PyTorch 2.0.x `CUDA error: operation not supported` when `Tensor.to` a different device
Labels: needs reproduction, module: cuda, triaged, module: regression

### 🐛 Describe the bug

I've created an Azure VM with 2 A10 GPUs (`standard_nv72ads_a10_v5`). When running Hugging Face code to use both the GPUs, I've accountered `CUDA error: operation not supported`, and turns out it is reproducible with this PyTorch snippet.

```python
import torch

a = torch.Tensor(torch.randn(5,5,5))
a = a.to("cuda:0")

# Move a to another device
b = a.to("cuda:1")
```

It shows Segmentation Fault, and with [faulthandler](https://docs.python.org/3/library/faulthandler.html) enabled, it shows the error:
```
RuntimeError: CUDA error: operation not supported
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
```

Notably when I downgrade PyTorch from 2.0.1 to 1.13.1, the same snippet works.

As PyTorch 2.0 should be backward compatible, I hope to understand how this could happen, since there are some new features of PyTorch 2.0 that I need.

### Versions

Output of `collect_env.py`
```
PyTorch version: 2.0.1+cu117
Is debug build: False
CUDA used to build PyTorch: 11.7
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 3.27.0
Libc version: glibc-2.31

Python version: 3.8.10 (default, May 26 2023, 14:05:08)  [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-1040-azure-x86_64-with-glibc2.29
Is CUDA available: True
CUDA runtime version: 10.1.243
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A10-24Q
GPU 1: NVIDIA A10-24Q

Nvidia driver version: 525.105.17
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:                   48 bits physical, 48 bits virtual
CPU(s):                          72
On-line CPU(s) list:             0-71
Thread(s) per core:              2
Core(s) per socket:              18
Socket(s):                       2
NUMA node(s):                    4
Vendor ID:                       AuthenticAMD
CPU family:                      25
Model:                           1
Model name:                      AMD EPYC 74F3 24-Core Processor
Stepping:                        1
CPU MHz:                         3194.042
BogoMIPS:                        6388.08
Hypervisor vendor:               Microsoft
Virtualization type:             full
L1d cache:                       1.1 MiB
L1i cache:                       1.1 MiB
L2 cache:                        18 MiB
L3 cache:                        128 MiB
NUMA node0 CPU(s):               0-17
NUMA node1 CPU(s):               18-35
NUMA node2 CPU(s):               36-53
NUMA node3 CPU(s):               54-71
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Mmio stale data:   Not affected
Vulnerability Retbleed:          Not affected
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 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext invpcid_single vmmcall fsgsbase bmi1 avx2 smep bmi2 invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr rdpru arat umip vaes vpclmulqdq rdpid

Versions of relevant libraries:
[pip3] torch==2.0.1
[pip3] triton==2.0.0
[conda] Could not collect
```

Output of NVIDIA's `deviceQuery`:
```
Detected 2 CUDA Capable device(s)

Device 0: "NVIDIA A10-24Q"
  CUDA Driver Version / Runtime Version          12.0 / 9.2
  CUDA Capability Major/Minor version number:    8.6
  Total amount of global memory:                 24298 MBytes (25478168576 bytes)
MapSMtoCores for SM 8.6 is undefined.  Default to use 64 Cores/SM
MapSMtoCores for SM 8.6 is undefined.  Default to use 64 Cores/SM
  (72) Multiprocessors, ( 64) CUDA Cores/MP:     4608 CUDA Cores
  GPU Max Clock rate:                            1695 MHz (1.70 GHz)
  Memory Clock rate:                             6251 Mhz
  Memory Bus Width:                              384-bit
  L2 Cache Size:                                 6291456 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
  Maximum Layered 1D Texture Size, (num) layers  1D=(32768), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(32768, 32768), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 65536
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  1536
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 3 copy engine(s)
  Run time limit on kernels:                     No
  Integrated GPU sharing Host Memory:            No
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Enabled
  Device supports Unified Addressing (UVA):      Yes
  Device supports Compute Preemption:            Yes
  Supports Cooperative Kernel Launch:            Yes
  Supports MultiDevice Co-op Kernel Launch:      Yes
  Device PCI Domain ID / Bus ID / location ID:   2 / 0 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

Device 1: "NVIDIA A10-24Q"
  CUDA Driver Version / Runtime Version          12.0 / 9.2
  CUDA Capability Major/Minor version number:    8.6
  Total amount of global memory:                 24298 MBytes (25478168576 bytes)
MapSMtoCores for SM 8.6 is undefined.  Default to use 64 Cores/SM
MapSMtoCores for SM 8.6 is undefined.  Default to use 64 Cores/SM
  (72) Multiprocessors, ( 64) CUDA Cores/MP:     4608 CUDA Cores
  GPU Max Clock rate:                            1695 MHz (1.70 GHz)
  Memory Clock rate:                             6251 Mhz
  Memory Bus Width:                              384-bit
  L2 Cache Size:                                 6291456 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
  Maximum Layered 1D Texture Size, (num) layers  1D=(32768), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(32768, 32768), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 65536
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  1536
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 3 copy engine(s)
  Run time limit on kernels:                     No
  Integrated GPU sharing Host Memory:            No
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Enabled
  Device supports Unified Addressing (UVA):      Yes
  Device supports Compute Preemption:            Yes
  Supports Cooperative Kernel Launch:            Yes
  Supports MultiDevice Co-op Kernel Launch:      Yes
  Device PCI Domain ID / Bus ID / location ID:   3 / 0 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
> Peer access from NVIDIA A10-24Q (GPU0) -> NVIDIA A10-24Q (GPU1) : Yes
> Peer access from NVIDIA A10-24Q (GPU1) -> NVIDIA A10-24Q (GPU0) : Yes

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 12.0, CUDA Runtime Version = 9.2, NumDevs = 2
Result = PASS
```

cc @ezyang @gchanan @zou3519 @peterjc123 @mszhanyi @skyline75489 @nbcsm @vladimir-aubrecht @iremyux @Blackhex @cristianPanaite @ptrblck