运行命令“bazel build tensorflow/examples/image_Retaining:Retain”时生成失败

Question

我正在尝试在Ubuntu14.04 LTS上使用Python2.7构建tensorflow，没有GPU。当我在终端上运行本教程中的以下命令时：

bazel build tensorflow/examples/image_retraining:retrain

它说无法使用日志进行构建：

ERROR: /home/yuan/tensorflow_source/tensorflow/tensorflow/python/BUILD:1826:1: Linking of rule '//tensorflow/python:_pywrap_tensorflow.so' failed: gcc failed: error executing command 
  (cd /home/yuan/.cache/bazel/_bazel_yuan/e5b8b6538ba16bbae5b1e0f5c26b7a12/execroot/tensorflow && \
  exec env - \
  /usr/bin/gcc -shared -o bazel-out/local-fastbuild/bin/tensorflow/python/_pywrap_tensorflow.so -Wl,--version-script tensorflow/tf_version_script.lds -pthread -Wl,-no-as-needed -B/usr/bin -B/usr/bin -pass-exit-codes '-Wl,--build-id=md5' '-Wl,--hash-style=gnu' -Wl,-S -Wl,@bazel-out/local-fastbuild/bin/tensorflow/python/_pywrap_tensorflow.so-2.params): com.google.devtools.build.lib.shell.BadExitStatusException: Process exited with status 1.
bazel-out/local-fastbuild/bin/tensorflow/core/libversion_lib.a(version_info.pic.o): In function `tf_git_version()':
version_info.cc:(.text+0x0): multiple definition of `tf_git_version()'
bazel-out/local-fastbuild/bin/tensorflow/core/libframework_internal.lo(version_info.pic.o):version_info.cc:(.text+0x0): first defined here
bazel-out/local-fastbuild/bin/tensorflow/core/libversion_lib.a(version_info.pic.o): In function `tf_compiler_version()':
version_info.cc:(.text+0xd): multiple definition of `tf_compiler_version()'
bazel-out/local-fastbuild/bin/tensorflow/core/libframework_internal.lo(version_info.pic.o):version_info.cc:(.text+0xd): first defined here
collect2: error: ld returned 1 exit status
Target //tensorflow/examples/image_retraining:retrain failed to build
INFO: Elapsed time: 52.885s, Critical Path: 34.63s

这是我的构建环境：

OS:Ubuntu14.04 LTS 64位内存12Gib
gcc版本：4.8.4
python版本：2.7.6
bazel版本：0.3.2
git版本的tensorflow源代码：v0。11.0rc0-1541-g3737ac3

有人有办法修复这个错误吗？谢谢！

Answer 1

@David谢谢你的帮助，看来我的./配置结果不如预期。

我最终通过以下步骤成功构建了

>

将张量流源同步到HEAD

快跑/重新配置，如果有任何错误，请参考此。

再次运行build命令

bazel build tensorflow/示例/图像再培训：再培训

我的构建结果不会有错误。