Following this link
I already have NVIDIA drivers and CUDA installed. Won't be explaining them here.
Steps:
$ git clone https://github.com/tensorflow/tensorflow$ cd tensorflow$ git checkout- You need to install bazel. Follow these instructions
- Install
pip,dev,numpy&wheel.
$ sudo apt-get install python-numpy python-dev python-pip python-wheel
Note: I am installing tensorflow in python 2.7 - Configuring the build.
$ cd tensorflow # cd to the top-level directory created
$ ./configure
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.15.2 installed.
Please specify the location of python. [Default is /usr/bin/python]:
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/local/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 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]:
Please specify the location where CUDA 9.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-9.0
Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7.0]: 7.1
Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-9.0]:
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
- Now build a pip package for TensorFlow with GPU support
$ bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
You have to wait for several minutes. - After you get the message stating the build completed successfully, run
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
This creates the python package which you will be installing after it is created. - Check the wheel file created in the /tmp/tensorflow_pkg folder and install the package by
$ sudo pip install /tmp//tensorflow_pkg/tensorflow-1.9.0-cp27-cp27mu-linux_x86_64.whl
Note: The wheel file name may change with respect to the settings you have configured. - To check if tensorflow is installed and which version, run
pip freeze | grep tensorflow - To check if the tensorflow you have installed is GPU supported, go to python terminal and run
import tensorflow as tf
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))Output will have Adding visible gpu devices: 0, this line and will also print the kind of GPU you are using
Note: To get CUDNN version use
cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
Here 7.1 translates to 7 bring CUDNN_MAJOR version and 1 being CUDNN_MINOR version
My system configurations:
-
GCC
$ gcc --version gcc (Ubuntu 5.4.0-6ubuntu1~16.04.10) 5.4.0 20160609 Copyright (C) 2015 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. -
NVCC
$ /usr/local/cuda-9.0/bin/nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2017 NVIDIA Corporation Built on Fri_Sep__1_21:08:03_CDT_2017 Cuda compilation tools, release 9.0, V9.0.176 -
CUDNN
$ cat /usr/local/cuda-9.0/include/cudnn.h | grep CUDNN_MAJOR -A 2 #define CUDNN_MAJOR 7 #define CUDNN_MINOR 1 #define CUDNN_PATCHLEVEL 4 -- #define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#include "driver_types.h" -
NVIDIA driver
$ nvidia-smi Tue Jul 31 11:29:52 2018
+-----------------------------------------------------------------------------+ | NVIDIA-SMI 390.67 Driver Version: 390.67 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | |===============================+======================+======================| | 0 GeForce GTX 105... Off | 00000000:01:00.0 On | N/A | | 0% 45C P8 N/A / 72W | 953MiB / 4038MiB | 15% Default | +-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | 0 1058 G /usr/lib/xorg/Xorg 388MiB | | 0 1736 G /opt/teamviewer/tv_bin/TeamViewer 16MiB | | 0 1974 G compiz 216MiB | | 0 2415 G ...-token=9CCC21897D6A22D6A4C9020F56B9AEA3 329MiB | +-----------------------------------------------------------------------------+