[hi] translate case studies

This is a Feature Request

What would you like to be added

Translate all the English paragraphs in case-study page to Hindi.

Comments

Page to be updated: https://kubernetes.io/hi/case-studies/

These paragraphs are extracted from markdown file of individual case study pages (Babylon, Appdirect, booking.com etc). Resolving it requires to localize each of these 4 case-study pages in Hindi first.

Oh I see

/assign

I think, We have to change every Case Study there in Hindi first

Localizing these 4 case-study pages (Babylon, AppDirect, Booking.com, Booz|Allen|Hamilton) is enough to resolve this issue

Yes @aj11anuj

I have created a PR For this @satyampsoni

Thank you for your efforts, everyone! However, I'd quickly like to request that unless triage has been accepted on the issue with a triage/accepted label, you do not commence your efforts. It might cause duplicate efforts to be underway and we do not want that.
/triage accepted

Yes, @divya-mohan0209 , we will definitely look into this!


Illegal instruction (core dumped) after running import tensorflow

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below):
1.6.0-cp27-cp27mu-manylinux1_x86_64 (can only guess since python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)" gives me an error already)
Python version: Python 2.7.12
Exact command to reproduce: import tensorflow

I created a fresh virtual environment: virtualenv -p python2 test_venv/
And installed tensorflow: pip install --upgrade --no-cache-dir tensorflow
import tensorflow gives me Illegal instruction (core dumped)
Please help me understand what's going on and how I can fix it. Thank you.
CPU information:
-cpu
          description: CPU
          product: Intel(R) Core(TM) i3 CPU       M 330  @ 2.13GHz
          bus info: cpu@0
          version: CPU Version
          capabilities: x86-64 fpu fpu_exception wp vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx rdtscp constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf pni dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm sse4_1 sse4_2 popcnt lahf_lm tpr_shadow vnmi flexpriority ept vpid dtherm arat cpufreq

EDIT
Stacktrace obtained with gdb:
#0  0x00007fffe5793880 in std::pair<std::__detail::_Node_iterator<std::pair<tensorflow::StringPiece const, std::function<bool (tensorflow::Variant*)> >, false, true>, bool> std::_Hashtable<tensorflow::StringPiece, std::pair<tensorflow::StringPiece const, std::function<bool (tensorflow::Variant*)> >, std::allocator<std::pair<tensorflow::StringPiece const, std::function<bool (tensorflow::Variant*)> > >, std::__detail::_Select1st, std::equal_to<tensorflow::StringPiece>, tensorflow::StringPieceHasher, std::__detail::_Mod_range_hashing, std::__detail::_Default_ranged_hash, std::__detail::_Prime_rehash_policy, std::__detail::_Hashtable_traits<true, false, true> >::_M_emplace<std::pair<tensorflow::StringPiece, std::function<bool (tensorflow::Variant*)> > >(std::integral_constant<bool, true>, std::pair<tensorflow::StringPiece, std::function<bool (tensorflow::Variant*)> >&&) ()
   from /media/gerry/hdd_1/ws_hdd/test_venv/local/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so
#1  0x00007fffe5795735 in tensorflow::UnaryVariantOpRegistry::RegisterDecodeFn(std::string const&, std::function<bool (tensorflow::Variant*)> const&) () from /media/gerry/hdd_1/ws_hdd/test_venv/local/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so
#2  0x00007fffe5770a7c in tensorflow::variant_op_registry_fn_registration::UnaryVariantDecodeRegistration<tensorflow::Tensor>::UnaryVariantDecodeRegistration(std::string const&) ()
   from /media/gerry/hdd_1/ws_hdd/test_venv/local/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so
#3  0x00007fffe56ea165 in _GLOBAL__sub_I_tensor.cc ()
   from /media/gerry/hdd_1/ws_hdd/test_venv/local/lib/python2.7/site-packages/tensorflow/python/../libtensorflow_framework.so
#4  0x00007ffff7de76ba in call_init (l=<optimized out>, argc=argc@entry=2, argv=argv@entry=0x7fffffffd5c8, env=env@entry=0xa7b4d0)
    at dl-init.c:72
#5  0x00007ffff7de77cb in call_init (env=0xa7b4d0, argv=0x7fffffffd5c8, argc=2, l=<optimized out>) at dl-init.c:30
#6  _dl_init (main_map=main_map@entry=0xa11920, argc=2, argv=0x7fffffffd5c8, env=0xa7b4d0) at dl-init.c:120
#7  0x00007ffff7dec8e2 in dl_open_worker (a=a@entry=0x7fffffffb5c0) at dl-open.c:575
#8  0x00007ffff7de7564 in _dl_catch_error (objname=objname@entry=0x7fffffffb5b0, errstring=errstring@entry=0x7fffffffb5b8,
    mallocedp=mallocedp@entry=0x7fffffffb5af, operate=operate@entry=0x7ffff7dec4d0 <dl_open_worker>, args=args@entry=0x7fffffffb5c0)
    at dl-error.c:187
#9  0x00007ffff7debda9 in _dl_open (
    file=0x7fffea7cbc34 "/media/gerry/hdd_1/ws_hdd/test_venv/local/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so", mode=-2147483646, caller_dlopen=0x51ad19 <_PyImport_GetDynLoadFunc+233>, nsid=-2, argc=<optimized out>, argv=<optimized out>, env=0xa7b4d0)
    at dl-open.c:660
#10 0x00007ffff75ecf09 in dlopen_doit (a=a@entry=0x7fffffffb7f0) at dlopen.c:66
#11 0x00007ffff7de7564 in _dl_catch_error (objname=0x9b1870, errstring=0x9b1878, mallocedp=0x9b1868, operate=0x7ffff75eceb0 <dlopen_doit>,
    args=0x7fffffffb7f0) at dl-error.c:187
#12 0x00007ffff75ed571 in _dlerror_run (operate=operate@entry=0x7ffff75eceb0 <dlopen_doit>, args=args@entry=0x7fffffffb7f0) at dlerror.c:163
#13 0x00007ffff75ecfa1 in __dlopen (file=<optimized out>, mode=<optimized out>) at dlopen.c:87
#14 0x000000000051ad19 in _PyImport_GetDynLoadFunc ()
#15 0x000000000051a8e4 in _PyImport_LoadDynamicModule ()
#16 0x00000000005b7b1b in ?? ()
#17 0x00000000004bc3fa in PyEval_EvalFrameEx ()
#18 0x00000000004c136f in PyEval_EvalFrameEx ()
#19 0x00000000004b9ab6 in PyEval_EvalCodeEx ()
#20 0x00000000004b97a6 in PyEval_EvalCode ()
#21 0x00000000004b96df in PyImport_ExecCodeModuleEx ()
#22 0x00000000004b2b06 in ?? ()
#23 0x00000000004a4ae1 in ?? ()

EDIT 2
Bazel version: N/A
CUDA/cuDNN version: N/A
GPU model and memory: N/A
After downgrading to an older version of tensorflow the error goes away. I've been advised that my CPU (see information above) might not work with some improvements in the new API. If this is the case, I suppose there's no solution for my problem. Therefore, I will close this thread. Feel free to correct me though. Thank you for your support

Thank you for your post. We noticed you have not filled out the following field in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Thanks.
Bazel version
CUDA/cuDNN version
GPU model and memory

I'm having the same (or similar) "illegal instruction" problem when I run
import tensorflow as tf

I'm only using the CPU 1.6 version.
After downgrading to the CPU 1.5 version, it doesn't have this problem.

How i can downgrade to the CPU 1.5 version?

Try running
pip uninstall tensorflow
And then
pip install tensorflow==1.5

Thanks konnerthg, even i was having the same problem. Your command helped me to sort this issue. Thanks again.

Same here.
With the latest wheel, I had the illegal instruction problem on Ubuntu 16.04, however I downgraded to tensorflow-gpu==1.5 and it works!

downgrade to 1.5 worked for me, too

@konnerthg Downgrading to 1.5 is just work around, this issue is not solved yet.
Which commit/PR solved this issue?

I am also getting this error in python 3.6

Hey !
Thank you for your solution ! Really. I have this problem for a week now and I was starting to become crazy ! Thx !

THANKS for solution.It worked on my Ubuntu 16.04, 64 bit, python3.5 .

Thanks for the solution! Downgrading to version 1.5 fixed the issue. Tested on a Ubuntu 16.04 server with python 2.7

Same issue, downgrading from Tensorflow 1.6 to 1.5 solved it. Running Xubuntu 16.04, Python 3.5.

Thanks for all this solve my issue on Python 3.6

_ (tensorflow) naniny@Aspire-E5-573:~$ pip unistall tensorflow

_(tensorflow) naniny@Aspire-E5-573:~$ pip install tensorflow==1.5

_(tensorflow) naniny@Aspire-E5-573:~$ python

_ (tensorflow) naniny@Aspire-E5-573:~$ import tensorflow as tf

now works without any problem ...

This is really weird. Does anyone know what causes the issue? I'm surprised that TensorFlow 1.6 would have a bug this big.

I am encountering this issue as well with tensorflow-gpu 1.6.0, on linux, using python 3.6.4.  I have installed tensorflow using pip itself.  Simply running this produces a SIGILL:
$ python3 -m tensorflow
zsh: illegal hardware instruction  python3 -m tensorflow

I get stack traces similar to what is mentioned in this ticket's description.
This seems to be occurring due to the use of AVX instructions in the latest Tensorflow packages uploaded to pip.  Running python3 through GDB and disassembling the crashing function points to this instruction:
=> 0x00007fffb9689660 <+80>:    vmovdqu 0x10(%r13),%xmm1

Which is an AVX instruction not supported on older or less-featureful CPUs that do not have AVX support.  The tensorflow(-gpu) 1.5.0 pip packages do not use AVX instructions, and thus there are no problems using it with these CPUs.
The solution would be for a build of tensorflow(-gpu) that is not compiled with AVX instructions to be published (or to build a copy locally).  The provided installation instructions do not mention any specific CPU requirements nor how to determine compatibility with the provided binaries.
In the meantime, reverting to tensorflow(-gpu) 1.5.0 using something like what @NinemillaKA mentioned above is an effective workaround.

I have the same issue, and, as many have commented, downgrade from 1.6.0 to 1.5.0.
For the record, I tried running tensorflow (CPU-only version) on 2 different computers:
Computer 1:
OS = Ubuntu 16.04 x64 LTS
Python = Python 3.6
pip version = 9.0.1
tensorflow version = TensorFlow 1.6.0
CPU = Intel Core 2 Quad Q6600  @2.40GHz

Computer 2:
OS = Ubuntu 16.04 x64 LTS
Python = Python 3.6
pip version = 9.0.1
tensorflow version = TensorFlow 1.6.0
CPU = Intel Celeron N2820 @2.413GHz

I agree with @nacl that we should have those requirements about the instruction set more clear, and if possible, a separated, updated build for processors that doesn't support AVX instructions.

The alternative to having a different build for each architecture type is to use dynamic dispatch. IE, PyTorch has one binary for all architectures and selects most efficient ops during runtime @caisq

Thanks

I also encounter the same issue. I tried it on two machines, and it works on one of them.
First, I installed it on my MacBook Pro. And I did not have any issues.

MacBook Pro (Retina, Mid 2012)
CPU = 2.3 GHz Intel Core i7
OS = MacOS 10.13.3
Python = Python 3.6.4
pip version = 9.0.3
TensorFlow version = 1.6.0

So I upgraded my MacPro. But this time, I am getting Illegal instruction: 4 when I try to import tensorflow.

Mac Pro (Mid 2010)
CPU = 2 x 2.4 GHz Quad-Core Intel Xeon
OS = MacOS 10.13.3
Python = Python 3.6.4
pip version = 9.0.3
TensorFlow version = 1.6.0

I would like to use TensorFlow 1.6 since it has new features like WarmStartSettings.

This is still an issue in 1.6 and potentially in 1.7.  Why is this closed?  @yaroslavvb 's solution seems reasonable.  I have downgraded to 1.5 for now.

@captainst that's Intel-specific release, different from the official release that you get by doing pip install. SIGILL issues after 1.6 upgrade are likely caused by adding AVX

I have the same issue.
Ubuntu 18.04 x64
Python 3.6.5rc1
TensorFlow 1.7.0

I had the same issue. Downgrade to 1.5 worked for me.

Same here.

Me too. Arch Linux and Intel CPU.

I want to use the latest tensorflow-gpu (1.7) and don't want to stick to 1.5. So is the solution to build tensorflow from source without AVX support enabled? I have an old Xeon E5420 but am using tensorflow-gpu

dmoham1476<EMAIL_ADDRESS>周六上午2:28写道：

I want to use the latest tensorflow-gpu (1.7) and don't want to stick to
1.5. So is the solution to build tensorflow from source without AVX support
enabled? I have an old Xeon E5420 but am using tensorflow-gpu
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You can build from source from the git clone master. It should auto adjust
to ur cpu.
Regards,
Jin

I have the same problem with 1.7 but I cannot downgrade at 1.5 because I need new attribute that are located in 1.6 and 1.7. How can I fix the problem?
This is my CPU: AMD A4-3300M APU with Radeon(tm) HD Graphics
It's to old to run tensorflow? Is tensorflow works with new CPU and GPU? My PC is 6-7 years old.

Downgrading to version 1.5 fixed the issue. I am using Ubuntu 16.04  with python 2.7

Same Problem
Ubuntu=16.10
python=3.6
pip=9.0.3
with tensorflow-gpu= 1.7
solved by:
pip install tensorflow-gpu==1.5

the same problem

same problem
Ubuntu 16.04
with tensorflow-gpu 1.7 and 1.6

Same problem on this Docker image running in a Paperspace notebook.
Issue is with versions 1.6 and 1.7

Having the same issue, downgraded to 1.5. Tensorflow imports now but I'm running a script that needs tensorflow_hub. Script is throwing RuntimeError: TensorFlow Hub depends on 'tf-nightly' build after 20180308 or 'tensorflow~=1.7'. Found tf.VERSION = 1.5.0

thanks going back to version 1.5 worked for me also

Same issue here trying to use 1.7 cpu on Linux

I had the same problem with tf`1.8 on CentOS 7, CPU only. Downgrading to 1.5 worked.

For those that do not want to downgrade if you build from source the problem is resolved.

Having the same problem, Downgrading to 1.5 worked for me.

I am unable to downgrade because I get the "illegal hardware instruction" when running pip. I'm using a pi running Rasbian Jessy. Any suggestions?

Just had this issue too, on tensorflow-gpu 1.8.0, at paperspace fast.ai template machine

I have the same issue with tensorflow-1.8.0. The problem is I can't downgrade to version 1.5 as I want to train with retrain.py and for this tensorflow version greater than 1.7 is a requirement. So, any suggestions?

Same issue here:
paperspace VM with fast.ai template
GPU: nvidia quadro P4000
tensorflow 1.8.0 installed in virtualenv as in https://www.tensorflow.org/install/install_linux#installing_with_virtualenv gave the error above
ubuntu 16.04, python 3.6.3
pip uninstall tensorflow && pip install tensorflow-gpu==1.5.0 fixed the problem. I have not tried compiling from source yet.

Hello everyone,  building from source solved the issue for me.
در تاریخ یکشنبه ۱۳ مهٔ ۲۰۱۸، ۱:۴۷ laurentS<EMAIL_ADDRESS>نوشت:

Same issue here:
paperspace VM with fast.ai template
GPU: nvidia quadro P4000
tensorflow 1.8.0 installed in virtualenv as in
https://www.tensorflow.org/install/install_linux#installing_with_virtualenv
gave the error above
ubuntu 16.04, python 3.6.3
pip uninstall tensorflow && pip install tensorflow-gpu==1.5.0 fixed the
problem. I have not tried compiling from source yet.
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I phase the same problem, but after shift to tensorflow-1.5 it worked for me.
My Problem:- error -> core dumped
Processor: AMD® A4-3330mx apu with radeon(tm) hd graphics × 2
Graphics:  AMD® Sumo
GNOME: 3.28.1
OS type:  64-bit, Ubuntu 18.04 LTS
Credit:-https://github.com/konnerthg

of course it works with earlier versions of tensorflow but i need more specifically the 1.7.0 version that is compatible with the new tensorflowjs. How can?

@mctrjalloh  buy new CPU, I guess

You have to build from sources it's not that complicated

Same for me:
OS: Ubuntu 16.04
Python: 3.5
NVIDIA Driver Version: 384.130

CUDA9.0+cuDNN7.1+Tensorflow-gpu1.5 is working

Same problem. Tested on Ubuntu 16 and Ubuntu 17, on 3 different machines each with >8GB RAM and >4ghz CPU. Also getting issue with GPU machines.

Same problem on my Ubuntu Server 16.04. Solved by compiling TensorFlow (r1.8) from source and pip install from that locally :+1:

The issue comes with docker images too. I don't want to compile from source. Is there a way around it? I don't want to downgrade either.

In my case, compiling TensorFlow (on Ubuntu 18.04) with Bazel solved the issue. The compilation did take time though.

My case as well, recompiling TensorFlow 1.9 solved the issue. However I encountered another issue related to numpy 1.15. Downgrading to numpy 1.14.5 and the compilation worked, and been able to install the pip package.

Why is this issue closed? It's still occurring in TensorFlow 1.10.

I posted some links to a few community builds of tensorflow here which might help avoid having to build from source.

Indeed, I followed the instructions found at https://www.tensorflow.org/install/install_linux and get nothing more than the "Illegal instruction (core dumped)" when testing as requested on that installation page.
This issue should either not be closed or have an actual solution that makes sense (i.e. not installing version 1.5)

well this issue seems to still going on.. but i have a very simple solution
that will make you follow the trends at the same time :-).
INSTALL CONDA !!!
to install conda, just google it :-)
create a conda evironment if you like:
conda create <name_of_environment>
and simply run:
conda install tensorflow
if the last command doesn't work then search through another channel by
running:
anaconda search tensorflow
this outputs a list of channels from where you can download it.
choose one channel and run:
anaconda show
this will prompt you the command you need to enter to downloading
tensorflow.
Run that command.
That's it !
MOVE TO CONDA !!!
On Thu, Aug 23, 2018 at 10:38 PM Alexis Wilke<EMAIL_ADDRESS>wrote:

Indeed, I followed the instructions found at
https://www.tensorflow.org/install/install_linux and get nothing more
than the "Illegal instruction (core dumped)" when testing as requested on
that installation page.
This issue should either not be closed or have an actual solution that
makes sense (i.e. not installing version 1.5)
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Root problem may have to do with protobuf and incompatibility around pthread_once and std::call_once. I ran into a segfault myself when importing tensorflow right after sentencepiece, and the maker of sentencepiece fixed it by making a patch for protobuf that replaces the std::call_once implementation with another.
https://github.com/google/sentencepiece/issues/186

To make this issue more constructive, I think it would be useful it TensorFlow would check for instructions it requires on the CPU first, and print an error if they are missing. Similarly how it currently says that some instructions are available but not compiled against. Then it would be easier to differentiate between bugs and simply not using correct binary for a given CPU.

Mr royyannick ..Infact i have been searching google for many times and it has affected my studying both Keras and Tensoflow but today you have made my day..You are great.
Thanks

I happened to reproduce this issue on a machine running an old CPU. Here is the article that explains the possible options to resolve the issue.
Those who want to install the latest TensorFlow for old CPU without AVX support but does not have the time to build from source can also download the WHL file from this Github repository.

This is BS. I rolled my installation back to 1.9 (not 'before 1.6' as you say in this article) and the binary worked (the day before yesterday).

If you run this on command line:

$ lsb_release -a| grep "Release" | awk '{print $2}'

$ grep flags -m1 /proc/cpuinfo | cut -d ":" -f 2 | tr '[:upper:]' '[:lower:]' | { read FLAGS; OPT="-march=native"; for flag in $FLAGS; do case "$flag" in "sse4_1" | "sse4_2" | "ssse3" | "fma" | "cx16" | "popcnt" | "avx" | "avx2") OPT+=" -m$flag";; esac; done; MODOPT=${OPT//_/\.}; echo "$MODOPT"; }

and see 16.04 for 1) and -mavx or -mavx2  for 2) in the output, it can be another problem that is not related with AVX support.
If those flags are not there, that's something that I should add into my note, thanks to you.

Same error here,
CentOS 7, Python 3.6.5, Intel CPU core2 duo e8500. pip install.
version 1.9 does't work. version 1.5 imports ok.

This is stated at https://www.tensorflow.org/install/install_sources
Note: Starting from 1.6 release, our prebuilt binaries will use AVX instructions. Older CPUs may not be able to execute these binaries.
I think that might have been mentioned at the much more prominent location!

This solved my issue:
After installing NVIDIA driver, CUDA Toolkit, and CUDNN.
First uninstall tensorflow-gpu:
$ pip uninstall tensorflow-gpu

Using Anaconda:
$ conda create -n tensorflow
$ conda install tensorflow-gpu -n tensorflow

Maybe related to AVX instruction. pip prebuilt tensorflow-1.6 is built with AVX instruction, some CPU doesn't have AVX instruction. pip prebuilt tensorflow-1.6 is not built with AVX instruction.
Suggestion: 1): use lower version of tensorflow
2): compile higher version of tensorflow from source

Yes. Indeed. It would be better, though, if the software would tell me rather than just crash. I don't have a problem with the requirement, just the way it is handled... On Linux, it would be very easy to check in /proc/cpuinfo for the flags line where avx would need to appear. If not, generate an error and exit(1).

System information

Lenovo-G500 8GB RAM          description: CPU
product: Intel(R) Core(TM) i3 CPU       M 330  @ 2.13GHz
bus info: cpu@0
version: CPU Version
OS; Ubuntu-16.05
pip : 18 version latest
I dont have gpu

i also getting   illegal instruction core dumped. tensorforflow 1.5 is working for me ,
but
I need to install tensorflowv1.10 0r latest for my project .
I tried to to install in tensorflow in different ways , those are

without anacoda , python 2.7,   using pip  ...pip install --upgrade tensorflow
2 without anacoda , python 3.5,   using pip     ""
3.without anacoda , python 3.6,   using pip   ""
4.with anacoda , python 2.7,   using conda     conda install -c conda-forge tensorflow
5.without anacoda , python 2.7,   using pip   ""
6.without anacoda , python 2.7,   using pip      ""

neither worked for me,
what is the issue.

@bandarikanth
The manner in which you install tensorflow shouldn’t matter. The problem is that the tensorflow 1.6+ prebuilt binaries require the AVX instruction set extensions, and your processor doesn’t support AVX. You can either build from source, move to a computer with a new-enough processor, or stick with 1.5.

works for me if downgrade to 1.5 (pip install tensorflow==1.5)

Related: https://github.com/tensorflow/tensorflow/issues/19584

I have this issue with tensorflow-gpu 2.0
▶ conda env export
name: Science
channels:
  - defaults
dependencies:
  - cudatoolkit=10.0.130=0
  - cudnn=7.3.1=cuda10.0_0
prefix: /home/archangel/anaconda3/envs/Science

▶ pip freeze | ack "tensor"
tensorflow-gpu==2.0.0a0
▶ ipython
Python 3.7.3 (default, Mar 27 2019, 22:11:17)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.4.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import tensorflow as tf
[1]    25429 illegal hardware instruction (core dumped)  ipython

[18556.882892] traps: ipython[25429] trap invalid opcode ip:7fc41cde1a22 sp:7ffe68904500 error:0 in libtensorflow_framework.so[7fc41c877000+104c000]
[18556.885033] audit: type=1701 audit(1556951396.587:43): auid=4294967295 uid=1000 gid=1000 ses=4294967295 pid=25429 comm="ipython" exe="/home/archangel/anaconda3/bin/python3.7" sig=4 res=1
[18556.894046] audit: type=1130 audit(1556951396.594:44): pid=1 uid=0 auid=4294967295 ses=4294967295 msg='unit=systemd-coredump@4-25462-0 comm="systemd" exe="/usr/lib/systemd/systemd" hostname=? addr=? terminal=?
 res=success'
[18557.506049] audit: type=1131 audit(1556951397.204:45): pid=1 uid=0 auid=4294967295 ses=4294967295 msg='unit=systemd-coredump@4-25462-0 comm="systemd" exe="/usr/lib/systemd/systemd" hostname=? addr=? terminal=?
 res=success'

I'm getting this crash on an i7-3520M which does support AVX.

Still have the problem with tensorflow 1.14.0 and 2.0.0b1.

Same error on Linux Mint 19 with 2.0.0b1.
Just installed with pip3 like instructed from the install page of the official site

tf1.5 isn't available in the Debian 8.8 repos.
Time to try avx.

This was ridiculously hard to find on managed cluster nodes, since the OS kills the related python processes before they can even write and flush this "Illegal instructions" line to a output log file, and the exit code of the python process seems to be 0.
I was also using 2.0.0-beta1, currently finding out if replacing it with 2.0.0 fixes this.

I also got this problem. I'm using python2. Downgrading to the CPU 1.5 version helped.

I'm having this problem with Tensorflow 2 runing in a virtual environment in Ubuntu 18.04.  NOT Impressed, you TF developers .

dmesg output (from bash):
[333908.854310] traps: python[12862] trap invalid opcode ip:7f8c46e6d820 sp:7ffc87609f78 error:0 in _pywrap_tensorflow_internal.so[7f8c3e250000+a9f8000]
linuxmint 19
Intel(R) Pentium(R) CPU        P6200  @ 2.13GHz
8Gb ram (kingston)
This is a BIG CPU-RELATED issue.

After reading this thread and having  the same experience, my problem is that my linux conputer is older and has a CPU which does not support the AVX instruction set. I have tensorflow 1.5 on another virtual environment, bu tto use tensorflow 2, I amd going to run my scripts on Google Colab

I don't have the knowledge to say if the requirement of AVX makes sense or not. What I know is that the problem presents itself not only with older CPUs, but also with fairly recent ones, like mine Intel N5000. I get that doing deep learning on a N5000 is a bit of a stretch, but if the tensorflow is supported also by the RaspberryPi, I don't see the problem.
Anyway, I installed the last version of TensorFlow (2.0) on my Intel N5000 by compiling it from source. It took 14 hours because I had to run the compilation on a single core, since it needs a lot of RAM and I have only 4Gb invited to the party.
I took inspiration from this guide here but the experience was far from smooth, there were constantly dependencies missing that I need to install and re-launch the compilation. And some other stuff too that I solved when the compilation crashed.
Have fun and thanks for the hassle. Providing through pip already binary compiled for non-AVX was clearly too much to add in your continuous integration worklow

Thanks for your response, Luca. I have a really old Ubuntu 18.04 desktop
which works really well except in running the TF2 and as a matter of fact,
the latest PyTorch (1.3.0) I think.
Torch 1.1.0 works fine for me, and regarding TF2, I use Google Colab which
works fine. Am a retired data analyst and maintaining my hobbyist profile
Thans for your post
On Sat, Dec 7, 2019 at 6:52 PM Luca Olivieri<EMAIL_ADDRESS>wrote:

I don't have the knowledge to say if the requirement of AVX makes sense or
not. What I know is that the problem presents itself not only with older
CPUs, but also with fairly recent ones, like mine Intel N5000. I get that
doing deep learning on a N5000 is a bit of a stretch, but if the tensorflow
is supported also by the RaspberryPi, I don't see the problem.
Anyway, I installed the last version of TensorFlow (2.0) on my Intel N5000
by compiling it from source. It took 14 hours because I had to run the
compilation on a single core, since it needs a lot of RAM and I have only
4Gb invited to the party.
I took inspiration from this guide here
https://tech.amikelive.com/node-882/how-to-build-and-install-the-latest-tensorflow-without-cuda-gpu-and-with-optimized-cpu-performance-on-ubuntu/
but the experience was far from smooth, there were constantly dependencies
missing that I need to install and re-launch the compilation. And some
other stuff too that I solved when the compilation crashed.
Have fun and thanks for the hassle. Providing through pip already binary
compiled for non-AVX was clearly too much to add in your continuous
integration worklow
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I had the same problem when running CI pipelines on a Gitlab server. The (emulated) CPU of the runners did not provide AVX instructions.
Installing Tensorflow with Conda instead of using PyPI's wheels fixed the problem. :+1:

I have the same issue with Tensorflow 2.1.0. What to do?

I managed to fix my problem by building from source using bazel. It created a whl file. Then I did pip install whl file path

Yes, if your CPU does not support AVX (the likely cause for Illegal instruction (core dumped) error) then you need to compile from source. This causes the code to be generated without AVX instructions and then you can use it.
Furthermore, this guarantees that the pip is built with the highest optimization level available to your platform, so you might actually see some speedup compared to using a pip built on a different platform. Focus on might.

To install tensorflow with conda run this command :
conda install -c conda-forge tensorflow
it works for me.


Revert "Support Nodejs@12+"

Reverts cabinjs/cabin#139

I'm reverting this because I want to support Node v6.4 out of the box without having XO lint errors.  Maybe once 14 becomes the go-to I'll revert this back


fix: work on node + browser

Currently the only working version of this lib is @importantimport/material-color-utilities

[x] passes all test cases
[x] TypeScript builds successfully
[x] does not break existing behavior

Fixes #35
This PR allows the NPM package to work on all modern browsers and on Node, where currently it does not work anywhere.
To maintain the correct behavior of the JS code being able to run in JS environments, ensure that all import statements point to a *.js file.
Recommended version bump: Minor
Reason: adds new functionality;

compatibility with Node.js (LTS, 16+)
compatibility with Gecko browser (FireFox 60+)
compatibility with Chromium browser (Chrome 61+)
compatibility with WebKit browser (Safari 11+)

The issue fixed by this PR was first created in this commit, meaning today marks 440 (four hundred forty) days of the TypeScript library being defunct on all JavaScript runtime environments.
See: #35, #68

@material-admin,  without this PR, the TypeScript library does not work
@kluever @guidezpl

It seems that Google apparently doesn't care much about the availability of this library...
or they ship TypeScript directly internally.

@kwaa It's quite common of Google to do this. Create something good (the Material You design system), then take a big ol' dump on it (this 467-day old issue rendering the library useless).
Such a shame, if they fixed these problems with their softwares they would probably push MS and Apple into obscurity.

LGTM

pulled updates to the fork & fixed newly introduced fatal syntax errors. @rodydavis , please review these changes if you have any concerns.
As this repo is a mirror, here is a bash command which will automatically apply the changes this PR makes;
echo "const f=require('fs');const p=require('path');const x=(d)=>{for(const t of f.readdirSync(d)){if(t.endsWith('.ts'))f.writeFileSync(p.join(d,t),f.readFileSync(p.join(d,t),'utf8').replace(/(im|ex)port(.+from.+?'.+)(?<!(\.js|jasmine))';/g,'$1port$2.js\';'),'utf8');else if(f.statSync(p.join(d,t)).isDirectory())x(p.join(d,t))}};x(process.cwd());" | node

If it turns out that the Material Foundation dev team for whatever reason won't include the .js extension that is required for ESM code to execute in a JavaScript runtime environment, then it would be a good idea to put in place some kind of enforcement.
Be it a github workflow
name: Fix fatal coding practice

on:
  push:
    branches:
      - "main"

jobs:
  fixfatalerrors:
    runs-on: ubuntu-latest

    steps:
      - name: Checkout
        uses: actions/checkout@v3

      - name: Setup Node
        uses: actions/setup-node@v3
        with:
          node-version: "18.x"
          registry-url: "https://registry.npmjs.org"

      - name: Fix Fatal Issues
        run: echo "const f=require('fs');const p=require('path');const x=(d)=>{for(const t of f.readdirSync(d)){if(t.endsWith('.ts'))f.writeFileSync(p.join(d,t),f.readFileSync(p.join(d,t),'utf8').replace(/(im|ex)port(.+from.+?'.+)(?<!(\.js|jasmine))';/g,'$1port$2.js\';'),'utf8');else if(f.statSync(p.join(d,t)).isDirectory())x(p.join(d,t))}};x(process.cwd());" | node

Or a pre-commit hook
#!/usr/bin/env sh

git stash

echo "const f=require('fs');const p=require('path');const x=(d)=>{for(const t of f.readdirSync(d)){if(t.endsWith('.ts'))f.writeFileSync(p.join(d,t),f.readFileSync(p.join(d,t),'utf8').replace(/(im|ex)port(.+from.+?'.+)(?<!(\.js|jasmine))';/g,'$1port$2.js\';'),'utf8');else if(f.statSync(p.join(d,t)).isDirectory())x(p.join(d,t))}};x(process.cwd());" | node

git add .

git stash pop

echo "\x1b[35mFIXED FATAL ISSUES IN THE CODEBASE: SEE STAGED CHANGES"

Or anything else. The key thing here is for the last 476 days (or longer) the typescript shipped from this repo (potentially others) has been categorically unusable and defunct, and that desperately needs to change.
Material design is, in my opinion, the best design system by a long shot. I, and many others, would very much like it if the tools made available to us did not cause our applications to crash immediately upon startup, or worse, at any point during runtime.
I hope I've made it clear how frustrating it has been to not be able to use something I believe to be such high quality due to such a basic syntactic error.

It would surprise me very much if this repo is the only one effected by this issue, particularly as the same developers working on the TypeScript here are almost certainly working on TypeScript elsewhere. It may be a good idea to check basically every TypeScript file belonging to google that the contributors to this project have been involved with as the same fatal error may be present.
As I said recently, if Google & it's child organisations fixed all these little errors (for context, the JS line, workflow, and pre-commit hook took me a combined total of 30 minutes to create, writing a .js extension in the first place is automated by every text editor unless you go out of your way to disable that) I'm certain that Google would utterly dominate every digital space it entered.

+1 🙏 @kluever

Thank you for your PR. I'm taking a look.

Thank you for your PR!
While we currently don't accept external contributions, we appreciate that you have brought this to our attention.
We have made this change internally as https://github.com/material-foundation/material-color-utilities/commit/41cf95d23acb9c1a9248257dc4571e27c502f795 (also extending the change to newly added files).
We are closing this PR and related issues. Thank you for your support.

Will update the internal script. Looks like it skipped this file

Awesome, I guess #82 will be short-lived. I'll still go ahead and make a list of misses, maybe this was the edge case, maybe the update to the internal script will have new ones. Better safe than sorry.


XHR Failed in getting extensions in remote-ssh

After the last update to:
Version: 1.83.0 (user setup)
Commit: e7e037083ff4455cf320e344325dacb480062c3c
Date: 2023-10-03T16:12:16.321Z
Electron: 25.8.4
ElectronBuildId: 24154031
Chromium: 114.0.5735.289
Node.js: 18.15.0
V8: <IP_ADDRESS>-electron.0
OS: Windows_NT x64 10.0.22621

I am no longer able to access extensions (CTRL+SHIFT+X) when connected to a remote linux server with ssh.
I get the error:
Error while fetching extensions. XHR Failed

It used to work till two days ago, right before the update. After update, that broke jupyter/python, I was able to reinstall python-related extensions. Now I get this error.
As a minor notice, VSC updates are becoming frightening. Every update breaks, for example, my python settings, especially with remote servers. Every time I need to uninstall and reinstall plenty of extensions. Now also this. Many users cannot afford spending days in fixing incomprehensible error messages and weird behaviours every other month.

I am sorry but, since I am using VSC for meeting some deadlines I have, I reinstalled everything for solving the problem.

Ok. I am closing this as you are not able to repro it. If you see the issue again, please share the requested information. Thanks.


Allow for both ES_EXPORT_YAML and ES_LOCAL_CHART

Also no longer warn about missing --version when using ES_LOCAL_CHART as that doesn't make sense.  (Actually the opposite.  Now warn if both are specified.)

Thanks!


Update OWNERS add yussufsh

What type of PR is this?

What this PR does / why we need it:
Which issue(s) this PR fixes:

Fixes #
Special notes for your reviewer:
Release note:
none

/cherrypick release-4.12

/cc @mkumatag


fix(gulp): replacing gulp-cssmin which has been deprecated and un-maintained with gulp-csso

Fixes #1251 - see the issue for motivation and other details

LGTM

Some interesting discussion regarding this stuff:
https://github.com/gulpjs/plugins/issues/210
https://github.com/plus3network/gulp-less/pull/221

the current flow by the gulp team is to use: https://github.com/postcss/gulp-postcss with a postcssnano plugin, or https://github.com/scniro/gulp-clean-css

LGTM

LGTM.


chore(effects): Add 'show' statements in effects.dart

Description
Adding explicit show statements to the imports in file effects.dart.
This is what's recommended in https://dart.dev/guides/libraries/create-library-packages, so this PR is just a starting point for a discussion on whether we'd want to go this route or not.
The main benefit of this approach is that it becomes much more explicit what is the API provided by each library file, and harder to accidentally expose something that was meant to be private.
Checklist

[x] I read the Contributor Guide and followed the process outlined there for submitting PRs.
[x] My PR includes unit or integration tests for all changed/updated/fixed behaviors and are passing (See Contributor Guide).
[x] My PR does not decrease the code coverage, or I have a very special case and explained on the PR description why this PR decreases the coverage.
[x] I updated/added relevant documentation (doc comments with ///) and updated/added examples in doc/examples.
[x] I have formatted my code with flutter format and the flutter analyze does not report any problems.
[x] I read and followed the Flame Style Guide.
[x] I have added a description of the change under [next] in CHANGELOG.md.
[x] I removed the Draft status, by clicking on the Ready for review button in this PR.
[x] I am willing to follow-up on review comments in a timely manner.

Breaking Change

[x] No, this is not a breaking change.

I looked at path and fluro which they refer to in the flutter documentation about packages, and none of them use the explicit show keyword. I think we can skip this for now, and take it up if it becomes a problem in the future.
https://github.com/dart-lang/path/blob/master/lib/path.dart
https://github.com/lukepighetti/fluro/blob/main/lib/fluro.dart

The others agreed, so I'll close this for now.


Spanish documentation

Recently we have been exchanging ideas with a Spanish developer (@Gonzalo2310) about translating Element docs into Spanish. As Element 2.0 is finally released, we are now ready for Spanish docs.
Since no one in our team speaks Spanish, we'll need the community's help. As of today, if you are interested in the idea and confident of your Spanish, you can contribute to the newly created es-doc branch: https://github.com/ElemeFE/element/tree/es-doc/examples .
The workflow is:

Check the todo list below
Claim one or more files by leaving a comment, then I'll move the file(s) to the working-in-progress category
Send a PR to the es-doc branch, and I'll move the file(s) to the finished category after the PR is merged

Todo
Component Documentations

icon
input-number
input
installation
layout
loading
menu
message-box
message
notification
pagination
popover
progress
quickstart
radio
rate
select
slider
steps
switch
table
tabs
tag
time-picker
tooltip
transfer
transition
tree
typography
upload

Website Pages

component
title
page

Working in Progress

cascader
checkbox
collapse
color-picker
container
custom-theme
date-picker
datetime-picker
dialog
dropdown
form
i18n

Finished

alert
badge
breadcrumb
button
card
carousel
color

Discussions should be focused on Spanish docs. Off-topic comments will be deleted.

I'm ready to take the first 5 [alert, badge, breadcrumb, and button]

Then I'll proceed to the next 3. [card, carousel and cascader]

I´ll take the next 3 (checkbox, collapse and color-picker)

I'll take the next 3 (color, container, custom-theme)

@SantiagoGdaR @Gonzalo2310 @fedegar33 @coderdiaz @carmencitaqiu Thanks.

next 3 (dropdown, form, i18n)

@Gonzalo2310 Moved to WIP.

next 3 (upload, table, loading)

next 3 (icon input-number input)

Upload, Table, Loading, Icon, InputNumber and Input are moved to WIP.

cascader, dropdown, i18n, form is finished

@Gonzalo2310 Don't worry, I'll move them when the PR is merged.

Hi, I would like to help with the translate, I'll take the Switch page for begin and help you guys.

@ProgramerGuy Switch is now moved to Finished.

Hello there, I'll take installation, layout and menu.

@sigfriedCub1990 Installation, Layout and Menu are moved to WIP.

Perfect, I'll take messagebox, message and notification to continue :D

@ProgramerGuy Updated.

I can help, whats left?

@kikoseijo At the top of this issue is a list.
Beware of what they have been recently selected and have not yet moved from the list.
Thank you

Pagination, popover and progress are my next choice :).

@sigfriedCub1990 Pagination, Popover and Progress are moved to WIP.
We're half way there. You guys are amazing!

I'll take quickstart, ratio and rate

@sigfriedCub1990 Quickstart, Radio and Rate are moved to WIP.

next 3 (select, slider and steps)

next 3 website pages (component, title, page)

message-box is done

form and table :D

@yodebian table is in progress

Updated.

I'll take tag and typography

@josewhitetower Tag and Typography are moved to WIP.

I'll take the next 3 (tabs, time-picker, tooltip)

Hi, i'm taking transfer, transition and tree

How are you guys translating things like input, placeholder, etc.?

I don't think so, the element's names stay as they are. I try to make the explanations as clear as possible

@thechosenjuan I think that things like input, placeholder, etc. are no longer words in English but computer terms. I don't know if it would be logical to translate them

Got it! I will leave as they are then. Thank you @Gonzalo2310

Updated.
Now the todo list is cleared!

Count  me in! If you want some Q&A etc. I'm actually Mexican despite appearances!
From a quick glance most components done. @Leopoldthecoder let me know where I can chip in.

@adavie1 Thanks. If you are interested, you can help translate our FAQ and contributing guide to Spanish.

@Leopoldthecoder will do. Thanks for letting me contribute.

Hi @Leopoldthecoder !
I would like to help translating to Spanish these 3 files: typography, tag and notification
Spanish is my native language :)

@josewhitetower Are you still interested in translating Tag and Typography? It's OK if you're busy with something else, then we could ask @stellamiranda for her help.
Also, @ProgramerGuy how about Notification?
No pressure guys, just a bit curious.

Bad timing sorry, give @stellamiranda and @ProgramerGuy  green light, I might check the translations later..

@stellamiranda Hi, could you help us with Tag and Typography?

@Leopoldthecoder Yes, work in progress :)

@Leopoldthecoder Can I help you with anything else?

@Leopoldthecoder:  what @Gonzalo2310  said! :-) Anything else you need?

@Gonzalo2310 @adavie1 I think DatePicker, DatetimePicker, Dialog and Notification are open again since our volunteers are either too busy or non-native speaker. Perhaps each of you can take two of them?
Plus, we'll need an overall review after all individual files are finished.

@Leopoldthecoder I have finished the translation of DatePicker,DatetimePicker,and I have commited a pull request No.#8206.Since the pull request are still open,is there any questions about this pr?

@carmencitaqiu I left some comments https://github.com/ElemeFE/element/pull/8206#pullrequestreview-77793561

@Leopoldthecoder I will modify the problems as soon as possible

@ProgramerGuy @Leopoldthecoder I'll do notification. ok?

notification done

@Gonzalo2310 @adavie1 DatePicker, DatetimePicker and Dialog are done. Could you review them since they're translated by a non-native speaker?

@Leopoldthecoder Yes!!

I am very grateful for the work of all those who have collaborated.
I didn't think so many people would add up.
I thought it would be a tedious job for months but it's been a little light and fast.
Thank you all for your efforts and especially @Leopoldthecoder for your constant dedication to this project.

@Leopoldthecoder of course! @Gonzalo2310 Cual harás?

@adavie1 Sorry. DatePicker, DatetimePicker and Dialog Fixed and uploaded already

Great.  :-D

@Gonzalo2310 It seems we can start the overall review now. Since the purpose of this review is to unify the docs' logic and wording, I think it should involve only one or two people. Let me know if you need anyone's help, or you can directly ping them here.

@Leopoldthecoder I start from 25/11 and publish progress. For now I can move forward without involving anyone else. If I see any delays, I'll let you know. ok?

@Gonzalo2310 Sounds good to me.

Sounds great, how could I participate in the translation?

Status for tag and typography? @Leopoldthecoder

@coderdiaz I'm not sure if @stellamiranda has started.
@stellamiranda Hi, could you update your progress here?

Only missing tag and typography

I'm afraid we'll have to find another person for Tag and Typography. Any volunteer?

@Leopoldthecoder I'll bring it up in a few minutes. I'll do it right now. It's already checked.

@Leopoldthecoder I don't know if I've done it right... as usual. :(

@Leopoldthecoder we will create CHANGELOG.es-ES.md?

@Gonzalo2310 It's good to have a Spanish changelog, but my concern is that it may not get updated in time. When a new version is released, we'll wait for the community to update the changelog, so there'll be a few days when the changelog doesn't reflect the latest changes.
This problem also affects component docs. Since we rely on the community to update the docs, there will always be some delay.
Do you have any idea to solve this?

I think that if at first the news is in English one day or two will not affect the community but I don't know if that's extra work for you.

I'm using CodeRelease.io to control repository changes.
What do you need to be calm (mail, to use some software?). I take care of any future changes

@Gonzalo2310 Sounds good to me. Then please translate the changelog. We can release the docs when the changelog is done.
Thank you.

@Leopoldthecoder  You'll have it today.

It cost me more than I thought, but that's it. Let's publish!!!

@Gonzalo2310 Thanks. It will be published next week.

Hi everyone! Thank you all for helping us with the Spanish documentation. I'm glad to say that it will be released tomorrow (actually it's now running perfectly on my computer).
Gracias, amigos!


Updated find_python_script to support MinGW64

Under a MinGW64 (MSys2) environment, the scripts are wrapped in .exe files and placed in the same directory as the Python runtime. The support for this scenario was added. The Python directory path was also refactored into a separate variable.

This PR is outdated, but the original issue is still open. We'll keep tracking of MinGW64 support in #117, but I'm not keeping all the pull requests around till we have an idea of if/when/how we're going to approach it.


Combine multiple authentication options

I have an application (web api) that queries an ADX database.
This web api runs in Azure, and I use the managed identity of the Web App service where the api is hosted to get access to the ADX database.
This is configured like this:
services.AddSingleton<ICslQueryProvider>(sp =>
{
    var settings = sp.GetService<IOptions<KustoSettings>>().Value;

    var kustoConnectionStringBuilder =
    new KustoConnectionStringBuilder(settings.AdxClusterUrl, settings.DatabaseName)
                                .WithAadSystemManagedIdentity();

    return KustoClientFactory.CreateCslQueryProvider(kustoConnectionStringBuilder);
});

However, when I run this api locally on my machine for debugging, this obviously doesn't work.  Therefore, I thought about doing this:
services.AddSingleton<ICslQueryProvider>(sp =>
{
    var settings = sp.GetService<IOptions<KustoSettings>>().Value;

    var kustoConnectionStringBuilder =
    new KustoConnectionStringBuilder(settings.AdxClusterUrl, settings.DatabaseName)
                                .WithAadSystemManagedIdentity()
                               .WithAadAzCliAuthentication();

    return KustoClientFactory.CreateCslQueryProvider(kustoConnectionStringBuilder);
});

My idea behind this was that one of the 2 authentication methods could be used.  When running on Azure, the System Managed Identity auth could be used, when running locally, I could use my Az CLI token.
However, this doesn't work.  When I run this locally, I get this error:

'ManagedIdentityCredential authentication unavailable. No Managed Identity endpoint found.'

When I run this in Azure, it doesn't work either as it then complains that there is no Azure CLI credential found.
Is there a way to define that one of the 2 authentication methods should be used ?

You can use a combination of KustoConnectionStringBuilder.WithAadAzureTokenCredentialsAuthentication(Azure.Core.TokenCredential tokenCredential) and Azure.Identity.DefaultAzureTokenCredentials to achive that.
https://learn.microsoft.com/en-us/dotnet/api/azure.identity.defaultazurecredential?view=azure-dotnet

For completeness sake, I've done it like this:
 var kustoConnectionStringBuilder =
                            new KustoConnectionStringBuilder(settings.AdxClusterUrl, settings.DatabaseName)
                               .WithAadAzureTokenCredentialsAuthentication(new DefaultAzureCredential(new DefaultAzureCredentialOptions()
                                {
                                    ExcludeEnvironmentCredential = true,
                                    ExcludeInteractiveBrowserCredential = true,
                                    ExcludeSharedTokenCacheCredential = true,
                                    ExcludeAzureCliCredential = false,
                                    ExcludeManagedIdentityCredential = false,
                                    ExcludeVisualStudioCredential = true
                                }));


Fix deunified build ignoring workspace package

While the deunified build created a number of parallel jobs, the package field wasn't properly passed to certain jobs as expected, leading to redundant checks.

this is still a wip, need to fix workspace package name resolution since they don't match the directory names.

fixed in https://github.com/FuelLabs/fuels-rs/pull/657


Allow the main index route to be ssg rendered with getStaticProps

Previously, the / route having associated data would cause the
build to fail as it would attempt to reference an /.html file
instead of /index.html
This also fixes a stability issue with the snapshot test for
_redirects, which are not necessarily generated in a stable order.

Hi @etrepum,
This is fantastic! Thank you for not only reporting the bug, but also diving into the code and fixing it. I really appreciate it :raised_hands:
I've pulled the branch and am merging it locally right now (there is a minor conflict with the test snapshot). Will publish new version of next-on-netlify asap!
Cheers,
Finn

I just merged and published it (next-on-netlify v2.1.0). :rocket:
I removed the part about the stability issue with the snapshot test because the order of the redirects is important. For example, more specific routes must come before less specific ones: /pages/abc > /pages/[id] > /pages/[...id]
But I hear your point about the instability of it and I will look into it — perhaps there's a solution that avoids the instability in the first place!
Thank you again for your contribution, @etrepum :slightly_smiling_face:
- Finn
PS: Let me know if you build something awesome with next-on-netlify — I would love to feature some projects in the README.

We're working on moving our https://donate.missionbit.org/ donation portal from a standalone Flask site deployed on Azure into our new next.js site for https://www.missionbit.org/ deployed on Netlify.
The source for the project is here: https://github.com/missionbit/missionbit.org
Technically it's already using my branch of next-on-netlify, but it's still in a state where the output is indistinguishable from next export because there aren't any API routes yet.

That's an amazing site and incredible work you're doing! Super happy to have it featured in the README now: https://github.com/FinnWoelm/next-on-netlify#showcase :blush:


Missing container image tag for v1.18

The GCR repositories for Cloud SQL Proxy do not have the image tag for v1.18 but has v1.18.0 instead, which is inconsistent with the tag format used in previous versions.

Hi @kyloon,
The container images are always tagged with a version matching the release tag on GitHub. We have switched to tagging our releases following a more strict semantic versioning format because it is required for Go modules to work properly and makes it easier for us to release more frequently in the future. We've backdated all of the releases to correctly follow this format, but going forward we won't continue to tag images without a PATCH version.


Update / enable Reports and Search for new project files

The Reports tool is critical for Shawn's end of year summary and resource planning. The way it's laid out now is exactly how Shawn wants it to be, so adding the new project data to be presented in that format is the goal. If that has to be a separate reporting system, it would be acceptable to have a "legacy reports" button for previous years project info.
Similarly, the ability to search for a name or project across applications and projects has become an essential everyday tool for using the tool. It needs to be able to search and provide pointers to new project data, as well as old. This doesn't have to be seamless as long as a link is provided for easy navigation to the target info.
We need to have this capability before we can release the new tool (AVT2.0) into production.

This looks good to me, Andy. I'm going to have Shawn take a look to make sure he's got what he needs. No work on this needed unless we hear requests back from Shawn. After that we'll close this.

Feedback from Shawn:

CSV files are awesome!

Change "Upcoming Projects" tab title to "Current Projects" and include both "upcoming" and "in progress" status projects

In "Current Projects" change "Volunteers" heading to "Volunteers Needed"

In "Current Projects" change "Cost" heading to "Estimated Cost"

Change "Projects" tab title to "Completed Projects"

Partners list - is there a way to click a link to show the projects the Partner worked on?

for both "Current Projects" and "Completed Projects"

sort list by Start Date
swap headings "Name" and "Status" to match column content

Hi Andy - these changes are important to Shawn. It would be great if you could work on this next and we can put the Reports module to bed. Thank you! ==> Dan

These changes were implemented in the recent commits.

Hi Andy - thanks for the changes you made. This issue kinda got long and I overloaded it, so I'm going to close it and open up a couple new issues with some specific requests for edits / corrections that I noticed today when I looked at it.


Environment variable

In the previous version of crawlab there was the option to create environment variables (pictured below). In the new version I did not find this option. Do you intend to add it?

It's planned and will be added. Thanks for the feedback


is it possible to use it with a PageControl?

Hi
Is it possible to use SwiftySound with a pageControl? I mean for example launching a sound when someone swipe to a new page, without having to press a play button? thx for your feedback on that

Of course it's possible. Not really related to the library itself, but take a look at valueChanged event that is triggered each time when a page is changed


There are scrolling bugs

Description
Excess Spaces and become blank in 3.0.
Screenshots

Drag and scroll wheel with mouse ，Excess Spaces .

in 2.2

in 3.0

Edition
Which edition of ReoGrid do you using?

Windows Form

Environment

OS: Windows 7
Language of OS: Chinese

表头固定后多余的横线，或者说多余的空白，这个问题已经解决了吗？


Watch networks config file for changes

Added watcher (based on #9370) to watch for changes in the mesh networks configuration file.
Reload the configuration from the file and clear the discovery cache when a change detected.

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434d1423410a1cff200b88378112c20941f53528
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434d1423410a1cff200b88378112c20941f53528
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[APPROVALNOTIFIER] This PR is NOT APPROVED
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/test istio-integ-k8s-tests

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2d02bc06a15dd0200fa7ac3d9f24b69076a0432e
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/test istio-pilot-e2e-envoyv2-v1alpha3-mcp

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prow/istio-pilot-e2e-envoyv2-v1alpha3.sh
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prow/istio-pilot-multicluster-e2e.sh
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prow/istio-pilot-e2e-envoyv2-v1alpha3-mcp.sh
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prow/istio-pilot-e2e-envoyv2-v1alpha3.sh
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Fix docker daemon start with old running container which use thirdparty volume plugin

Signed-off-by: Lei Jitang leijitang@huawei
Fixes #15720.
The docker daemon dies(kill -9 $(cat /var/run/docker.pid) could leave some containers with state
"Running": true
For example, on my system, I user kill -9 to kill the docker daemon, and the state of the running container has a state  "Running": true,
root@ubuntu:/var/lib/docker/containers/d95e7fc1f3b4046707cbd6dd9c90704302d850196eb9bfbc59a9f388c91825d9# cat config.json | jq .
{
  "State": {
    "Running": true,
    "Paused": false,

On the next daemon start, the daemon will detect these containers and stop
them(https://github.com/docker/docker/blob/master/daemon/daemon.go#L205)
But if these old running containers use a thirdparty volume plugin and the thirdparty
plugin is not running, container.prepareMountPoints() (https://github.com/docker/docker/blob/master/daemon/daemon.go#L201)
will failed and exit the register, and the old running container will still
has a Running : true. This will cause some issues:
these containers sill be shown on docker ps
but docker stop docker kill docker rm these containers
will causes a daemon exception.

LGTM

LGTM


Explain defaultAutoCommit=true property more clearly in docs

Describe the improvement
Need to make it clear that defaultAutoCommit=true is the default and recommended config and commitOnReturn="true" is recommended for most of the cases where defaultAutoCommit="false". This can be explained more clearly using example use cases as well.
[1] https://is.docs.wso2.com/en/5.10.0/setup/changing-to-mssql/
Refer to the descriptions below for further clarification:
defaultAutoCommit - if this is set to true the, the tomcat will make sure that each and every sql statement will be committed soon as it is executed. However in the code level we also tries to execute set os SQL as a transaction and tries to commit them at the end of the block, In such cases since the default auto commit is set to true, and if we try to commit the same from the code block as well, there is a high possibility that you will get the exception as below since the such queries would be already committed. Hence the recommendation is to set it to false.
org.postgresql.util.PSQLException: Cannot commit when autoCommit is enabled
commitOnReturn - This parameter will make sure that when the particular connection return back to the pool, it will be added to the pool followed by a commit, this is required since we do not commit all the queries thats executed from our code base such as SELECT queries..
In general the SELECT do not need to be committed, However with specific to the postgreSQL what we have seen is that every SELECT has to be committed before it returns to the pool, otherwise postgreSQL will holding Access Share level lock to the connection. Hence the recommendation is to set it to true.
rollbackOnReturn - This parameter will make sure that when the particular connection return back to the pool , it will be added to the pool followed by a rollback, This is not required. However if this is set to true the parameter commitOnReturn will be not effective. Hence the recommendation is to set it to false.

Closing this issue. We will handle this with [1].
[1] https://github.com/wso2/product-is/issues/14521


Bump golang to v1.14.1

Bump golang to the latest version, v1.14.1 as in go v1.14 it has better vendor support.

@manishtomar @dmcgowan @thaJeztah can you please close this PR in favor of https://github.com/docker/distribution/pull/3222?

I can close this one, thanks @olegburov!

Thanks, @chenrui333.

no worries.


Fixing failing tests

Signed-off-by: Karanjot Singh<EMAIL_ADDRESS>Description

Test

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Additional Information
Tradeoff

Potential improvement

Closing, this is now superseded by #41. I've fixed the broken e2e tests in a similar way, but without changing their structure too much (I didn't introduce the jq dependency for example).

Thanks @flavio! I think the issue was with the parsing output therefore i used jq to parse json.


Feature/suggest ens domain

Fixes #954.
Changes proposed in this pull request:

Setup graphQL for ENS
Show user ENS names as suggestions

There is my draft PR
How do I need to handle the loading status of fetching names?
What message do I need to show the user if he doesn't have any ENS names, and how it should look?

I would require wallet connection at the beginning. Then you can look for ENS domains and display them to chose from, plus a "Register Domain" button that just links to the ENS website and later we implement registration through snapshot interface. Text input is not needed at all I think.

@bonustrack What would you say?

Added some improvements

@sarmatdev resolve conflicts plz

Committed my changes. This is ready to be merged I'd say.

Cool, here is some suggestion

Dont load suggestion if user is not logged
Use a small circle loading and not this fat loading placeholder

Don't show "Looks like you dont have ENS domains", now i can see it even if request to query ENS domain is not resolved yet, I think we can just remove it

Maybe a better way to imagine this would be like this:

If user is not logged, just show a "Connect wallet" button like this:

If user is logged but don't have any domain, show a page to register a space like this:

The next button would redirect to ENS website

If user is logged and have domain show the domains as buttons and before the form like this:

@sarmatdev I'll take over from here, if that's ok for you. :)

@sarmatdev I'll take over from here, if that's ok for you. :)

Yes, do it if you are want

Closing in favor of: ...


Improved REQUIREMENTS.txt format and added missing dependencies

Hello @garciparedes,
Thank you for pointing out the requirements issues. I quickly updated myself the requirements since there were other packages not included in this PR.