<p dir="auto">NOTE: Only file GitHub issues for bugs and feature requests.  All other topics will be closed.</p>
<p dir="auto">For general support from the community, see <a href="https://stackoverflow.com/questions/tagged/tensorflow" rel="nofollow">StackOverflow</a>.<br>
To make bugs and feature requests more easy to find and organize, we close issues that are deemed<br>
out of scope for GitHub Issues and point people to StackOverflow.</p>
<p dir="auto">For bugs or installation issues, please provide the following information.<br>
The more information you provide, the more easily we will be able to offer<br>
help and advice.</p>
<h3 dir="auto">What related GitHub issues or StackOverflow threads have you found by searching the web for your problem?</h3>
<p dir="auto">Only one, but it was not solved.</p>
<h3 dir="auto">Environment info</h3>
<p dir="auto">Operating System:<br>
Windows 10 (anaconda 4.3.8)<br>
<code class="notranslate">conda --version conda 4.3.8</code><br>
Installed version of CUDA and cuDNN:<br>
<code class="notranslate">nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2016 NVIDIA Corporation Built on Sat_Sep__3_19:05:48_CDT_2016 Cuda compilation tools, release 8.0, V8.0.44</code></p>
<p dir="auto">If installed from binary pip package, provide:</p>
<ol dir="auto">
<li>A link to the pip package you installed:<br>
<code class="notranslate">pip install --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-0.12.0rc0-cp35-cp35m-win_amd64.whl</code></li>
<li>The output from <code class="notranslate">python -c "import tensorflow; print(tensorflow.__version__)"</code>.<br>
<code class="notranslate">I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library cublas64_80.dll locally I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library cudnn64_5.dll locally I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library cufft64_80.dll locally I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library nvcuda.dll locally I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\dso_loader.cc:128] successfully opened CUDA library curand64_80.dll locally</code></li>
</ol>
<h3 dir="auto">If possible, provide a minimal reproducible example (We usually don't have time to read hundreds of lines of your code)</h3>
<p dir="auto">When I tried  <a href="https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5_MultiGPU/multigpu_basics.py">Single GPU computing example with tensorflow</a> and get the following error:<br>
<code class="notranslate">Placeholder_1: (Placeholder): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] Placeholder_1: (Placeholder)/job:localhost/replica:0/task:0/gpu:0 MatMul_10: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_10: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_11: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_11: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_12: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_12: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_13: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_13: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_14: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_14: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_15: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_15: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_16: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_16: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_17: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_17: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_18: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_18: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_19: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_19: (MatMul)/job:localhost/replica:0/task:0/gpu:0 Placeholder: (Placeholder): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] Placeholder: (Placeholder)/job:localhost/replica:0/task:0/gpu:0 MatMul: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_1: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_1: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_2: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_2: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_3: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_3: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_4: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_4: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_5: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_5: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_6: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_6: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_7: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_7: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_8: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_8: (MatMul)/job:localhost/replica:0/task:0/gpu:0 MatMul_9: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul_9: (MatMul)/job:localhost/replica:0/task:0/gpu:0 AddN: (AddN): /job:localhost/replica:0/task:0/cpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] AddN: (AddN)/job:localhost/replica:0/task:0/cpu:0 E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_blas.cc:372] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\stream.cc:1390] attempting to perform BLAS operation using StreamExecutor without BLAS support E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_blas.cc:372] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\stream.cc:1390] attempting to perform BLAS operation using StreamExecutor without BLAS support</code></p>
<h3 dir="auto">What other attempted solutions have you tried?</h3>
<p dir="auto">Then I tried a sample matrix multiplication:<br>
<code class="notranslate">sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:885] Found device 0 with properties: name: Quadro M2000M major: 5 minor: 0 memoryClockRate (GHz) 1.137 pciBusID 0000:01:00.0 Total memory: 4.00GiB Free memory: 3.35GiB I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:906] DMA: 0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:916] 0:   Y I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -&gt; (device: 0, name: Quadro M2000M, pci bus id: 0000:01:00.0) Device mapping: /job:localhost/replica:0/task:0/gpu:0 -&gt; device: 0, name: Quadro M2000M, pci bus id: 0000:01:00.0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\direct_session.cc:255] Device mapping: /job:localhost/replica:0/task:0/gpu:0 -&gt; device: 0, name: Quadro M2000M, pci bus id: 0000:01:00.0</code></p>
<p dir="auto">and the following error:</p>
<p dir="auto"><code class="notranslate">a = tf.random_normal((100,100))</code><br>
<code class="notranslate">b = tf.random_normal((100,500))</code><br>
<code class="notranslate">c = tf.matmul(a,b)</code><br>
<code class="notranslate">sess.run(c)</code><br>
<code class="notranslate">random_normal_1/RandomStandardNormal: (RandomStandardNormal): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal_1/RandomStandardNormal: (RandomStandardNormal)/job:localhost/replica:0/task:0/gpu:0 random_normal_1/mul: (Mul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal_1/mul: (Mul)/job:localhost/replica:0/task:0/gpu:0 random_normal_1: (Add): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal_1: (Add)/job:localhost/replica:0/task:0/gpu:0 random_normal/RandomStandardNormal: (RandomStandardNormal): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal/RandomStandardNormal: (RandomStandardNormal)/job:localhost/replica:0/task:0/gpu:0 random_normal/mul: (Mul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal/mul: (Mul)/job:localhost/replica:0/task:0/gpu:0 random_normal: (Add): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal: (Add)/job:localhost/replica:0/task:0/gpu:0 MatMul: (MatMul): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] MatMul: (MatMul)/job:localhost/replica:0/task:0/gpu:0 random_normal_1/stddev: (Const): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal_1/stddev: (Const)/job:localhost/replica:0/task:0/gpu:0 random_normal_1/mean: (Const): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal_1/mean: (Const)/job:localhost/replica:0/task:0/gpu:0 random_normal_1/shape: (Const): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal_1/shape: (Const)/job:localhost/replica:0/task:0/gpu:0 random_normal/stddev: (Const): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal/stddev: (Const)/job:localhost/replica:0/task:0/gpu:0 random_normal/mean: (Const): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal/mean: (Const)/job:localhost/replica:0/task:0/gpu:0 random_normal/shape: (Const): /job:localhost/replica:0/task:0/gpu:0 I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\simple_placer.cc:827] random_normal/shape: (Const)/job:localhost/replica:0/task:0/gpu:0 E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_blas.cc:372] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\stream.cc:1390] attempting to perform BLAS operation using StreamExecutor without BLAS support</code><br>
`</p>
<p dir="auto">Like <a class="user-mention notranslate" data-hovercard-type="user" data-hovercard-url="/users/kingtaurus/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" href="https://github.com/kingtaurus">@kingtaurus</a> and <a class="user-mention notranslate" data-hovercard-type="user" data-hovercard-url="/users/menggangmark/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" href="https://github.com/menggangmark">@menggangmark</a>,</p>
<p dir="auto">I then copied the cudnn64_5.dll (cuda\bin\cudnn64_5.dll) from that zip archive into C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin;</p>
<p dir="auto">cuda\include\cudnn.h to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\include;</p>
<p dir="auto">and</p>
<p dir="auto">cuda\lib\x64\cudnn.lib to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\lib\x64\</p>
<p dir="auto">cupti64_80.dll (C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\extras\CUPTI\libx64) to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin;<br>
and cupti.lib(C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\extras\CUPTI\libx64) to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\lib\x64</p>
<p dir="auto">WHERE C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0 is my install PATH for the CUDA toolkit.<br>
I had already added C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin\ to my PATH</p>
<p dir="auto">As many of us (<a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="269996549" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/14126" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/14126/hovercard" href="https://github.com/tensorflow/tensorflow/issues/14126">#14126</a>,<a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="275089746" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/14691" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/14691/hovercard" href="https://github.com/tensorflow/tensorflow/issues/14691">#14691</a>,<a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="248135560" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/12052" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/12052/hovercard" href="https://github.com/tensorflow/tensorflow/issues/12052">#12052</a>), I am trying to get TF1.4 build successfully on windows using the latest version of everything. As far as I can judge <strong>I could do it</strong> but with some hacks. As it is too long for me to complete, I would like to share what I did for help finalizing. It is too early for a PR.</p>
<p dir="auto">I am using CMake 3.9.6 (though 3.10 came out). I have low cmake skill level.<br>
I am not trying the python bindings.<br>
VS2017 is the community edition.</p>
<p dir="auto">Without GPU it is easy. The only issue is the heap overflow (C1002 or C1006 <a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="239041379" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/11096" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/11096/hovercard" href="https://github.com/tensorflow/tensorflow/issues/11096">#11096</a>). The trick is to reduce parallel build by <code class="notranslate">msbuild /m:4 /p:CL_MPCount=2 ...</code> such that 4*2 is approximately the number of core you really have (at least it worked for me). Using <code class="notranslate">/Zm2000</code> did not work for me, despite a lot of available memory (32G).</p>
<p dir="auto">With GPU it is more tricky: the <code class="notranslate">tf_core_gpu_kernels.vcxproj</code> does not compile at all. AFAIU, the CMake strategy changed from v3.6, to allow parallel computing. CUDA is now treated as another language. Without modifications nvcc simply returns with code error 1 (or nothing happen I am not sure). Here are my modifications (from v1.4).</p>
<p dir="auto">From <code class="notranslate">tensorflow/tensorflow/contrib/cmake/</code><br>
1/ adapt <code class="notranslate">cmakelists.txt</code> a little:</p>
<ul dir="auto">
<li>Change <code class="notranslate">CUDA 8.0</code> to <code class="notranslate">CUDA 9.0</code> l.223.</li>
<li>Add <code class="notranslate">enable_language("CUDA")</code> l.224.</li>
<li><strong>The <code class="notranslate">set(CUDA_NVCC_FLAGS ...)</code> directives do not work anymore</strong>. See below.</li>
<li>Add capabilities 6.0 and 6.1 in l.232, as well l.246. Might not be needed (it is only for performance).</li>
<li>Change <code class="notranslate">64_80</code> to <code class="notranslate">64_90</code> and <code class="notranslate">64_6</code> to <code class="notranslate">64_7</code> l.247 and 248, similarly in l.272-276.</li>
</ul>
<p dir="auto">2/ in <code class="notranslate">tf_core_kernels.cmake</code>:</p>
<ul dir="auto">
<li>Add <code class="notranslate">set_source_files_properties(${tf_core_gpu_kernels_srcs} PROPERTIES LANGUAGE CUDA)</code> to recognize '.cu.cc' extensions as cuda files in l.209.</li>
<li>Rename <code class="notranslate">cuda_add_library(...)</code> as <code class="notranslate">add_library(...)</code> l.210.</li>
</ul>
<p dir="auto">3/ edit <strong>(this is the trick)</strong> <code class="notranslate">tf_core_gpu_kernels.vcxproj</code>, in the release section:</p>
<ul dir="auto">
<li>Encompass cl.exe flags, ie <code class="notranslate">/bigobj /nologo ... -Ob2</code>  with the <code class="notranslate">-Xcompiler="/bigobj ... -Ob2"</code> directive l.147. These former flags are for the c++ compiler not for nvcc and result in the crash.</li>
<li>Add just before <code class="notranslate">--expt-relaxed-constexpr</code>, still in the <code class="notranslate">AdditionalOptions</code>.</li>
<li>Switch <code class="notranslate">PerformDeviceLink</code>from <code class="notranslate">false</code> to <code class="notranslate">true</code> l.164.</li>
</ul>
<p dir="auto">Then everything compile (msbuild on  tf_tutorials_example_trainer.vcxproj) (and this tuto works). The remaining point before PR is to avoid third step, i.e. give the right directives to nvcc, by understanding how the CUDA_NVCC_FLAGS works, and add the linking. Hope this solution will work without missing symbols (<a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="196378243" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/6396" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/6396/hovercard" href="https://github.com/tensorflow/tensorflow/issues/6396">#6396</a>).</p>
<p dir="auto">Otherwise it is a nightmare: both CUDA 8 and CMake 3.6 are not aware of VS2017. CMake compilation is not incremental (<a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="270841160" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/14194" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/14194/hovercard" href="https://github.com/tensorflow/tensorflow/issues/14194">#14194</a>) and takes about 4-5H (could use precompiled headers especially in tf_core_kernels)...</p>