<p dir="auto"><em>Please make sure that this is a bug. As per our <a href="https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md">GitHub Policy</a>, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template</em></p>
<p dir="auto"><strong>System information</strong></p>
<ul dir="auto">
<li>Have I written custom code (as opposed to using a stock example script provided in TensorFlow):</li>
<li>OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows10 64bit</li>
<li>Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:</li>
<li>TensorFlow installed from (source or binary): binary</li>
<li>TensorFlow version (use command below): 1.12, 1.11</li>
<li>Python version:3.6.8</li>
<li>Bazel version (if compiling from source):</li>
<li>GCC/Compiler version (if compiling from source):</li>
<li>CUDA/cuDNN version:7.4.2, 7.3.1</li>
<li>GPU model and memory: CUDA 9.0</li>
</ul>
<p dir="auto"><strong>Describe the current behavior</strong><br>
I have installed TF using pip, I have tested and it was able to detect the GPU, but when start to train, it throws the error below:</p>
<blockquote>
<p dir="auto">UnknownError (see above for traceback): Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.<br>
[[node FirstStageFeatureExtractor/InceptionV2/InceptionV2/Conv2d_1a_7x7/separable_conv2d (defined at C:\Users\bahra\Anaconda3\lib\site-packages\tensorflow\contrib\layers\python\layers\layers.py:2777)  = Conv2D[T=DT_FLOAT, data_format="NCHW", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](FirstStageFeatureExtractor/InceptionV2/InceptionV2/Conv2d_1a_7x7/separable_conv2d/depthwise, FirstStageFeatureExtractor/InceptionV2/Conv2d_1a_7x7/pointwise_weights/read/_165)]]<br>
[[{{node BatchMultiClassNonMaxSuppression/map/while/Exit_6/_76}} = _Recv<a href="">client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_1252_BatchMultiClassNonMaxSuppression/map/while/Exit_6", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"</a>]]</p>
</blockquote>
<p dir="auto"><strong>Note</strong><br>
I have tried TF 1.12, 1.11, and 1.8.0 all have the same problem.<br>
Why it throwing this error and how to solve?</p>
<p dir="auto">Before this error, I was able to train, and it was successfully worked, but when to start the second time training then this error happens.</p>
<h3 dir="auto">System information</h3>
<ul dir="auto">
<li><strong>Have I written custom code (as opposed to using a stock example script provided in TensorFlow)</strong>:<br>
No</li>
<li><strong>OS Platform and Distribution (e.g., Linux Ubuntu 16.04)</strong>:<br>
Mac OS X 10.12.4, Darwin</li>
<li><strong>TensorFlow installed from (source or binary)</strong>:<br>
Source, git tag 1.2.0 RC 2</li>
<li><strong>TensorFlow version (use command below)</strong>:<br>
1.2 RC 2</li>
<li><strong>Bazel version (if compiling from source)</strong>:<br>
bazel version<br>
..............<br>
Build label: 0.4.3-homebrew<br>
Build target: bazel-out/local-opt/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar<br>
Build time: Thu Dec 22 15:20:15 2016 (1482420015)<br>
Build timestamp: 1482420015<br>
Build timestamp as int: 1482420015</li>
<li><strong>CUDA/cuDNN version</strong>:<br>
N/A</li>
<li><strong>GPU model and memory</strong>:<br>
N/A</li>
<li><strong>Exact command to reproduce</strong>:<br>
./configure<br>
Please specify the location of python. [Default is /usr/bin/python]:<br>
Found possible Python library paths:<br>
/Library/Python/2.7/site-packages<br>
Please input the desired Python library path to use.  Default is [/Library/Python/2.7/site-packages]</li>
</ul>
<p dir="auto">Using python library path: /Library/Python/2.7/site-packages<br>
Do you wish to build TensorFlow with MKL support? [y/N] y<br>
MKL support will be enabled for TensorFlow<br>
Do you wish to download MKL LIB from the web? [Y/n] Y<br>
Darwin is unsupported yet</p>
<p dir="auto">You can collect some of this information using our environment capture script:<br>
<a href="https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh">https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh</a><br>
N/A<br>
You can obtain the TensorFlow version with</p>
<p dir="auto">python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"</p>
<h3 dir="auto">Describe the problem</h3>
<p dir="auto">Darwin / Mac OS X support for Intel's optional MKL optimizations. MKL appears to have darwin support, so I am unsure why it is not supported in Tensorflow. I imagine this is on a to-do, but a publicly tracked feature request might be helpful. Thank you.</p>
<h3 dir="auto">Source code / logs</h3>
<p dir="auto">N/A</p>