-v8a/ATen/core/ivalue_inl.h":1306, please report a bug to PyTorch. Expected Tuple but got String
    Exception raised from toTuple at ../../../../src/main/cpp/libtorch_include/arm64-v8a/ATen/core/ivalue_inl.h:1306 (most recent call first):
    (no backtrace available)
A/libc: Fatal signal 6 (SIGABRT), code -6 in tid 11742 (objectdetection)

### Versions

Collecting environment information...
PyTorch version: 1.13.0.dev20220615
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: CentOS Linux 7 (Core) (x86_64)
GCC version: (GCC) 7.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.17

Python version: 3.9.12 (main, Jun  1 2022, 11:38:51)  [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-3.10.0-1160.53.1.el7.x86_64-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 11.3.58
GPU models and configuration: 
GPU 0: NVIDIA A100-PCIE-40GB
GPU 1: NVIDIA A100-PCIE-40GB
GPU 2: NVIDIA A100-PCIE-40GB
GPU 3: NVIDIA A100-PCIE-40GB
GPU 4: NVIDIA A100-PCIE-40GB
GPU 5: NVIDIA A100-PCIE-40GB
GPU 6: NVIDIA A100-PCIE-40GB
GPU 7: NVIDIA A100-PCIE-40GB

Nvidia driver version: 495.29.05
cuDNN version: Probably one of the following:
/usr/lib64/libcudnn.so.8.2.2
/usr/lib64/libcudnn_adv_infer.so.8.2.2
/usr/lib64/libcudnn_adv_train.so.8.2.2
/usr/lib64/libcudnn_cnn_infer.so.8.2.2
/usr/lib64/libcudnn_cnn_train.so.8.2.2
/usr/lib64/libcudnn_ops_infer.so.8.2.2
/usr/lib64/libcudnn_ops_train.so.8.2.2
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.22.3
[pip3] pytorch-lightning==1.6.4
[pip3] torch==1.13.0.dev20220615
[pip3] torchaudio==0.13.0.dev20220615
[pip3] torchmetrics==0.9.1
[pip3] torchvision==0.14.0.dev20220615
[conda] blas                      1.0                         mkl  
[conda] cudatoolkit               11.3.1               h2bc3f7f_2  
[conda] mkl                       2021.4.0           h06a4308_640  
[conda] mkl-service               2.4.0            py39h7f8727e_0  
[conda] mkl_fft                   1.3.1            py39hd3c417c_0  
[conda] mkl_random                1.2.2            py39h51133e4_0  
[conda] numpy                     1.22.3           py39he7a7128_0  
[conda] numpy-base                1.22.3           py39hf524024_0  
[conda] pytorch                   1.13.0.dev20220615 py3.9_cuda11.3_cudnn8.3.2_0    pytorch-nightly
[conda] pytorch-lightning         1.6.4                    pypi_0    pypi
[conda] pytorch-mutex             1.0                        cuda    pytorch-nightly
[conda] torchaudio                0.13.0.dev20220615      py39_cu113    pytorch-nightly
[conda] torchmetrics              0.9.1                    pypi_0    pypi
[conda] torchvision               0.14.0.dev20220615      py39_cu113    pytorch-nightly