2017-05-22 38 views
1

guys!我想通過遵循Installing TensorFlow from Sources。經過步驟調用以下命令建立一個PIP封裝tensorflow:$ bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package,但是,我得到了這些如下:Bazel問題,同時只用CPU支持構建TensorFlow的pip程序包

ERROR: error loading package '': Encountered error while reading extension file 
'closure/defs.bzl': no such package '@io_bazel_rules_closure//closure': Error do 
wnloading [http://mirror.bazel.build/github.com/bazelbuild/rules_closure/archive 
/aac19edc557aec9b603cd7ffe359401264ceff0d.tar.gz, https://github.com/bazelbuild/ 
rules_closure/archive/aac19edc557aec9b603cd7ffe359401264ceff0d.tar.gz] to /priva 
te/var/tmp/_bazel_WilliamHuang/75f5fa598a7d55b225c399e7e82a3908/external/io_baze 
l_rules_closure/aac19edc557aec9b603cd7ffe359401264ceff0d.tar.gz: All mirrors are 
down: []. 
INFO: Elapsed time: 58.126s 

我的./configure如下:

Do you wish to build TensorFlow with MKL support? [y/N] n 
No MKL support will be enabled for TensorFlow 
Please specify optimization flags to use during compilation when 
bazel option "--config=opt" is specified [Default is -march=native]: 
Do you wish to build TensorFlow with Google Cloud Platform support? 
[y/N] n 
No Google Cloud Platform support will be enabled for TensorFlow 
Do you wish to build TensorFlow with Hadoop File System support? 
[y/N] n 
No Hadoop File System support will be enabled for TensorFlow 
Do you wish to build TensorFlow with the XLA just-in-time compiler 
(experimental)? [y/N] n 
No XLA JIT support will be enabled for TensorFlow 
Do you wish to build TensorFlow with VERBS support? [y/N] n 
No VERBS support will be enabled for TensorFlow 
Do you wish to build TensorFlow with OpenCL support? [y/N] n 
No OpenCL support will be enabled for TensorFlow 
Do you wish to build TensorFlow with CUDA support? [y/N] n 
No CUDA support will be enabled for TensorFlow 

而且我巴澤爾的版本是0.4.5

Build label: 0.4.5-homebrew 

希望你們能幫我這個問題。提前致謝。

回答

0

我已經通過設置$ bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package之前代理的

export http_proxy=http://proxy_ip:port (e.g. export http_proxy=http://10.110.0.25:8888) 
export https_proxy=http://proxy_ip:port 
解決了這個問題
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