Could not find cuda drivers on your machine, GPU will not be used

最新推荐文章于 2025-06-01 13:40:14 发布

原创最新推荐文章于 2025-06-01 13:40:14 发布 · 2.5k 阅读

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#tensorflow2 #python

我安装了cuda，pytorch可以检查gpu，但是tensorflow检测不到,从这里安装tensorflow：

pip install --extra-index-url https://pypi.nvidia.com tensorflow[and-cuda]

2024-04-04 13:51:41.596916: I external/local_tsl/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.

2024-04-04 13:51:41.635006: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered

2024-04-04 13:51:41.635035: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered

2024-04-04 13:51:41.636666: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered

2024-04-04 13:51:41.643580: I external/local_tsl/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.

2024-04-04 13:51:41.643842: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.

2024-04-04 13:51:42.742450: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT

2024-04-04 13:51:44.259895: W tensorflow/core/common_runtime/gpu/gpu_device.cc:2256] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for

your platform. Skipping registering GPU devices... tensorflow [] [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU')] pytorch True 1