TorchScript unsupport tuple unpacking  as function inputs.
Labels: oncall: jit

### 🐛 Describe the bug

```
from typing import Tuple
def ff(a:int, b:int, c:int, d:int=1):
    print(a, b, c, d)


def f(x: Tuple[int]):
    ff(*x)

f((1,2,3)) # 1,2,3,1
```
Pure python works well with unpacking tuple as function inputs, but it did not work with torch.jit.script.
```
@torch.jit.script
def _f(x: Tuple[int]):
    ff(*x)
```
will raise RuntimeError as :
```
RuntimeError: 

ff(int a, int b, int c, int d=1) -> (NoneType):
Argument b not provided.
:
  File "/tmp/ipykernel_11140/631393143.py", line 3
@torch.jit.script
def _f(x: Tuple[int]):
    ff(*x)
    ~~ <--- HERE
```



### Versions

Collecting environment information...
PyTorch version: 1.12.0+cu113
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.5 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.27

Python version: 3.9.13 | packaged by conda-forge | (main, May 27 2022, 16:58:50)  [GCC 10.3.0] (64-bit runtime)
Python platform: Linux-5.4.0-100-generic-x86_64-with-glibc2.27
Is CUDA available: True
CUDA runtime version: 11.3.109
GPU models and configuration: 
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 3090

Nvidia driver version: 470.63.01
cuDNN version: Probably one of the following:
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn.so.8.4.1
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.4.1
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.4.1
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.4.1
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.4.1
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.4.1
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.4.1
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.5
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.4.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] numpy==1.22.4
[pip3] pytorch-lightning==1.7.0
[pip3] pytorch-wpe==0.0.1
[pip3] torch==1.12.0+cu113
[pip3] torch-complex==0.4.3
[pip3] torch-tb-profiler==0.4.0
[pip3] torchaudio==0.12.0+cu113
[pip3] torchmetrics==0.9.3
[conda] numpy                     1.22.4           py39hc58783e_0    conda-forge
[conda] pytorch-lightning         1.7.0                    pypi_0    pypi
[conda] pytorch-wpe               0.0.1                    pypi_0    pypi
[conda] torch                     1.12.0+cu113             pypi_0    pypi
[conda] torch-complex             0.4.3                    pypi_0    pypi
[conda] torch-tb-profiler         0.4.0                    pypi_0    pypi
[conda] torchaudio                0.12.0+cu113             pypi_0    pypi
[conda] torchmetrics              0.9.3                    pypi_0    pypi