fix(testing): check torch.cuda.is_available() before get_device_capability

[PHclaw]

Summary

Fixes #45341

get_device_properties() crashes with an error on machines that have CUDA installed (torch.version.cuda is not None) but no physical GPU available. This happens on cloud instances like Lightning AI Studio where CUDA runtime is present but no GPU is attached.

Bug

# Line 3207-3210
if IS_CUDA_SYSTEM or IS_ROCM_SYSTEM:
    import torch
    major, minor = torch.cuda.get_device_capability()  # Crashes if no GPU!

IS_CUDA_SYSTEM is set to True when torch.version.cuda is not None, but this only means CUDA runtime is available, not that a GPU is actually present.

Fix

• Add torch.cuda.is_available() check to the condition on line 3207
• Remove the redundant import torch (torch is already imported at module level for IS_CUDA_SYSTEM/IS_ROCM_SYSTEM checks)

if (IS_CUDA_SYSTEM or IS_ROCM_SYSTEM) and torch.cuda.is_available():
    major, minor = torch.cuda.get_device_capability()

This gracefully falls through to the else branch when no GPU is available, returning (torch_device, None, None) instead of crashing.

[Rocketknight1]

PR already open at #45351