'MPS' issue: torch.multinomial() returning [-9223372036854775808]
Labels: triaged, module: mps

### 🐛 Describe the bug

torch.multinomial(probs, num_samples=1) returning is returning: [-9223372036854775808]
Here's an example:
```
% ipython
Python 3.10.9 (main, Jan 11 2023, 09:18:20) [Clang 14.0.6 ]
Type 'copyright', 'credits' or 'license' for more information
IPython 8.7.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import numpy as np

In [2]: import torch

In [3]: probs = torch.tensor(np.loadtxt("probs0.txt"), dtype=torch.float32, device
   ...: ='mps')

In [4]: torch.multinomial(probs, num_samples=1)
Out[4]: 
tensor([[-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808],
        [-9223372036854775808]], device='mps:0')

In [5]: probs = torch.tensor(np.loadtxt("probs0.txt"), dtype=torch.float32, device
   ...: ='cpu')

In [6]: torch.multinomial(probs, num_samples=1)
Out[6]: 
tensor([[13],
        [ 1],
        [13],
        [ 0],
        [13],
        [81],
        [13],
        [81],
        [13],
        [ 0]])

```
[probs0.txt](https://github.com/pytorch/pytorch/files/10472535/probs0.txt)

 

### Versions

```
% python collect_env.py
Collecting environment information...
PyTorch version: 2.0.0a0+gitf4b804e
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: macOS 13.1 (x86_64)
GCC version: Could not collect
Clang version: 14.0.0 (clang-1400.0.29.202)
CMake version: version 3.22.1
Libc version: N/A

Python version: 3.10.9 (main, Jan 11 2023, 09:18:20) [Clang 14.0.6 ] (64-bit runtime)
Python platform: macOS-10.16-x86_64-i386-64bit
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] audiolm-pytorch==0.0.1
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.23.5
[pip3] pytorch-transformers==1.1.0
[pip3] torch==2.0.0a0+gitf8b2879
[pip3] torch-struct==0.5
[pip3] torch-summary==1.4.5
[pip3] torch-utils==0.1.2
[pip3] torchaudio==0.13.0.dev20221015
[pip3] torchtraining-nightly==1604016577
[pip3] torchvision==0.15.0a0+8985b59
[pip3] vector-quantize-pytorch==0.9.2
[conda] nomkl                     3.0                           0  
[conda] numpy                     1.23.5          py310he50c29a_0  
[conda] numpy-base                1.23.5          py310h992e150_0  
[conda] pytorch-transformers      1.1.0                    pypi_0    pypi
[conda] torch                     2.0.0a0+git7ef7c57          pypi_0    pypi
[conda] torch-struct              0.5                      pypi_0    pypi
[conda] torch-summary             1.4.5                    pypi_0    pypi
[conda] torch-utils               0.1.2                    pypi_0    pypi
[conda] torchaudio                0.13.0.dev20221015          pypi_0    pypi
[conda] torchtraining-nightly     1604016577               pypi_0    pypi
[conda] torchvision               0.15.0a0+8985b59          pypi_0    pypi
[conda] vector-quantize-pytorch   0.9.2                    pypi_0    pypi

```

cc @kulinseth @albanD @malfet @DenisVieriu97 @razarmehr @abhudev