Trick:获取实验室内存最大的GPU进行代码运行

# 确定设备为GPU
num_gpus = torch.cuda.device_count()
target_gpu_id = None
for gpu_id in range(num_gpus):
    gpu_props = torch.cuda.get_device_properties(gpu_id)
    if gpu_props.total_memory >= 80 * 1000**3:  # 实验室空闲的GPU内存没这么大
        target_gpu_id = gpu_id
        break
if target_gpu_id is not None:
    device = torch.device(f"cuda:{target_gpu_id}")
    print(f"Selected GPU {target_gpu_id}: {gpu_props.name}, Total Memory: {gpu_props.total_memory} bytes")
    #运行的代码
else 
	 print("Error: CUDA is not available even though a suitable GPU was detected.")
    sys.exit(1)