$ lsb_release -a No LSB modules are available. Distributor ID: Ubuntu Description: Ubuntu 18.04 LTS Release: 18.04 Codename: bionic
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$ gcc --version gcc (Ubuntu 7.3.0-16ubuntu3) 7.3.0 Copyright (C) 2017 Free Software Foundation, Inc. This is free software; see the sourcefor copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
$ ./configure WARNING: An illegal reflective access operation has occurred WARNING: Illegal reflective access by com.google.protobuf.UnsafeUtil (file:~/.cache/bazel/_bazel_jiapei/install/ce085f519b017357185750fe457b4648/_embedded_binaries/A-server.jar) to field java.nio.Buffer.address WARNING: Please consider reporting this to the maintainers of com.google.protobuf.UnsafeUtil WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations WARNING: All illegal access operations will be denied in a future release WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command"bazel shutdown". You have bazel 0.15.0 installed. Please specify the location of python. [Default is /usr/bin/python]:
Found possible Python library paths: /usr/local/lib/python3.6/dist-packages /usr/lib/python3/dist-packages Please input the desired Python library path to use. Default is [/usr/local/lib/python3.6/dist-packages]
Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]: Y jemalloc as malloc support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]: Y Google Cloud Platform support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Hadoop File System support? [Y/n]: Y Hadoop File System support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Amazon AWS Platform support? [Y/n]: Y Amazon AWS Platform support will be enabled for TensorFlow.
Do you wish to build TensorFlow with Apache Kafka Platform support? [Y/n]: Y Apache Kafka Platform support will be enabled for TensorFlow.
Do you wish to build TensorFlow with XLA JIT support? [y/N]: N No XLA JIT support will be enabled for TensorFlow.
Do you wish to build TensorFlow with GDR support? [y/N]: N No GDR 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 SYCL support? [y/N]: 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]: 9.2
Please specify the location where CUDA 9.2 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]: 7.1.4
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]: N No TensorRT support will be enabled for TensorFlow.
Please specify the NCCL version you want to use. [Leave empty to default to NCCL 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: 5.2]
Do you want to use clang as CUDA compiler? [y/N]: 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]: 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]: 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
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg Wed Jul 11 00:09:09 PDT 2018 : === Preparing sources indir: /tmp/tmp.5X0zsqfxYo /media/jiapei/Data/Downloads/machinelearning/deeplearning/tensorflow/tensorflow /media/jiapei/Data/Downloads/machinelearning/deeplearning/tensorflow/tensorflow /media/jiapei/Data/Downloads/machinelearning/deeplearning/tensorflow/tensorflow Wed Jul 11 00:09:35 PDT 2018 : === Building wheel warning: no files found matching '*.dll' under directory '*' warning: no files found matching '*.lib' under directory '*' warning: no files found matching '*.h' under directory 'tensorflow/include/tensorflow' warning: no files found matching '*' under directory 'tensorflow/include/Eigen' warning: no files found matching '*.h' under directory 'tensorflow/include/google' warning: no files found matching '*' under directory 'tensorflow/include/third_party' warning: no files found matching '*' under directory 'tensorflow/include/unsupported' Wed Jul 11 00:10:58 PDT 2018 : === Output wheel file is in: /tmp/tensorflow_pkg
Let's have a look at what's been built:
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$ ls /tmp/tensorflow_pkg/ tensorflow-1.9.0rc0-cp36-cp36m-linux_x86_64.whl
4.2 Pip Installation
And, let's have tensorflow-1.9.0rc0-cp36-cp36m-linux_x86_64.whl installed.
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$ pip3 install /tmp/tensorflow_pkg/tensorflow-1.9.0rc0-cp36-cp36m-linux_x86_64.whl Processing /tmp/tensorflow_pkg/tensorflow-1.9.0rc0-cp36-cp36m-linux_x86_64.whl Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (0.31.1) Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (0.2.0) Requirement already satisfied: numpy>=1.13.3 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (1.14.5) Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (0.7.1) Requirement already satisfied: six>=1.10.0 in ./.local/lib/python3.6/site-packages (from tensorflow==1.9.0rc0) (1.11.0) Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (1.13.0) Requirement already satisfied: absl-py>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (0.2.2) Requirement already satisfied: tensorboard<1.9.0,>=1.8.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (1.8.0) Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (1.1.0) Requirement already satisfied: setuptools<=39.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (39.1.0) Requirement already satisfied: protobuf>=3.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.9.0rc0) (3.6.0) Requirement already satisfied: bleach==1.5.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.9.0,>=1.8.0->tensorflow==1.9.0rc0) (1.5.0) Requirement already satisfied: html5lib==0.9999999 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.9.0,>=1.8.0->tensorflow==1.9.0rc0) (0.9999999) Requirement already satisfied: werkzeug>=0.11.10 in ./.local/lib/python3.6/site-packages (from tensorboard<1.9.0,>=1.8.0->tensorflow==1.9.0rc0) (0.14.1) Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.9.0,>=1.8.0->tensorflow==1.9.0rc0) (2.6.11) Successfully installed tensorflow-1.9.0rc0
Let's test if Tensorflow has been successfully installed.
4.3 Check Tensorflow
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$ python Python 3.6.5 (default, Apr 1 2018, 05:46:30) [GCC 7.3.0] on linux Type "help", "copyright", "credits" or "license"for more information. >>> import tensorflow as tf >>> tf.__version__ '1.9.0-rc0'
5. Keras Installation
After successfully check out Keras, we can easily have Keras installed by command python setup.py install.
Installed /usr/local/lib/python3.6/dist-packages/Keras-2.2.0-py3.6.egg Processing dependencies for Keras==2.2.0 Searching for Keras-Preprocessing==1.0.1 Best match: Keras-Preprocessing 1.0.1 Adding Keras-Preprocessing 1.0.1 to easy-install.pth file
Using /usr/local/lib/python3.6/dist-packages Searching for Keras-Applications==1.0.2 Best match: Keras-Applications 1.0.2 Adding Keras-Applications 1.0.2 to easy-install.pth file
Using /usr/local/lib/python3.6/dist-packages Searching for h5py==2.8.0 Best match: h5py 2.8.0 Adding h5py 2.8.0 to easy-install.pth file
Using /usr/local/lib/python3.6/dist-packages Searching for PyYAML==3.13 Best match: PyYAML 3.13 Adding PyYAML 3.13 to easy-install.pth file
Using /usr/local/lib/python3.6/dist-packages Searching for six==1.11.0 Best match: six 1.11.0 Adding six 1.11.0 to easy-install.pth file
Using /usr/lib/python3/dist-packages Searching for scipy==1.1.0 Best match: scipy 1.1.0 Adding scipy 1.1.0 to easy-install.pth file
Using /usr/local/lib/python3.6/dist-packages Searching for numpy==1.14.5 Best match: numpy 1.14.5 Adding numpy 1.14.5 to easy-install.pth file
Using /usr/local/lib/python3.6/dist-packages Finished processing dependencies for Keras==2.2.0
That's all for today. I think Python is seriously cool, handy indeed. I myself will still recommend Pytorch, but it seems Tensorflow and Keras are also very popular in North America.