CUDA issue on the Compute Instance

PyTorch cannot detect GPUs on the Compute Instance with NVIDIA A100 GPUs. `nvidia-smi` and `nvcc --version` can return the installed CUDA version and CUDA toolkit versions. But PyTorch returns the following:

```bash
# python -c "import torch; print(torch.cuda.is_available())"
/opt/conda/lib/python3.8/site-packages/torch/cuda/__init__.py:80: UserWarning: CUDA initialization: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 802: system not yet initialized (Triggered internally at /opt/pytorch/pytorch/c10/cuda/CUDAFunctions.cpp:112.)
return torch._C._cuda_getDeviceCount() > 0
False
```

I tried to pull PyTorch container from Nvidia NGC, AML base images, or compile PyTorch using pip/conda with GPU support. All have the same CUDA issue. I also cannot compile NCCL test on the Compute Instance with GPUs.

However, everything works fine on the Computer Cluster VMs. NCCL compiles/runs file and PyTorch has no issue with CUDA. I suspect CUDA is installed but not configured correctly on the Compute Instance VMs.

先在 Compute Instance 上重現 `python -c "import torch; print(torch.cuda.is_available())"`，並與正常運作的 Computer Cluster VMs 比較。檢查回報的 `nvidia-smi`、`nvcc --version` 輸出以及 CUDA 初始化錯誤，然後確認 PyTorch 能偵測到 A100 GPU，且 NCCL 測試能夠編譯並執行。

由索引模型根據 Issue 內容生成。