bazel

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: building tf (following this ) ./configure && bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package fails: root@commandor:/opt/tf/sc/tensorflow# bazel build --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --config=opt //tensorflow/tools/pip_package:build_pip_package WARNING: /home/ertosns/.cache/bazel/_bazel_root/502c46fd2b7f9ff136e0381cc7e075fe/external/protobuf_archive/WORKSPACE:1: Workspace name in /home/ertosns/.cache/bazel/_bazel_root/502c46fd2b7f9ff136e0381cc7e075fe/external/protobuf_archive/WORKSPACE (@com_google_protobuf)

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I built bazel-0.4.0 successfully. Then I tried upgrading it to the latest version bazel-0.5.1 using $ ./compile.sh compile ../bazel-0.4.0/output/bazel.exe It's giving me an error, bazel-0.5.0 , bazel-0.4.5 gave me same error ERROR LOG: bazel-0.4.4 gave me different error ERROR LOG: 回答1: If you already have bazel installed, you can upgrade by running bazel build //src:bazel on a fresh clone of the git repository . Or just download distribution archive and run ./compile . Details: https://bazel.build/versions/master/docs/install-compile-source

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I want to create a Bazel C++ project with gtest for unit tests. What is the minimal setup? (I only have Bazel installed on my computer and I am running under Linux) 回答1: The project structure is: Files related to Bazel+GTest WORKSPACE There you download gtest from github: new_git_repository( name = "googletest", build_file = "gmock.BUILD", remote = "https://github.com/google/googletest", tag = "release-1.8.0", ) You define a gmock BUILD file defined below: gmock.BUILD This BUILD file is in charge of compiling gtest/gmock: cc_library( name =

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I try to build tensorflow-serving using bazel but I've encountered some errors during the building ERROR:/private/var/tmp/_bazel_Kakadu/3f0c35881c95d2c43f04614911c03a57/external/local_config_cc/BUILD:49:5: in apple_cc_toolchain rule @local_config_cc//:cc-compiler-darwin_x86_64: Xcode version must be specified to use an Apple CROSSTOOL. ERROR: Analysis of target '//tensorflow_serving/sources/storage_path:file_system_storage_path_source_proto' failed; build aborted. I've already tried to use bazel clean and bazel clean --expunge but it didn't

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: Trying to run tensorflow on Raspberry PI 3B. Following the Guide on: https://github.com/samjabrahams/tensorflow-on-raspberry-pi/blob/master/GUIDE.md#3-build-bazel Everything goes fine until the following step: pi@raspberrypi:~/tf/tensorflow $ bazel build -c opt --jobs 1 --copt="-mfpu=neon-vfpv4" --copt="-funsafe-math-optimizations" --copt="-ftree-vectorize" --copt="-fomit-frame-pointer" --local_resources 1024,1.0,1.0 --verbose_failures tensorflow/tools/pip_package:build_pip_package gcc is 4.8, bazel is 5.4 Raspbian 9 (Stretch) ERROR: /home

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: 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. 回答1: I was not able to find a way to get coverage.dat

在使用tensorflow这个功能时候需要先下载tensorflow的源代码： git clone https: //github.com/tensorflow/tensorflow.git 进入tensorflow根目录，这里使用tools文件下的两个工具进行量化压缩：graph_transforms、quantization。 安装bazel进行tensorflow工具包的编译。 这里需要注意的是，bazel最好使用最新的，这样编译tensorflow就不会报接口未部署的一些错误。 Linux安装bazel： https://github.com/bazelbuild/bazel/release 找到bazel-x.x.x-installer-linux-x86_64.sh下载到本地并安装。可以按照git的安装方法进行安装。 安装完毕后开始进行编译tensorflow： bazel build tensorflow/tools/graph_transforms:transform_graph bazel build tensorflow/tools/quantization:quantize_graph 编译需要占据很多内存以及cpu资源，建议在性能好点的机器上编译。 编译完成后使用： bazel - bin/tensorflow/tools/graph_transforms

编写此文主要为了介绍在Ubuntu16.04上搭建Tensorflow-lite编译环境，涉及目标硬件为Armv7架构，8核Cortex-A7。 1、开发环境介绍： OS：Ubuntu16.04 64位 目标平台：Armv7 交叉工具链：gcc-linaro-arm-linux-gnueabihf-4.9-2014.9_linux Tensorflow版本：2.0.0 2、下载Tensorflow git clone https://github.com/tensorflow/tensorlfow.git 3、安装Bazel 打开网页，使用第一种方法：Use the binary installer https://docs.bazel.build/versions/master/install-ubuntu.html 1) sudo apt-get install pkg-config zip g++ zlib1g-dev unzip python3 2)打开链接： https://github.com/bazelbuild/bazel/releases ，下载最新sh文件： bazel-0.29.0-installer-linux-x86_64.sh 3)运行Bazel：chmod +x bazel-0.29.0-installer-linux-x86_64.sh .

tensorflow官方网站变为： https://tensorflow.google.cn/ CUDA: cat /usr/local/cuda/version.txt cuDNN: cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2 1. keras tensorflow 1.5 和 keras 2.1.4搭配 tensorflow 1.4 和 keras2.1.3搭配 tensorflow 1.3 和keras 2.1.2 搭配 tensorflow 1.2 和keras 2.1.1搭配 版本 Python 版本 编译器 编译工具 cuDNN CUDA tensorflow_gpu-2.0.0-alpha0 2.7、3.3-3.6 GCC 4.8 Bazel 0.19.2 7.4.1以及更高版本 CUDA 10.0 (需要 410.x 或更高版本) tensorflow_gpu-1.13.0 2.7、3.3-3.6 GCC 4.8 Bazel 0.19.2 7.4 10 tensorflow_gpu-1.12.0 2.7、3.3-3.6 GCC 4.8 Bazel 0.15.0 7 9 tensorflow_gpu-1.11.0 2.7、3.3-3.6 GCC 4.8 Bazel 0.15.0 7 9