ImportError: cannot import name 'Store' from 'torch.distributed'
Labels: oncall: distributed, triaged

### 🐛 Describe the bug

Hello,

I am trying to run YoloNAS on the nvidia Orin NX. I can have successfully for YoloV7 working but YoloNAS is complaining about torch.distributed.

Here is some information about my Orin:
torch                         2.0.0+nv23.5
torchmetrics                  0.8.0
torchvision                   0.15.1
Python                         3.8.10
Model: NVIDIA Orin NX Developer Kit - Jetpack 5.1 [L4T 35.2.1]

The error I get is the following:

ImportError: cannot import name 'Store' from 'torch.distributed' (/home/rebotnix/.local/lib/python3.8/site-packages/torch/distributed/__init__.py)

Checking in python:
>>> import torch
>>> torch.distributed.is_available()
False
>>> 

Any suggestions would be much appreciated.

All the best,

Simon


### Versions

rebotnix@rebotnix:~/Documents/yolo-nas$ python collect_env.py
Collecting environment information...
PyTorch version: 2.0.0+nv23.05
Is debug build: False
CUDA used to build PyTorch: 11.4
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (aarch64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.26.4
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-5.10.104-tegra-aarch64-with-glibc2.29
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/aarch64-linux-gnu/libcudnn.so.8.6.0
/usr/lib/aarch64-linux-gnu/libcudnn_adv_infer.so.8.6.0
/usr/lib/aarch64-linux-gnu/libcudnn_adv_train.so.8.6.0
/usr/lib/aarch64-linux-gnu/libcudnn_cnn_infer.so.8.6.0
/usr/lib/aarch64-linux-gnu/libcudnn_cnn_train.so.8.6.0
/usr/lib/aarch64-linux-gnu/libcudnn_ops_infer.so.8.6.0
/usr/lib/aarch64-linux-gnu/libcudnn_ops_train.so.8.6.0
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: False

CPU:
Architecture:                    aarch64
CPU op-mode(s):                  32-bit, 64-bit
Byte Order:                      Little Endian
CPU(s):                          8
On-line CPU(s) list:             0-7
Thread(s) per core:              1
Core(s) per socket:              8
Socket(s):                       1
Vendor ID:                       ARM
Model:                           1
Model name:                      ARMv8 Processor rev 1 (v8l)
Stepping:                        r0p1
CPU max MHz:                     1984.0000
CPU min MHz:                     115.2000
BogoMIPS:                        62.50
L1d cache:                       512 KiB
L1i cache:                       512 KiB
L2 cache:                        2 MiB
L3 cache:                        4 MiB
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:        Mitigation; __user pointer sanitization
Vulnerability Spectre v2:        Not affected
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Not affected
Flags:                           fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop asimddp uscat ilrcpc flagm

Versions of relevant libraries:
[pip3] numpy==1.23.0
[pip3] torch==2.0.0+nv23.5
[pip3] torchmetrics==0.8.0
[pip3] torchvision==0.15.1
[conda] Could not collect


cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @H-Huang @kwen2501 @awgu