Issue 1:
Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows10 64bit

Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:

TensorFlow installed from (source or binary): binary

TensorFlow version (use command below): 1.12, 1.11

Python version:3.6.8

Bazel version (if compiling from source):

GCC/Compiler version (if compiling from source):

CUDA/cuDNN version:7.4.2, 7.3.1

GPU model and memory: CUDA 9.0

Describe the current behavior

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:

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.

[[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)]]

[[{{node BatchMultiClassNonMaxSuppression/map/while/Exit_6/_76}} = _Recvclient_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"]]

Note

I have tried TF 1.12, 1.11, and 1.8.0 all have the same problem.

Why it throwing this error and how to solve?

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.

Issue 2:
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):

Mac OS X 10.12.4, Darwin

TensorFlow installed from (source or binary):

Source, git tag 1.2.0 RC 2

TensorFlow version (use command below):

1.2 RC 2

Bazel version (if compiling from source):

bazel version

..............

Build label: 0.4.3-homebrew

Build target: bazel-out/local-opt/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar

Build time: Thu Dec 22 15:20:15 2016 (1482420015)

Build timestamp: 1482420015

Build timestamp as int: 1482420015

CUDA/cuDNN version:

N/A

GPU model and memory:

N/A

Exact command to reproduce:

./configure

Please specify the location of python. [Default is /usr/bin/python]:

Found possible Python library paths:

/Library/Python/2.7/site-packages

Please input the desired Python library path to use. Default is [/Library/Python/2.7/site-packages]

Using python library path: /Library/Python/2.7/site-packages

Do you wish to build TensorFlow with MKL support? [y/N] y

MKL support will be enabled for TensorFlow

Do you wish to download MKL LIB from the web? [Y/n] Y

Darwin is unsupported yet

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

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

N/A

You can obtain the TensorFlow version with

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

Describe the problem

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.

Source code / logs

N/A