Update main.py

main.py

@@ -29,40 +29,27 @@ for i in range(device_count):
 
 import os
 
-nvidia_devices = [dev for dev in os.listdir('/dev') if dev.startswith('nvidia')]
-print("NVIDIA 设备文件:", nvidia_devices)
-for dev in nvidia_devices:
-    path = os.path.join('/dev', dev)
-    print(f"设备 {path} 的权限:", oct(os.stat(path).st_mode))
-import ctypes
-
-try:
-    ctypes.CDLL('libcuda.so')
-    print("CUDA 库已加载。")
-except Exception as e:
-    print("无法加载 CUDA 库，错误信息:", e)
-
-import os
-
-cuda_visible_devices = os.environ.get('CUDA_VISIBLE_DEVICES', '未设置')
-print("CUDA_VISIBLE_DEVICES:", cuda_visible_devices)
-
 try:
-    torch.cuda.init()
-    x = torch.tensor([1.0], device='cuda')
-    print("CUDA 张量创建成功:", x)
+    ctypes.CDLL('libnvidia-ml.so')
+    print("成功加载 libnvidia-ml.so。")
 except Exception as e:
-    print("无法在 CUDA 上创建张量，错误信息:", e)
+    print("无法加载 libnvidia-ml.so，错误信息:", e)
 
-import subprocess
+import glob
 
-# 查看 GPU 信息
+libs = glob.glob('/usr/lib*/**/libnvidia-*.so*', recursive=True)
+print("NVIDIA 驱动库文件:", libs)
+print("LD_LIBRARY_PATH:", os.environ.get('LD_LIBRARY_PATH', '未设置'))
 try:
-    result = subprocess.run(['lspci'], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-    gpu_info = [line for line in result.stdout.decode().split('\n') if 'NVIDIA' in line]
-    print("GPU 信息:", gpu_info)
+    with open('/proc/driver/nvidia/version') as f:
+        print(f.read())
 except Exception as e:
-    print("无法获取 GPU 信息，错误信息:", e)
+    print("无法读取驱动程序版本信息，错误信息:", e)
+print("PyTorch 安装路径:", torch.__file__)
+cuda_paths = [path for path in os.listdir('/usr/local') if path.startswith('cuda')]
+print("CUDA 安装路径:", cuda_paths)
+print("PyTorch CUDA 版本:", torch.version.cuda)
+print("系统 CUDA 版本:", os.environ.get('CUDA_VERSION', '未设置'))
 
     
 def run_main(