加载运行时CuDNN库: 7.0.5，但源代码是用: 7.2.1编译的。

Question

我该如何解决这个错误？

$ python tensorboard_viz.py
/scratch/sjn-p3/anaconda/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
2018-10-24 19:49:39.925967: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-10-24 19:49:40.093637: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1411] Found device 0 with properties: 
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6705
pciBusID: 0000:05:00.0
totalMemory: 10.92GiB freeMemory: 10.03GiB
2018-10-24 19:49:40.238084: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1411] Found device 1 with properties: 
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6705
pciBusID: 0000:06:00.0
totalMemory: 10.92GiB freeMemory: 10.76GiB
2018-10-24 19:49:40.238960: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1490] Adding visible gpu devices: 0, 1
2018-10-24 19:49:41.287661: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-10-24 19:49:41.287712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977]      0 1 
2018-10-24 19:49:41.287733: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0:   N Y 
2018-10-24 19:49:41.287748: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 1:   Y N 
2018-10-24 19:49:41.288287: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1103] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9694 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:05:00.0, compute capability: 6.1)
2018-10-24 19:49:41.434704: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1103] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 10405 MB memory) -> physical GPU (device: 1, name: GeForce GTX 1080 Ti, pci bus id: 0000:06:00.0, compute capability: 6.1)
2018-10-24 19:49:44.406950: E tensorflow/stream_executor/cuda/cuda_dnn.cc:343] Loaded runtime CuDNN library: 7.0.5 but source was compiled with: 7.2.1.  CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library.  If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
Segmentation fault

您能提供正确的命令吗？

Answer 1

我也有同样的问题，下面的方法很好。

pip3 uninstall tensorflow-gpu

pip3 install tensorflow-gpu==1.9.0

注意:我使用的是'pip3‘，因为我使用python-3.x，如果您使用python-2.x，可以使用'pip’来代替。

Answer 2

我也遇到了同样的问题，我通过安装回溯中建议的CuDNN库来解决这个问题(加载的运行时cuDNN库: 7.0.5，但是源代码是用:7.2.1编译的)。

我用cuDNN v7.2.1 (2018年8月7日)代替了CUDA 9.2的cuDNN版本，它对我很有用。这样，您可以维护您的tensorflow-gpu版本。

您可以从cuDNN Archive：https://developer.nvidia.com/rdp/cudnn-archive获得这个库

确保您的整个配置与一个经过测试的构建配置相匹配：https://www.tensorflow.org/install/source_windows#tested_构建_配置 https://www.tensorflow.org/install/source#tested_构建_配置

Answer 3

请在带有Tensorflow版本的terminal....problem中键入这个

sudo pip安装-升级-强制-重新安装tensorflow-gpu=1.9.0