張量流錯誤 CUDA驅動程序版本不足於CUDA運行時版本

Question

我收到錯誤消息：

Python 3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 17:14:51)
[GCC 7.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
2018-08-14 14:35:53.739970: I         tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-08-14 14:35:53.948699: 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
2018-08-14 14:35:53.949210: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1405] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8755
pciBusID: 0000:00:05.0
totalMemory: 11.17GiB freeMemory: 11.11GiB
2018-08-14 14:35:53.949241: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1484] Adding visible gpu devices: 0
2018-08-14 14:35:53.949419: 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 "/usr/local/anaconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1494, in __init__
super(Session, self).__init__(target, graph, config=config)
  File "/usr/local/anaconda3/envs/tensorflow/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.

在以下環境中進行操作。

• Tesla K80 GPU機器
• Ubuntu 16.04
• CUDA 9.0
• cudnn7 = 7.1.4.18
• 的Python 3.6.6
• 張量流1.10

有人可以幫幫我嗎？

Answer 1

您需要更新GPU驅動程序。 CUDA 9.0需要驅動程序版本384.XX。

請參閱此處： nvidia 304.125的cuda版本是什么