bazel

编译 方法1： 1234567 ./configurebazel build --config=opt //tensorflow/tools/pip_package:build_pip_packagebuild出错清理：/root/.cache/bazel把下面的之前出错的缓存文件给删除掉生成whell包bazel-bin/tensorflow/tools/pip_package/build_pip_package /root/tensorflow/wheel_pkg/build_withSource 方法2： 1234 yes "" | python configure.pybazel build --config=mkl --copt=-mavx2 --copt=-O3 --copt=-DINTEL_MKL_QUANTIZED -s //tensorflow/tools/pip_package:build_pip_package生成whell包bazel-bin/tensorflow/tools/pip_package/build_pip_package /root/tensorflow/wheel_pkg/build_withSource 编译命令和过程分析 视频： https://www.youtube.com/watch?v=Rw-KrbfyABQ https://www

编译 方法1： 1234567 ./configurebazel build --config=opt //tensorflow/tools/pip_package:build_pip_packagebuild出错清理：/root/.cache/bazel把下面的之前出错的缓存文件给删除掉生成whell包bazel-bin/tensorflow/tools/pip_package/build_pip_package /root/tensorflow/wheel_pkg/build_withSource 方法2： 1234 yes "" | python configure.pybazel build --config=mkl --copt=-mavx2 --copt=-O3 --copt=-DINTEL_MKL_QUANTIZED -s //tensorflow/tools/pip_package:build_pip_package生成whell包bazel-bin/tensorflow/tools/pip_package/build_pip_package /root/tensorflow/wheel_pkg/build_withSource 编译命令和过程分析 视频： https://www.youtube.com/watch?v=Rw-KrbfyABQ https://www

This is like a follow up question from Build an android app using Tensorflow . I'd like to separate the android example project from tensorflow git repo and be able to build it separately with tensorflow as a dependency. This is my folder structure my_project |-- WORKSPACE |-- android | |-- BUILD | `-- ... |-- tensorflow | |-- tensorflow | | | |-- workspace.bzl | | | |-- tensorflow.bzl | | | `-- ... | |-- WORKSPACE | |-- BUILD . `-- ... where android app is just a copy of Tensorflow Android example . The root WORKSPACE file has following contents: workspace(name = "my_android_app") local

I have access to a large IBM Power8 machine, and would like to install TensorFlow on it. Naturally, I tried the quick pip install, but it failed: sudo pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.6.0-cp27-none-linux_x86_64.whl tensorflow-0.6.0-cp27-none-linux_x86_64.whl is not a supported wheel on this platform. Storing debug log for failure in /home/pv/.pip/pip.log Unfortunately, pip.log cotains little useful info. /usr/bin/pip run on Sat Feb 6 17:29:34 2016 tensorflow-0.6.0-cp27-none-linux_x86_64.whl is not a supported wheel on this platform. Exception

源码安装tf的时候，会用到Bazel，版本不对应，后面会引起好多麻烦。 echo "deb [arch=amd64] http://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list curl https://bazel.build/bazel-release.pub.gpg | sudo apt-key add - sudo apt-get update sudo apt-get install bazel 这种安装方式，会把bazel更新到最新的版本，但是编译tensorflow的时候，不同tensorflow要与bazel的版本是对应的，如果这么做的话，后面的操作就会出错，可能还不知道怎么解决。 正确的做法应该是下载对应的版本来安装bazel，tensorflow与bazel的版本应该在tensorflow的官网查找： https://tensorflow.google.cn/install/source linux下tensorflow与python、GCC、Bazel的版本关系，GCC一般支持C++11就可以，但bazel就真的还是要对应好版本，不然一大堆问题，会掉进坑里各种折腾。 Bazel 编译选项 从源代码编译 TensorFlow

Problem Statement: I would like to use Golang TensorFlow to run my model in Raspberry PI 3. To use TensorFlow go, I need to have libtensorflow.so and libtensorflow_framework.so c++ shared library. I was trying to build from source using bazel v0.20.0 but facing a problem and its erroring out at last. Goal: Build libtensorflow.so for tensorflow r1.11.0 or r1.12.0 Any help is appreciated. I found solution: Couple of things to take care. ***For Tensorflow < v1.5*** Follow instruction here: https://blog.meinside.pe.kr/TensorFlow-and-Go-on-Raspberry-Pi/ ***For Tensorflow v1.11.0 - v1.12.0***

u@u160406:~/tf1.13/tensorflow$ git checkout r1.13 分支 r1.13 设置为跟踪来自 origin 的远程分支 r1.13。 切换到一个新分支 'r1.13' u@u160406:~/tf1.13/tensorflow$ ./configure WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown". You have bazel 0.24.1 installed. Please downgrade your bazel installation to version 0.21.0 or lower to build TensorFlow! u@u160406:~/tf1.13/tensorflow$ git checkout r1.15 分支 r1.15 设置为跟踪来自 origin 的远程分支 r1.15。 切换到一个新分支 'r1.15' u@u160406:~/tf1.13/tensorflow$ ./configure WARNING: --batch mode is deprecated. Please instead

I am using genhtml command to generate html coverage report from Bazel generated coverage.dat file: genhtml bazel-testlogs/path/to/TestTarget/coverage.dat --output-directory coverage The problem with using genhtml is that I have to provide the paths to the coverage.dat files (which are generated in bazel-testlogs/..) Is it possible to fetch those coverage.dat files as an output from another rule? I would like to not have to call genthml command directly, but have Bazel handle everything. I was not able to find a way to get coverage.dat files as an output of a bazel rule. However, I was able to