<p>我在ubuntu16.04桌面上运行tensorflow。</p>
<p>我以前用GPU运行代码很好。<strong>但今天我找不到具有以下代码的gpu设备</p>
<p><code>
import tensorflow as tf
from tensorflow.python.client import device_lib as _device_lib
with tf.Session() as sess:
local_device_protos = _device_lib.list_local_devices()
print(local_device_protos)
[print(x.name) for x in local_device_protos]
</code></p>
<p>当我运行<code>tf.Session()</code>时,我意识到了下面的问题</p>
<blockquote>
<p>cuda_driver.cc:406] failed call to cuInit: CUDA_ERROR_UNKNOWN</p>
</blockquote>
<p>我在系统详细信息中检查我的Nvidia驱动程序,然后<code>nvcc -V</code>,<code>nvida-smi</code>检查驱动程序、cuda和cudnn。一切似乎都很好。</p>
<p>然后我去其他驱动程序检查驱动程序的详细信息,在那里我发现有许多版本的NVIDIA驱动程序和最新版本的选择。但当我第一次安装驱动程序时,只有一个。</p>
<p>所以我选择一个旧版本,并应用更改</p>
<p>然后我运行<code>tf.Session()</code>问题也在这里。我想我应该重新启动我的电脑,在我重新启动之后,这个问题就消失了。</p>
<p><code>
sess = tf.Session()
2018-07-01 12:02:41.336648: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-07-01 12:02:41.464166: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:898] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-07-01 12:02:41.464482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1356] Found device 0 with properties:
name: GeForce GTX 1070 major: 6 minor: 1 memoryClockRate(GHz): 1.8225
pciBusID: 0000:01:00.0
totalMemory: 7.93GiB freeMemory: 7.27GiB
2018-07-01 12:02:41.464494: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1435] Adding visible gpu devices: 0
2018-07-01 12:02:42.308689: I tensorflow/core/common_runtime/gpu/gpu_device.cc:923] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-07-01 12:02:42.308721: I tensorflow/core/common_runtime/gpu/gpu_device.cc:929] 0
2018-07-01 12:02:42.308729: I tensorflow/core/common_runtime/gpu/gpu_device.cc:942] 0: N
2018-07-01 12:02:42.309686: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1053] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7022 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1070, pci bus id: 0000:01:00.0, compute capability:
</code></p>