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System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10. Intel Core i7-6600U
• TensorFlow installed from (source or binary): Source
• TensorFlow version (use command below):1.2.0-rc0
• Bazel version (if compiling from source): No
• CUDA/cuDNN version:No
• GPU model and memory:No
• Exact command to reproduce:
  I built tensorflow on Windows following the instructions from
  https://github.com/tensorflow/tensorflow/tree/r0.12/tensorflow/contrib/cmake
  My goal was to enable the SIMD options for performance improvements.

1. Set up toolchain for for 64-bit: vcvarsall amd64
2. Invoked CMAKE
   C:\Projects\tensorflow\tensorflow\contrib\cmake\build>cmake .. -A x64 -DCMAKE_BUILD_TYPE=Release -DSWIG_EXECUTABLE=C:/tools/swigwin-3.0.12\swigwin-3.0.12/swig.exe -DPYTHON_EXECUTABLE=C:\Users\sergio.murillo\AppData\Local\Programs\Python\Python35/PYTHON.EXE -DPYTHON_LIBRARIES=C:\Users\sergio.murillo\AppData\Local\Programs\Python\Python35\libs\python35.lib -Dtensorflow_WIN_CPU_SIMD_OPTIONS=/arch:AVX
3. To build the PIP package
   MSBuild /p:Configuration=Release /filelogger tf_python_build_pip_package.vcxproj
   It build with no errors.
4. Install whl
   pip install .\tf_python\dist\tensorflow-1.2.0rc0-cp35-cp35m-win_amd64.whl
5. Validate installation

import tensorflow as tf

hello = tf.constant('Hello, Tensorflow!')
sess = tf.Session()

You can collect some of this information using our environment capture script:

https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh

You can obtain the TensorFlow version with

python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"

Describe the problem

Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.

I built tensorflow on Windows following the instructions from
https://github.com/tensorflow/tensorflow/tree/r0.12/tensorflow/contrib/cmake
My goal was to enable the SIMD options for performance improvements. It builds without errors, but when I open a tensorflow session it still shows the warnings telling that SIMD was not enabled.

1. Set up toolchain for for 64-bit: vcvarsall amd64
2. Invoked CMAKE
   C:\Projects\tensorflow\tensorflow\contrib\cmake\build>cmake .. -A x64 -DCMAKE_BUILD_TYPE=Release -DSWIG_EXECUTABLE=C:/tools/swigwin-3.0.12\swigwin-3.0.12/swig.exe -DPYTHON_EXECUTABLE=C:\Users\sergio.murillo\AppData\Local\Programs\Python\Python35/PYTHON.EXE -DPYTHON_LIBRARIES=C:\Users\sergio.murillo\AppData\Local\Programs\Python\Python35\libs\python35.lib -Dtensorflow_WIN_CPU_SIMD_OPTIONS=/arch:AVX
3. To build the PIP package
   MSBuild /p:Configuration=Release /filelogger tf_python_build_pip_package.vcxproj
   It build with no errors.
4. Install whl
   pip install .\tf_python\dist\tensorflow-1.2.0rc0-cp35-cp35m-win_amd64.whl
5. Validate installation: This is when despite compiling and building without errors, I see the warnings about the SIMD instructions that should have been enabled in CMAKE with -Dtensorflow_WIN_CPU_SIMD_OPTIONS=/arch:AVX

import tensorflow as tf
hello = tf.constant('Hello, Tensorflow!')
sess = tf.Session()
2017-05-25 14:23:37.872523: W c:\projects\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2017-05-25 14:23:37.873758: W c:\projects\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-25 14:23:37.873870: W c:\projects\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-25 14:23:37.874002: W c:\projects\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-25 14:23:37.874191: W c:\projects\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-25 14:23:37.874379: W c:\projects\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-05-25 14:23:37.874565: W c:\projects\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.

I followed the instructions, but it seems that SIMD options were not build/compiled. Did I missed something?
Thanks!

Source code / logs

Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem.

msbuild.zip