python - Tensorflow 2.3.0 未检测到 GPU

Question

tensorflow 没有检测到 GPU 卡。我遵循了 Nvidia 网站和 tensorflow/install/gpu 上建议的程序。
我该如何解决？
我正在使用以下软件包和驱动器:
英伟达

[nvcc: NVIDIA (R) Cuda compiler driver

Copyright (c) 2005-2019 NVIDIA Corporation

Built on Sun_Jul_28_19:12:52_Pacific_Daylight_Time_2019

Cuda compilation tools, release 10.1, V10.1.243][1]

库德恩
版本 8.0.2
tensorflow

Name                      Version                   Build  Channel
tensorflow                2.3.0                    pypi_0    pypi
tensorflow-addons         0.11.1                   pypi_0    pypi
tensorflow-estimator      2.3.0                    pypi_0    pypi

我使用以下代码进行检查；

Python 3.7.7 (default, May  6 2020, 11:45:54) [MSC v.1916 64 bit (AMD64)]
Type "copyright", "credits" or "license" for more information.

IPython 7.17.0 -- An enhanced Interactive Python.

from tensorflow.python.client import device_lib
device_lib.list_local_devices()

结果

2020-08-20 22:58:38.419555: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll 
Out[1]:  [name: "/device:CPU:0"  device_type: "CPU"  memory_limit: 268435456  locality {  }  incarnation: 12639439165040732604,  name: "/device:XLA_CPU:0"  device_type: "XLA_CPU"  memory_limit: 17179869184  locality {  }  incarnation: 2249215130251849864  physical_device_desc: "device: XLA_CPU device",  name: "/device:XLA_GPU:0"  device_type: "XLA_GPU"  memory_limit: 17179869184  locality {  }  incarnation: 7640064762024919839  physical_device_desc: "device: XLA_GPU device"]
2020-08-20 22:58:38.419555: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2020-08-20 22:58:40.332579: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-08-20 22:58:40.340307: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x22481a47710 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-08-20 22:58:40.341741: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-08-20 22:58:40.342711: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library nvcuda.dll
2020-08-20 22:58:40.362324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:  pciBusID: 0000:01:00.0 name: GeForce GTX 1050 computeCapability: 6.1 coreClock: 1.493GHz coreCount: 5 deviceMemorySize: 4.00GiB deviceMemoryBandwidth: 104.43GiB/s 
2020-08-20 22:58:40.362354: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll 
2020-08-20 22:58:40.366447: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cublas64_10.dll 
2020-08-20 22:58:40.369790: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cufft64_10.dll 
2020-08-20 22:58:40.370968: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library curand64_10.dll 
2020-08-20 22:58:40.374957: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusolver64_10.dll 
2020-08-20 22:58:40.377382: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cusparse64_10.dll 
2020-08-20 22:58:40.378955: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudnn64_7.dll'; dlerror: cudnn64_7.dll not found
2020-08-20 22:58:40.378977: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1753] 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...
2020-08-20 22:58:40.455688: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-08-20 22:58:40.455717: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263]      0
2020-08-20 22:58:40.455728: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0:   N
2020-08-20 22:58:40.458391: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x22490b5c830 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2020-08-20 22:58:40.458412: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): GeForce GTX 1050, Compute Capability 6.1

Answer 1

检查软件要求:Here
它说 cudnn 版本 = 7.6
确保您已安装所有 c++ 可再发行组件 - Here
确保你有合适的 python 版本。 - Here
最后，确保您已在系统中设置了 Cuda 和 cudnn 的路径。

Make sure the installed NVIDIA software packages match the versions listed above. In particular, TensorFlow will not load without the cuDNN64_7.dll file. To use a different version, see the Windows build from source guide.

这在 TensorFlow 文档中说明，这似乎是您的问题