验证GPU有效性的python代码

验证GPU有效性通常通过NVIDIA CUDA库的Python接口，例如`torch`或`cupy`，来进行。以下是一个简单的例子，使用PyTorch来检查CUDA是否可用以及GPU的状态：

# 首先确保已经安装了PyTorch和cuda相关的包
try:
    import torch
except ImportError:
    print("PyTorch not installed. Please install it for GPU verification.")
else:
    # 检查是否有可用的CUDA设备
    if torch.cuda.is_available():
        device = torch.device("cuda")
        print(f"CUDA is available. Running on {device}...")
        
        # 获取当前GPU的一些信息，如名称、显存大小等
        print(f"Device name: {torch.cuda.get_device_name(0)}")
        print(f"Memory allocated: {torch.cuda.memory_allocated(device) / (1024 ** 3):.2f} GB")
        print(f"Memory cached: {torch.cuda.memory_cached(device) / (1024 ** 3):.2f} GB")
        print("\nCurrent GPU status:")
        print(torch.cuda.memory_summary())
    else:
        print("CUDA is NOT available or the machine does not have a CUDA-capable GPU.")