1 安裝Python3 的依賴
sudo apt-get install python3-numpy python3-dev python3-pip python3-wheel２從源碼安裝Bazel
sudo apt-get install openjdk-8-jdk.
從 release page 下載最新版的安裝包
tar -zxvf bazelXXXX.tgz -C bazel
cd bazel
bash ./compile.sh
cp out/bazel /usr/bin/3 從源碼安裝TensorFlow
$ git clone https://github.com/tensorflow/tensorflow
$ cd tensorflow
$ git checkout Branch # where Branch is the desired branch(like v1.2.1)
$ ./configure
Please specify the location of python. [Default is /usr/local/bin/python]: /usr/bin/python3
Found possible Python library paths:
/usr/local/lib/python3.4/dist-packages
/usr/lib/python3/dist-packages
Please input the desired Python library path to use. Default is [/usr/local/lib/python3.4/dist-packages]
/usr/lib/python3/dist-packages
Do you wish to build TensorFlow with MKL support? [y/N] y
MKL support will be enabled for TensorFlow
Do you wish to download MKL LIB from the web? [Y/n] n
Please specify the location where MKL is installed. [Default is /opt/intel/mklml]: /opt/intel/mkl
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]: -march=native
Do you wish to use jemalloc as the malloc implementation? [Y/n] y
jemalloc enabled
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
Extracting Bazel installation...
........
INFO: Starting clean (this may take a while). Consider using --async if the clean takes more than several minutes.
Configuration finished
$ bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 -k //tensorflow/tools/pip_package:build_pip_package
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
$ sudo pip3 install /tmp/tensorflow_pkg/XXX.whl(或者換成pip3 install --user /tmp/tensorflow_pkg/XXX.whl)其中 –copt=-mavx 等等參數使用SIMD指令集增強計算性能。實際測算大概有30%左右的性能提升
Installing with virtualenv
Take the following steps to install TensorFlow with Virtualenv:
Install pip and virtualenv by issuing one of the following commands:
$ sudo apt-get install python-pip python-dev python-virtualenv # for Python 2.7
$ sudo apt-get install python3-pip python3-dev python-virtualenv # for Python 3.n
Create a virtualenv environment by issuing one of the following commands:
$ virtualenv --system-site-packages targetDirectory # for Python 2.7
$ virtualenv --system-site-packages -p python3 targetDirectory # for Python 3.n
where targetDirectory specifies the top of the virtualenv tree. Our instructions assume that targetDirectory is ~/tensorflow, but you may choose any directory.
Activate the virtualenv environment by issuing one of the following commands:
$ source ~/tensorflow/bin/activate # bash, sh, ksh, or zsh
$ source ~/tensorflow/bin/activate.csh # csh or tcsh
The preceding source command should change your prompt to the following:
(tensorflow)$
Issue one of the following commands to install TensorFlow in the active virtualenv environment:
(tensorflow)$ pip install --upgrade tensorflow # for Python 2.7
(tensorflow)$ pip3 install --upgrade tensorflow # for Python 3.n
(tensorflow)$ pip install --upgrade tensorflow-gpu # for Python 2.7 and GPU
(tensorflow)$ pip3 install --upgrade tensorflow-gpu # for Python 3.n and GPU
If the preceding command succeeds, skip Step 5. If the preceding command fails, perform Step 5.
(Optional) If Step 4 failed (typically because you invoked a pip version lower than 8.1), install TensorFlow in the active virtualenv environment by issuing a command of the following format:
(tensorflow)$ pip install --upgrade tfBinaryURL # Python 2.7
(tensorflow)$ pip3 install --upgrade tfBinaryURL # Python 3.n
where tfBinaryURL identifies the URL of the TensorFlow Python package. The appropriate value of tfBinaryURLdepends on the operating system, Python version, and GPU support. Find the appropriate value for tfBinaryURL for your system here. For example, if you are installing TensorFlow for Linux, Python 2.7, and CPU-only support, issue the following command to install TensorFlow in the active virtualenv environment:
(tensorflow)$ pip3 install --upgrade \
https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.2.1-cp34-cp34m-linux_x86_64.whl
If you encounter installation problems, see Common Installation Problems.
Next Steps
After installing TensorFlow, validate the installation.
Note that you must activate the virtualenv environment each time you use TensorFlow. If the virtualenv environment is not currently active, invoke one of the following commands:
$ source ~/tensorflow/bin/activate # bash, sh, ksh, or zsh
$ source ~/tensorflow/bin/activate.csh # csh or tcsh
When the virtualenv environment is active, you may run TensorFlow programs from this shell. Your prompt will become the following to indicate that your tensorflow environment is active:
(tensorflow)$
When you are done using TensorFlow, you may deactivate the environment by invoking the deactivate function as follows:
(tensorflow)$ deactivate
The prompt will revert back to your default prompt (as defined by the PS1 environment variable).
Uninstalling TensorFlow
To uninstall TensorFlow, simply remove the tree you created. For example:
$ rm -r targetDirectory