Failed linking MKL when buildng TensorFlow - tensorflow

Question

I try to build tensorflow v1.13 with MKL. The build is performed successfully, the pip package is correctly created, but when I test the package, MKL is clearly not used in the end, i.e. when I run in Python 3.6.8:
import tensorflow
print("Is MKL enabled?{}".format(tensorflow.pywrap_tensorflow.IsMklEnabled()))
It returns "False"
I am operating on CentOS 7 in the following conda environment:
# Name Version Build Channel
blas 1.0 mkl
ca-certificates 2019.1.23 0
certifi 2018.1.18 py36_2 intel
cloog 0.18.0 0
cython 0.29.6 py36he6710b0_0
gcc 4.8.5 7
gmp 6.1.2 h6c8ec71_1
icc_rt 2019.3 intel_199 intel
intel-openmp 2019.3 intel_199 intel
intelpython 2019.3 0 intel
isl 0.12.2 0
keras-applications 1.0.7 pypi_0 pypi
keras-preprocessing 1.0.9 pypi_0 pypi
libedit 3.1.20181209 hc058e9b_0
libffi 3.2.1 hd88cf55_4
libgcc-ng 8.2.0 hdf63c60_1
libgfortran-ng 7.3.0 hdf63c60_0
libstdcxx-ng 8.2.0 hdf63c60_1
mkl 2019.3 intel_199 intel
mkl-dnn 0.14 2 intel
mkl_fft 1.0.11 py36h7b7c402_0 intel
mkl_random 1.0.2 py36h7b7c402_4 intel
mock 2.0.0 py36_0
mpc 1.0.3 hec55b23_5
mpfr 3.1.5 h11a74b3_2
ncurses 6.1 he6710b0_1
numpy 1.16.2 py36h7e9f1db_0
numpy-base 1.16.2 py36hde5b4d6_0
openmp 2018.0.3 intel_0 intel
openssl 1.1.1b h7b6447c_1
pbr 5.1.3 py_0
pip 19.0.3 py36_0
python 3.6.8 h0371630_0
readline 7.0 h7b6447c_5
setuptools 40.8.0 py36_0
six 1.12.0 py36_0
sqlite 3.27.2 h7b6447c_0
tbb 2019.4 intel_199 intel
tk 8.6.8 hbc83047_0
wheel 0.33.1 py36_0
xz 5.2.4 h14c3975_4
zlib 1.2.11 h7b6447c_3
Bazel is in version 0.23.0
GCC is in version 7.3.1 (see below)
I use the following command lines to build the tensorflow package:
scl enable devtoolset-7 bash
bazel build --config=mkl --config=opt --copt=-march=x86-64 --copt=-mavx --copt=-msse4.1 --copt=-msse4.2 --copt=-O2 --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" //tensorflow/tools/pip_package:build_pip_package
./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
Obviously, many warnings occur, but none of them is related to MKL. Noteworthy, I am using GCC7 here. I tried GCC4 and GCC5. I am using
That didn't change the problem. Does someone have a clue about why MKL is not linked?

Answer 1

As tensorflow version==1.13 is the latest release ,it might not be stable(https://www.tensorflow.org/versions/)
It worked fine installing with tensorflow version==1.11 using the below steps.
git clone https://github.com/tensorflow/tensorflow
cd tensorflow
git checkout r1.11
conda create -n <conda_environment_name> python=3.6
source activate <conda_environment_name>
conda install numpy bazel
conda install -c intel mkl-dnn
conda install -c conda-forge keras-preprocessing
Configure your system build by running the following at the root of your TensorFlow source tree:
$./configure
bazel build command for Support for the Intel® MKL-DNN.
bazel build --config=mkl -c opt //tensorflow/tools/pip_package:build_pip_package
create a directory tfwheels to place the wheel files and run the below commands
mkdir tfwheels
bazel-bin/tensorflow/tools/pip_package/build_pip_package /home/<your_path>/tfwheels/tensorflow_pkg
pip install /home/<your_path>/tfweels/tensorflow_pkg/tensorflow-<version>-cp36-cp36m-linux_x86_64.whl
for tensorflow version==1.12(similar steps)
refer
https://software.intel.com/en-us/articles/intel-optimization-for-tensorflow-installation-guide
Hope this helps.