tensorflow-gpu 在 LINUX 上运行失败

Question

我已经在 ubuntu 16.04 上安装了 CUDA 和 cuDnn。

CUDA 版本 : 9.0 // 带有驱动程序版本 390.87

cuDNN 版本：7.2 for CUDA9.0

import tensorflow as tf

工作正常，但是

tf.Session() 

呈现以下错误。

2018-09-15 16:43:23.281375: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2018-09-15 16:43:23.281431: E tensorflow/core/common_runtime/direct_session.cc:158] Internal: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
Traceback (most recent call last):
 File "<stdin>", line 1, in <module>
 File "/home/imhgchoi/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1494, in __init__
super(Session, self).__init__(target, graph, config=config)
 File "/home/imhgchoi/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 626, in __init__
self._session = tf_session.TF_NewSession(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: Failed to create session.

错误消息暗示我安装了错误版本的 CUDA 驱动程序，但我迷路了。我不确定要采取什么措施来纠正这种情况。

---

添加环境变量后

这只会增加新的错误..

2018-09-15 17:13:39.684390: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2018-09-15 17:13:39.767963: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:897] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-09-15 17:13:39.768481: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1405] Found device 0 with properties: 
name: GeForce GTX 1050 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.506
pciBusID: 0000:09:00.0
totalMemory: 3.94GiB freeMemory: 3.41GiB
2018-09-15 17:13:39.768502: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2018-09-15 17:13:39.768635: E tensorflow/core/common_runtime/direct_session.cc:158] Internal: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version

Answer 1

也许是你的环境变量导致了这个问题。 试试这个：

在你的 ~/.bashrc 文件末尾添加这些行并打开一个终端并简单地在那里启动一个 python 会话然后导入 tensorflow（你应该通过 apt 安装 tensporflow-gpu）并查看它是否有效：

sudo vim ~/.bashrc

并在文件末尾添加这些并重新启动终端：

export CUDA_HOME="/usr/local/cuda-9.0"
export LD_LIBRARY_PATH="${CUDA_HOME}/lib64"
export PATH="${CUDA_HOME}/bin:${PATH}"
export DYLD_LIBRARY_PATH="${CUDA_HOME}/lib"

编辑.1

请确保“usr/local/cuda-9.0”是您安装cuda的目录。