Erroneous specifiers in declaration files.

TypeScript Version:  3.0.1

Search Terms: import, eac
Code
// A *self-contained* demonstration of the problem follows...
// Test this by running `tsc` on the command-line, rather than through another build tool such as Gulp, Webpack, etc.
import styled from "react-emotion"

const Form = styled('div')({ color: "red" })

export default Form

Expected behavior:
When run with --declaration, the output I expected was:
import * as React from "react";
export declare const Form: import("create-emotion-styled/types/react").StyledOtherComponent<{}, React.DetailedHTMLProps<React.HTMLAttributes<HTMLDivElement>, HTMLDivElement>, any>;
export default Form;

Actual behavior:
When run with --declaration, the generated .d.ts file contains:
/// <reference path="../../node_modules/create-emotion/types/index.d.ts" />
/// <reference types="react" />
export declare const Form: import("create-emotion-styled/types/react").StyledOtherComponent<{}, import("eac").DetailedHTMLProps<import("eac").HTMLAttributes<HTMLDivElement>, HTMLDivElement>, any>;
export default Form;

What's really strange is import("eac"). Where in the world is this coming from? 🤔
Playground Link:
I can't add a playground link because it depends on import.
Related Issues: https://github.com/emotion-js/emotion/issues/788

If I had to guess: "eac" is the middle 3 characters of "react" and we're trimming the leading and trailing characters expecting them to be quotations (ambient modules are supposed to always be quoted), but they're not. 😄

awesome!


rules: strict checks on hidden files and repository files that are modified

Signed-off-by: Lorenzo Fontana<EMAIL_ADDRESS>What type of PR is this?
/kind rule-update
Any specific area of the project related to this PR?
/area rules
What this PR does / why we need it:
In "Create Hidden Files or Directories", when a directory or a file is created the rule is triggered but it should also trigger when a file or directory is moved to become and hidden one, this PR uses the modify macro to do that additional check.
In "Update Package Repository" when a directory or a file is updated in the sensitive packages folder the rule is triggered, however it was not triggered when a file is moved into those directories. This PR fixes that using the modify macro.
Which issue(s) this PR fixes:
NONE
Special notes for your reviewer:
Does this PR introduce a user-facing change?:

rules: "Create Hidden Files or Directories" and "Update Package Repository" now trigger also if the files are moved and not just if modified or created.

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/lgtm

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Configure BTP Destinations in SAP Build Process Automation

Tutorials: https://developers.sap.com/tutorials/spa-create-destination.html
The destination should be http and not https

hello,
I believe that you refer to step 1 point 6.
do you mean the change needs to be done inthe type or url?


sequence cumsum and predict method

Hello,
Take an example with titanic dataset and logistic regression :
titanic_copy = titanic.copy()
titanic_copy.eval("col_1", "1")
titanic_copy.cumsum(column = "col_1", name = "col_id" )
titanic_copy.drop(columns = ["col_1"])

from verticapy.learn.linear_model import LogisticRegression
drop(schema + ".lr_titanic", cursor = cur, method = "model")
model = LogisticRegression(name = schema + ".lr_titanic")
model.fit(titanic_copy, ["fare", "age"], "survived")
model.predict(titanic_copy,
              X = ["fare", "age"],
              name = "prediction_proba",
             inplace = True)

show the current relation of titanic_copy :

All seems to be ok.
use the command :
titanic_copy.drop("prediction_proba")
show the current relation of titanic_copy :

We have the line :
PREDICT_LOGISTIC_REG("fare", "age" USING PARAMETERS model_name = 'DTDSWSP310.lr_titanic', type = 'probability', match_by_pos = 'true') AS "prediction_proba"
use an other time the command :
model.predict(titanic_copy,
              X = ["fare", "age"],
              name = "prediction_proba",
             inplace = True)

And current relation :

We can't make a loop with predict method if we use cumsum before.
Regards,,
Alexandre

Thanks for reporting this issue. It is corrected and it will be released in the next PR.


build: Update build.sh to run fully manual build

Also, add ubuntu-16.10-x64 to the list of architectures to build for.

Hi @nadiasvertex, I'm your friendly neighborhood Microsoft Pull Request Bot (You can call me MSBOT). Thanks for your contribution!

In order for us to evaluate and accept your PR, we ask that you sign a contribution license agreement. It's all electronic and will take just minutes. I promise there's no faxing. https://cla.microsoft.com.

TTYL, MSBOT;

That sounds great. I will make th or changes.
On Mon, Dec 5, 2016, 2:05 PM Sergei Vorobev<EMAIL_ADDRESS>wrote:

@vors commented on this pull request.
In build.sh https://github.com/PowerShell/PowerShell/pull/2832:

if hash powershell 2>/dev/null; then
echo 'Continuing with powershell -noprofile -c Start-PSBuild'
powershell -noprofile -c "Import-Module ./build.psm1; Start-PSBuild"
else

echo 'No powershell, see docs/building/linux.md or macos.md to build PowerShell!'

echo 'Continuing with full manual build'
./build-from-scratch.sh

You right, it's silly.
I was thinking we are using this script for the CI build and didn't want
to complicate the CI troubleshooting.
But turns out that script is not used and purely for the convenience here.
Please, ignore my comment about the separating logic into a different
file: since we call it anyway, there is no need to do it. Sorry for going
back and forth on it.
Couple more things:

build.sh will never be as fully-featured as build.psm1 file. I.e.
build.psm1 can find dotnet, if it's not in the path, can run dotnet
build or dotnet publish, etc. I think it's better to avoid duplicating
all such logic and use build.sh precisely for the bootstrapping on the
new platforms. If we agree about this purpose, then my suggestion would be
to replace

pushd src/powershell-unix
dotnet build --configuration Linux
popd
by
dotnet publish --configuration Linux ./src/powershell-unix/ --output bin
And add an echo message about the build location, something like You can
run powershell from bin/.

publish will create a self-contained build of powershell.
Putting it in bin/ will allow to avoid complicated logic about
figuring out where the build was made
this version could be used for the build with .psm1 and would not
interfere with the standard location (avoid "file in use" problem).

build.sh doesn't perform analog of Restore-PSModule (adding PS
modules from myget and psgallery). It's worth to have a message with this
information at the end of the build to avoid confusion.

—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/PowerShell/PowerShell/pull/2832, or mute the thread
https://github.com/notifications/unsubscribe-auth/AB8JvCcph1OdwgySUuL4jaQkQbE6FVSyks5rFGB3gaJpZM4LCEBA
.

I like this change a lot 😄

@nadiasvertex your build issue with #2735 complaining about Microsoft.CodeAnalysis.dll is due to src/TypeCatalogParser/Main.cs the call x.Name.ToLower() making the filenames in lowercase and thus later on not matching the case-sensitive paths.  Not sure why this was there explicitly, but removing that call will get you past this.

@SteveL-MSFT x.Name.ToLower() is there explicitly because of .NET CLI's behavior, per #2162. We verified this was intended change on their end in https://github.com/dotnet/cli/issues/4141.

@andschwa well, this is awkward since dotnet restore on my Ubuntu 16.10 system has packages with Pascal casing...

@SteveL-MSFT file a bug with .NET CLI, see if they purposefully changed it back 😄

@andschwa I think the difference is a breaking change they made with preview3 vs preview2.  On my Windows box and Ubuntu16.10, I have preview2 (as far as I can tell, preview3 isn't available on 16.10).  This PR may have to wait until we have preview3.

@SteveL-MSFT @nadiasvertex:
I installed the exact build that Start-PSBootstrap is currently pinned to on an Ubuntu 16.10 box, did a dotnet restore, and confirmed that these packages are not restored lower-cased:
docker run -it ubuntu:16.10 bash
apt-get update
apt-get install libunwind8 libicu57 libcurl3 git curl
curl -sO https://raw.githubusercontent.com/dotnet/cli/v1.0.0-preview2-1-3177/scripts/obtain/dotnet-install.sh
bash dotnet-install.sh -c preview -v 1.0.0-preview2-1-00317
git clone https://github.com/PowerShell/PowerShell.git
cd PowerShell/
~/.dotnet/dotnet --version
~/.dotnet/dotnet restore
ls ~/.nuget/packages/

And got:
1.0.0-preview2-1-003177.dotnetSentinel
Libuv
Microsoft.Build
Microsoft.Build.Framework
Microsoft.Build.Utilities.Core
Microsoft.CSharp
Microsoft.CodeAnalysis.Analyzers
Microsoft.CodeAnalysis.CSharp
Microsoft.CodeAnalysis.Common
Microsoft.CodeAnalysis.VisualBasic
Microsoft.DiaSymReader
Microsoft.DiaSymReader.Native
Microsoft.DotNet.Cli.Utils
...

So I dug a bit further, and in 32a8601f926b164bbdf74ad1b6c4c8ef927fe1a8 the ToLower() was removed because:

.NET Core 1.1 ships with an older dotnet/cli than has currently been used, so we revert to use case-sensitive directory names for dependencies.

(This corresponds to @SteveL-MSFT finding the change is in preview3, but not preview2; and I didn't realize we'd reverted the tooling back that far.)


Feature/cli

:tada: This PR is included in version 1.1.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Fix lilyweight

this PR changes calculateLilyWeight to use getWeightRaw instead of getWeight

weight doesnt seem to be the same

  weight doesnt seem to be the same

the 2 photos you posted have the exact same number
or am I blind?

wait i am blind

😹 looking at wrong section

weight doesnt seem to be the same

the 2 photos you posted have the exact same number
or am I blind?

Think he's sarcastic or he thinks the "." in lily discord bots is to separate thousands instead of decimals


feat: add vscode-java-decompiler jars.

Just saw https://github.com/williamboman/mason.nvim/issues/193 and decided to try to make a package for it.
Some notes:
Since the vscode-java-decompiler repository has the required jar files already committed in, I have left the run empty since it's required by the yaml spec.
Tried the workflow on my fork and it seems to pass the tests. Although admittedly, I don't know how to test this out on my local machine.

Tried the workflow on my fork and it seems to pass the tests. Although admittedly, I don't know how to test this out on my local machine.

Yeah I need to make it simpler to test package definitions, I'm leaning towards being able to hot-patch the registry by loading the current buffer (package.yaml) through so one can test it normally through :MasonInstall.
FWIW I do this to test it locally (this assumes https://github.com/mason-org/actions is checked out at ../mason-org-actions):
$ MASON_VERBOSE_LOGS=1 RUNNER_DEBUG=1 GITHUB_ACTION_PATH=doesntmatter PACKAGES="packages/vscode-java-decompiler/package.yaml" TARGET=darwin_arm64 nvim --head
less -c 'luafile ../mason-org-actions/tests/test-runner.lua' -c 1cq


Boot problem

What happened?
Even after preparing the card and writing the AT28C64B several times, the card crashes at the message:
Waiting for RPi FW:000F..._
Sometimes it logs into ProDOS, but most of the time I have to log into the OS and give a command: sudo reboot
Hardware Version
Sixth Prototype (Self-assembled)
Firmware Version
000F
Driver Version
0024 (fix VT100 arrow keys)
Shell Version
000D (added version info)
Where are you seeing this problem?
ProDOS access
What computer is this running on?
Apple //e (enhanced / platinum)

Can you see from the logs on the RPi? Is the apple2driver service crashing? Also, be careful with reflashing the AT28C64B as they have a limited number of write cycles. I have worn out a couple of chips during development.

I had the same problem after I set up the RPI Zero WH with the provided script. I solved the issue by starting the installation from scratch with a stable internet connection.
Checked my installation as follows - on Raspbian:

sudo systemctl --> showed that the apple2driver failed to start
sudo journalctl -u apple2driver --> told me, that the folder home/pi/apple2-IO-RPi was completely missing

make sure while setting up the image, that you name the user "pi"


Try restoring sonar build

Hi @S-Streulicht I simplified and standardized the library builds. Also put PNG config as static and not dynamic. So this is frozen in. I temporyarily removed the runtime sanitizer builds, but I will restore these soon.
As a final step, I will add PNG hash tests to CI on multi-platform.
So this thing is looking good. Your work (which wa sinspirational) is on the books.


Can't install AutoAWQ 0.2 on Windows

I downloaded autoawq-0.2.2+cu118-cp310-cp310-win_amd64.whl in releases but failed to install it.
The error message is as follows。
ERROR: autoawq_kernels-0.0.5+cu118-cp310-cp310-windows_amd64.whl is not a supported wheel on this platform.

Then I tried installing the historical versions and found that version 0.1.8 installs correctly, any >=0.2.0  can not be installed.
But version0.1.8also doesn't work, when I try to run it after installing it, I get the following error
D:\Program\VLM\gptq>C:/Software/Miniconda/envs/gptq/python.exe d:/Program/VLM/gptq/Quant_awq.py
Traceback (most recent call last):
  File "d:\Program\VLM\gptq\Quant_awq.py", line 1, in <module>
    from awq import AutoAWQForCausalLM
  File "C:\Software\Miniconda\envs\gptq\lib\site-packages\awq\__init__.py", line 2, in <module>
    from awq.models.auto import AutoAWQForCausalLM
  File "C:\Software\Miniconda\envs\gptq\lib\site-packages\awq\models\__init__.py", line 1, in <module>
    from .mpt import MptAWQForCausalLM
  File "C:\Software\Miniconda\envs\gptq\lib\site-packages\awq\models\mpt.py", line 1, in <module>
    from .base import BaseAWQForCausalLM
  File "C:\Software\Miniconda\envs\gptq\lib\site-packages\awq\models\base.py", line 12, in <module>
    from awq.quantize.quantizer import AwqQuantizer
  File "C:\Software\Miniconda\envs\gptq\lib\site-packages\awq\quantize\quantizer.py", line 11, in <module>
    from awq.modules.linear import WQLinear_GEMM, WQLinear_GEMV
  File "C:\Software\Miniconda\envs\gptq\lib\site-packages\awq\modules\linear.py", line 4, in <module>
    import awq_inference_engine  # with CUDA kernels
ImportError: DLL load failed: The specified module could not be found.

HI @kirayomato, could you try to install the main branch to confirm the issue is still present? Also, are you using WSL2 (a requirement)?
pip install git+https://github.com/casper-hansen/AutoAWQ.git

HI @kirayomato, could you try to install the main branch to confirm the issue is still present? Also, are you using WSL2 (a requirement)?
pip install git+https://github.com/casper-hansen/AutoAWQ.git

Still unable to install. I'm not using wsl2.
D:\Program\VLM\gptq>pip install git+https://github.com/casper-hansen/AutoAWQ.git
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple
Collecting git+https://github.com/casper-hansen/AutoAWQ.git
  Cloning https://github.com/casper-hansen/AutoAWQ.git to c:\users\admin\appdata\local\temp\pip-req-build-7db2ri3w
  Running command git clone --filter=blob:none --quiet https://github.com/casper-hansen/AutoAWQ.git 'C:\Users\admin\AppData\Local\Temp\pip-req-build-7db2ri3w'
  Resolved https://github.com/casper-hansen/AutoAWQ.git to commit 68c727a1a338a1e8d988e8f6094e0d38040e0bb6
  Preparing metadata (setup.py) ... done
ERROR: autoawq_kernels-0.0.6+cu118-cp310-cp310-windows_amd64.whl is not a supported wheel on this platform.

I'm not sure how to solve this issue unfortunately. I do not have a Windows PC at my disposal and it used to work. Open to contributions if you figure out what the issue is.

I'm monitoring this issue as it prevents me from updating AutoAWQ in my project.

Hi @oobabooga, I would love to resolve this issue but I have no means to reproduce it currently. The wheels build on Windows, so my immediate assumption is that it could be an environment/dependency issue

@oobabooga @casper-hansen Triton is now a dependency of AutoAWQ since 0.2.1. There are no Triton builds for windows, thus the dependency can't be resolved. Triton is Linux only

Triton has been removed in 0.2.3 as I realized it was not needed anyways.

@kirayomato it seems this issue relates to not using WSL2 as far as I can see. As noted in the AutoAWQ-kernels repository, WSL2 is a requirement for Windows users.
Please refer to Microsoft's documentation and let me know if you face any further issues on your Windows machine.
https://learn.microsoft.com/en-us/windows/wsl/install

@kirayomato it seems this issue relates to not using WSL2 as far as I can see. As noted in the AutoAWQ-kernels repository, WSL2 is a requirement for Windows users.
Please refer to Microsoft's documentation and let me know if you face any further issues on your Windows machine. https://learn.microsoft.com/en-us/windows/wsl/install
So this repository actually not support Windows? WSL2 is Linux.

It doesn’t support pure Windows as Microsoft has trouble supporting CUDA code. Not much I can do about it


Compile issues as dynamic module with MUSL

I'm trying to get pagespeed to build as a dynamic module for nginx. I'm on Alpine which is a MUSL system.
I've built PSOL from source (with some adjustment to get it to compile).
When attempting to build the nginx module I'm getting a compilation error:

/usr/lib/gcc/x86_64-alpine-linux-musl/5.3.0/../../../../x86_64-alpine-linux-musl/bin/ld: /home/test/nginx/clean/ngx_pagespeed-<IP_ADDRESS>-beta-dynamic//psol/lib/Release/linux/x64/pagespeed_automatic.a(142.deflate.o.o): relocation R_X86_64_PC32 against symbol 'pagespeed_ol_deflateResetKeep' can not be used when making a shared object; recompile with -fPIC
/usr/lib/gcc/x86_64-alpine-linux-musl/5.3.0/../../../../x86_64-alpine-linux-musl/bin/ld: final link failed: Bad value
collect2: error: ld returned 1 exit status
objs/Makefile:1170: recipe for target 'objs/ngx_pagespeed.so failed

The PSOL was compiled with:
make all BUILDTYPE=Release CXXFLAGS=" -I/usr/include/apr-1 -I/home/test/nginx/libpng-1.2.56 -D_GLIBCXX_USE_CXX11_ABI=0 -Duse_system_libs=1 -Duse_system_icu=1" CFLAGS=" -I/usr/include/apr-1 -I/home/test/nginx/libpng-1.2.56 -D_GLIBCXX_USE_CXX11_ABI=0 -Duse_system_libs=1 -Duse_system_icu=1"
GCC -v

Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/libexec/gcc/x86_64-alpine-linux-musl/5.3.0/lto-wrapper
Target: x86_64-alpine-linux-musl
Configured with: /home/buildozer/aports/main/gcc/src/gcc-5.3.0/configure --prefix=/usr --mandir=/usr/share/man --infodir=/usr/share/info --build=x86_64-alpine-linux-musl --host=x86_64-alpine-linux-musl --target=x86_64-alpine-linux-musl --with-pkgversion='Alpine 5.3.0' --enable-checking=release --disable-fixed-point --disable-libstdcxx-pch --disable-multilib --disable-nls --disable-werror --disable-symvers --enable-__cxa_atexit --enable-esp --enable-cloog-backend --enable-languages=c,c++,objc,java,fortran,ada --disable-libssp --disable-libmudflap --disable-libsanitizer --enable-shared --enable-threads --enable-tls --with-system-zlib
Thread model: posix
gcc version 5.3.0 (Alpine 5.3.0)

Any help getting this to build would be appreciated.

Sounds like something like -fPIC may be needed for CXXFLAGS.
On Tue, Mar 29, 2016 at 11:53 AM, Caleb Champlin<EMAIL_ADDRESS>wrote:

I'm trying to get pagespeed to build as a dynamic module for nginx. I'm on
Alpine which is a MUSL system.
I've built PSOL from source (with some adjustment to get it to compile).
When attempting to build the nginx module I'm getting a compilation error:
/usr/lib/gcc/x86_64-alpine-linux-musl/5.3.0/../../../../x86_64-alpine-linux-musl/bin/ld:
/home/test/nginx/clean/ngx_pagespeed-<IP_ADDRESS>-beta-dynamic//psol/lib/Release/linux/x64/pagespeed_automatic.a(142.deflate.o.o):
relocation R_X86_64_PC32 against symbol 'pagespeed_ol_deflateResetKeep' can
not be used when making a shared object; recompile with -fPIC
/usr/lib/gcc/x86_64-alpine-linux-musl/5.3.0/../../../../x86_64-alpine-linux-musl/bin/ld:
final link failed: Bad value
collect2: error: ld returned 1 exit status
objs/Makefile:1170: recipe for target 'objs/ngx_pagespeed.so' failed
The PSOL was compiled with:
make all BUILDTYPE=Release CXXFLAGS=" -I/usr/include/apr-1
-I/home/test/nginx/libpng-1.2.56 -D_GLIBCXX_USE_CXX11_ABI=0
-Duse_system_libs=1 -Duse_system_icu=1" CFLAGS=" -I/usr/include/apr-1
-I/home/test/nginx/libpng-1.2.56 -D_GLIBCXX_USE_CXX11_ABI=0
-Duse_system_libs=1 -Duse_system_icu=1"
GCC -v
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/libexec/gcc/x86_64-alpine-linux-musl/5.3.0/lto-wrapper
Target: x86_64-alpine-linux-musl
Configured with: /home/buildozer/aports/main/gcc/src/gcc-5.3.0/configure
--prefix=/usr --mandir=/usr/share/man --infodir=/usr/share/info
--build=x86_64-alpine-linux-musl --host=x86_64-alpine-linux-musl
--target=x86_64-alpine-linux-musl --with-pkgversion='Alpine 5.3.0'
--enable-checking=release --disable-fixed-point --disable-libstdcxx-pch
--disable-multilib --disable-nls --disable-werror --disable-symvers
--enable-__cxa_atexit --enable-esp --enable-cloog-backend
--enable-languages=c,c++,objc,java,fortran,ada --disable-libssp
--disable-libmudflap --disable-libsanitizer --enable-shared
--enable-threads --enable-tls --with-system-zlib
Thread model: posix
gcc version 5.3.0 (Alpine 5.3.0)
Any help getting this to build would be appreciated.
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Sorry I should have mentioned I've already tried building both PSOL and NGINX with -fPIC with no change

Weird. Did you include it in CFLAGS as well?
On Tue, Mar 29, 2016 at 12:50 PM, Caleb Champlin<EMAIL_ADDRESS>wrote:

Sorry I should have mentioned I've already tried building both PSOL and
NGINX with -fPIC with no change
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Yup. The only thing I didn't do is compile PSOL with LDFLAGS -shared.

Sorry, looks like I missed CFLAGS on your line above... I am stumped,
hopefully one my colleagues can chime in.
One other thing that's worth pointing out:  Stuff
like:  -Duse_system_libs=1 -Duse_system_icu=1" needs to be passed to gyp,
not to make --- passing it to make doesn't do anything.
(Though those haven't really been tested for psol.a, just mod_pagespeed,
anyway --- you might need to remove some .a files from the Makefile that
makes the .a, and add some -l
lines at nginx level).
That's actually sort of relevant since the object file you get the link
erorr on comes from zlib, which you probably intended to dynamic link
anyway.
On Tue, Mar 29, 2016 at 4:22 PM, Caleb Champlin<EMAIL_ADDRESS>wrote:

Yup. The only thing I didn't do is compile PSOL with LDFLAGS -shared.
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Okay we can probably close this, it appears that your comment about removing the static libraries from the psol Makefile and adding them to the nginx compilation. Thanks for your help!
For anyone who comes across this in the future looking for information on how to get pagespeed to work on Alpine/MUSL here's a quick guide:
Grab and build a local version of libpng1.2
Download the PSOL source
Patch chromium to compile on MUSL (this is only needed until upstream chromium is used in PSOL, as these changes have already been applied in latest Chromium source)
See: https://codereview.chromium.org/1422623002/#ps40001 https://codereview.chromium.org/1514483008
psol-chromium.stacktrace.patch.txt
After it's been patched compile mod_pagespeed:
make BUILDTYPE=Release CXXFLAGS=" -I/usr/include/apr-1 -I/home/test/nginx/libpng-1.2.56 -fPIC -D_GLIBCXX_USE_CXX11_ABI=0" CFLAGS=" -I/usr/include/apr-1 -I/home/test/nginx/libpng-1.2.56 -fPIC -D_GLIBCXX_USE_CXX11_ABI=0"
Move to pagespeed/automatic
Remove the following static libraries from the make file: libapr, libaprutil, libjpeg, libjpeg_turbo, libicudata, libicuuc, libpng, libopenssl, libzlib
Compile PSOL
make all BUILDTYPE=Release CXXFLAGS=" -I/usr/include/apr-1 -I/home/test/nginx/libpng-1.2.56 -fPIC -D_GLIBCXX_USE_CXX11_ABI=0" CFLAGS=" -I/usr/include/apr-1 -I/home/test/nginx/libpng-1.2.56 -fPIC -D_GLIBCXX_USE_CXX11_ABI=0"
Once that's done you should have a pagespeed_automatic.a available for use, and you can now build nginx.
I built ngx_pagespeed as a dynamic module using the following:
./configure --with-ipv6 --with-file-aio --with-pcre-jit --with-http_dav_module --with-http_ssl_module --with-http_stub_status_module --with-http_gzip_static_module --with-http_v2_module --with-http_auth_request_module --with-mail --with-mail_ssl_module --add-dynamic-module=/home/test/nginx/clean/ngx_pagespeed-<IP_ADDRESS>-beta-dynamic/ --with-cc-opt="-fPIC" --with-ld-opt="-luuid -lapr-1 -laprutil-1 -licudata -licuuc -lpng12 -lturbojpeg -ljpeg -fPIC"

Did you also pass in the -D flags to gyp? It's potentially risky if you
don't, since it may end up using wrong header files  (the ones for bundled
versions, not system ones) for things like the SSL library otherwise, which
may be problematic
if the two aren't binary compatible (likely an issue with system OpenSSL
vs. bundled BoringSSL).
On Wed, Mar 30, 2016 at 1:10 PM, Jeffrey Crowell<EMAIL_ADDRESS>wrote:

Closed #1166 https://github.com/pagespeed/ngx_pagespeed/issues/1166.
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I am trying to build from an alpine container, I tried following  the guide
I am stuck at:
CC(target) out/Release/obj.target/apr/third_party/apr/src/locks/unix/global_mutex.o
  CC(target) out/Release/obj.target/apr/third_party/apr/src/locks/unix/proc_mutex.o
third_party/apr/src/locks/unix/proc_mutex.c: In function 'proc_mutex_proc_pthread_create':
third_party/apr/src/locks/unix/proc_mutex.c:384:15: warning: implicit declaration of function 'pthread_mutexattr_setrobust_np' [-Wimplicit-function-declaration]
     if ((rv = pthread_mutexattr_setrobust_np(&mattr,
               ^
third_party/apr/src/locks/unix/proc_mutex.c:385:48: error: 'PTHREAD_MUTEX_ROBUST_NP' undeclared (first use in this function)
                                                PTHREAD_MUTEX_ROBUST_NP))) {
                                                ^
third_party/apr/src/locks/unix/proc_mutex.c:385:48: note: each undeclared identifier is reported only once for each function it appears in
third_party/apr/src/locks/unix/proc_mutex.c: In function 'proc_mutex_proc_pthread_acquire':
third_party/apr/src/locks/unix/proc_mutex.c:440:13: warning: implicit declaration of function 'pthread_mutex_consistent_np' [-Wimplicit-function-declaration]
             pthread_mutex_consistent_np(mutex->pthread_interproc);
             ^
third_party/apr/apr.target.mk:394: recipe for target 'out/Release/obj.target/apr/third_party/apr/src/locks/unix/proc_mutex.o' failed
make: *** [out/Release/obj.target/apr/third_party/apr/src/locks/unix/proc_mutex.o] Error 1

@cchamplin What version of Nginx and ngx_pagespeed you have been using? I don't quite understand what patches should be applied? Those you have linked don't seem to match with the contents of mod_pagespeed repo.

@natostanco I'm not 100% on that one, APR was not directly built as part of my process, and I don't recall doing anything to prevent it from being built.
@iler I built against the prepackaged source  available here https://github.com/pagespeed/mod_pagespeed/issues/968 specifically version <IP_ADDRESS>

As an aside FYI I've been asked to try and put together and APK build of this whole thing, which hopefully I'll be able to get to some evening this week.

@cchamplin Thanks. Will try with that. And +1 for APK build.

@cchamplin if you did not pass anything to gyp and then synced again to update the gyp files you must have built apr too...

@cchamplin Any chance you faced this problem https://gist.github.com/iler/f1e519168bace48545d494edb7b2baa6? I'm building Docker container and it's failing. You can see the build commands from my Dockerfile https://gist.github.com/iler/90a87a46b50ffe218417871288247afc

for that thing I just renamed __timezone to timezone in the file specified file. But icu should be provide by the system, to use system libs when syncing from gclient I had to export GYP_DEFINES="use_system_libs=1 ...etc" then sync with gclient, even tough it still downloads the src files it should use system libs

@iler

You'll want to make sure you're passing use_system_libs=1 (specifically use_system_icu=1) to gyp.
In pagespeed/automatic I believe you can probably get away with just make psol instead of make all.
There are a few other files that need patching for this whole thing to work which I forgot in my original post (sorry!). The patch I attached to this file is also slightly wrong (but unlikely to actually cause any issues in this situation)
You'll also need to bring over PSOL content (necessary includes and pagespeed_automatic.a) into your ngx_pagespeed directory before trying to ./configure nginx.
As an aside building pagespeed inside an alpine docker container is less than desirable (especially for any production purposes) unless you're going to copy the binary out and use just that in another container or you clean up the downloaded libraries (your container will be extremely bloated, which is the opposite of what you want with alpine).

 It should be available here https://github.com/cchamplin/alpine-ngx-pagespeed
This will need some testing as it's first draft, my guess is I might be missing a few makedepends.
This should also work a general instructions to get it ngx pagespeed built on Alpine.
FYI: This only works against nginx-1.9.11+ as it is linked as a dynamic module.

@cchamplin Thanks a lot for your efforts! I will go through your repo and work from there.
And, yes, I'm aware of bloating the Docker container. I just wanted to slice the build to separate RUN commands to be able to use cache for the working parts of the build. If I encounter some problems I won't have to start downloading everything from scratch. Eventually when everything is working I will change this to one RUN command and do the proper cleanups. But thanks anyway :)

fyi the difference between compiling statically (without system libs) and with shared libraries (with system libs and deleted files) installing the required packages on alpine (apr apr-util libjpeg-turbo icu pcre) is ~4mb without even removing superfluous stuff added by the pkgs, so the packages themselves are pretty slim >.>

Just to update here that I got this working. Here is my implementation for Docker https://github.com/iler/alpine-nginx-pagespeed if someone needs some advices on this. Thanks @cchamplin for the help!


Communication: Unnecessary gray area in empty dropdown

Describe the bug
When there are no options available in the collapsible/dropdown menu of the communication section of a course, an unnecessary and unappealing empty grey area is displayed. This behavior is not ideal for user experience and is less common in user interfaces.
To Reproduce

Go to Course Management page
Click Communications button of a course
Click an empty option in the collapsible menu
Notice the unnecessary gray empty area

Expected behavior

The collapsible menu should not expand when there are no options available.
Alternatively, a message such as "No options available" should be displayed instead of an unnecessary gray area.

Screenshots

Which version of Artemis are you seeing the problem on?
7.4.2
What browsers are you seeing the problem on?
Chrome
Additional context
No response
Relevant log output
No response

Normally, as like other modules on sidebar, we do not intend to display empty accordions. However, we cannot remove this one due to an impediment caused by private messages and group chats, which require the plus button on the accordion to create chats. This should change in upcoming versions.


[IMPROVEMENT] Build longhorn-engine and longhorn-instance-manager without static libqcow library

Is your improvement request related to a feature? Please describe (👍 if you like this request)
Currently, we rely on the libqcow static lib when building longhorn-engine and longhorn-instance-manager
# Install libqcow
RUN wget -O - https://s3-us-west-1.amazonaws.com/rancher-longhorn/libqcow-alpha-20181117.tar.gz | tar xvzf - -C /usr/src
RUN cd /usr/src/libqcow-20181117 && \
    ./configure
RUN cd /usr/src/libqcow-20181117 && \
    make -j$(nproc) && \
    make install
RUN ldconfig

...

# Build longhorn-instance-manager for integration testing
RUN cd /go/src/github.com/longhorn && \
    git clone https://github.com/longhorn/longhorn-instance-manager.git && \
    cd longhorn-instance-manager && \
    go build -o ./longhorn-instance-manager -tags netgo -ldflags "-linkmode external -extldflags -static" && \
    cp -r integration/rpc/ ${DAPPER_SOURCE}/integration/rpc/ && \
    install longhorn-instance-manager /usr/local/bin

This ticket is for researching if we can

install the libqcow-devel from zypper
and build the longhorn-engine and instance-manager without static link lib

cc @derekbit

testing: https://ci.longhorn.io/job/private/job/longhorn-tests-regression/6727/

@derekbit tried to build the binary with
RUN zypper -n addrepo --refresh https://download.opensuse.org/repositories/openSUSE:Backports:SLE-15-SP3/standard/openSUSE:Backports:SLE-15-SP3.repo

RUN zypper install -n libbfio-devel libqcow-devel
RUN ldconfig

# Build longhorn-instance-manager for integration testing
RUN cd /go/src/github.com/longhorn && \
    git clone https://github.com/longhorn/longhorn-instance-manager.git && \
    cd longhorn-instance-manager && \
    # go build -o ./longhorn-instance-manager -tags netgo -ldflags "-linkmode external -extldflags -static" && \
    go build -o ./longhorn-instance-manager -tags netgo -ldflags "-linkmode external -extldflags -Wl,-Bdynamic,-lqcow" && \
    cp -r integration/rpc/ ${DAPPER_SOURCE}/integration/rpc/ && \
    install longhorn-instance-manager /usr/local/bin

But instance-manager failed to start because of
longhorn-instance-manager: error while loading shared libraries: libqcow.so.1: cannot open shared object file: No such file or directory

We still need static lib and we can only get those libs from building the source code

@ChanYiLin Have you tried to install libqcow instead? libqcow-devel is for the development purpose, so that should be headers only.


update reports 05/08

Moving forward because it is only updating the reports.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 0.85%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
18

Relevant Lines:
2118

💛  - Coveralls


PCA.transform needs .compute().compute() to have the graph executed

What happened:
I think something is wrong while using PCA (and other estimators as well).
To get the output of .transform it's necessary to run .compute().compute()
If i do .transform.compute(), a delayed object is returned
What you expected to happen:
just .transform(X).compute() should be enough
Minimal Complete Verifiable Example:
import numpy as np
import dask.array as da
from dask_ml.decomposition import PCA

X = np.array([[-1, -1, 1], [-2, -1, 0], [-3, -2, 1], [1, 1, 1], [2, 1, 2], [3, 2, 2]])
dX = da.from_array(X, chunks=X.shape)
pca = PCA(n_components=2)
pca.fit(dX)

X_ = pca.transform(dX)

print(X_.compute().compute())
# This returns
# >> [[-1.38758417  0.22742705]
# >>  [-2.41405112 -0.72889357]
# >> [-3.56312482  0.5469439 ]
# >>  [ 1.31943832 -0.52697288]
# >>  [ 2.34590527  0.42934773]
# >>  [ 3.69941652  0.05214777]]

# This returns a delayed object
#print(X_.compute())

Environment:

Dask version: 2021.11.2
Dask-ml version: 1.9.0
Distributed version:  2021.11.2
Python version: 3.8.12
Operating System: Debian GNU/Linux 10 (buster)
Install method: Installed using conda from conda-forge

Thanks

The double compute looks like a bug. If you want to take a look at what's going on that'd be great.

I can't repro with dask 2021.11.2 and dask-ml 1.9.0


[BUG] senderProfile or sendClassificaiotn wrong when journeys are retrieved with retrieve-all

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
details to follow
Expected Behavior
No response
Steps To Reproduce

Go to '...'
Click on '....'
Run '...'
See error...

Version
7.5.0
Environment

OS:
Node:
npm:

Participation

[ ] I am willing to submit a pull request for this issue.

Additional comments
No response

cannot reproduce with retrieve cred/bu (without types)

i strongly believe this was a false positive and hence I'm closing it


PHOENIX-4864 Fix NullPointerException while Logging some DDL Statements

Fixed the error. Still to add corresponding test case. @vincentpoon @karanmehta93

Added the corresponding test case. @vincentpoon @karanmehta93

Nice test coverage @ashuparekh
This PR is almost good to go!

@karanmehta93 Incorporated the above suggestions

Already merged.


Print version info after installing CLI

The macos-latest CI failures I believe are due to https://github.com/jozu-ai/kitops/issues/284


Indicate when data was last added for country/radar

By @adokter:

@stijnvanhoey @peterdesmet Since a few days the data seem to flowing in again, maybe something broke in Sweden which was solved when people got back from Christmas.
Without any doubt such hickups will happen more often in the future. It would be good if we could see relatively quickly when certain radars stop providing data. A crude but simple solution would be if next to each country folder and radar folder the date of latest addition would be shown at http://enram.github.io/data-repository/. Is that a tweak that could be made before the start of this spring migration season (Mar 1), or does that require a real project?

Hi guys,
I had a look at the repo to see if data is coming in regularly. The coverage.csv does come in handy then. One question though: what is the number you get in the column vp_files? The total number of vp's for the last day data was transferred? Or the total number of vp's that's available on the repo for that radar?

it's by day

Pretty sure it is the number of vp files for that date.

Thx!


BUG: Fix dark mode issue, enhance SEO

Is there an existing issue for this?

[X] I have searched the existing issues

What went down?

Add relevant alt attributes to enhance SEO

https://github.com/mdazfar2/HelpOps-Hub/assets/114163734/a85d446f-13a1-4f3c-9b4e-b322b282a6d7

fix darkmode issue in input box of newsletter subscription
fix resource not found color according to theme

Record

[X] I agree to follow this project's Code of Conduct
[X] I'm a GSSOC'24 contributor
[ ] I'm a VSoC'24 contributor
[X] I want to work on this issue

@vansh-codes Issue acknowledged! You are assigned.


JUnit5 assertThrows BugCLI252Test

Hi @nhojpatrick
Please rebase on master and implement your FIXME items.

Codecov Report

Merging #139 (488b14d) into master (4076cc4) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master     #139   +/-   ##
=========================================
  Coverage     93.20%   93.20%
  Complexity      567      567
=========================================
  Files            21       21
  Lines          1206     1206
  Branches        214      214
=========================================
  Hits           1124     1124
  Misses           46       46
  Partials         36       36

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more

@garydgregory rebased and updated for Java 8.


Installation Issue:  Couldn't open CUDA library libcuda.so.1.

In the step where I have to run
bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu
I get the following messages:
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so.7.0 locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so.7.0 locally
I tensorflow/stream_executor/dso_loader.cc:102] Couldn't open CUDA library libcuda.so.1. LD_LIBRARY_PATH:...
...
...
...
failed to find libcuda.so on this system: Failed precondition: could not dlopen DSO: libcuda.so.1; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
...
...
...
E tensorflow/stream_executor/cuda/cuda_driver.cc:491] failed call to cuInit: CUDA_ERROR_NO_DEVICE
...
...
...
I tensorflow/core/common_runtime/gpu/gpu_init.cc:81] No GPU devices available on machine.
Environment info
Operating System: Debian 8
Installed version of CUDA and cuDNN: CUDA 7.0, cuDNN 4.0.7
(please attach the output of ls -l /path/to/cuda/lib/libcud*):
/usr/local/cuda/lib/libcudadevrt.a
/usr/local/cuda/lib/libcudart.so -> libcudart.so.7.0
/usr/local/cuda/lib/libcudart.so.7.0 -> libcudart.so.7.0.28
/usr/local/cuda/lib/libcudart.so.7.0.28
/usr/local/cuda/lib/libcudart_static.a

The commit hash (git rev-parse HEAD)
554ddd9ad2d4abad5a9a31f2d245f0b1012f0d10
The output of bazel version
Build target: bazel-out/local-fastbuild/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar
Build time: Thu Jan 01 00:00:00 1970 (0)
Build timestamp: Thu Jan 01 00:00:00 1970 (0)
Build timestamp as int: 0

P.S. I have two GPUs installed on my server. One is used for GUI (AMD) and the other is used for computation (NVIDIA).
Should I do anything to make sure the second GPU is being used?

Did you check on your system if libcuda.so.* does exist ? On my system it is in /usr/local/nvidia/lib64 and another of my system it is in /usr/lib/.
If it does exist, then set the LD_LIBRARY_PATH env variable to point to the correct path. If it doesn't you might've to install it on your system.
Cuda should not recognize the AMD device as a valid cuda target, so you should run on the right GPU.

I have libcuda.so.7, but not libcuda.so.1
Should I reinstall cuda drivers?

You could just ln -s libcuda.so.7.* libcuda.so.1 and see if it works.

I tried this solution. Now I get the following messages:
E tensorflow/stream_executor/cuda/cuda_driver.cc:491] failed call to cuInit: CUresult(-1) ... I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:185] libcuda reported version is: Not found: was unable to find libcuda.so DSO loaded into this program I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:356] driver version file contents: """NVRM version: NVIDIA UNIX x86_64 Kernel Module  340.96  Sun Nov  8 22:33:28 PST 2015

@MahdiNazemi  Do you solve this problem? I also face the same situation. Thanks!

@MahdiNazemi  Do you solve this problem? I also face the same situation. Thanks!

@chocolate9624 I still have this issue. Please let me know if you find a solution.

@chocolate9624 Could you find any solutions to the problem? I'm still looking for a solution...

Your driver (kernel module) is really old: 340.96. Can you upgrade to a more recent driver/cuda?

I updated to the latest version on jessie-backports which is 352.79, but it didn't solve the issue.

@MahdiNazemi  I solved this problem by comparing with other machines.  In /use/lib64
libcuda.so -> /usr/lib64/libcuda.so.1
libcuda.so.1 -> /usr/lib64/nvidia/libcuda.so.1
libcuda.so.1 should be linked to   /usr/lib64/nvidia/libcuda.so.1
Good luck!

Thanks a lot @chocolate9624.
Finally, I was able to solve the issue. It looks like none of the drivers that are available on Debian (jessie, jessie-backports, and stretch) can make the GPU work (not my Quadro nor my Tesla). I used the driver that is available on Nvidia's website and it solved the problem.

That's good to know. Is it an issue with the driver version, or about where they install to?

I installed 3 different versions, i.e. 340.96, 352.79, and 367.44, but none of them worked. I don't think the problem is with the driver version, but I'm not sure if it's about where they are installed or not.

Hi, I have solved it by these steps:
1.sudo apt install nvidia-361-dev
2.sudo find /usr/ -name 'libcuda.so.1' (then you will know path of libcuda.so.1)
3.just cp the libcuda.so.1 to /usr/local/cuda/lib/
actually the libcuda.so.1 you find is a link, see:

@ShiKaiWi Which repo does the nvidia-361-dev come from? I am seeing following when I try to install it.
E: Unable to locate package nvidia-361-dev

@soichih Hi, my os is ubuntu 16.04 so this repo is provided by default. So I suggest you can try to install nvidia-3**-dev (I guess the  version is 352 if you use ubuntu 14.04) and then try to find the libcuda.so.1.

Looks resolved. Thanks all.

Hi, I have solved it by these steps:
1.$ sudo apt install nvidia-361-dev
2.$ sudo find /usr/ -name 'libcuda.so.1' (then you will know path of libcuda.so.1)
3. just copy the libcuda.so.1 to /usr/local/cuda/lib/
actually the libcuda.so.1 you find is a link file, see:

it works for me

hello sir i make mistake and accidentally delete the libcuda.so.1 like this :

how can i solve this problem ?

Directory of C:\Windows\System32\lxss\lib
09/18/2020  03:53 PM              .
08/30/2020  09:51 AM           124,664 libcuda.so
09/12/2020  08:44 AM           832,936 libd3d12.so
09/12/2020  08:44 AM         5,073,944 libd3d12core.so
09/12/2020  08:44 AM        25,069,816 libdirectml.so
09/12/2020  08:44 AM           878,768 libdxcore.so
08/30/2020  09:51 AM        40,496,936 libnvwgf2umx.so
6 File(s)     72,477,064 bytes
1 Dir(s)  643,723,309,056 bytes free
C:\Windows\System32\lxss\lib>mklink libcuda.so.1 libcuda.so
symbolic link created for libcuda.so.1 <<===>> libcuda.so

hello sir i make mistake and accidentally delete the libcuda.so.1 like this :

how can i solve this problem ?
or is that red icon mean deleted ? i'm not really s

hello sir i make mistake and accidentally delete the libcuda.so.1 like this :

how can i solve this problem ?
or is that red icon mean deleted ? i'm not really sure

Could you manage to solve that issue? Because my libcudart.so is also in red color .
Thanks in advance!

where I can find those on Mac ?
libcuda.so -> ?
libcuda.so.1 ->?


Master

hi, was this an intentional PR? The IP addr fix looks potentially interesting, but looks like there's lots of cruft.

Sorry about that, not intentional. This is just our temporary workaround until I find the root-cause.


⚠ Bofrost.at has degraded performance

In 4caea0d, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 1729 ms

Resolved: Bofrost.at performance has improved in 9dc8ab0 after 31 minutes.


Support new format policy sources

It required some changes to how evaluators are organized. There is now one evaluator for each "source group".
Also remove the "hard coded" data source since it's now possible to list it explicitly. This will require the adding the main EC data souce explicitly to default config in the e2e tests.
Reference: https://issues.redhat.com/browse/HACBS-1397

Thanks @zregvart. I'll move it to draft until everything is passing and the comments are addressed.


Always support TLS1.2

Hi @StefanMaron,
We have a (now quite old) server where some developers are running VSCode.
It seems as if TLS1.2 is not supported by default in their PowerShell sessions, so the call to download the dll always fails. (without notice as it seems)
I added one line to add support for TLS1.2 before downloading the dll.
This change is only affecting the running PowerShell session, so it should be pretty harmless.

Thanks, I will try to merge and push this over the weekend

Hi @StefanMaron,
Are there anything more I can do to help you out here? I assume that you're busy with life :)
One thing could be to rewrite the download logic to use the https module to increase the error handling possibility. Firing of a PowerShell script comes with it's challenges, as noticed. ;)


[docs] We want the previous docs side nav layout back

Duplicates

[X] I have searched the existing issues

Latest version

[X] I have tested the latest version

Summary 💡
It seems you have changed the documentation layout. But it is far disturbing than helping us. Why did you stuck the sponsors tab in the bottom speically when every mui user needs to search for components deep down? Also we get little space to look for components list.
Examples 🌈
https://mui.com/material-ui/getting-started/installation/
Motivation 🔦
This layout is irritating as hell. Previous layout was quiet good and we could see sponsors before components and we have no problem as it was not irritating us. Now it is irritating really.

Hey there @ChetSocio, appreciate the feedback! Our intention with the change was to improve the navigation experience by removing the sponsors from the front & center and giving the side nav content more visibility at first glance at the docs ⎯ but your perspective is valuable and we hadn't considered it before, so thanks again!
To confirm it then, the sponsors being fixed at the bottom is hurting your navigation as you usually are scrolling deep on the list of components?

yes really, the way it was organized previously was really good and never irritated us.I myself as a visitor loved that and never was a problem when scrolling for components. We could see sponsors as well as downward navigation was a good experience. The way it is now is distrubing as well as irritating

It feels strange for me too: https://github.com/mui/material-ui/pull/38050#discussion_r1268272649

I'm reopening as we are testing different layouts at this point. I think we can update this issue once we settle on a direction.

Another idea, https://formkit.com/getting-started/what-is-formkit makes the diamond sponsors in a sticky position.
https://github.com/mui/material-ui/assets/3165635/96a36855-13a5-4de3-b604-9cfe42fb8381

A different type of execution, the first time I see this kind: https://formkit.com/getting-started/what-is-formkit puts the diamond sponsors in a sticky position.
Screen.Recording.2023-09-01.at.19.09.01.mov

Yes, this is acceptable as it will serve it's purpose as well as won't distrub devs

@oliviertassinari Shall we close this one as per the recent email thread you sent out about this topic?

Yup I am closing this as you seem to have done what i was thinking and now its a  lot better on right side . You got many benefits: its easy to click on right side than left side, its now visible properly, it is not distrubing devs anymore. Thanks

Shall we close this one as per the recent email thread you sent out about this topic?

@danilo-leal that thread: https://groups.google.com/a/mui.com/g/core/c/NMMUNFCsayM. Yes, I think we can close. With the data we have available, the current placement seems OK.
Another angel I didn't use in that thread: considering the alternative libraries we compete with, this ad placement seem to be the one that has the least potential to negatively differentiate us.


Reduce package size

Remove all images from the package but the icon. Reference them from other location.

Hi, can I just delete the image directory from the package directory after installing the package? It doesn't affect the functionality, I assume? Thanks!
Great package! I thought nobody would write a package for EBNF..

Happy to hear you like the package.
I guess you can delete the directory, but why deleting it ones it's already on your PC?
The issue here was to reduce the package size in order to send less bits throuw the wire durring install.


Start fixing up documentation and comments

Not sure if we should use JSDoc or if there is anything better we could be using?

Might be something to look in to: https://esdoc.org/

@JenkinsDev most likely I'll use ESDoc for the actual API Documentation and http://www.mkdocs.org/ for dev/theme documentation

Hi! I am developing ESDoc. Thanks using it :smile:
ESDoc provides the two features that are Manual Integration and ESDoc Hosting Service. The features might help you.
Feel free this proposal.
Thanks.

thanks @h13i32maru! Will definitely start implementing ESDoc soon :)


Pr test wip 2

Sorry for the spam. I can't reproduce a source compat test failure locally.

@swift-ci Please test compiler performance

Build comment file:
Compilation-performance test failed


Microsoft Entra admin consent with user assignment required

The section "I have an application that requires user assignment. A user that I assigned to an application is being asked to request admin consent instead of being able to consent themselves. Why is that?". Explains that this limitation exists, but it does not explain the "Why is that?" part.
I would like to understand why it is not possible to consent to scopes if the user assignment is required, when it is otherwise possible if user assignment is set to "not required".
Could you please explain the reason for this limitation?

Document Details
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.

ID: b05e9501-9970-560d-a45c-5a705ab120bd
Version Independent ID: a507819e-a4c0-7772-5e21-fd351bdb6028
Content: Frequently asked questions about the admin consent workflow - Microsoft Entra ID
Content Source: docs/identity/enterprise-apps/admin-consent-workflow-faq.md
Service: active-directory
Sub-service: app-mgmt
GitHub Login: @omondiatieno
Microsoft Alias: jomondi

@TimoWilhelm
Thanks for your feedback! We will investigate and update as appropriate.

@TimoWilhelm
Thanks for bringing this to our attention.
I'm going to assign this to the document author so they can take a look at it accordingly.
@omondiatieno please review it.


Create base template

Create base template that can extend all the templates for all view.

[x] Add simple bootstrap style
[x] Add hardcoded navigation to views

hardcoded navigation is too early, we need the views first will create separate issue for this once all 0.1 views are in place...

We can have base template same style as PyCon SK 2016, eg. with some fixtures we can easily build replica of the site (replica is probably on higher version as we dont have all the functionality, but list sponsors for example might work fine)...

PR merged


Debian9

Add a new page for Debian 9 installation
Recent posts on the forum indicates that Debian 9 is used in various locations
The web section will need to be adjusted
This will require some changes to omeroweb-install
cc @mtbc
https://trello.com/c/00CYQi2t/29-debian-installation-page

@mtbc
Staged at http://www.openmicroscopy.org/site/support/omero5.3-staging/sysadmins/unix/server-debian9-ice36.html

I will fix the web link in another PR since it requires some changes in another repo

https://github.com/ome/omeroweb-install/pull/17 omeroweb-install is now opened
Merging this PR
I will fix the link when the omeroweb-install PR  is in


Add CL2 kind provider

What type of PR is this?

/kind feature
What this PR does / why we need it:
Adds a kind provider for CL2. More details here: https://github.com/kubernetes/perf-tests/issues/1693
Which issue(s) this PR fixes:

Part of https://github.com/kubernetes/perf-tests/issues/1693
Special notes for your reviewer:
SSH to master to be tackled in a separate PR
Does this PR introduce a user-facing change?:

Support kind as a CL2 provider

Additional documentation e.g., KEPs (Kubernetes Enhancement Proposals), usage docs, etc.:

/cc @mm4tt

/ok-to-test

This is amazing. Thanks so much, @lyzs90!
/lgtm
/approve


ECDSA key version mismatch from openssl pem files

Hi there,
I'm trying to generate ECDSA key pairs, using these 2 commands (on debian):
openssl ecparam -genkey -name secp521r1 -noout -out ecdsa-p521-private.pem
openssl ec -in ecdsa-p521-private.pem -pubout -out ecdsa-p521-public.pem

I end up with these pem contents:
-----BEGIN EC PRIVATE KEY-----
MIHcAgEBBEIBrLSlt+M2LjhfoZw0kcdA9F2cbSlCHmPeCyj/PzXryszQMQ8KQb+1
CZX6B1eXgRi7LIVRDUWVoV9A098tqIuXwaagBwYFK4EEACOhgYkDgYYABAHHPcnH
n1gziRFXawb+fOnnpd8dDRqhgk6yiZsvV9oUKvu7tv+5XavCsdtZIiEaqCctjdGp
01KExDqYCnh2S9ABiwFstThkfIcJ8NkRLHPMEGeQnJFeCE3gAY4MJsd89hAn+7xy
q39PVnqLR3spPc8CKVYwluzvyNhNcU6RSZLJHjWJ8w==
-----END EC PRIVATE KEY-----

-----BEGIN PUBLIC KEY-----
MIGbMBAGByqGSM49AgEGBSuBBAAjA4GGAAQBxz3Jx59YM4kRV2sG/nzp56XfHQ0a
oYJOsombL1faFCr7u7b/uV2rwrHbWSIhGqgnLY3RqdNShMQ6mAp4dkvQAYsBbLU4
ZHyHCfDZESxzzBBnkJyRXghN4AGODCbHfPYQJ/u8cqt/T1Z6i0d7KT3PAilWMJbs
78jYTXFOkUmSyR41ifM=
-----END PUBLIC KEY-----

But when I try to read the private key, I'm getting this exception:
java.security.spec.InvalidKeySpecException: java.security.InvalidKeyException: IOException : version mismatch: (supported:     00, parsed:     01
I tried using the pem files in test directory https://github.com/auth0/java-jwt/tree/master/lib/src/test/resources (ec512-key-private.pem, ec512-key-public.pem) and that pair works. So it might be the way I generate the pem files that's messing things up. If you can share how you generated your test pem files that would be great.
Thx!

You are doing it fine. I think you just forgot to convert the private key to this "newer" pem format:
openssl pkcs8 -topk8 -inform pem -in file.key -outform pem -nocrypt -out file.pem

See if that works. Cheers

Ah, that works! Thanks for the pointer!

You are doing it fine. I think you just forgot to convert the private key to this "newer" pem format:
openssl pkcs8 -topk8 -inform pem -in file.key -outform pem -nocrypt -out file.pem

See if that works. Cheers

what is newer format? where i can read about it?
thanks fore reply

You are doing it fine. I think you just forgot to convert the private key to this "newer" pem format:
openssl pkcs8 -topk8 -inform pem -in file.key -outform pem -nocrypt -out file.pem

See if that works. Cheers

what is newer format? where i can read about it?
thanks fore reply

I used this tool class. But it shows me error of public key null. can anyone help me?


[ TF 2.0 ] tf.function throws exception

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 18.04
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): pip install tensorflow-gpu==2.0.0-alpha0
Python version: 3.7.3
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version: CUDA 10/cuDNN 7.5
GPU model and memory:  GeForce GTX 980 4G

Describe the current behavior
I ported Deep Deterministic Policy Gradient algorithm to tf-2.0 and it works fine when I run the function with
with tf.device("/gpu:0"): but fails when I try to wrap the function with tf.function
Code to reproduce the issue
Code Repo
Other info / logs
/miniconda3/envs/rl/bin/python /media/seagull/use_me/seagull/github/DDPG/ddpg-pendulam/pendulam_train_script.py
WARNING: Logging before flag parsing goes to stderr.
W0501 21:58:48.871961<PHONE_NUMBER>09536 tf_logging.py:161] Entity <bound method RoboschoolMujocoXmlEnv.reset of <roboschool.gym_pendulums.RoboschoolInvertedPendulum object at 0x7f2a9ccfe780>> could not be transformed and will be staged without change. Error details can be found in the logs when running with the env variable AUTOGRAPH_VERBOSITY >= 1. Please report this to the AutoGraph team. Cause: Unexpected error transforming <bound method RoboschoolMujocoXmlEnv.reset of <roboschool.gym_pendulums.RoboschoolInvertedPendulum object at 0x7f2a9ccfe780>>. If you believe this is due to a bug, please set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output when filing the bug report. Caused by: node <gast.gast.Attribute object at 0x7f2a2043dcf8> has ctx unset
Traceback (most recent call last):
  File "/media/seagull/use_me/seagull/github/DDPG/ddpg-pendulam/pendulam_train_script.py", line 39, in <module>
    scores = ddpg()
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 426, in __call__
    self._initialize(args, kwds, add_initializers_to=initializer_map)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 370, in _initialize
    *args, **kwds))
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1313, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1580, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1512, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 694, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 317, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 686, in wrapper
    ), args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 392, in converted_call
    result = converted_f(*effective_args, **kwargs)
  File "/tmp/tmp0cbzqvh_.py", line 51, in tf__ddpg
    ag__.for_stmt(ag__.converted_call(range, None, ag__.ConversionOptions(recursive=True, verbose=0, strip_decorators=(tf.function, defun_1, ag__.convert, ag__.do_not_convert, ag__.converted_call), force_conversion=False, optional_features=(), internal_convert_user_code=True), (1, n_episodes + 1), {}), None, loop_body_1, ())
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 81, in for_stmt
    return _py_for_stmt(iter_, extra_test, body, init_state)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 90, in _py_for_stmt
    state = body(target, *state)
  File "/tmp/tmp0cbzqvh_.py", line 37, in loop_body_1
    state, score, break__1 = ag__.for_stmt(ag__.converted_call(range, None, ag__.ConversionOptions(recursive=True, verbose=0, strip_decorators=(tf.function, defun_3, ag__.convert, ag__.do_not_convert, ag__.converted_call), force_conversion=False, optional_features=(), internal_convert_user_code=True), (max_t,), {}), extra_test, loop_body, (state, score, break__1))
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 81, in for_stmt
    return _py_for_stmt(iter_, extra_test, body, init_state)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 90, in _py_for_stmt
    state = body(target, *state)
  File "/tmp/tmp0cbzqvh_.py", line 21, in loop_body
    action = ag__.converted_call('act', agent, ag__.ConversionOptions(recursive=True, verbose=0, strip_decorators=(tf.function, defun_4, ag__.convert, ag__.do_not_convert, ag__.converted_call), force_conversion=False, optional_features=(), internal_convert_user_code=True), ([state_1],), {})[0]
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 392, in converted_call
    result = converted_f(*effective_args, **kwargs)
  File "/tmp/tmpsruok5vd.py", line 6, in tf__act
    action = ag__.converted_call('actor_local', self, ag__.ConversionOptions(recursive=True, verbose=0, strip_decorators=(tf.function, defun, ag__.convert, ag__.do_not_convert, ag__.converted_call, defun_1, ag__.convert, ag__.do_not_convert, ag__.converted_call), force_conversion=False, optional_features=(), internal_convert_user_code=True), (tf.convert_to_tensor(state),), {})
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 1108, in convert_to_tensor_v2
    as_ref=False)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 1186, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 304, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 245, in constant
    allow_broadcast=True)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 283, in _constant_impl
    allow_broadcast=allow_broadcast))
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/tensor_util.py", line 476, in make_tensor_proto
    _GetDenseDimensions(values)))
ValueError: Argument must be a dense tensor: [array([0.        , 0.        , 0.99759441, 0.06932093, 0.        ])] - got shape [1, 5], but wanted [1].

@Jonathan-Livingston-Seagull, In order to expedite the trouble-shooting process, Can you please provide minimum code snippet to reproduce the issue reported here. Thanks!

When I tried to make the following minimal example, I have found the reason for the reported issue. However I get another exception after solving that one. Please find the minimal code below. The source of the error seems like calling 'np.isfinite()' method inside the tf function definition. In my real code this method is being called by a third party lib that I use inside my tf function definition.
import random
import numpy as np

import tensorflow as tf

class Actor(tf.keras.Model):
    def __init__(self, action_size, fc1_units=400, fc2_units=300):
        super(Actor, self).__init__()
        self.fc1 = tf.keras.layers.Dense(units=fc1_units, activation=tf.nn.relu)
        self.fc2 = tf.keras.layers.Dense(units=fc2_units, activation=tf.nn.relu)
        self.fc3 = tf.keras.layers.Dense(action_size, activation=tf.nn.tanh)

    def call(self, state):
        return self.fc3(self.fc2(self.fc1(tf.convert_to_tensor(state))))

class Agent():

    def __init__(self, state_size, action_size, random_seed):
        self.state_size = state_size
        self.action_size = action_size
        self.seed = random.seed(random_seed)

        # Actor Network (w/ Target Network)
        self.actor_local = Actor(action_size)

    def act(self, state, add_noise=True):
        action = self.actor_local(tf.convert_to_tensor(state))
        return tf.clip_by_value(action, -1, 1)

agent = Agent(state_size=5, action_size=1, random_seed=2)

@tf.function
def ddpg():
    import numpy as np
    state = np.arange(5).astype(np.float64).reshape((1, -1))
    state = agent.act(state)
    np.isfinite(state)
    return state

scores = ddpg()

#with tf.device("/gpu:0"):
#    scores = ddpg()
#    print("run is successful")

Exception:

WARNING: Logging before flag parsing goes to stderr.
W0503 18:53:51.962915<PHONE_NUMBER>53408 tf_logging.py:161] Entity <method-wrapper '__call__' of numpy.ufunc object at 0x5594ba8c9580> could not be transformed and will be staged without change. Error details can be found in the logs when running with the env variable AUTOGRAPH_VERBOSITY >= 1. Please report this to the AutoGraph team. Cause: Object conversion is not yet supported. If you are trying to convert code that uses an existing object, try including the creation of that object in the conversion. For example, instead of converting the method of a class, try converting the entire class instead. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/README.md#using-the-functional-api for more information.
Traceback (most recent call last):
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 369, in converted_call
    experimental_partial_types=partial_types)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 513, in to_graph
    arg_values, arg_types)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/conversion.py", line 196, in entity_to_graph
    'Object conversion is not yet supported. If you are '
NotImplementedError: Object conversion is not yet supported. If you are trying to convert code that uses an existing object, try including the creation of that object in the conversion. For example, instead of converting the method of a class, try converting the entire class instead. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/README.md#using-the-functional-api for more information.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/media/seagull/use_me/seagull/github/DDPG/ddpg-pendulam/ddpg_agent_tf.py", line 43, in <module>
    scores = ddpg()
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 426, in __call__
    self._initialize(args, kwds, add_initializers_to=initializer_map)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 370, in _initialize
    *args, **kwds))
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1313, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1580, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1512, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 694, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 317, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 686, in wrapper
    ), args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 392, in converted_call
    result = converted_f(*effective_args, **kwargs)
  File "/tmp/tmp4fw9we40.py", line 8, in tf__ddpg
    ag__.converted_call('isfinite', np, ag__.ConversionOptions(recursive=True, verbose=0, strip_decorators=(tf.function, defun_2, ag__.convert, ag__.do_not_convert, ag__.converted_call), force_conversion=False, optional_features=(), internal_convert_user_code=True), (state,), {})
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 390, in converted_call
    return _call_unconverted(f, args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 188, in _call_unconverted
    return f(*args, **kwargs)
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

@Jonathan-Livingston-Seagull I think you need to use tf.py_function. Please check the code below which works without any issue. Thanks!
import random
import numpy as np

import tensorflow as tf

class Actor(tf.keras.Model):
    def __init__(self, action_size, fc1_units=400, fc2_units=300):
        super(Actor, self).__init__()
        self.fc1 = tf.keras.layers.Dense(units=fc1_units, activation=tf.nn.relu)
        self.fc2 = tf.keras.layers.Dense(units=fc2_units, activation=tf.nn.relu)
        self.fc3 = tf.keras.layers.Dense(action_size, activation=tf.nn.tanh)

    def call(self, state):
        return self.fc3(self.fc2(self.fc1(state)))

class Agent():

    def __init__(self, state_size, action_size, random_seed):
        self.state_size = state_size
        self.action_size = action_size
        self.seed = random.seed(random_seed)

        # Actor Network (w/ Target Network)
        self.actor_local = Actor(action_size)

    def act(self, state, add_noise=True):
        action = self.actor_local(state)
        return tf.clip_by_value(action, -1, 1)

agent = Agent(state_size=5, action_size=1, random_seed=2)

def check_state(state):
  return np.isfinite(state)

@tf.function
def ddpg():
    #import numpy as np
    state = np.arange(5).astype(np.float64).reshape((1, -1))
    state = agent.act(state)
    #np.isfinite(state)
    tf.py_function(check_state,inp=[state],Tout=[tf.bool])
    return state

scores = ddpg()

with tf.device("/gpu:0"):
    scores = ddpg()
    print("run is successful")

@jvishnuvardhan Thanks . that solved that issue. However I encountered another issue which I explained in the toy example below.
I wanted to break my loop based on the value returned from py_function as shown below.

import numpy as np
import tensorflow as tf

def dummy_py_function():
    return np.random.random(5), np.random.choice([True, False])

@tf.function
def random_break():
    for i in range(10):
        random_array, done = tf.py_function(dummy_py_function, inp=[], Tout=[tf.float32, tf.bool])
        if done:
            break
        else:
            continue

random_break()

This throws the following exception
Traceback (most recent call last):
  File "/media/seagull/use_me/seagull/github/DDPG/ddpg-pendulam/test.py", line 18, in <module>
    random_break()
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 426, in __call__
    self._initialize(args, kwds, add_initializers_to=initializer_map)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 370, in _initialize
    *args, **kwds))
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1313, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1580, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1512, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 694, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 317, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 686, in wrapper
    ), args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 392, in converted_call
    result = converted_f(*effective_args, **kwargs)
  File "/tmp/tmpjfr3w2a8.py", line 25, in tf__random_break
    break_, = ag__.for_stmt(ag__.converted_call(range, None, ag__.ConversionOptions(recursive=True, verbose=0, strip_decorators=(tf.function, defun, ag__.convert, ag__.do_not_convert, ag__.converted_call), force_conversion=False, optional_features=(), internal_convert_user_code=True), (10,), {}), extra_test, loop_body, (break_,))
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 81, in for_stmt
    return _py_for_stmt(iter_, extra_test, body, init_state)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/operators/control_flow.py", line 88, in _py_for_stmt
    if extra_test is not None and not extra_test(*state):
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 660, in __bool__
    raise TypeError("Using a `tf.Tensor` as a Python `bool` is not allowed. "
TypeError: Using a `tf.Tensor` as a Python `bool` is not allowed. Use `if t is not None:` instead of `if t:` to test if a tensor is defined, and use TensorFlow ops such as tf.cond to execute subgraphs conditioned on the value of a tensor.

However the following code works fine. I have noticed that the issue appears when the py_function returns more than one value.
import numpy as np
import tensorflow as tf

def dummy_py_function():
    return np.random.choice([True, False])

@tf.function
def random_break():
    for i in range(10):
        done = tf.py_function(dummy_py_function, inp=[], Tout=[tf.bool])
        if done:
            break
        else:
            continue

random_break()

@Jonathan-Livingston-Seagull You could do this. I am not sure whether we can return two different data types from py.funciton. Below, I have split the py_function into to two py_functions. It runs through without any issues. thanks!
import numpy as np
import tensorflow as tf

def dummy_py_function():
    return np.random.random(5)

def dummy_py_function2():
    return np.random.choice([True, False])

@tf.function
def random_break():
    for i in range(10):
      print(i)
      random_array = tf.py_function(dummy_py_function, inp=[], Tout=[tf.float32])
      done = tf.py_function(dummy_py_function2, inp=[], Tout=[tf.bool])
      print(random_array)
      print(done)
      if done:
          break
      else:
          continue

random_break()

@jvishnuvardhan You are right, as I mentioned in my previous message if the number of returned value from the py_function is one than it run through.

I think this is not about the different return datatypes, even if I return the same datatype, it does not work as soon as the py_function returns more than one value. i.e the code below does not work

import tensorflow as tf

def dummy_py_function1():
    return False, False

@tf.function
def random_break():
    for i in range(10):
        print(i)
        done1, done2 = tf.py_function(dummy_py_function1, inp=[], Tout=[tf.bool, tf.bool])
        if done1:
            print("breaking")
            break
        else:
            continue

random_break()

The second point is that the "if condition" always satisfied even if you return False from the function in the code you provided above.

@Jonathan-Livingston-Seagull Thanks! please close if the issue was resolved. Thanks!

@Jonathan-Livingston-Seagull Thanks! please close if the issue was resolved. Thanks!

When I tried to make the following minimal example, I have found the reason for the reported issue. However I get another exception after solving that one. Please find the minimal code below. The source of the error seems like calling 'np.isfinite()' method inside the tf function definition. In my real code this method is being called by a third party lib that I use inside my tf function definition.
import random
import numpy as np

import tensorflow as tf

class Actor(tf.keras.Model):
    def __init__(self, action_size, fc1_units=400, fc2_units=300):
        super(Actor, self).__init__()
        self.fc1 = tf.keras.layers.Dense(units=fc1_units, activation=tf.nn.relu)
        self.fc2 = tf.keras.layers.Dense(units=fc2_units, activation=tf.nn.relu)
        self.fc3 = tf.keras.layers.Dense(action_size, activation=tf.nn.tanh)

    def call(self, state):
        return self.fc3(self.fc2(self.fc1(state)))

class Agent():

    def __init__(self, state_size, action_size, random_seed):
        self.state_size = state_size
        self.action_size = action_size
        self.seed = random.seed(random_seed)

        # Actor Network (w/ Target Network)
        self.actor_local = Actor(action_size)

    def act(self, state, add_noise=True):
        action = self.actor_local(state)
        return tf.clip_by_value(action, -1, 1)

agent = Agent(state_size=5, action_size=1, random_seed=2)

@tf.function
def ddpg():
    import numpy as np
    state = np.arange(5).astype(np.float64).reshape((1, -1))
    state = agent.act(state)
    np.isfinite(state)
    return state

scores = ddpg()

#with tf.device("/gpu:0"):
#    scores = ddpg()
#    print("run is successful")

Exception:

WARNING: Logging before flag parsing goes to stderr.
W0503 18:53:51.962915<PHONE_NUMBER>53408 tf_logging.py:161] Entity <method-wrapper '__call__' of numpy.ufunc object at 0x5594ba8c9580> could not be transformed and will be staged without change. Error details can be found in the logs when running with the env variable AUTOGRAPH_VERBOSITY >= 1. Please report this to the AutoGraph team. Cause: Object conversion is not yet supported. If you are trying to convert code that uses an existing object, try including the creation of that object in the conversion. For example, instead of converting the method of a class, try converting the entire class instead. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/README.md#using-the-functional-api for more information.
Traceback (most recent call last):
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 369, in converted_call
    experimental_partial_types=partial_types)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 513, in to_graph
    arg_values, arg_types)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/conversion.py", line 196, in entity_to_graph
    'Object conversion is not yet supported. If you are '
NotImplementedError: Object conversion is not yet supported. If you are trying to convert code that uses an existing object, try including the creation of that object in the conversion. For example, instead of converting the method of a class, try converting the entire class instead. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/README.md#using-the-functional-api for more information.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/media/seagull/use_me/seagull/github/DDPG/ddpg-pendulam/ddpg_agent_tf.py", line 43, in <module>
    scores = ddpg()
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 426, in __call__
    self._initialize(args, kwds, add_initializers_to=initializer_map)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 370, in _initialize
    *args, **kwds))
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1313, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1580, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 1512, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 694, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py", line 317, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py", line 686, in wrapper
    ), args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 392, in converted_call
    result = converted_f(*effective_args, **kwargs)
  File "/tmp/tmp4fw9we40.py", line 8, in tf__ddpg
    ag__.converted_call('isfinite', np, ag__.ConversionOptions(recursive=True, verbose=0, strip_decorators=(tf.function, defun_2, ag__.convert, ag__.do_not_convert, ag__.converted_call), force_conversion=False, optional_features=(), internal_convert_user_code=True), (state,), {})
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 390, in converted_call
    return _call_unconverted(f, args, kwargs)
  File "/miniconda3/envs/rl/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py", line 188, in _call_unconverted
    return f(*args, **kwargs)
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

Could you share how U solve the W501 issue? Appreciated.

Closing this out since I understand it to be resolved, but please let me know if I'm mistaken. Please open a new ticket if the issue persists again. Thanks!


Prefixes not showing in chat

Hi
I am trying to make groups have prefixes on my server but they will not display in chat
I have Vault and EssentialsX chat
I have LuckPerms 4.1.25 and EssentialdXChat <IP_ADDRESS>

Can you give some example screenshots?
What's the output of /lp user <you> info - do the correct prefixes / suffixes show?
What steps have you already taken to try to diagnose/resolve the issue?

I have checked vault like it says and vault says LuckPerms is active and I have seen if I need to add a placeholder which I seems I don’t. I have tried updating both plugins to

I am sorry if this inconveniences you but I have to leave right now I will be back tomorrow though. Sorry

Most likely an issue with your Essentials config then.
Make sure add-prefix-suffix is set to true, and that your chat format is configured correctly.


OpaqueData field shall conform to the selected opaque data format in OtherParamsSelection.

Currently there is no format check for OpaqueData Field in CHALLENGE_AUTH response message, MEASUREMENTS response message and GET_CSR request message.

Refer to paragraph 353 Table 36 — Successful CHALLENGE_AUTH response message format in
https://www.dmtf.org/sites/default/files/standards/documents/DSP0274_1.2.1.pdf
OpaqueData Field:
The Responder can include Responder-specific information and/or
information that its transport defines. If present, this field shall
conform to the selected opaque data format in
OtherParamsSelection .

Refer to paragraph 806 in
https://www.dmtf.org/sites/default/files/standards/documents/DSP0274_1.2.1.pdf
If the OpaqueDataFmt1 bit is selected in OtherParamsSelection of ALGORITHMS , then all opaque data fields in SPDM messages shall use the format that Table 92 — General opaque data format defines.

What can be checked?

What can be checked?

For example,
Refer to paragraph 808 Table 93 — Opaque element defines the format for each element in OpaqueList.

ID Field: Shall be one of the values in the ID column of Table 50 — Registry or standards body ID.

Need add check if ID Field is one of the values  in the ID column of Table 50 — Registry or standards body ID.

AlignPadding Field: If 4 + VendorIDLen + OpaqueElementDataLen does not fall on a 4-byte boundary, this field shall be present and of the correct length to ensure 4 + VendorIDLen +OpaqueElementDataLen + AlignPaddingSize is a multiple
of 4. The value of this field shall be all zeros and the size of this field shall be 0, 1, 2 or 3.

Need add check if 4 + VendorIDLen + OpaqueElementDataLen fall on a 4-byte boundary.


Update TextInput component

Fixes https://github.com/MLH-Fellowship/react-native/issues/59
Summary
The PR is part of an effort to update the code comments to match the current documentation on the React Native website. The project is a part of the MLH Fellowship program and involves the automatic generation of the website docs from code comments and flow types as the end result.
To learn more about the project you can visit the project wiki:

Project Details
RN Docs Standards

Link to the documentation(the source of truth):

textinput.md

Changes

Update the title and prop description from docs.
Remove unnecessary * from the code comments.
Add Snack player example specified in the docs to the code comments as JSDoc.
Add @type annotation to parse supported datatype by the prop.
Add @platform annotation to specify platforms supported by a prop.
Add @default annotation to parse default value of prop.

Changelog
[Internal]
Test Plan
All changes are made to the code comments and thus there is no need for testing.
Reviewed by @jevakallio

Thanks for this contribution, @ani4aniket, and apologies for not getting around to it until now. This MLH-Fellowship project has been abandoned so we're going to close this PR to focus on active ones. If you feel this is an error or if you'd like to pick this up again, please let me know!


WIP: Move type field into special key, make Enums correctly typed.

There's a baste bug that's blocking this right now related to typeKey being imported twice. Once that's fixed, I can start porting enum values to use this system

Coverage decreased (-0.4%) to 97.437% when pulling fa6360a788ea7b85fe6e3175c0b60f91ae47c0e4 on fix-enums into e0fbc2581454024f160bfd2f84553c7fe74b980b on master.

Moving ahead with this despite the coverage decrease.


bootstrap : TabError: inconsistent use of tabs and spaces in indentation

Hi,
a small typo apparently in script/lib/util.py : a tab should be replaced by 4 spaces.
Traceback (most recent call last):
  File "./script/bootstrap", line 8, in <module>
    import lib.util as util
  File "/home/pronecker/src/libchromiumcontent/script/lib/util.py", line 76
    vsvarsall = "C:\\Program Files (x86)\\Microsoft Visual Studio {0}\\VC\\vcvarsall.bat".format(vs_version)

Can you please create a PR with a fix?

Hey there,
It's been a long time coming but the libchromiumcontent repository is being archived as it is no longer used in the Electron build system (🎉 this is a good thing).
If your issue is still relevant to Electron in it's current build system (please verify first) then you should probably raise a similar issue on electron/electron.
Thanks 😄


Setting a datasource with any method throws TypeError on 1.9.2

Just tried to add a datasource with any method to the grid options and this is the error message shown:
Using ready():
TypeError: Cannot read property 'setDatasource' of null
    at Grid.setDatasource (grid.js:202)
    at Object.Grid.addApi.api.setDatasource (grid.js:512)

Setting datasource property before grid is initialized:
TypeError: Cannot read property 'setDatasource' of null
    at Grid.setDatasource (grid.js:202)
    at new Grid (grid.js:77)

Using onNewDatasource():
TypeError: Cannot read property 'setDatasource' of null
    at Grid.setDatasource (grid.js:202)
    at Object.Grid.addApi.api.onNewDatasource (grid.js:515)

I can confirm that this error happens when the dontUseScrolls: true option is used. Any idea why the pagination controller is not initialized when this option is used?
if (useScrolls) {
    paginationController = new PaginationController();
    paginationController.init(this.ePagingPanel, this, gridOptionsWrapper);
}

you can't do paging when 'dontUseScrolls', it's not supported.
the dontUseScrolls is intended for printing a grid (i'm going to change it's name soon), the grid is laid out differently. so you just can't do datasource things when in print mode.


[bug] switch network does not redirect to metamask

Is there an existing issue for this?

[X] I have searched the existing issues

RainbowKit Version
0.12.5
wagmi Version
0.12.2
Current Behavior
network switch does not redirect to metamask
Expected Behavior
network switch redirect to metamask
Steps To Reproduce
No response
Link to Minimal Reproducible Example (CodeSandbox, StackBlitz, etc.)
No response
Anything else?
No response

I believe we fixed this with https://github.com/rainbow-me/rainbowkit/pull/1145. Just released as 0.12.7. Let me know if you're still experiencing the issue.