ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.

Environment info
Operating System:
OS  10.10.5
Installed version of CUDA and cuDNN:
$ ls -l /usr/local/cuda/lib/libcud*
-rwxr-xr-x  1 root           wheel      8280 Apr 13 01:02 /usr/local/cuda/lib/libcuda.dylib
lrwxr-xr-x  1 root           wheel        45 Apr 13 01:03 /usr/local/cuda/lib/libcudadevrt.a -> /Developer/NVIDIA/CUDA-7.5/lib/libcudadevrt.a
lrwxr-xr-x  1 root           wheel        50 Apr 13 01:03 /usr/local/cuda/lib/libcudart.7.5.dylib -> /Developer/NVIDIA/CUDA-7.5/lib/libcudart.7.5.dylib
lrwxr-xr-x  1 root           wheel        46 Apr 13 01:03 /usr/local/cuda/lib/libcudart.dylib -> /Developer/NVIDIA/CUDA-7.5/lib/libcudart.dylib
lrwxr-xr-x  1 root           wheel        49 Apr 13 01:03 /usr/local/cuda/lib/libcudart_static.a -> /Developer/NVIDIA/CUDA-7.5/lib/libcudart_static.a
-rwxr-xr-x@ 1 production204  staff  60108616 Feb  8  2016 /usr/local/cuda/lib/libcudnn.4.dylib
lrwxr-xr-x  1 root           admin        47 Aug 29 18:08 /usr/local/cuda/lib/libcudnn.5.dylib -> /Developer/NVIDIA/CUDA-7.5/lib/libcudnn.5.dylib
lrwxr-xr-x  1 root           admin        45 Aug 29 18:08 /usr/local/cuda/lib/libcudnn.dylib -> /Developer/NVIDIA/CUDA-7.5/lib/libcudnn.dylib
-rw-r--r--@ 1 production204  staff  59311504 Feb  8  2016 /usr/local/cuda/lib/libcudnn_static.a

The output from python -c "import tensorflow; print(tensorflow.__version__)".
(can't get that far, but i'm using 0.10)

>>> import tensorflow
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.dylib locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.dylib locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.dylib locally
Segmentation fault: 11

If installed from source, provide

The commit hash (git rev-parse HEAD)

4c49dbebef05442c7e72d6129a30574fcd13f0e1

The output of bazel version

$ bazel version
Build label: 0.3.1-homebrew
Build target: bazel-out/local-fastbuild/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar
Build time: Thu Aug 4 09:59:58 2016<PHONE_NUMBER>)
Build timestamp:<PHONE_NUMBER>
Build timestamp as int:<PHONE_NUMBER>

If possible, provide a minimal reproducible example (We usually don't have time to read hundreds of lines of your code)
$ bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
INFO: Elapsed time: 0.076s

What other attempted solutions have you tried?

Downgrading to cuDNN4, switching between 4 and 5
Re-installing bazel
Modifying CROSSTOOL file according to various threads
Manually linking CUDA libraries during ./configure to not use symlinked libraries
Various other hacks over the last week 😭

I got this recently too, I was somehow successful by just re-running ./configure and then immediately running bazel build, but I'm not sure what's going on.

I just tried de-installing TF completely and then re-running with the same ./configure settings:
$ ./configure
Please specify the location of python. [Default is /Library/Frameworks/Python.framework/Versions/2.7/bin/python]:
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] y
Google Cloud Platform support will be enabled for TensorFlow
Found possible Python library paths:
  /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages
  /Library/Python/2.7/site-packages
Please input the desired Python library path to use.  Default is [/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages]

/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 7.5
Please specify the location where CUDA 7.5 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Please specify the Cudnn version you want to use. [Leave empty to use system default]: 5
Please specify the location where cuDNN 5 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
[Default is: "3.5,5.2"]: 3.0
INFO: Starting clean (this may take a while). Consider using --expunge_async if the clean takes more than several minutes.
.
INFO: Waiting for response from Bazel server (pid 63884)...
WARNING: /private/var/tmp/_bazel_production204/ed2bbf43bcd665c40f1e3ebaa04f68f6/external/boringssl_git/WORKSPACE:1: Workspace name in /private/var/tmp/_bazel_production204/ed2bbf43bcd665c40f1e3ebaa04f68f6/external/boringssl_git/WORKSPACE (@boringssl) does not match the name given in the repository's definition (@boringssl_git); this will cause a build error in future versions.
INFO: All external dependencies fetched successfully.
Configuration finished

Then running a simplified build command:
$ bazel build -c opt --config=cuda tensorflow/...

After a very verbose and lengthy compile attempt, I received this error message (it caused OS X Terminal app to hang permanently as well, so I couldn't copy-paste, had to take a screenshot):
https://www.dropbox.com/s/riu5f4n5aj1opmk/Screenshot 2016-08-30 16.33.48.png?dl=0

Yes if you are developing TF it happens quite often. I think it might be something related with the caching system of bazel. After few hours it resets and I have to re run the configure again.

+cc @damienmg
This seems to be a bug in Bazel.
Next time this happens, can you take a look at directory bazel-tensorflow/external/local_config_cuda/crosstool and let me know which files are there?

@davidzchen thanks for your reply.
This error or some version of it is consistent:
$ ls -l
total 32
-rwxr-xr-x  1 production204  wheel   925 Aug 30 14:45 BUILD
-rwxr-xr-x  1 production204  wheel  9068 Aug 30 14:45 CROSSTOOL
drwxr-xr-x  3 production204  wheel   102 Aug 30 14:45 clang

production204@Trevors-MacBook-Pro crosstool $

I just saw your screenshot, and that appears to be a different problem than the no such package '@local_config_cuda//crosstool': BUILD file not found on package path. error, which seems to be a caching issue.
Do you mean that the crosstool_wrapper_driver_is_not_gcc error occurs consistently? Is it causing your Terminal.app to hang every time? If it reproduces consistently, you re-run the command with --verbose_failures?

I meant that my TF builds seem to fail related to crosstool consistently, probably my naivete on the specifics for me to think that crosstool_wrapper_driver_is_not_gcc and CROSSTOOL could be the same problem!

No problem. The naming could be a bit confusing. The @local_config_cuda//crosstool error may be an issue with Bazel's caching; I have ran into it a couple of times myself, and it usually goes away after I re-run ./configure.
Were you able to reproduce the crosstool_wrapper_driver_is_not_gcc error again? Looking at your screenshot, it looks like the headerpad_max_install_names flag is not spelled correctly for some reason since it is complaining about eaderpad_max_install_names.

I am getting the same missing crosstool on Linux. The strange thing is that there isn't even a bazel-tensorflow directory:
[david@SQUIDS tensorflow]$ ls
ACKNOWLEDGMENTS  avro.BUILD   boringssl.BUILD  bzip2.BUILD  CONTRIBUTING.md  farmhash.BUILD  gmock.BUILD  ISSUE_TEMPLATE.md  jsoncpp.BUILD  nanopb.BUILD  png.BUILD      README.md   six.BUILD   third_party  util       zlib.BUILD
AUTHORS          boost.BUILD  bower.BUILD      configure    eigen.BUILD      gif.BUILD       grpc.BUILD   jpeg.BUILD         LICENSE        navbar.md     _python_build  RELEASE.md  tensorflow  tools        WORKSPACE

bazel is 0.3.1, and I have ran ./configure four times now.

I do see that eaderpad_max_install_names reference in the screenshot above, however, after searching through all the files and folders in my TF directory I don't see that text anywhere, only headerpad_max_install_names. I don't know why the h would be getting clipped off.

@Dapid That is interesting. How did you run the ./configure script? Can you paste the output
@damienmg Is there currently a way to inspect the contents of /external after running bazel fetch but before the Bazel output directories get symlinked?
@trevorwelch FWIW, most of the noise in the output are compiler warnings. The dyld: Library not loaded: @rpath/libcudart.7.5.dylib error is interesting. Can you verify whether the file bazel-bin/tensorflow/cc/tutorials_example_trainer.runfiles/local_config_cuda/cuda/lib/libcudart.7.5.dylib exists? If not, what files are under the bazel-bin/tensorflow/cc/tutorials_example_trainer.runfiles/local_config_cuda/cuda/lib directory?

@davidzchen
./configure
Please specify the location of python. [Default is /home/david/.virtualenvs/py35/bin/python]:
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] n
No Google Cloud Platform support will be enabled for TensorFlow
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow
Please specify which gcc should be used by nvcc as the host compiler. [Default is /bin/gcc]: /usr/local/cuda/bin/gcc
Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]:
Please specify the Cudnn version you want to use. [Leave empty to use system default]:
libcudnn.so resolves to libcudnn.4
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
[Default is: "3.5,5.2"]: 5.0
INFO: Reading 'startup' options from /home/david/.bazelrc: --batch
Warning: ignoring LD_PRELOAD in environment.
INFO: Starting clean (this may take a while). Consider using --expunge_async if the clean takes more than several minutes.
INFO: Reading 'startup' options from /home/david/.bazelrc: --batch
Warning: ignoring LD_PRELOAD in environment.
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/boringssl_git/WORKSPACE:1: Workspace name in /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/boringssl_git/WORKSPACE (@boringssl) does not match the name given in the repository's definition (@boringssl_git); this will cause a build error in future versions.
INFO: All external dependencies fetched successfully.
Configuration finished

git log
commit 6ce5b5c8298273e3861a75fb6ccde63b9dd157c5
Author: Sanders Kleinfeld<EMAIL_ADDRESS>Date:   Sun Aug 28 01:00:52 2016 -0400

On branch r0.10.

@davidzchen
It does exist:
tensorflow$ cd bazel-bin/tensorflow/cc/tutorials_example_trainer.runfiles/local_config_cuda/cuda/lib/

lib$ ls -l
total 40
lrwxr-xr-x  1 production204  wheel  126 Aug 31 11:03 libcublas.7.5.dylib -> /private/var/tmp/_bazel_production204/ed2bbf43bcd665c40f1e3ebaa04f68f6/external/local_config_cuda/cuda/lib/libcublas.7.5.dylib
lrwxr-xr-x  1 production204  wheel  126 Aug 31 11:03 libcudart.7.5.dylib -> /private/var/tmp/_bazel_production204/ed2bbf43bcd665c40f1e3ebaa04f68f6/external/local_config_cuda/cuda/lib/libcudart.7.5.dylib
lrwxr-xr-x  1 production204  wheel  123 Aug 31 11:03 libcudnn.5.dylib -> /private/var/tmp/_bazel_production204/ed2bbf43bcd665c40f1e3ebaa04f68f6/external/local_config_cuda/cuda/lib/libcudnn.5.dylib
lrwxr-xr-x  1 production204  wheel  125 Aug 31 11:03 libcufft.7.5.dylib -> /private/var/tmp/_bazel_production204/ed2bbf43bcd665c40f1e3ebaa04f68f6/external/local_config_cuda/cuda/lib/libcufft.7.5.dylib
lrwxr-xr-x  1 production204  wheel  126 Aug 31 11:03 libcurand.7.5.dylib -> /private/var/tmp/_bazel_production204/ed2bbf43bcd665c40f1e3ebaa04f68f6/external/local_config_cuda/cuda/lib/libcurand.7.5.dylib

lib$

I can confirm this also building on a Debian (sid, uptodate of today) system.

I've found I can induce this by Ctrl-C'ing in the middle of a fresh bazel build.

Ubuntu-16.04, CUDA 8, java 1.8.0_101, bazel 0.3.1
Building from master today
Started ./configure in a virtual instance in VirtualBox, did a CTRL-C because it was taking too long. Went home, fired up the instance again, deleted tensorflow repo, cloned it again.
Did ./configure again with same options as before, it worked well except one warning at the beginning:
Found stale PID file (pid=20777). Server probably died abruptly, continuing...

Ignored it, and did the command to build for GPU:
bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package

And it failed immediately:
INFO: Waiting for response from Bazel server (pid 9635)...
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
INFO: Elapsed time: 4.667s

There are two issues being discussed in this thread. @trevorwelch, let's move the Library not loaded: @rpath/libcudart.7.5.dylib discussion over to #4187.
For the '@local_config_cuda//crosstool': BUILD file not found issue:

If the Bazel output directories (i.e. bazel-tensorflow, etc.) exist, what is the output of ls -l bazel-tensorflow/external/local_config_cuda/crosstool?
If not, what is the output of ls -l $(bazel info output_base)/external/local_config_cuda/crosstool

i experience the same issue. tf 0.10. mac os el capitain. bazel 0.3.0

@asimonov - Can you print the contents of the local_config_cuda/crosstool directory as I mentioned in my comment above?

David,
I cannot find local_config_cuda/crosstool directory anywhere in tensorflow directory.
Kind Regards,
Alexey

On 3 Sep 2016, at 20:59, David Z. Chen<EMAIL_ADDRESS>wrote:
@asimonov https://github.com/asimonov - Can you print the contents of the local_config_cuda/crosstool directory as I mentioned in my comment above?
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Reply to this email directly, view it on GitHub https://github.com/tensorflow/tensorflow/issues/4105#issuecomment-244566755, or mute the thread https://github.com/notifications/unsubscribe-auth/AAOr9jkI6txztNytQvsTCtcTUtlP5lrgks5qmdGbgaJpZM4Jw5M2.

@davidzchen I'm getting a broken symlink to
~/.cache/bazel/_bazel_/d217f35631206796f447d50c6f1d6243/external/local_config_cuda/crosstool

@asimonov @rasmi - Does the contents of the `local_config_cuda/cuda

@davidzchen -- assuming you mean @jmhodges gist, yes. Just a bunch of cuda library files. Sure enough, running ./configure and building again produces the crosstool directory with BUILD, CROSSTOOL, and a clang/bin/crosstool_wrapper_driver_is_not_gcc files. I was getting errors with crosstool_wrapper_driver_is_not_gcc earlier when using gcc 4.9.1, and now I'm getting entirely unrelated errors in highwayhash when using gcc 4.7.2. Not sure if that has anything to do with it or if that's helpful, since this error seems further upstream from these compilation errors.

@jmhodges
@rasmi
@davidzchen
here my solution :)
https://github.com/JimmyKon/tensorflow_build_issue_fix

On the error of   '@local_config_cuda//crosstool': BUILD file not found:
$ bazel info output_base
Warning: ignoring LD_PRELOAD in environment.
.
/home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63
$ ls -l $(bazel info output_base)/external/local_config_cuda/crosstool
Warning: ignoring LD_PRELOAD in environment.
total 20
-rwxrwxr-x. 1 david david  925 Sep  1 13:38 BUILD
drwxrwxr-x. 3 david david 4096 Sep  1 13:38 clang
-rwxrwxr-x. 1 david david 8870 Sep  1 13:38 CROSSTOOL

Note that this only happens when I set a non default GCC, but since it is incompatible with CUDA I can only build for CPU.

i solved this by careful setting the cuda/cudnn/gcc version when using ./configure

This is what I have:
AlexPro:tensorflow alex$ bazel info output_base
/private/var/tmp/_bazel_alex/9a8b7d02e7f6ce832d52efe09806ba70
AlexPro:tensorflow alex$ ls -la /private/var/tmp/_bazel_alex/9a8b7d02e7f6ce832d52efe09806ba70/external/local_config_cuda
total 8
drwxr-xr-x    4 alex  wheel   136  6 Sep 07:10 .
drwxr-xr-x  168 alex  wheel  5712  6 Sep 07:10 ..
-rw-r--r--    1 alex  wheel   116  6 Sep 07:10 WORKSPACE
drwxr-xr-x    9 alex  wheel   306  6 Sep 07:10 cuda

On 6 Sep 2016, at 02:51, Wei Wu<EMAIL_ADDRESS>wrote:
same here, when ls -l $(bazel info output_base)/external/local_config_cuda, there is noly cuda directory, no crosstool.
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@tornadomeet can you show exactly what you used in configure?

Odd. It appears that even though you are running the ./configure script to build with GPU support, cuda_configure seems to think that GPU support is disabled.
The way that cuda_configure determines whether GPU support is enabled is whether TF_NEED_CUDA is set to "1", which is what the ./configure script sets if you answered y to whether to build with GPU support.
If you are consistently reproducing the '@local_config_cuda//crosstool': BUILD file not found error, can you apply this patch and run your ./configure script and paste the debug (warning) messages from cuda_configure.bzl in the output?

I've solved the same problem by putting bazel  build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package into the last line of configure.
Looks like bazel configuration does not complete on bazel fetch //... in some cases.
source configure might work too.

@Dapid i do not saved the configure info, can we get this anywhere(except the info output to the screen during configure)?

Anyone solved the issue? please help
OS: Ubuntu 16.04, Cuda toolkit 8.0, cudnn-8.0-linux-x64-v5.1, GPU nvidia 1070
other settings:
CUDA_HOME=/usr/local/cuda-8.0
LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64
PATH=/usr/local/cuda-8.0/bin:/home/gopi/bin:/home/gopi/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
My command window shown below .
gopi@gp:/home/tensorflow$ sudo ./configure
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python2.7
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] N
No Google Cloud Platform support will be enabled for TensorFlow
Found possible Python library paths:
/usr/local/lib/python2.7/dist-packages
/usr/lib/python2.7/dist-packages
Please input the desired Python library path to use.  Default is [/usr/local/lib/python2.7/dist-packages]
/usr/local/lib/python2.7/dist-packages
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]: /usr/bin/gcc-5
Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 8.0
Please specify the location where CUDA 8.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-8.0
Please specify the Cudnn version you want to use. [Leave empty to use system default]: 5.1.5
Please specify the location where cuDNN 5.1.5 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-8.0]:
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
[Default is: "3.5,5.2"]: 6.1
.
INFO: Starting clean (this may take a while). Consider using --expunge_async if the clean takes more than several minutes.
.
INFO: All external dependencies fetched successfully.
Configuration finished
gopi@gp:/home/tensorflow$ bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.

@gopi77
I met this error once after upgrade my gcc on my mac.
you can reinstall bazel and execute "bazel clean" before compile.

@gopi77 - Is there a reason why you are running ./configure as sudo? Can you try running it without sudo?
@Dapid @nsuke - Can one of you apply the patch I linked in my comment above, reproduce the failure, and paste the output that you get as described so that we can get some more state on why the error is happening?

Hi JimmyKon
I reinstalled bazel, even got fresh clone of tensorflow in different area. But the errors remain
gopi@gp:~/tensorflow$ bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
.
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
Anyone succeeded with this combination ?
OS: Ubuntu 16.04, Cuda toolkit 8.0, cudnn-8.0-linux-x64-v5.1, GPU nvidia 1070, nvidia driver 370.23.
Repeated installation of ubuntu, toolkit, nvidia drivers, tensorflow many times in the last 3 weeks. still no luck with GPU based run.
But cuda toolkit examples are working fine Ex: bilateral filter and also CPU only version of tensorflow binary working fine.
Davidzchen,
I got python error and it disappeared using sudo ./configure.
Note: I mentioned compute capability as 6.1 (not visible in previous mail) for my nvidia 1070 card
Regards
Gopi. J

the error of ./configure without sudo shown below >>>
gopi@gp:~/tensorflow$ ./configure
Please specify the location of python. [Default is /usr/bin/python]:
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] N
No Google Cloud Platform support will be enabled for TensorFlow
./configure: line 66: tensorflow/tools/swig/swig_path: Permission denied
Found possible Python library paths:
/usr/local/lib/python2.7/dist-packages
/usr/lib/python2.7/dist-packages
Please input the desired Python library path to use.  Default is [/usr/local/lib/python2.7/dist-packages]
/usr/local/lib/python2.7/dist-packages
./util/python/python_config.sh: line 154: tools/bazel.rc: Permission denied

@davidzchen in my case, it turned out that it works fine as long as I don't modify files under third_party/gpus between configure and build.
(It was due to #4233 if that matters)
Here's failure log with your patch:
$ ./configure
...
WARNING: /home/nsuke/tensorflow/third_party/gpus/cuda_configure.bzl:119:5: TF_NEED_CUDA: 1.
WARNING: /home/nsuke/tensorflow/third_party/gpus/cuda_configure.bzl:360:3: cuda_configure: _create_cuda_repository.
...
$ touch third_party/gpus/cuda_configure.bzl
$ bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
WARNING: /home/nsuke/tensorflow/third_party/gpus/cuda_configure.bzl:122:5: TF_NEED_CUDA not set.
WARNING: /home/nsuke/tensorflow/third_party/gpus/cuda_configure.bzl:304:3: cuda_configure: _create_dummy_repository.
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
INFO: Elapsed time: 0.553s

@gopi77 Seems that you have some permissions issue in the directory where you have cloned the tensorflow repo. Can you fix your permission issues and try again?
@nsuke Thanks, the debug messages and your explanation are very helpful. Yes, if you modify files under third_party/gpus, then Bazel will re-fetch. Since the environment variables read by cuda_configure (such as TF_NEED_CUDA, etc.) are no longer set (as they were set by the configure script), then cuda_configure() will run with all default values, in which case, it will configure with GPU support disabled. Is #4233 the reason why you were modifying files under third_party/gpus between running ./configure and bazel build?

I have just pulled the latest version of tensorflow, re-ran ./config and build now works. Not sure if you have applied any fixes...

On 6 Sep 2016, at 23:07, David Z. Chen<EMAIL_ADDRESS>wrote:
@gopi77 https://github.com/gopi77 Seems that you have some permissions issue in the directory where you have cloned the tensorflow repo. Can you fix your permission issues and try again?
@nsuke https://github.com/nsuke Thanks, the debug messages and your explanation are very helpful. Yes, if you modify files under third_party/gpus, then Bazel will re-fetch. Since the environment variables read by cuda_configure (such as TF_NEED_CUDA, etc.) are no longer set (as they were set by the configure script), then cuda_configure() will run with all default values, in which case, it will configure with GPU support disabled. Is #4233 https://github.com/tensorflow/tensorflow/pull/4233 the reason why you were modifying files under third_party/gpus between running ./configure and bazel build?
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@asimonov There have not been any fixes that went in for cuda_configure since 4c49dbebef05442c7e72d6129a30574fcd13f0e1, which went in 10 days ago and should be related to this issue.
All: If you are experiencing the '@local_config_cuda//crosstool': BUILD file not found issue, the most likely cause of the problem is that cuda_configure is being re-run during bazel build and is re-configuring with GPU support disabled.

Are you modifying any files under third_party/gpus between running ./configure and bazel build? If so, then the reason why you are experiencing the error is because Bazel is re-fetching as explained here. Please explain why you need to do so, and we'll see if we can come up with a solution to avoid that.
If not, please follow the instructions here so that I can have more state on why the error is happening.

interesting…
I just did a pull, re-ran configure then checked that crosstool is there:
AlexPro:tensorflow alex$ ls -l $(bazel info output_base)/external/local_config_cuda
total 8
-rw-r--r--   1 alex  wheel  116  7 Sep 00:05 WORKSPACE
drwxr-xr-x   5 alex  wheel  170  7 Sep 00:05 crosstool
drwxr-xr-x  11 alex  wheel  374  7 Sep 00:05 cuda
then started the build
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
I went through but failed later with 3 errors. Did not have time to check why. But at least the crosstool issue was gone.
Interestingly when i started build second time it failed with same crosstool issue.

On 7 Sep 2016, at 02:20, David Z. Chen<EMAIL_ADDRESS>wrote:
@asimonov https://github.com/asimonov There have not been any fixes that went in for cuda_configure since 4c49dbe https://github.com/tensorflow/tensorflow/commit/4c49dbebef05442c7e72d6129a30574fcd13f0e1, which went in 10 days ago and should be related to this issue.
All: If you are experiencing the '@local_config_cuda//crosstool': BUILD file not found issue, the most likely cause of the problem is that cuda_configure is being re-run during bazel build and is re-configuring with GPU support disabled.
Are you modifying any files under third_party/gpus between running ./configure and bazel build? If so, then the reason why you are experiencing the error is because Bazel is re-fetching as explained here https://github.com/tensorflow/tensorflow/issues/4105#issuecomment-245110873. Please explain why you need to do so, and we'll see if we can come up with a solution to avoid that.
If not, please follow the instructions here https://github.com/tensorflow/tensorflow/issues/4105#issuecomment-244868298 so that I can have more state on why the error is happening.
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ah, just found the build error:
ERROR: /Users/alex/dev/tensorflow/tensorflow/stream_executor/BUILD:5:1: C++ compilation of rule '//tensorflow/stream_executor:stream_executor' failed: crosstool_wrapper_driver_is_not_gcc failed: error executing command external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc '-D_FORTIFY_SOURCE=1' -fstack-protector -fcolor-diagnostics -Wall -Wthread-safety -Wself-assign ... (remaining 112 argument(s) skipped): com.google.devtools.build.lib.shell.BadExitStatusException: Process exited with status 1.
so it does look like the same issue. but this time it was going further (first try). before i would be failing straight away.

On 7 Sep 2016, at 07:56, Alexey Simonov<EMAIL_ADDRESS>wrote:
interesting…
I just did a pull, re-ran configure then checked that crosstool is there:
AlexPro:tensorflow alex$ ls -l $(bazel info output_base)/external/local_config_cuda
total 8
-rw-r--r--   1 alex  wheel  116  7 Sep 00:05 WORKSPACE
drwxr-xr-x   5 alex  wheel  170  7 Sep 00:05 crosstool
drwxr-xr-x  11 alex  wheel  374  7 Sep 00:05 cuda
then started the build
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
I went through but failed later with 3 errors. Did not have time to check why. But at least the crosstool issue was gone.
Interestingly when i started build second time it failed with same crosstool issue.

On 7 Sep 2016, at 02:20, David Z. Chen<EMAIL_ADDRESS><EMAIL_ADDRESS>wrote:
@asimonov https://github.com/asimonov There have not been any fixes that went in for cuda_configure since 4c49dbe https://github.com/tensorflow/tensorflow/commit/4c49dbebef05442c7e72d6129a30574fcd13f0e1, which went in 10 days ago and should be related to this issue.
All: If you are experiencing the '@local_config_cuda//crosstool': BUILD file not found issue, the most likely cause of the problem is that cuda_configure is being re-run during bazel build and is re-configuring with GPU support disabled.
Are you modifying any files under third_party/gpus between running ./configure and bazel build? If so, then the reason why you are experiencing the error is because Bazel is re-fetching as explained here https://github.com/tensorflow/tensorflow/issues/4105#issuecomment-245110873. Please explain why you need to do so, and we'll see if we can come up with a solution to avoid that.
If not, please follow the instructions here https://github.com/tensorflow/tensorflow/issues/4105#issuecomment-244868298 so that I can have more state on why the error is happening.
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Reply to this email directly, view it on GitHub https://github.com/tensorflow/tensorflow/issues/4105#issuecomment-245146614, or mute the thread https://github.com/notifications/unsubscribe-auth/AAOr9sr0Pn6-eGfqbw6p_9DdyW0AydGyks5qnhF0gaJpZM4Jw5M2.

@davidzchen I updated the repo (branch r0.10), applied the patch, and here are the results:
[david@SQUIDS tensorflow]$ ./configure
Please specify the location of python. [Default is /home/david/.virtualenvs/py35/bin/python]:
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] n
No Google Cloud Platform support will be enabled for TensorFlow
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]: /usr/local/cuda/bin/gcc
Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]:
Please specify the Cudnn version you want to use. [Leave empty to use system default]:
libcudnn.so resolves to libcudnn.5
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
[Default is: "3.5,5.2"]: 5.0
Warning: ignoring LD_PRELOAD in environment.
.
INFO: Starting clean (this may take a while). Consider using --expunge_async if the clean takes more than several minutes.
Warning: ignoring LD_PRELOAD in environment.
.
WARNING: /home/david/gits/tensorflow/third_party/gpus/cuda_configure.bzl:95:5: TF_NEED_CUDA: 1.
WARNING: /home/david/gits/tensorflow/third_party/gpus/cuda_configure.bzl:336:3: cuda_configure: _create_cuda_repository.
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/boringssl_git/WORKSPACE:1: Workspace name in /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/boringssl_git/WORKSPACE (@boringssl) does not match the name given in the repository's definition (@boringssl_git); this will cause a build error in future versions.
INFO: All external dependencies fetched successfully.
Configuration finished
[david@SQUIDS tensorflow]$ bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
Warning: ignoring LD_PRELOAD in environment.
WARNING: /home/david/gits/tensorflow/third_party/gpus/cuda_configure.bzl:95:5: TF_NEED_CUDA: 1.
WARNING: /home/david/gits/tensorflow/third_party/gpus/cuda_configure.bzl:336:3: cuda_configure: _create_cuda_repository.
WARNING: /home/david/gits/tensorflow/util/python/BUILD:11:16: in includes attribute of cc_library rule //util/python:python_headers: 'python_include' resolves to 'util/python/python_include' not in 'third_party'. This will be an error in the future.
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/bit_depth.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/gemmlowp.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/map.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/output_stages.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/profiling/instrumentation.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/profiling/profiler.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
INFO: Found 1 target...
ERROR: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/zlib_archive/BUILD:7:1: C++ compilation of rule '@zlib_archive//:zlib' failed: crosstool_wrapper_driver_is_not_gcc failed: error executing command external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc -U_FORTIFY_SOURCE '-D_FORTIFY_SOURCE=1' -fstack-protector -fPIE -Wall -Wunused-but-set-parameter ... (remaining 35 argument(s) skipped): com.google.devtools.build.lib.shell.BadExitStatusException: Process exited with status 1.
In file included from external/zlib_archive/zlib-1.2.8/zconf.h:395:0,
                 from external/zlib_archive/zlib-1.2.8/zlib.h:34,
                 from external/zlib_archive/zlib-1.2.8/zutil.h:22,
                 from external/zlib_archive/zlib-1.2.8/deflate.h:16,
                 from external/zlib_archive/zlib-1.2.8/deflate.c:52:
/usr/include/limits.h:123:26: error: no include path in which to search for limits.h
 # include_next <limits.h>
                          ^
In file included from external/zlib_archive/zlib-1.2.8/zconf.h:421:0,
                 from external/zlib_archive/zlib-1.2.8/zlib.h:34,
                 from external/zlib_archive/zlib-1.2.8/zutil.h:22,
                 from external/zlib_archive/zlib-1.2.8/deflate.h:16,
                 from external/zlib_archive/zlib-1.2.8/deflate.c:52:
/usr/include/sys/types.h:146:20: fatal error: stddef.h: No such file or directory
 #include <stddef.h>
                    ^
compilation terminated.
Target //tensorflow/tools/pip_package:build_pip_package failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 2.827s, Critical Path: 0.40s
[david@SQUIDS tensorflow]$ bazel build -c opt --config=cuda --verbose_failures //tensorflow/tools/pip_package:build_pip_package
Warning: ignoring LD_PRELOAD in environment.
WARNING: /home/david/gits/tensorflow/third_party/gpus/cuda_configure.bzl:95:5: TF_NEED_CUDA: 1.
WARNING: /home/david/gits/tensorflow/third_party/gpus/cuda_configure.bzl:336:3: cuda_configure: _create_cuda_repository.
WARNING: /home/david/gits/tensorflow/util/python/BUILD:11:16: in includes attribute of cc_library rule //util/python:python_headers: 'python_include' resolves to 'util/python/python_include' not in 'third_party'. This will be an error in the future.
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/bit_depth.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/gemmlowp.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/map.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/public/output_stages.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/profiling/instrumentation.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
WARNING: /home/david/.cache/bazel/_bazel_david/47d00ffdd2fc0515138a34f138cebd63/external/gemmlowp/BUILD:102:12: in hdrs attribute of cc_library rule @gemmlowp//:eight_bit_int_gemm: Artifact 'external/gemmlowp/profiling/profiler.h' is duplicated (through '@gemmlowp//:eight_bit_int_gemm_public_headers' and '@gemmlowp//:gemmlowp_headers').
INFO: Found 1 target...

In file included from external/re2/util/util.h:9:0,
                 from external/re2/util/strutil.cc:5:
/usr/include/stdio.h:33:21: fatal error: stddef.h: No such file or directory
 # include <stddef.h>
                     ^
compilation terminated.
Target //tensorflow/tools/pip_package:build_pip_package failed to build
INFO: Elapsed time: 0.834s, Critical Path: 0.36s

Hi
I tried cloning the latest code and followed the steps as pe https://www.tensorflow.org/versions/r0.10/get_started/os_setup.html#installing-from-sources
Now the ./configure & bazel build are success, but some other failure, pasted below.
gopi@gp:~/tensorflow$ bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
....
....
....
Target //tensorflow/cc:tutorials_example_trainer up-to-date:
bazel-bin/tensorflow/cc/tutorials_example_trainer
INFO: Elapsed time: 1142.181s, Critical Path: 1109.17s
gopi@gp:~/tensorflow$ bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so.5.1.5 locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so.8.0 locally
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:925] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
I tensorflow/core/common_runtime/gpu/gpu_device.cc:951] Found device 0 with properties:
name: GeForce GTX 1070
major: 6 minor: 1 memoryClockRate (GHz) 1.835
pciBusID 0000:01:00.0
Total memory: 7.92GiB
Free memory: 7.43GiB
I tensorflow/core/common_runtime/gpu/gpu_device.cc:972] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] 0:   Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:1041] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1070, pci bus id: 0000:01:00.0)
Floating point exception (core dumped)

Not entirely sure if it is the same issue, but I'm also receiving a BUILD file not found on package path error.
~$ bazel test //home/Documents/magenta-master/magenta ERROR: no such package 'home/Documents/magenta-master/magenta': BUILD file not found on package path.
Iḿ using Bazel 0.3.1 on Ubuntu 16.04

ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path. ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
after restart system, even with the recomendations above
"bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer" is taking too long to execute, i've closed after 1 hour
OS: Ubuntu 16.04, Cuda toolkit 8.0, cudnn-8.0-linux-x64-v5.1, GPU nvidia 1070, Bazel 3.1

It got worse. Before, if I deleted/recloned the repo and tried again, it would compile. Now it always fails.
root@machine-learning:/vagrant/packages/tensorflow# bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
INFO: Waiting for response from Bazel server (pid 17980)...
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path.
INFO: Elapsed time: 8.671s

# git rev-parse HEAD
warning: refname 'HEAD' is ambiguous.
1cb04a68d24187d4d02689e2bc8aba9b7abee154

root@machine-learning:/vagrant/packages/tensorflow# ls *bazel*
ls: cannot access '*bazel*': No such file or directory
root@machine-learning:/vagrant/packages/tensorflow# ls -l $(bazel info output_base)/external/local_config_cuda/crosstool
ls: cannot access '/root/.cache/bazel/_bazel_root/b0bb79a433b74dfa52314ef9af1d2ddd/external/local_config_cuda/crosstool': No such file or directory
root@machine-learning:/vagrant/packages/tensorflow# tree $(bazel info output_base)/external/local_config_cuda
/root/.cache/bazel/_bazel_root/b0bb79a433b74dfa52314ef9af1d2ddd/external/local_config_cuda
|-- cuda
|   |-- BUILD
|   |-- build_defs.bzl
|   |-- cuda_config.h
|   |-- extras
|   |   `-- CUPTI
|   |       |-- include
|   |       |   `-- cupti.h
|   |       `-- lib64
|   |           `-- libcupti.so
|   |-- include
|   |   |-- cublas.h
|   |   |-- cuda.h
|   |   `-- cudnn.h
|   |-- lib64
|   |   |-- libcublas.so
|   |   |-- libcudart.so
|   |   |-- libcudart_static.a
|   |   |-- libcudnn.so
|   |   |-- libcufft.so
|   |   `-- libcurand.so
|   `-- platform.bzl
`-- WORKSPACE

@davidzchen

Are you modifying any files under third_party/gpus between running ./configure and bazel build?

Yes, that makes sense. I'm modifying bazel-tensorflow/external/protobuf/BUILD to fix this issue here and third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc.tpl to fix this issue here. I got it to compile after re-running ./configure and bazel build.

All the compilation failures I've seen before only happen on the master branch. None of these issues persists when I switch to the r0.10 branch. Last night I was able to complete a build, Ubuntu 16.04, CUDA 8RC, cuDNN 5.1, nvidia-driver-370, python-2.7, and compute capability 6.1 (for Pascal GPU) - as soon as I switched to r0.10.

Hi,
I am getting a similar error when running ./configure. "ERROR: The specified --crosstool_top '@local_config_cuda//crosstool:CROSSTOOL' is not a valid cc_toolchain_suite rule." Is this related to this issue.
My configuration :
export TF_NEED_GCP=0
export TF_NEED_CUDA=1
export TF_CUDA_VERSION=7.5
export TF_CUDNN_VERSION=5
Is this related to this issue ? I switched to r0.10 branch but still able to reproduce the issue.

@anirudh2290 which version of bazel are you using ?
I've got the same error with this commit and after: bazelbuild/bazel@0d32fc88d6d179bedef4a04bc22c44583365b859
0.3.1 should be fine.

@nsuke thank you. that was the problem. reverting to a previous commit worked.

@anirudh2290 yes this is a recent change in Bazel. @davidzchen we should not longer use a filegroup to refer to crosstool but use cc_toolchain_suite

@damienmg Understood. I have added those changes to #4285

Got this problem ERROR: no such package '@local_config_cuda//crosstool':  again today.
After various attempts the below steps worked.

sudo apt-get upgrade bazel
./configure (i didn't repeat this step >> $ git clone https://github.com/tensorflow/tensorflow)

To build with GPU support:

bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package

mkdir _python_build
cd _python_build
ln -s ../bazel-bin/tensorflow/tools/pip_package/build_pip_package.runfiles/org_tensorflow/* .
ln -s ../tensorflow/tools/pip_package/* .
python setup.py develop

cd tensorflow/models/image/mnist
$ python convolutional.py

meet the same issue.

Hi. I'm getting "ERROR: no such package '@local_config_cuda//crosstool': BUILD file not found on package path." as well with:

bazel: https://github.com/bazelbuild/bazel/releases/download/0.3.1/bazel-0.3.1-installer-linux-x86_64.sh
tensorflow: commit a6c5f8e4e013e54fed8dfcf49fb6de365f018022 (patched according to https://github.com/tensorflow/tensorflow/issues/4312#issuecomment-246109583 to avoid the ios/android errors)
cuda: http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_7.5-18_amd64.deb
python 3.5 as package from: sudo add-apt-repository -y ppa:fkrull/deadsnakes; sudo apt-get update;
sudo apt-get -y install python3.5
forced to use wheel>0.25.0

The issue for me happens deterministically, if I run tensorflow ./configure while trying to avoid interactive questions:
set vars to avoid interactive
export PYTHON_BIN_PATH=/usr/bin/python
No way to confirm the following default value to ./util/python/python_config.sh without actually hitting the Return key: :-((
/usr/lib/python3/dist-packages
export TF_NEED_GCP=n
export TF_NEED_CUDA=y
export GCC_HOST_COMPILER_PATH=/usr/bin/gcc
export TF_CUDA_VERSION=7.5
export CUDA_TOOLKIT_PATH=$CUDA_HOME
export TF_CUDNN_VERSION=4
export CUDNN_INSTALL_PATH=$CUDA_HOME
export TF_CUDA_COMPUTE_CAPABILITIES=3.0
If I run ./configure without setting the above variables, ie.:
ubuntu@aws17:~/tensorflow$ ./configure
~/tensorflow ~/tensorflow
Please specify the location of python. [Default is /usr/bin/python]:
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]
No Google Cloud Platform support will be enabled for TensorFlow
Found possible Python library paths:
/usr/local/lib/python3.5/dist-packages
/usr/lib/python3/dist-packages
Please input the desired Python library path to use.  Default is [/usr/local/lib/python3.5/dist-packages]
/usr/local/lib/python3.5/dist-packages
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]:
Please specify the location where CUDA  toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Please specify the Cudnn version you want to use. [Leave empty to use system default]:
Please specify the location where cuDNN  library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
libcudnn.so resolves to libcudnn.4
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
[Default is: "3.5,5.2"]: 3.0
then the compilation works.
Note that there is probably no way to pass blank values (indicating "use the default" as opposed to undefined values indicating "I have not answered yet") for several of the variables. So ./configure in the interactive mode is getting various things blank while the less interactive ./configure has these values filled.

A similar error now appears during the building process:
/home/kamal/.cache/bazel/_bazel_kamal/f9ae4eca457b390bb2ebe780caca64e0/external/protobuf/BUILD:333:1: Linking of rule '@protobuf//:protoc' failed: crosstool_wrapper_driver_is_not_gcc failed: error executing command
  (cd /home/kamal/.cache/bazel/_bazel_kamal/f9ae4eca457b390bb2ebe780caca64e0/execroot/tensorflow && \
  exec env - \
  external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc -o bazel-out/host/bin/external/protobuf/protoc bazel-out/host/bin/external/protobuf/_objs/protoc/external/protobuf/src/google/protobuf/compiler/main.o bazel-out/host/bin/external/protobuf/libprotoc_lib.a bazel-out/host/bin/external/protobuf/libprotobuf.a bazel-out/host/bin/external/protobuf/libprotobuf_lite.a -lpthread -lstdc++ -B/usr/bin/ -pie -Wl,-z,relro,-z,now -no-canonical-prefixes -pass-exit-codes '-Wl,--build-id=md5' '-Wl,--hash-style=gnu' -Wl,-S -Wl,--gc-sections): com.google.devtools.build.lib.shell.BadExitStatusException: Process exited with status 1.
bazel-out/host/bin/external/protobuf/_objs/protoc/external/protobuf/src/google/protobuf/compiler/main.o: In function `main':
main.cc:(.text.startup.main+0x2ad): undefined reference to `vtable for google::protobuf::compiler::php::Generator'
main.cc:(.text.startup.main+0x5fc): undefined reference to `vtable for google::protobuf::compiler::php::Generator'
main.cc:(.text.startup.main+0x707): undefined reference to `vtable for google::protobuf::compiler::php::Generator'
collect2: error: ld returned 1 exit status
Target //tensorflow/cc:tutorials_example_trainer failed to build

I think this might be related to	4316aeb

Hi,
Facing similar issues for tensorflow build.
I am trying Tensoflow from the source and receive build error for
a) C++ compilation of rule '@grpc//:gpr' failed: crosstool_wrapper_driver_is_not_gcc failed: error executing command external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
b) ERROR: I/O error while writing action log: No space left on device.
Enviornment:
Cuda 8.0
CuDNN 5
Ubuntu 16.04
bazel 0.3
Nvidia K80
Azure VM N6 (56 GB Memory)
Tried ./configure and build several times. Configure is successful but build fails.
Also tried, bazel clean, bazel clean --explunge and ran the build with reduced number of jobs
bazel build -c opt --config=cuda --jobs=10 //tensorflow/cc:tutorials_example_trainer
but the error continues..
Looked at this thread and also
https://github.com/tensorflow/tensorflow/issues/190
Here is the full error message:
52adb8ea4f53b1b72067611e8a7eb020/external/grpc/BUILD:69:1: C++ compilation of rule '@grpc//:gpr' failed: crosstool_wrapper_driver_is_not_gcc failed: error executing command external/local_config_cuda/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc -U_FORTIFY_SOURCE '-D_FORTIFY_SOURCE=1' -fstack-protector -fPIE -Wall -Wunused-but-set-parameter ... (remaining 38 argument(s) skipped): com.google.devtools.build.lib.shell.BadExitStatusException: Process exited with status 1.
ERROR: I/O error while writing action log: No space left on device.
java.util.logging.ErrorManager: 2
java.io.IOException: No space left on device
at java.io.FileOutputStream.writeBytes(Native Method)
at java.io.FileOutputStream.write(FileOutputStream.java:326)
at java.io.BufferedOutputStream.flushBuffer(BufferedOutputStream.java:82)
at java.io.BufferedOutputStream.flush(BufferedOutputStream.java:140)
at java.util.logging.FileHandler$MeteredStream.flush(FileHandler.java:196)
at sun.nio.cs.StreamEncoder.implFlush(StreamEncoder.java:297)
at sun.nio.cs.StreamEncoder.flush(StreamEncoder.java:141)
at java.io.OutputStreamWriter.flush(OutputStreamWriter.java:229)
at java.util.logging.StreamHandler.flush(StreamHandler.java:259)
at java.util.logging.FileHandler.publish(FileHandler.java:683)
at java.util.logging.Logger.log(Logger.java:738)
at java.util.logging.Logger.doLog(Logger.java:765)
at java.util.logging.Logger.log(Logger.java:788)
at java.util.logging.Logger.info(Logger.java:1489)
at com.google.devtools.build.lib.profiler.AutoProfiler$LoggingElapsedTimeReceiver.accept(AutoProfiler.java:315)
at com.google.devtools.build.lib.profiler.AutoProfiler$SequencedElapsedTimeReceiver.accept(AutoProfiler.java:262)
at com.google.devtools.build.lib.profiler.AutoProfiler.completeAndGetElapsedTimeNanos(AutoProfiler.java:226)
at com.google.devtools.build.lib.buildtool.ExecutionTool.saveCaches(ExecutionTool.java:725)
at com.google.devtools.build.lib.buildtool.ExecutionTool.executeBuild(ExecutionTool.java:470)
at com.google.devtools.build.lib.buildtool.BuildTool.buildTargets(BuildTool.java:201)
at com.google.devtools.build.lib.buildtool.BuildTool.processRequest(BuildTool.java:333)
at com.google.devtools.build.lib.runtime.commands.BuildCommand.exec(BuildCommand.java:69)
at com.google.devtools.build.lib.runtime.BlazeCommandDispatcher.execExclusively(BlazeCommandDispatcher.java:488)
at com.google.devtools.build.lib.runtime.BlazeCommandDispatcher.exec(BlazeCommandDispatcher.java:324)
at com.google.devtools.build.lib.runtime.CommandExecutor.exec(CommandExecutor.java:49)
at com.google.devtools.build.lib.server.RPCService.executeRequest(RPCService.java:70)

@sskgit - This looks like b) no space left on device is the reason for a) compilation of a file fails. You'll notice from the bazel-* symlinks in the tensorflow directory point to $HOME/.cache/bazel/..., so check you've got enough space on the partition you have $HOME mounted to.

@darrengarvey Thanks for your response.
I tried sudo df and here is the output
df
Filesystem     1K-blocks     Used Available Use% Mounted on
udev            28837212        0  28837212   0% /dev
tmpfs            5771196     9244   5761952   1% /run
/dev/sda1       29711408 29329736    365288  99% /
tmpfs           28855968        0  28855968   0% /dev/shm
tmpfs               5120        0      5120   0% /run/lock
tmpfs           28855968        0  28855968   0% /sys/fs/cgroup
none                  64        0        64   0% /etc/network/interfaces.dynamic.d
/dev/sdb1      356513788<PHONE_NUMBER>78264   1% /mnt
tmpfs            5771196        0   5771196   0% /run/user/1000
It shows mounted on / has almost no space, and I think $VM/Username (i.e. $HOME) is on the same mount /, as there is no $HOME mounted on, in the output. Is this the right command?
At / (used space)
du -sch
2.3G    .
2.3G    total
At $HOME (used space)
du -sch
4.4G    .
4.4G    total
So, I am not sure what is occupying the remaining space? Total storage on this VM is 380 GB.
Is there any way to get rid of bazel logs? Is it causing the space issue? If so, where?
Thanks
Also, if it is how do I free up some space?

@sskgit Running bazel clean --expunge should remove all of the generated files for the workspace. How much free space do you have after running that command?
@martinwicke Sorry for the late reply. I have been on call for a good part of the past week. That looks like a linker error in protobuf and does not seem related to this particular change. crosstool_wrapper_driver_is_not_gcc is a wrapper script that calls gcc. Is this on a newer version of protobuf?

@davidzchen Thanks for your response.
used bazel clean --expunge (this cleaned 500MB space) and re-configured tensorflow using ./configure
Run the bazel build again..
bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
ERROR: /$HOME/Downloads/tensorflow/tensorflow/core/kernels/BUILD:1710:1: error while parsing .d file: /$HOME/.cache/bazel/_bazel_gpuadmin/52adb8ea4f53b1b72067611e8a7eb020/execroot/tensorflow/bazel-out/local_linux-opt/bin/tensorflow/core/kernels/_objs/depth_space_ops_gpu/tensorflow/core/kernels/depthtospace_op_gpu.cu.pic.d (No such file or directory).
nvcc warning : option '--relaxed-constexpr' has been deprecated and replaced by option '--expt-relaxed-constexpr'.
: fatal error: when writing output to : No space left on device
compilation terminated.
Target //tensorflow/tools/pip_package:build_pip_package failed to build
At $HOME:
du -sch
4.6G	.
4.6G	total
At /:
du -sch
2.3G	.
2.3G	total
df -h
Filesystem      Size  Used Avail Use% Mounted on
udev             28G     0   28G   0% /dev
tmpfs           5.6G  9.1M  5.5G   1% /run
/dev/sda1        29G   29G  9.8M 100% /
tmpfs            28G     0   28G   0% /dev/shm
tmpfs           5.0M     0  5.0M   0% /run/lock
tmpfs            28G     0   28G   0% /sys/fs/cgroup
none             64K     0   64K   0% /etc/network/interfaces.dynamic.d
/dev/sdb1       340G  133M  340G   1% /mnt
tmpfs           5.6G     0  5.6G   0% /run/user/1000
This is a fairly new machine with few installer software (<200MB)

@sskgit Interesting. Can you open a bug at bazelbuild/bazel for this issue? Thanks.

@davidzchen Opened an issue with bazel as well. I have tried the build almost 10 times in last couple of days. Still trying to figure why the build fails and how do I complete the build successfully.

Space issue caused my Tensorflow build to fail. Clearing some space on the / mount made the build successful and Tensorflow now works as expected.
Thanks everyone for your help!

This is happening for me too. I already have TF installed and working for GPU via the runfile but I wanted to compile it for optimizations. I get:
ERROR: Skipping '//tensorflow/tools/pip_package:build_pip_package': error loading package 'tensorflow/tools/pip_package': Encountered error while reading extension file 'cuda/build_defs.bzl': no such package '@local_config_cuda//cuda': Traceback (most recent call last):
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 1039
                _create_local_cuda_repository(repository_ctx)
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 976, in _create_local_cuda_repository
                _host_compiler_includes(repository_ctx, cc)
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 145, in _host_compiler_includes
                get_cxx_inc_directories(repository_ctx, cc)
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 120, in get_cxx_inc_directories
                set(includes_cpp)
depsets cannot contain mutable items
WARNING: Target pattern parsing failed.
ERROR: no such package '@local_config_cuda//crosstool': Traceback (most recent call last):
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 1039
                _create_local_cuda_repository(repository_ctx)
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 976, in _create_local_cuda_repository
                _host_compiler_includes(repository_ctx, cc)
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 145, in _host_compiler_includes
                get_cxx_inc_directories(repository_ctx, cc)
        File "/home/user/bin/tensorflow/third_party/gpus/cuda_configure.bzl", line 120, in get_cxx_inc_directories
                set(includes_cpp)
depsets cannot contain mutable items
INFO: Elapsed time: 4.869s
FAILED: Build did NOT complete successfully (3 packages loaded)
    currently loading: tensorflow/tools/pip_package

Steps to reproduce:
git clone --recurse-submodules https://github.com/tensorflow/tensorflow
cd tensorflow
$ ./configure
WARNING: Running Bazel server needs to be killed, because the startup options are different.
Please specify the location of python. [Default is /home/user/.pyenv/versions/3.6.2/bin/python]:
Found possible Python library paths:
/home/user/.pyenv/versions/3.6.2/lib/python3.6/site-packages
Please input the desired Python library path to use.  Default is /home/user/.pyenv/versions/3.6.2/lib/python3.6/site-packages
Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]: y
jemalloc as malloc support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]: n
No Google Cloud Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Hadoop File System support? [y/N]: n
No Hadoop File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with XLA JIT support? [y/N]: y
XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with VERBS support? [y/N]: n
No VERBS support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL support? [y/N]: n
No OpenCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: y
CUDA support will be enabled for TensorFlow.

Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to default to CUDA 8.0]:
Please specify the location where CUDA 8.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-8.0
"Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 6.0]:
Please specify the location where cuDNN 6 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-8.0]:/usr/lib/x86_64-linux-gnu
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 6.1]
Do you want to use clang as CUDA compiler? [y/N]: n
nvcc will be used as CUDA compiler.

Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Do you wish to build TensorFlow with MPI support? [y/N]: n
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:
Add "--config=mkl" to your bazel command to build with MKL support.
Please note that MKL on MacOS or windows is still not supported.
If you would like to use a local MKL instead of downloading, please set the environment variable "TF_MKL_ROOT" every time before build.
Configuration finished
$ bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=cuda -k //tensorflow/tools/pip_package:build_pip_package

If you notice that I've done something wrong, please let me know. I saw someone before mention something about LD_LIBRARY_PATH which I have set to /usr/local/cuda-8.0/lib64. I figured it was fine since as I said, I already have TF installed and running from the runfile download. I would like to be able to compile from source though.

I’m also facing the same challenge - unable to build tensor flow on a gpu server.  Below given are the details.  OS is Ubuntu 16.04LTS
user@gpu-devbox:~/Workouts/tensorflow$ python --version
Python 2.7.12

user@gpu-devbox:~/Workouts/tensorflow$ gcc --version
gcc (Ubuntu 5.4.0-6ubuntu1-16.04.4) 5.4.0 20160609
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

user@gpu-devbox:~/Workouts/tensorflow$ bazel version
Build label: 0.5.3
Build target: bazel-out/local-fastbuild/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar
Build time: Fri Jul 28 08:34:59 2017<PHONE_NUMBER>)
Build timestamp:<PHONE_NUMBER>
Build timestamp as int:<PHONE_NUMBER>

user@gpu-devbox:~/Workouts/tensorflow$ ./configure
WARNING: Running Bazel server needs to be killed, because the startup options are different.
Please specify the location of python. [Default is /usr/bin/python]:
Found possible Python library paths:
/usr/local/lib/python2.7/dist-packages
/usr/lib/python2.7/dist-packages
Please input the desired Python library path to use.  Default is /usr/local/lib/python2.7/dist-packages
Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]:
jemalloc as malloc support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]:
No Google Cloud Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Hadoop File System support? [y/N]:
No Hadoop File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with XLA JIT support? [y/N]:
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with VERBS support? [y/N]:
No VERBS support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL support? [y/N]:
No OpenCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: Y
CUDA support will be enabled for TensorFlow.

Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to default to CUDA 8.0]:
Please specify the location where CUDA 8.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
"Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 6.0]:
Please specify the location where cuDNN 6 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 6.1,6.1,6.1,6.1]6.1
Do you want to use clang as CUDA compiler? [y/N]:
nvcc will be used as CUDA compiler.

Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:
Do you wish to build TensorFlow with MPI support? [y/N]:
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:
Add "--config=mkl" to your bazel command to build with MKL support.
Please note that MKL on MacOS or windows is still not supported.
If you would like to use a local MKL instead of downloading, please set the environment variable "TF_MKL_ROOT" every time before build.
Configuration finished

user@gpu-devbox:~/Workouts/tensorflow$ echo $CUDA_HOME
/usr/local/cuda-8.0

user@gpu-devbox:~/Workouts/tensorflow$ echo $LD_LIBRARY_PATH
/usr/local/cuda-8.0/lib64

user@gpu-devbox:~/Workouts/tensorflow$ bazel build --config=opt --config=cuda --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" ./tensorflow/tools/pip_package:build_pip_package
.......
ERROR: no such package '@local_config_cuda//crosstool': Traceback (most recent call last):
    File "/home/u19061/Workouts/tensorflow/third_party/gpus/cuda_configure.bzl", line 1039
        _create_local_cuda_repository(repository_ctx)
    File "/home/user/Workouts/tensorflow/third_party/gpus/cuda_configure.bzl", line 976, in _create_local_cuda_repository
        _host_compiler_includes(repository_ctx, cc)
    File "/home/user/Workouts/tensorflow/third_party/gpus/cuda_configure.bzl", line 145, in _host_compiler_includes
        get_cxx_inc_directories(repository_ctx, cc)
    File "/home/user/Workouts/tensorflow/third_party/gpus/cuda_configure.bzl", line 120, in get_cxx_inc_directories
        set(includes_cpp)
depsets cannot contain mutable items
INFO: Elapsed time: 5.488s
FAILED: Build did NOT complete successfully (3 packages loaded)

Also - If when checked the cache doesn’t contain crosstool - Am I missing something here?
user@devbox:~/Workouts/tensorflow$ ls -l $(bazel info output_base)/external/local_config_cuda/crosstool
total 4
-rwxrwxr-x 1 user user 1267 Aug  1 16:32 BUILD

@itssujeeth #11949 fixes the issue when building tensorflow with gpu support using bazel 0.5.3.


not nil is inconsistent?

Bug Report
if a = @a
  # here `a` can't be nil
end

should be:(like dart)
if a  =  @a!

because it not consistent with:
a  = @a
In this case a can still be nil

Make sure a similar issue does not exist yet: use the search box, search engine and look at Stack Overflow.
Include reproducible code: we should be able to paste it into an editor, compile and run it and get the same error as you. Otherwise it's impossible for us to reproduce the bug.
Don't only use play.crystal-lang.org or carc.in: code might be lost and the issue will remain incomplete. Write code in the issue itself.
Reduce code, if possible, to the minimum size that reproduces the bug.
If all of the above is impossible due to a large project, create a branch that reproduces the bug and point us to it.
Include Crystal compiler version (crystal -v) and OS. If possible, try to see if the bug still reproduces on master.

So your proposal is the addition of ! in the if condition? If so, this wouldn't be compatible with the language or at the very least would produce some very confusing syntax, such as the following:
def something! : Int32?
end

if a = random!!
  # less readable here, why are there two exclamations?
end

Your argument for not being consistent with a = @a also doesn't make much sense because that is just passing a reference of @a to a, there is no nil checking being performed here unlike in the if statement.

I can see no inconsistency. The type restriction inside the if branch comes from the if condition.
A singleton assignment without a conditional has no such circumstances, thus it's not comparable.
Adding a trailing exclamation mark would be semantically unnecessary clutter.


fix: #35 - added globalErrorHandling and resolved issue

issue #35: resolved
Related Issues:
Issue #35: Global Exception Handling
Fixes #35
Description:

added a new middleware: globalErrorHandlingMiddleware.js which contains the logic for handling any sort of unhandled errors encountered during the request-response cycle. the middleware will log the details and send an 'error' response to the client.
modified app.js: the modification is made so that the globalErrorHandlingMiddleware works perfectly at times required. And is able to catch exceptions during the request and response cycle.

Checklist:

[x] I have tested my changes.
[x] My code follows the project's coding standards.
[x] I have updated the documentation (if applicable).

Screenshots:

middleware:

app.js:

Additional information
The middleware does handle the connection errors. but the response and logging can be improved to exactly pinpoint where the problem is for future debugging. At the present moment it only tells that something went wrong during the request-response cycle. but doesn't actually tell what actually happened and where exactly it happened.

issue noted. I will add handling for mongoDB errors. which would be a specific type of error requested

@AnupK1234 I've removed the global error handling functionality and added a specific error handling middleware (MongoError). Please have a look again and let me know if more changes are to be made.


localhost:5000/devices post not working

The body of the post is as follows:
{
    "identifier": "abcs",
    "name": "Floor Lamp",
    "device_type": "switch",
    "controller_gateway": "123456789"
}

And here is the issue am getting, not sure what the issue is:
HELP NEEDED.
Traceback (most recent call last):
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1997, in call
return self.wsgi_app(environ, start_response)
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1985, in wsgi_app
response = self.handle_exception(e)
File "/usr/local/lib/python3.9/site-packages/flask_restful/init.py", line 273, in error_router
return original_handler(e)
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1540, in handle_exception
reraise(exc_type, exc_value, tb)
File "/usr/local/lib/python3.9/site-packages/flask/_compat.py", line 32, in reraise
raise value.with_traceback(tb)
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1982, in wsgi_app
response = self.full_dispatch_request()
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1614, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/usr/local/lib/python3.9/site-packages/flask_restful/init.py", line 273, in error_router
return original_handler(e)
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1517, in handle_user_exception
reraise(exc_type, exc_value, tb)
File "/usr/local/lib/python3.9/site-packages/flask/_compat.py", line 32, in reraise
raise value.with_traceback(tb)
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1612, in full_dispatch_request
rv = self.dispatch_request()
File "/usr/local/lib/python3.9/site-packages/flask/app.py", line 1598, in dispatch_request
return self.view_functionsrule.endpoint
File "/usr/local/lib/python3.9/site-packages/flask_restful/init.py", line 480, in wrapper
resp = resource(*args, **kwargs)
File "/usr/local/lib/python3.9/site-packages/flask/views.py", line 84, in view
return self.dispatch_request(*args, **kwargs)
File "/usr/local/lib/python3.9/site-packages/flask_restful/init.py", line 595, in dispatch_request
resp = meth(*args, **kwargs)
File "/usr/src/app/device_registry/init.py", line 62, in post
args = parser.parse_args()
File "/usr/local/lib/python3.9/site-packages/flask_restful/reqparse.py", line 305, in parse_args
value, found = arg.parse(req, self.bundle_errors)
File "/usr/local/lib/python3.9/site-packages/flask_restful/reqparse.py", line 163, in parse
source = self.source(request)
File "/usr/local/lib/python3.9/site-packages/flask_restful/reqparse.py", line 108, in source
values.update(value)
File "/usr/local/lib/python3.9/site-packages/werkzeug/datastructures.py", line 554, in update
for key, value in iter_multi_items(mapping):
TypeError: cannot unpack non-iterable ellipsis object

Hi there,
It has something to do with the package version in the requirements.txt
Changing the requirements.txt works for me.
Flask==2.0.1
flask-restful==0.3.9
markdown==2.6.11
Reference from Stackoverflow here:
https://stackoverflow.com/questions/68120834/non-iterable-ellipsis-in-flask-restful-parser-parse-args


Custom buttons

Developers should be able to add custom buttons. Proposed syntax:
$this->crud->addButton('button_name', 'model_function_name');
// by default this will place the button before edit and delete
// ex: $this->crud->addButton('send_email', 'getSendEmailButton');

// other methods:
$this->crud->removeButton('send_email');
$this->crud->setButtonsOrder(['edit', 'send_email', 'delete']);

This way, I think, we'll leave a lot of space for customization. On your model, you could do something like:
public function getSendEmailButton() {
    return " Send email";
}

and you can have your checks or complex logic there. Ex:

show the button to some users and others not.
show the button for some entries and others not.
show different url depending on some model attribute.
etc.

What I don't like about this is that it does imply you'll be writing some HTML in the model, which is a bit ugly... What do you think? Any better solutions?
--
Note: I also see the need for custom bulk buttons in the future. But that's another topic.

How about something like this :
$this->crud->addButton(new SendEmailFormAction()); // addButton typehint implements CrudFormActionHandler

// extends CrudFormAction ?
class SendEmailFormAction implements CrudFormActionHandler
{
    public function getView()
    {
        return '<button name="handleRequest" type="submit">Send Email</button>';
    }

    public function handleRequest(CrudRequest $request, Crud $crud)
    {
        // send the email to $crud->getRecord() and use $request->all();
        // redirect, show message, something
    }
}

interface CrudFormActionHandler
{
    public function handleRequest(CrudRequest $request, Crud $crud);
}

This is a more correct approach from a programming perspective, I agree.
Hmmm... I think this brings up the question of how abstract do we want the core to be? A lot of questions I get on Github/readme.io/email are very very basic, so I conclude a lot of beginner/intermediate PHP programmers are using Backpack. I'm already spending about 3-4 hours a day answering questions, with only 1000 downloads. I can't imagine what would come after 10.000 downloads or 20.000 downloads and a deeper level of abstraction.
The only solution I see here is that, in order to cater to them too, but also to advanced programmers, we need to keep abstraction as low as possible, because advanced/expert programmers will always be able to customize it however they like, use extra classes, interfaces, traits, whereas beginner/intermmediates won't know how to.
I think we should keep these core principles in mind:

you should be able to create a CRUD panel with as few files as possible;
any PHP MVC developer should be able to understand how a CRUD panel works, from beginner to expert;

That being said, I'm not saying no, I'm just wondering which way to go. @Ghitu @cristiantone @mariusconstantin2503 @fede91it ? What do you think?

https://laravel-backpack.readme.io/docs/crud-fields
This will become an array hell:
[   // PageOrLink
    'name' => 'type',
    'label' => "Type",
    'type' => 'page_or_link',
    'page_model' => '\Backpack\PageManager\app\Models\Page'
],
[  // Select
   'label' => "Category",
   'type' => 'select',
   'name' => 'category_id', // the db column for the foreign key
   'entity' => 'category', // the method that defines the relationship in your Model
   'attribute' => 'name', // foreign key attribute that is shown to user
   'model' => "App\Models\Tag" // foreign key model
],
[       // SelectMultiple = n-n relationship (with pivot table)
    'label' => "Tags",
    'type' => 'select_multiple',
    'name' => 'tags', // the method that defines the relationship in your Model
    'entity' => 'tags', // the method that defines the relationship in your Model
    'attribute' => 'name', // foreign key attribute that is shown to user
    'model' => "App\Models\Tag", // foreign key model
    'pivot' => true, // on create&update, do you need to add/delete pivot table entries?
]

No IDE autocompletion possible, so you always have to go to the docs to see the options possible for maybe tens (>100?) of different form fields.
When using objects, you can apply sensible defaults for, name, attribute, label based on the field name, with auto translations like label('MyModel.field_name', 'default label');
Also the model can be guessed for a FormField user_id that it should find the hasOne User();
So you can do :
new DropdownField('user_id', /*optional name*/, /* optional collection or array of items*/);

And by default it will will provide a map of ['id', getTilte()] or something.
That will help beginners a lot, by having real usable sensible defaults by just boilerplating their models and controllers.

Please see these examples how I use your crud right now (work in process):
https://gist.github.com/axyr/4328d6dba6462d6639347e226182d218
https://gist.github.com/axyr/336934ff114cb943e26bdf9823affd97
https://gist.github.com/axyr/2bf47beaa6af77d7fd48836a694372d2
By applying namingconventions, I only have to create MyModelController extends ModelAdminController to get a list and form view for MyModel.

I'm not sure if this is within your thinking as well, but there's also (IMO) a pretty strong need for custom buttons on a given view, e.g. if I would want to add an "Export to CSV" button that exports the current view to a CSV.

Hmm, you're right, @codydh. So the places where you will be able to add buttons should be:

top of the list view (next to the Add button);
each line (before or after the Edit and Delete buttons);

So then, I think it's best to define some "stacks" where we have buttons and let developers insert buttons there. The stacks above could be named top_buttons and line_buttons
$this->crud->addButtonFromModelFunction('stack_name', 'button_name', 'model_function_name');
$this->crud->addButtonFromView('stack_name', 'button_name', 'view_path');

// other methods:
$this->crud->removeButton('stack_name', 'send_email');
$this->crud->setButtonsOrder('stack_name', ['edit', 'send_email', 'delete']);

This should be pretty future-proof, because

you can create buttons that just go to a page or buttons that do something with javascript;
when bulk actions come along, I can easily see the bottom_buttons stack coming too, and the syntax doesn't need to change then;

...or should we just name the stacks top, bottom and line?

This makes complete sense to me.

should we just name the stacks top, bottom and line?

Seems sensible also.

Done in 2.1 (dev branch right now). Documentation here.


Update moj_elektro_api.py

Bugfix

Sorry, just noticed your PR.... already did a fix + some version bumps. Tnx anyway!


feat: handle cluster with empty credentials on destroy

Refactored code moved common parts for gke_cluster and eks_cluster to
common file, added description to eks_cluster resource so we can use doc
generator

https://www.terraform.io/language/meta-arguments/depends_on
recommended to always add comment with depends_on. I think it would be nice since we had issues without it


How to use my own server for searching Elementum payload and returning results without Burst?

From my understand, Elementum creates a payload and send it to Burst which does searching and returns the results in a format that Elementum understands.
I want to use my own server (nodejs app) to receive the payload and do the searching and filtering and return the data to Elementum.
Is this possible? if yes, how can I send Elementum payload to my server and in which format should I return the result.

@movianlost elementum is posting search request to all script.elementum.* addons, enabled in Kodi.
Example of that: https://github.com/fugkco/script.elementum.jackett


Create files from template only in new modules

It’s surprising that you can create a module, make some functions, run them, remove main.go and it’ll still run, just with the default ones from the template.
Instead of stopping dagger call from doing codegen automatically, I think it would be more reasonable to just not use the template unless you’re using --sdk for a new module. So if you remove main.go or some other file, it errors rather than re-creating on an ephemeral container, which is more surprising.
The client will still be regenerated, just not the initial template files for modules with an existing source.
As a pre-requisite, runtime modules need to know whether they’re creating a new module or not. dagger init --sdk is easy to detect because ModSource.ConfigExists(ctx) returns false. But when adding sources through a dagger develop --sdk, that happens on an existing module but we can’t look for "sdk" field in dagger.json because that’s added in by the CLI before loading the module.
In Python, for example, we would look for the existence of a pyproject.toml file and assume it’s a new module if it doesn’t exist, but now it can be used to configure essential things like Python’s version for the runtime, which is used for the codegen’s base image.
So rather than have the SDKs try to figure it out, have the server set an init boolean in the constructor or call a separate Init function when first adding sources to a module, so it’s easy and consistent for SDKs to apply the template then.

This feels a bit like https://github.com/dagger/dagger/issues/6621#issuecomment-1934787396?

This feels a bit like #6621 (comment)?

Yes, thanks!
Close as duplicate.


[core] Default to measuring a fixed load as opposed to maximum throughput

Measuring at maximum throughput is usually bad practice. Defaulting to a low throttle would encourage users to go through a concious process of selecting the relevant load and the client side resources required to provide it and measure it.

most of the time when I use YCSB I'm looking for bottom-line changes in overall throughput. What's the disadvantage of having each client at max? The one thing I can think of is inconsistency if the client machine doesn't have enough resources for the number of client threads, but that's an issue even when picking a fixed load since it comes from the user, no?

Measuring at max throughput means effectively ignoring response time. It's a relevant measure for batch jobs but not for any responsive system. At max throughput there's no expected schedule, so there's no way to detect coordinated omission scale (you are guaranteed CO issues at max throughput).
A better approach is to automatically calibrate the clients to achieve maximum sustainable throughput for a given SLA(e.g. max throughput such that 99%tile is still below 100ms). I would go for that as a separate piece of work though.


Library doesn't work when using iframe as normal app

So I've created this app:
sysend.on('input', text => {
    console.log({text});
    input.value = text;
});
input.addEventListener('input', () => {
    console.log(input.value);
    sysend.broadcast('input', input.value);
});

but it doesn't synchronize from page to iframes. It only works for iframes to the main page.
Probably because iframe works in proxy mode, not as an app.
It should work somehow, so you can demo the library.

Because of this Codepen demos doesn't work:
https://codepen.io/jcubic/pen/BaJQrYV?editors=1111

The solution may be a function that should and will be called on a proxy file.
Maybe proxy without argument.
sysend.proxy()

this will indicate proxy file.

The issue is fixed. Will create another demo. This will probably also allow using the library on Codepen and CodeSandbox (for now in single way channel, allow single iframe proxy is tracked in #37)


I want better search performance

add indexing for retrieving backlinks and titles
only openBox once during userChange
Refactor HiveDB into it's own class
In getSearchNotes, I will sort the notes then I'll iterate through the notes I will use a while loop until I find first 50 notes that match the search condition. Then I will return them.
Use StreamBuilder to async load the search results

Instead use IsarDatabase along with the string wildcard to supplement search
Match isn't supported on web
Instead, just use a lazybox to load notes, also refactor Hive into its own database class

Should be closed by #505 , can reopen if this is still an issue


ADD: change doc for release 2.5.0 and 2.4.3

What problem does this PR solve?
Add changelog for 2.5.0 and 2.4.3
What is changed and how it works?
Check List
Tests

No code

Related changes

Need to update the documentation

Need to cherry-pick to release-2.4

@shiyuhang0 @zhangyangyu @sunxiaoguang PTAL

https://github.com/pingcap/tispark/pull/2101 this pr

/run-all-tests

/run-all-tests

@sunxiaoguang Plz add label need-to-cherry-pick-to-2.4

#2101 this pr is important for fix the bacthwrite data loss problem. should we put it into changelog

@shiyuhang0 It had already been released in version https://github.com/pingcap/tispark/releases/tag/v2.4.2
but release-2.4 misses in changelog, add them in this pr or another?


Fix home page text appearance

#Fix Home page text appearance

the issue number:  #189
the issue link
I fixed the appearance of the home page text by adjusting the margins. I added a class to the div that contains the text and selected it in the CSS file, setting the margin to 'auto.' This adjustment resolved the issue the text appearance. However, it also removed the gap between the image and the text. To address this, I added the 'gap' property to the container and made further adjustments, ensuring everything looks as intended.

#Fix Home page text appearance

the issue number:  🔴 BUG: padding missing #189
the issue link
I fixed the appearance of the home page text by adjusting the margins. I added a class to the div that contains the text and selected it in the CSS file, setting the margin to 'auto.' This adjustment resolved the issue the text appearance. However, it also removed the gap between the image and the text. To address this, I added the 'gap' property to the container and made further adjustments, ensuring everything looks as intended.

I am facing a minor issue because the edits I pushed are not working as expected. Once I resolve this problem, I will re-pull the changes to ensure they are functioning correctly.


[benchmark] Gather more independent samples for changes

Multimodal benchmarks with significant delta between the modes can report false performance changes when we gather too few independent samples. This increases the minimal number of independent samples for potential performance changes from 5 to 10.
Resolves SR-9907.

@swift-ci please benchmark

@swift-ci please smoke test

@eeckstein Please review 🙏

Oh man! 🤦♂
Let me see how these other fake changes profile in detail...

@swift-ci please benchmark again...

@swift-ci please benchmark again...

@swift-ci please benchmark

@swift-ci please benchmark

DataCreateMediumArray has weakly bi-modal runtime distribution, but nowhere near the DataAppendLargeToLarge severity. I'd say this false change is more of an argument against using minimum as the typical value for a benchmark.

Performance: -O

TEST
OLD
NEW
DELTA
RATIO

Improvement

DataAppendDataSmallToSmall
4560
4040
-11.4%
1.13x (?)

Performance: -Osize

TEST
OLD
NEW
DELTA
RATIO

Improvement

SortLettersInPlace
554
513
-7.4%
1.08x (?)

Performance: -Onone

TEST
OLD
NEW
DELTA
RATIO

Improvement

DataAppendArray
5600
5200
-7.1%
1.08x (?)

How to read the data
The tables contain differences in performance which are larger than 8% and
differences in code size which are larger than 1%.
If you see any unexpected regressions, you should consider fixing the
regressions before you merge the PR.
Noise: Sometimes the performance results (not code size!) contain false
alarms. Unexpected regressions which are marked with '(?)' are probably noise.
If you see regressions which you cannot explain you can try to run the
benchmarks again. If regressions still show up, please consult with the
performance team (@eeckstein).

Hardware Overview
  Model Name: Mac Pro
  Model Identifier: MacPro6,1
  Processor Name: 12-Core Intel Xeon E5
  Processor Speed: 2.7 GHz
  Number of Processors: 1
  Total Number of Cores: 12
  L2 Cache (per Core): 256 KB
  L3 Cache: 30 MB
  Memory: 64 GB

Humph… Increasing the number of independent samples seems to get rid of the false changes from DataAppendLargeToLarge, but it also exposes false changes from the rest of the DataBenchmarks… 🤷♂ I've seen the same two benchmarks jump out before (hidden comment on #21848), so it's hard to say if gathering more independent samples increases the chance of false change reports... let's try again.
@swift-ci please benchmark

Performance: -Onone

TEST
OLD
NEW
DELTA
RATIO

Improvement

DataAppendArray
5600
5100
-8.9%
1.10x (?)

How to read the data
The tables contain differences in performance which are larger than 8% and
differences in code size which are larger than 1%.
If you see any unexpected regressions, you should consider fixing the
regressions before you merge the PR.
Noise: Sometimes the performance results (not code size!) contain false
alarms. Unexpected regressions which are marked with '(?)' are probably noise.
If you see regressions which you cannot explain you can try to run the
benchmarks again. If regressions still show up, please consult with the
performance team (@eeckstein).

Hardware Overview
  Model Name: Mac Pro
  Model Identifier: MacPro6,1
  Processor Name: 12-Core Intel Xeon E5
  Processor Speed: 2.7 GHz
  Number of Processors: 1
  Total Number of Cores: 12
  L2 Cache (per Core): 256 KB
  L3 Cache: 30 MB
  Memory: 64 GB

The DataAppendArray is jumpy in -Onone because of setup overhead from the fillBuffer function. I'll fix that one in the upcoming Janitor Duty.


MaterialUI styling implemented

Styling with the use of CSS and MaterialUI

Work On Next: More details displayed

No merge conflicts identified
Clear to merge


Broker_connection

Create a bridge between app and the code in the backend

As a user I want my app to connect to my car in the simulator
Acceptance Criteria:


Moving Columns Example

Is there any chance I could humbly request an example in the documentation for when you move a card between two columns. There are comments alluding to it in the docs like this line:

Do this if the original component may be unmounted during the dragging and later “resurrected” with a different parent. For example, when moving a card across the lists in a Kanban board,

But I can't for the life of me figure out how to drop it like its hot where i need it and remove it from whence it came.

I had to do it manually for reactware library, you can take a look at the example to get an idea as to what I did, but i'd recommend to use something like react-beatufull-dnd if you just want lists.

Bumping this. I love the flexibility of React DND (e.g. more than just moving items in a list!), but it would be nice if we could get a little more insight into a dynamic, multi-column drag and drop scenario.
For instance, what if I want to move a card from one list to another and use the hover method two move the cards of the destination list out of the way?
Currently tinkering with this, but it's not immediately apparent to me how, or if, this is even possible. Love this package, just looking for a bit more insight into a very common use-case.


”Vetiș”, ”Decebal”, ”Oar” are listed in the drop-down menu

Description:
When user writes ”Vetiș”, ”Decebal”, ”Oar” the locations appear in the drop-down menu next to the comune and the county which is a part according to the law.
Precondition:
The website is up an running.

Step 1
Write in the search bar "Vetiș"

Expected results
The location appears in the drop-down menu as "Sat Vetiș, SATU MARE (Vetiș)".

Step 2
Press "x" button.

Expected results
The location was deleted from the search bar.

Step 3
Write in the search bar "Decebal"

Expected results
The location appears in the drop-down menu as "Sat Decebal, SATU MARE (Vetiș)".

Step 4
Press "x" button.

Expected results
The location was deleted from the search bar.

Step 5
Write in the search bar "Oar"

Expected results
The location appears in the drop-down menu as "Sat Oar, SATU MARE (Vetiș)".


Long time Initializing...

Actually initialization takes a very long time. Even on one video card it's about 10 minutes.

I have noticed that too. Although i find that if u just leave it alone for 15- 20 mins or longer and come back and hit -s it kicks in and starts working.I do not know why but has worked every time for me.

Hello Richard, nice tool you have develop. Please what could cause the error "BitCrack64.exe has stopped working.......a programme caused the programme to stop working correctly....." Please help me with ideas.... Thanks.

GPU initialization is in latest release.


pythonPackages.imagecorruptions: init at 1.1.0

Motivation for this change
pythonPackages.imagecorruptions: init at 1.1.0
This is needed by imgaug tests
https://github.com/NixOS/nixpkgs/pull/80098
https://github.com/NixOS/nixpkgs/pull/79982
Things done

[ ] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[ ] Fits CONTRIBUTING.md.
@CMCDragonkai @jonringer

@GrahamcOfBorg build pythonPackages.imagecorruptions
@GrahamcOfBorg build python3Packages.imagecorruptions
@GrahamcOfBorg build python38Packages.imagecorruptions

failures dont look related to the package