centos6 安装 tensorflow
2018-03-19 本文已影响0人
cfnju
目标
在centos6 cpu环境安装tensorflow
系统环境：
lsb_release -a
LSB Version: :base-4.0-amd64:base-4.0-noarch:core-4.0-amd64:core-4.0-noarch:graphics-4.0-amd64:graphics-4.0-noarch:printing-4.0-amd64:printing-4.0-noarch
Distributor ID: CentOS
Description: CentOS release 6.9 (Final)
Release: 6.9
Codename: Final
安装过程
通过anaconda来安装
# wiki: https://blog.abysm.org/2016/06/building-tensorflow-centos-6/
# https://docs.anaconda.com/anaconda/install/linux
wget https://repo.continuum.io/archive/Anaconda2-5.1.0-Linux-x86_64.sh
# for cpu version
conda install tensorflow
问题1： 提示tensorflow存在冲突，通过conda info tensorflow查看，存在多个版本
解决方案：conda install -c conda-forge tensorflow
查看官方文档 https://anaconda.org/conda-forge/tensorflow, 给出的安装命令如下
conda install -c conda-forge tensorflow
# 提示有新版本，于是升级conda先：
conda update -n base conda
# 结束后，继续安装
conda install -c conda-forge tensorflow
问题2： 网络原因导致部分组件安装失败
Downloading and Extracting Packages
openssl 1.0.2n: ######6 | 4%
tensorflow 1.5.0: | 0%
libprotobuf 3.5.2: | 0%
CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://conda.anaconda.org/conda-forge/linux-64/openssl-1.0.2n-0.tar.bz2>
Elapsed: -
An HTTP error occurred when trying to retrieve this URL.
HTTP errors are often intermittent, and a simple retry will get you on your way.
CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://conda.anaconda.org/conda-forge/linux-64/tensorflow-1.5.0-py27_0.tar.bz2>
Elapsed: -
An HTTP error occurred when trying to retrieve this URL.
HTTP errors are often intermittent, and a simple retry will get you on your way.
CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-3.5.2-0.tar.bz2>
Elapsed: -
An HTTP error occurred when trying to retrieve this URL.
HTTP errors are often intermittent, and a simple retry will get you on your way.
解决方案：下载压缩包之后，离线安装
conda install --offline ./libprotobuf-3.5.2-0.tar.bz2
conda install --offline ./openssl-1.0.2n-0.tar.bz2
conda install --offline ./tensorflow-1.5.0-py27_0.tar.bz2
试用
import tensorflow as tf 报错如下：
Python 2.7.14 |Anaconda custom (64-bit)| (default, Dec 7 2017, 17:05:42)
[GCC 7.2.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/root/anaconda2/lib/python2.7/site-packages/tensorflow/__init__.py", line 24, in <module>
from tensorflow.python import *
File "/root/anaconda2/lib/python2.7/site-packages/tensorflow/python/__init__.py", line 52, in <module>
from tensorflow.core.framework.graph_pb2 import *
File "/root/anaconda2/lib/python2.7/site-packages/tensorflow/core/framework/graph_pb2.py", line 6, in <module>
from google.protobuf import descriptor as _descriptor
File "/root/anaconda2/lib/python2.7/site-packages/google/protobuf/descriptor.py", line 46, in <module>
from google.protobuf.pyext import _message
ImportError: /root/anaconda2/lib/python2.7/site-packages/google/protobuf/pyext/_message.so: undefined symbol: _ZNK6google8protobuf10TextFormat17FieldValuePrinter9PrintBoolB5cxx11Eb
>>> quit()
解决方案：
推测是pb的版本有问题，于是
conda update libprotobuf
Solving environment: | done
## Package Plan ##
environment location: /root/anaconda2
added / updated specs:
- libprotobuf
The following packages will be downloaded:
package | build
---------------------------|-----------------
libprotobuf-3.5.1 | h6f1eeef_0 4.2 MB
The following packages will be DOWNGRADED:
libprotobuf: 3.5.2-0 <unknown> --> 3.5.1-h6f1eeef_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
libprotobuf 3.5.1: ##############################################################################################################2 | 69% libprotobuf 3.5.1: ############################################################################################################################################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
再次尝试import：pass
Python 2.7.14 |Anaconda custom (64-bit)| (default, Dec 7 2017, 17:05:42)
[GCC 7.2.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
/root/anaconda2/lib/python2.7/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
>>>
运行demo的过程中出现的其它warning
>>> sess = tf.Session()
2018-03-20 21:31:25.376805: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX
搜索了一下，这不是error，只是提示从源代码编译的tensorflow可能会更加快
This isn't an error, just warnings saying if you build TensorFlow from source it can be faster on your machine.
SO question about this: [http://stackoverflow.com/questions/41293077/how-to-compile-tensorflow-with-sse4-2-and-avx-instructions](http://stackoverflow.com/questions/41293077/how-to-compile-tensorflow-with-sse4-2-and-avx-instructions)
TensorFlow guide to build from source: [https://www.tensorflow.org/install/install_sources](https://www.tensorflow.org/install/install_sources)
