機械学習を試してみようと思いTensorFlowを導入しようとしたが少しハマったため、記録しておく
バージョン
CentOS：7.5
TensorFlow：1.8.0
CUDA： 9.1
cuDNN：7.1.3
最初次のサイトを参考にして導入しようとしたが、CUDAのバージョンが9.0じゃないと動作しないため、ソースからインストールを行った。
ソースからインストールするのに参考にしたのは下記のサイトです。
Installing TensorFlow from Sources
実際に導入した際の手順
- Gitからtensorflowを得る
$ git clone https://github.com/tensorflow/tensorflow - Bazelをインストールする
通常のリポジトリからではBazelは導入できないため、リポジトリを追加してインストールを行う$ wget https://copr.fedorainfracloud.org/coprs/vbatts/bazel/repo/epel-7/vbatts-bazel-epel-7.repo $ sudo mv vbatts-bazel-epel-7.repo /etc/yum.repos.d/ $ sudo yum install bazel
- 手順1でダウンロードしたディレクトリに移動し、設定する
$ cd tensorflow $ ./configure WARNING: Running Bazel server needs to be killed, because the startup options are different. You have bazel 0.13.0- (@non-git) installed. Please specify the location of python. [Default is /home/{User}/.pyenv/versions/anaconda3-5.1.0/envs/tensorflow/bin/python]: Found possible Python library paths: /home/yuya/.pyenv/versions/anaconda3-5.1.0/envs/tensorflow/lib/python3.6/site-packages Please input the desired Python library path to use. Default is [/home/{User}/.pyenv/versions/anaconda3-5.1.0/envs/tensorflow/lib/python3.6/site-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]: 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 Amazon S3 File System support? [Y/n]: n No Amazon S3 File System support will be enabled for TensorFlow. Do you wish to build TensorFlow with Apache Kafka Platform support? [Y/n]: n No 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]: 9.1 Please specify the location where CUDA 9.1 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]: 7.1.3 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. [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: 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 - ビルド実施
次のようにリンクを貼らないとエラーが起こるので次のコマンドを実行する
$ sudo ln -s /usr/local/cuda/include/crt/math_functions.hpp /usr/local/cuda/include/math_functions.hpp
ビルド開始$ bazel build --config=mkl --config=monolithic --config=cuda //tensorflow/tools/pip_package:build_pip_package (...省略... ) ./tensorflow/core/kernels/cwise_ops.h(199): warning: __device__ annotation on a defaulted function("scalar_right") is ignored Target //tensorflow/tools/pip_package:build_pip_package up-to-date: bazel-bin/tensorflow/tools/pip_package/build_pip_package INFO: Elapsed time: 2151.254s, Critical Path: 168.00s INFO: 5277 processes, local. INFO: Build completed successfully, 5387 total actions - パッケージの作成
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg - パッケージからインストール
$ pip install /tmp/tensorflow_pkg/tensorflow-1.8.0-cp36-cp36m-linux_x86_64.whl - 正常にインストールできたか確認
$ python Python 3.6.4 |Anaconda, Inc.| (default, Mar 13 2018, 01:15:57) [GCC 7.2.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import tensorflow as tf >>> hello = tf.constant('Hello, TensorFlow!') 2018-05-12 21:22:39.196485: E tensorflow/core/framework/op_kernel.cc:1242] OpKernel ('op: "_MklConv2DWithBiasBackpropBias" device_type: "CPU" constraint { name: "T" allowed_values { list { type: DT_FLOAT } } } label: "MklOp"') for unknown op: _MklConv2DWithBiasBackpropBias >>> sess = tf.Session() 2018-05-12 21:22:39.199427: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-12 21:22:39.371104: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1349] Found device 0 with properties: name: GeForce GTX 1080 major: 6 minor: 1 memoryClockRate(GHz): 1.911 pciBusID: 0000:02:00.0 totalMemory: 7.92GiB freeMemory: 6.96GiB 2018-05-12 21:22:39.371163: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1428] Adding visible gpu devices: 0 2018-05-12 21:22:39.614577: I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] Device interconnect StreamExecutor with strength 1 edge matrix: 2018-05-12 21:22:39.614618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:922] 0 2018-05-12 21:22:39.614628: I tensorflow/core/common_runtime/gpu/gpu_device.cc:935] 0: N 2018-05-12 21:22:39.614806: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1046] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6721 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080, pci bus id: 0000:02:00.0, compute capability: 6.1) 2018-05-12 21:22:39.690978: I tensorflow/core/common_runtime/process_util.cc:64] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance. >>> print(sess.run(hello)) b'Hello, TensorFlow!'
以上！
