来源:
https://www.tensorflow.org/install/source
#安装 Python 和 TensorFlow 软件包依赖项
#ubuntu
sudo apt install python-dev python-pip # or python3-dev python3-pip
#安装 TensorFlow pip 软件包依赖项（如果使用虚拟环境，请省略 --user 参数）
pip3 install -U --user pip six numpy wheel setuptools mock future>=0.17.1 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip3 install -U --user keras_applications==1.0.6 --no-deps
pip3 install -U --user keras_preprocessing==1.0.5 --no-deps来源:
https://docs.bazel.build/versions/master/install.html
#ubuntu
##Step 1: Install required packages
####################################
# Ubuntu 16.04 (LTS) uses OpenJDK 8 by default:
sudo apt-get install openjdk-8-jdk
# Ubuntu 18.04 (LTS) uses OpenJDK 11 by default:
sudo apt-get install openjdk-11-jdk
#Step 2: Run the installe
################################
#Next, download the Bazel binary installer named bazel-<version>-installer-linux-x86_64.sh from the Bazel releases page on GitHub.
# https://github.com/bazelbuild/bazel/releases
https://github.com/bazelbuild/bazel/releases?after=0.18.1
######
##注意:tensflow 1.10.0 版本与bazel版本对应:
##官方参考:https://www.tensorflow.org/install/source#linux
## tensorflow-1.10.0 2.7、3.3-3.6 GCC 4.8 Bazel 0.15.0
#####
Run it as follows:
chmod +x bazel-<version>-installer-linux-x86_64.sh
./bazel-<version>-installer-linux-x86_64.sh --user
The --user flag installs Bazel to the $HOME/bin directory on your system and sets the .bazelrc path to $HOME/.bazelrc. Use the --help command to see additional installation options.
#Step 3: Set up your environment
#############################################
export PATH="$PATH:$HOME/bin"
You can also add this command to your ~/.bashrc or ~/.zshrc file to make it permanent.
可参考这里的配置: no AVX instruction
https://github.com/naruai/wiki/blob/master/TensorFlow/BuildTensorFlowWOAVX.md
./configure 配置选项:
###########################################
# ./configure
Extracting Bazel installation...
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.25.2 installed.
Please specify the location of python. [Default is /usr/bin/python]:
Found possible Python library paths:
/usr/lib/python3/dist-packages
/usr/local/lib/python3.6/dist-packages
Please input the desired Python library path to use. Default is [/usr/lib/python3/dist-packages]
################
Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
--config=mkl # Build with MKL support.
--config=monolithic # Config for mostly static monolithic build.
--config=gdr # Build with GDR support.
--config=verbs # Build with libverbs support.
--config=ngraph # Build with Intel nGraph support.
--config=numa # Build with NUMA support.
--config=dynamic_kernels # (Experimental) Build kernels into separate shared objects.
Preconfigured Bazel build configs to DISABLE default on features:
--config=noaws # Disable AWS S3 filesystem support.
--config=nogcp # Disable GCP support.
--config=nohdfs # Disable HDFS support.
--config=noignite # Disable Apache Ignite support.
--config=nokafka # Disable Apache Kafka support.
--config=nonccl # Disable NVIDIA NCCL support.
Configuration finished
./configure
You have bazel 0.15.0 installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python2.7
Found possible Python library paths:
/usr/local/lib/python2.7/dist-packages
/usr/lib/python2.7/dist-packages
Please input the desired Python library path to use. Default is [/usr/lib/python2.7/dist-packages]
Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]:
jemalloc as malloc support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]:
Google Cloud Platform support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Hadoop File System support? [Y/n]:
Hadoop File System support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Amazon AWS Platform support? [Y/n]:
Amazon AWS Platform support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Apache Kafka Platform support? [Y/n]:
Apache Kafka Platform support will be enabled for TensorFlow.
Do you wish to build TensorFlow with XLA JIT support? [y/N]:
No XLA JIT support will be enabled for TensorFlow.
Do you wish to build TensorFlow with GDR support? [y/N]:
No GDR support will be enabled for TensorFlow.
Do you wish to build TensorFlow with VERBS support? [y/N]:
No VERBS support will be enabled for TensorFlow.
Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]:
No OpenCL SYCL support will be enabled for TensorFlow.
Do you wish to build TensorFlow with CUDA support? [y/N]: Y
CUDA support will be enabled for TensorFlow.
Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 9.0]: 9.0
Please specify the location where CUDA 9.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7.0]: 7.0
Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Do you wish to build TensorFlow with TensorRT support? [y/N]:
No TensorRT support will be enabled for TensorFlow.
Please specify the NCCL version you want to use. If NCLL 2.2 is not installed, then you can use version 1.3 that can be fetched automatically but it may have worse performance with multiple GPUs. [Default is 2.2]: 1.3
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your
build time and binary size. [Default is: 3.5,7.0] 6.1
Do you want to use clang as CUDA compiler? [y/N]:
nvcc will be used as CUDA compiler.
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Do you wish to build TensorFlow with MPI support? [y/N]:
No MPI 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]:
Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]:
Not configuring the WORKSPACE for Android builds.
Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See tools/bazel.rc for more details.
--config=mkl # Build with MKL support.
--config=monolithic # Config for mostly static monolithic build.
Configuration finished
编译选项:来自https://github.com/naruai/wiki/blob/master/TensorFlow/BuildTensorFlowWOAVX.md
bazel build --local_ram_resources=2048 --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --config=opt --config=noaws --config=nonccl //tensorflow/tools/pip_package:build_pip_package bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package
仅仅支持cpu
bazel build 命令会创建一个名为 build_pip_package 的可执行文件，此文件是用于编译 pip 软件包的程序。请如下所示地运行该可执行文件，以在 /tmp/tensorflow_pkg 目录中编译 .whl 软件包
# ./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
# cp /tmp/tensorflow_pkg/tensorflow-1.14.0-cp36-cp36m-linux_x86_64.whl /tfwork/ pip install /tmp/tensorflow_pkg/tensorflow-version-tags.whl
安装Python3 环境
yum -y install python3-dev python3-pip安装gcc
yum -y install gcc 安装patch
sudo yum install patchgc++
yum install gcc-c++缺少Python.h
yum install -y python3-devel.x86_64
必须把 Python.h 所在目录下了所有头文件都保存到 /usr/include/ 下安装bzael
1,Download the corresponding .repo file from Fedora COPR and copy it to /etc/yum.repos.d/.
https://copr.fedorainfracloud.org/coprs/vbatts/bazel/repo/epel-7/vbatts-bazel-epel-7.repo
2,Run the following command:
yum install bazelconfigur 时要指定python的位置,使用路径 如/usr/bin/python3
原文：https://www.cnblogs.com/g2thend/p/12452382.html