updateClassifiers does not respect Ivy configuration mappings

When a dependency uses non-standard configurations, and does not have a "compile" configuration, it is possible to include it in libraryDependencies using a configuration mapping like this
libraryDependencies += "ossjava" % "freemarker" % "2.3.19" % "compile->runtime"

(This is a private library available on a filesystem resolver, so don't look for it on the Web)
This makes the "update" task work. However, "updateClassifiers" does not seem to detect the Ivy configuration mapping and still looks for "compile" and fails
This is the ivy.xml that is looked up by the filesystem resolver, you'll notice it has only "runtime" nothing else
<?xml version="1.0" encoding="UTF-8"?>
<ivy-module version="2.0" xmlns:extra="http://ant.apache.org/ivy/extra">

  <info organisation="ossjava" module="freemarker" revision="2.3.19">
  </info>

  <configurations>
    <conf name="runtime" description="Core runtime dependencies"/>
  </configurations>

  <publications>
    <artifact name="freemarker-2.3.19" type="src" ext="src.jar" conf="runtime"/>
    <artifact name="freemarker-2.3.19" type="jar" ext="jar" conf="runtime"/>
  </publications>

  <dependencies/>

</ivy-module>

Finally, this is the message that SBT provides:
[info] Resolving org.fusesource.jansi#jansi;1.4 ...
[warn]  ::::::::::::::::::::::::::::::::::::::::::::::
[warn]  ::          UNRESOLVED DEPENDENCIES         ::
[warn]  ::::::::::::::::::::::::::::::::::::::::::::::
[warn]  :: ossjava#freemarker;2.3.19: configuration not found in ossjava#freemarker;2.3.19: 'default(compile)'. Missing configuration: 'compile'.  Missing configuration: 'compile'. It was required from default#a$sources_javadoc_2.10;0.1-SNAPSHOT test-internal

Here is a way to test this.
Add this to build.sbt
resolvers += new RawRepository({
    val res = new org.apache.ivy.plugins.resolver.FileSystemResolver
    res.setName("fake-lib")
    res.addIvyPattern("/tmp/brunon/fake-lib/ivy-[module]-[revision].xml")
    res.addArtifactPattern("/tmp/brunon/fake-lib/lib/[artifact](.[classifier]).[ext]")
    res
})

Then create the ivy.xml file in that directory, and put any kind of JAR file there
> find /tmp/brunon/fake-lib -type f
/tmp/brunon/fake-lib/ivy/ivy-freemarker-2.3.19.xml
/tmp/brunon/fake-lib/lib/freemarker-2.3.19.jar

:+1:

I have tested this with SBT 0.13.9 and then tried all previous versions all the way to 0.13.0, same behavior. This is not a new bug it seems.

Further note: the problem occurs only if the ivy.xml file does not have a configuration called default
Look at this for an example of the problem: https://github.com/vladimir-lu/sbt-runtime-conf-issue

Here's another reproduction using sbt.
producer/
build.sbt
val fooFile = taskKey[File]("sample artifact")
val RuntimeX = config("runtime")

lazy val root = (project in file(".")).
  settings(
    name := "classifier-test",
    organization := "com.example",
    version := "0.1-SNAPSHOT",
    fooFile := { baseDirectory.value / "foo.txt" },
    addArtifact( Artifact("classifier-test", "text", "txt", "runtime"), fooFile),
    ivyConfigurations := Seq(RuntimeX, Configurations.ScalaTool),
    publishArtifact in Compile := false,
    publishArtifact in Test := false,
    publishMavenStyle := false,
    autoScalaLibrary := false,
    crossPaths := false
  )

foo.txt
foo

client/
build.sbt
lazy val root = (project in file(".")).
  settings(
    name := "classifier-test-consumer",
    libraryDependencies += "com.example" % "classifier-test" % "0.1-SNAPSHOT" % "compile->runtime"
  )

steps

In producer/, run sbt publishLocal. This publishes a module that only has runtime configuration.
In client/, run sbt updateClassifiers.

problems
[info] Set current project to classifier-test-consumer (in build file:/Users/eugene/work/quick-test/sbt-2264/consumer/)
[info] Resolving org.fusesource.jansi#jansi;1.4 ...
[warn] 	::::::::::::::::::::::::::::::::::::::::::::::
[warn] 	::          UNRESOLVED DEPENDENCIES         ::
[warn] 	::::::::::::::::::::::::::::::::::::::::::::::
[warn] 	:: com.example#classifier-test;0.1-SNAPSHOT: configuration not found in com.example#classifier-test;0.1-SNAPSHOT: 'default(compile)'. Missing configuration: 'compile'. It was required from classifier-test-consumer#classifier-test-consumer$sources_javadoc_2.10;0.1-SNAPSHOT test-internal
[warn] 	::::::::::::::::::::::::::::::::::::::::::::::

/cc @Duhemm

The likely culprit is https://github.com/sbt/sbt/blob/0.13.9/ivy/src/main/scala/sbt/UpdateReport.scala#L35:
private[this] def addConfiguration(mod: ModuleID): ModuleID = if (mod.configurations.isEmpty) mod.copy(configurations = Some(configuration)) else mod

ok, it looks like these three commits have to be cherry picked onto 0.13.9. @eed3si9n @Duhemm am I missing anything?
#9120e4c #3442ae2 #480ea22

@fommil This was originally fixed on 0.13 branch, and it'll be part of 0.13.10.

@eed3si9n yeah, but I need to cherry pick onto an in-house 0.13.9 build.

Then you probably need all commits on #2297

@eed3si9n cool, got them. That seems to work for some simple manual testing, thanks! :smile:


fix: omit tests package

caused by https://github.com/googleapis/python-resource-manager/pull/62/commits/8fa2ec41d6ab4cf4975b2663afcd86fe40256d20
Apoligies if I'm missing something: I'm not entirely sure why the local packages/namespaces are still being generated but then discarded for the actual setuptools.setup.
Thank you for opening a Pull Request! Before submitting your PR, there are a few things you can do to make sure it goes smoothly:

[x] Make sure to open an issue as a bug/issue before writing your code!  That way we can discuss the change, evaluate designs, and agree on the general idea
[x] Ensure the tests and linter pass
[x] Code coverage does not decrease (if any source code was changed)
[x] Appropriate docs were updated (if necessary)

Fixes #194 🦕

Thanks for reporting and fixing this issue @s22chan !


JSON Forms support

Implement additional UI for Girder that would support JSON-editor compatible forms. Required features:

Ability to easily add new / edit existing forms
Store input provided via forms as database entries
Allow to upload multiple files / folder via forms
Associate metadata (e.g. sample Id) with data inputted via a form
Sync data with GDrive

First production version of the plugin deployed @ data.htmdec.org on Apr 30, 2024.


Mod causes HAN-D's drones to not work on allies

Not a bug, but it removes HAN-D's ability to heal others with his drones, so I feel like it's notable. The drones seem to rely on collision with an ally/enemy to do their thing. It would be good if an exception could be made for HAN-D's drones.

Thanks for the report, not going to promise anything since it seems like a pretty minor issue. And if it's a big deal you can always just disable this mod instead. I'll probably look into it if I end up updating the mod sometime.

This should now be possible to fix via the config in version 1.1.0.
Please re-open if this is not the case


Run tests on node 8,10,12

#181

Codecov Report

Merging #185 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #185   +/-   ##
=======================================
  Coverage   99.26%   99.26%
=======================================
  Files          14       14
  Lines         409      409
=======================================
  Hits          406      406
  Misses          3        3

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@purplecabbage Thanks for the help on this!


Update README.md to include safe: server option required for include …

Hi @shishkin, Thank you for creating this Asciidoc integration for Astro.
Small PR:
I propose to add the safe: "server" option to integration settings, as that is required for the include::[] directive to work, which is shown in the demo file. Also added file path as comments to make it unambiguous.
Looking forward to explore further with this.

Thanks @arnoan and sorry for this taking so long.


Update the entry point of the crate documentation

Explain some common use cases for this crate.
Show better examples.
Show the new serde_as annotation.

bors r+


Add sha checksum functionality

As a developer
I would like to know that software I’m downloading is what I expect
So that I am confident I’m not installing any old rubbish

Works for me :+1:


Strange memory consumption, that is slowly increasing

GORM Playground Link
https://github.com/go-gorm/playground/pull/161
Description
I am using Gorm a lot (v1, now v2), but I spot something, that attracted my attention. My services are very slowly, but steadily, consuming more and more memory. I dig deeper and removed code one thing after another. At the end I was left just with one function, that repeatedly downloads data from database.
So after that I minimize that function to not download anything, just open and close the connection.
Then I made a simple program, that only opens the connection and closes.
See attached gif that show this behavior and two screenshots that show the memory increase after a while.
The memory is increasing not constantly, looks like at logarithmic scale, but is increasing still.
Maybe I am doing something wrong, but I did not found anything wrong with the code.
And yes, I need to open and closes connections as I need. I cannot opens - in my real program - one connection at the beginning and then reuse it everywhere.

Hello,
I have tested it pprof and used GODEBUG=gctrace=1 to test the program, seems no leak happened, so this should not a GORM issue.
Thank you.

also tested with sqlDB, err := sql.Open("mysql", dbDSN), got same issue, seems like golang doesn't release the memory to OS or the OS just haven't take the memory from the go application yet.

meanwhile I found out that, when manually calling garbage collector with runtime.GC() before the end of the loop, the memory DOES NOT increases that fast.
It increases still... looks like... but at a very very very low speed.
I tested it for about 5 hours and it looks like it hit the limit above which it does not increase. Maybe I let it run for a weekend to confirm this.
But from this observation, the "problem" may be with garbage collector, maybe not collecting properly those database connections, or maybe collecting them at somewhat slow or strange speed (collecting them at slower rate that new are made - but that does not make sense to me).
Also I made a different test: as I am using postgres, I tested this postgres driver: https://github.com/jackc/pgx.
Similar results.
And also this library: github.com/lib/pq gave me similar results.
So this is obviously not the case of gorm, but something different.
Do you think I should raise an issue directly to go?

I have the same issue @petrjahoda also using postgres.
It takes about 8GBs of RAM in my case ...
I will try runtime.GC().

same error here, looks like driver is doing something wrong, after 100k calls, the process was taking around 1GB of RAM and didn't release memory

@SbstnErhrdt https://github.com/jackc/pgx/issues/845#issuecomment-1050465698


Sentry CLI Failing - Proposition for env variable to disable telemetry

Describe the bug
Sentry CLI causing Failed Builds.
Sentry CLI API request failing because of SSL peer certificate or SSH remote key was not OK.
This happens in the image building process of docker at Stage 7/7 RUN pnpm build
Output log of this stage:
#0 3.523
#0 3.523 ><EMAIL_ADDRESS>build /app
#0 3.523 > next build
#0 3.523
#0 4.359 warn  - You have enabled experimental features (legacyBrowsers, browsersListForSwc) in next.config.mjs.
#0 4.359 warn  - Experimental features are not covered by semver, and may cause unexpected or broken application behavior. Use at your own risk.
#0 4.359
#0 4.599 Attention: Next.js now collects completely anonymous telemetry regarding usage.
#0 4.600 This information is used to shape Next.js' roadmap and prioritize features.
#0 4.600 You can learn more, including how to opt-out if you'd not like to participate in this anonymous program, by visiting the following URL:
#0 4.600 https://nextjs.org/telemetry
#0 4.600
#0 5.137 info  - Linting and checking validity of types...
#0 14.94
#0 14.94 ./src/pages/index.jsx
#0 14.94 123:6  Warning: React Hook useEffect has a missing dependency: 'nextauth.user'. Either include it or remove the dependency array.  react-hooks/exhaustive-deps
#0 14.94
#0 14.94 info  - Need to disable some ESLint rules? Learn more here: https://nextjs.org/docs/basic-features/eslint#disabling-rules
#0 15.01 info  - Creating an optimized production build...
#0 55.41 Failed to compile.
#0 55.41
#0 55.41 Sentry CLI Plugin: Command failed: /app/node_modules/.pnpm/@sentry+cli@1.74.5/node_modules/@sentry/cli/sentry-cli releases new wGc6VlB6l9Br9FQAYwq7F
#0 55.41 error: API request failed
#0 55.41   caused by: [60] SSL peer certificate or SSH remote key was not OK (SSL certificate problem: unable to get local issuer certificate)
#0 55.41
#0 55.41 Add --log-level=[info|debug] or export SENTRY_LOG_LEVEL=[info|debug] to see more output.
#0 55.41 Please attach the full debug log to all bug reports.
#0 55.41
#0 55.41 Sentry CLI Plugin: Command failed: /app/node_modules/.pnpm/@sentry+cli@1.74.5/node_modules/@sentry/cli/sentry-cli releases new wGc6VlB6l9Br9FQAYwq7F
#0 55.41 error: API request failed
#0 55.41   caused by: [60] SSL peer certificate or SSH remote key was not OK (SSL certificate problem: unable to get local issuer certificate)
#0 55.41
#0 55.41 Add --log-level=[info|debug] or export SENTRY_LOG_LEVEL=[info|debug] to see more output.
#0 55.41 Please attach the full debug log to all bug reports.
#0 55.41
#0 55.41
#0 55.41 > Build failed because of webpack errors

Proposition to also have an environment variable for disabling telemetry.
Reproduction
Cloning Repo > Setting Environment Variables > docker compose up > FAILING IN BUILDING
System Info
System:
    OS: Linux 5.4 Debian GNU/Linux 11 (bullseye) 11 (bullseye)
    CPU: (8) x64 Intel(R) Xeon(R) CPU E5-1650 v3 @ 3.50GHz
    Memory: 13.25 GB / 20.00 GB
    Container: Yes
    Shell: 5.1.4 - /bin/bash
  Binaries:
    Node: 16.17.0 - ~/.nvm/versions/node/v16.17.0/bin/node
    npm: 8.15.0 - ~/.nvm/versions/node/v16.17.0/bin/npm

Used Package Manager
pnpm
Validations

[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Check that this is a concrete bug. For Q&A, please open a GitHub Discussion instead.
[X] The provided reproduction is a minimal reproducible of the bug.

I forked this repository and manually removed all sentry-related functions. As I use Docker/Docker Swarm I just log to the console.
Unfortunately, I have two other errors and I created Issues for that.
After they are solved I will commit my fork.

Until this gets fixed, here is a temporal workaround.

Sorry just saw this now! Fixed in the latest commit on main :+1:


concerning the late connect method(schemaBuilder.connect()) after applying Windows Update

【environment】
Windows 8.1
Memory 4 GB
CPU 3.59 GHz
lovefield 2.1.9
Browser IE 11 updated version: 11.0.56 (KB 4092946), 11.0.60 (KB 4103768)
【An event】
After applying the Windows Monthly Update in April, May 2018, execute the connect method(schemaBuilder.connect()) and add it to IndexDB
It took about 5 to 8 seconds to connect.
In my environment / system, there are three tables in the DB connected by the connect method(schemaBuilder.connect()).
About 4,500 of them (capacity 3 MB) are stored in one table among them.
Before the monthly update in April 2018 (11.0.49) it took only 1-2 seconds.
Why did the connect(schemaBuilder.connect()) method take time?
【Supplement】
Even raising the version of lovefield(2.1.10, 2.1.11, 2.1.12) did the same.
I confirmed the operation with Chrome (67.0), it took about 1 second.

Not sure if we will support Windows 8 and Internet Explorer in the near future. Can you try on Windows 10 and Edge? As you mentioned, modern browsers like Chrome takes just 1 second to run. Performance-wise, there is very little we can do if Microsoft already gave up on their old platform/browser.

I'm sorry I have not received a reply.
Since the system that I am creating is mainly used from Windows 8 and IE 11,
It is meaningless to check the operation with Edge.
I think that it takes time to connect by bulk loading.

After that, the table created by lovefield will have id as the primary key,
Is it possible to rewrite id to an arbitrary value?
Because id is the primary key, you can use the IndexedDB API to create a table created with lovefield
When searching, it will be a full scan.

It's not as simple as people often think "lazy load". It's designed so for a reason: JavaScript does not provide locking, the only thing we have is the guarantee of single thread accessing heap. As a result, to provide long-living transactions, we MUST load everything upfront.
As to the primary key, that's your schema's issue. Lovefield let you specify what to index and that's not necessarily be id. What you see id is our internal data structure. Because we are bulk loading no matter what, IndexedDB indexing is irrelevant.
Also, IE11 IndexedDB performance is not great either. Please consider using Chrome or upgrade to Window 10. As I mentioned earlier, there's no way for a JavaScript library to make up the speed of an abandoned Microsoft product. IE 11 will be slow one way or the other.


Does the tensorflow support structured numpy array as inputs?

data = np.array([(1,2.), (2,3.)],dtype=[('foo', 'i4'),('bar', 'f4')])
I want to feed this into
x = tf.placeholder("float", [None,2])
Will the tensorflow automatically convert they datatypes?

At present, TensorFlow only supports primitive NumPy datatypes. If you need to represent a tensor of a tuple of values, you can instead use a (Python) tuple of tensors (see e.g. the tf.QueueBase documentation for an example).


MissingTargetFrameworkException

I got exception when install AutoT4MVC on Windows 10.
02.05.2015 09:17:47 - Microsoft VSIX Installer
02.05.2015 09:17:47 - -------------------------------------------
02.05.2015 09:17:47 - Initializing Install...
02.05.2015 09:17:48 - Extension Details...
02.05.2015 09:17:48 - 	Identifier      : c676817c-46cc-47d3-b03c-8a05f499d4a5
02.05.2015 09:17:48 - 	Name            : AutoT4MVC
02.05.2015 09:17:48 - 	Author          : Bennor McCarthy
02.05.2015 09:17:48 - 	Version         : 1.5.2
02.05.2015 09:17:48 - 	Description     : An extension for Visual Studio which automatically runs your T4MVC templates at build time and when you create/remove/rename/save a file that T4MVC cares about.
02.05.2015 09:17:48 - 	Locale          : en-US
02.05.2015 09:17:48 - 	MoreInfoURL     : http://bennor.github.io/AutoT4MVC/
02.05.2015 09:17:48 - 	InstalledByMSI  : False
02.05.2015 09:17:48 - 	SupportedFrameworkVersionRange : [4.5]
02.05.2015 09:17:48 -
02.05.2015 09:17:48 - 	Supported Products :
02.05.2015 09:17:48 - 		Microsoft.VisualStudio.Pro
02.05.2015 09:17:48 - 			Version : [11.0,14.0]
02.05.2015 09:17:48 - 		Microsoft.VisualStudio.Premium
02.05.2015 09:17:48 - 			Version : [11.0,14.0]
02.05.2015 09:17:48 - 		Microsoft.VisualStudio.Ultimate
02.05.2015 09:17:48 - 			Version : [11.0,14.0]
02.05.2015 09:17:48 -
02.05.2015 09:17:48 - 	References      :
02.05.2015 09:17:48 -
02.05.2015 09:17:48 - Searching for applicable products...
02.05.2015 09:17:48 - Found installed product - Microsoft Visual Studio 2010 Shell - Integrated Mode
02.05.2015 09:17:48 - Found installed product - Microsoft Visual Studio Premium 2013
02.05.2015 09:17:49 - The extension with ID 'c676817c-46cc-47d3-b03c-8a05f499d4a5' is not installed to Microsoft Visual Studio Premium 2013.
02.05.2015 09:17:49 - Found installed product - Microsoft Visual Studio Professional 2013
02.05.2015 09:17:49 - Found installed product - Microsoft Visual Studio 2013 Shell (Integrated)
02.05.2015 09:17:49 - Found installed product - Global Location
02.05.2015 09:17:49 - Found installed product - ssms
02.05.2015 09:17:50 - The following target products have been selected...
02.05.2015 09:17:50 - 	Microsoft Visual Studio Premium 2013
02.05.2015 09:17:50 -
02.05.2015 09:17:51 - Beginning to install extension to Microsoft Visual Studio Premium 2013...
02.05.2015 09:17:51 - Install Error : Microsoft.VisualStudio.ExtensionManager.MissingTargetFrameworkException: The extension 'AutoT4MVC' requires a version of the .NET Framework that is not installed.
at Microsoft.VisualStudio.ExtensionManager.ExtensionManagerService.CheckForValidDotNetFramework(IExtension extension)
at Microsoft.VisualStudio.ExtensionManager.ExtensionManagerService.CheckForInstallBlockers(InstallableExtensionImpl extension, IInstalledExtensionList modifiedInstalledExtensionsList, Boolean isNestedExtension, Boolean& olderVersionInstalled)
at Microsoft.VisualStudio.ExtensionManager.ExtensionManagerService.InstallInternal(InstallableExtensionImpl extension, Boolean perMachine, Boolean isNestedExtension, IDictionary2 extensionsInstalledSoFar, List1 extensionsUninstalledSoFar, IInstalledExtensionList modifiedInstalledExtensionsList, AsyncOperation asyncOp, UInt64 totalBytesToWrite, UInt64& totalBytesWritten)
at Microsoft.VisualStudio.ExtensionManager.ExtensionManagerService.BeginInstall(IInstallableExtension installableExtension, Boolean perMachine, AsyncOperation asyncOp)
at Microsoft.VisualStudio.ExtensionManager.ExtensionManagerService.InstallWorker(IInstallableExtension extension, Boolean perMachine, AsyncOperation asyncOp)

Will look into it soon. Are you able to tell me which versions of the .NET framework are installed on Win 10?

I wasn't able to reproduce it (with VS 2015 RC Community Edition on Windows 10 Insider Preview), but I think I've found a solution. Can you try installing the VSIX, from https://github.com/bennor/AutoT4MVC/releases/tag/v1.5.2 and let me know if it works.

Hi,
I removed Windows 10 from my PC because I had many problems with AutoT4MVC, Telerik, WinRT symulator, etc.
Thanks for your reply.
P.S. AutoT4MVC is great tool for me:)
Miroslaw Slanda
Poland

Od: Bennor McCarthy<EMAIL_ADDRESS>Wysłano: 9 maja 2015 05:38
Do: bennor/AutoT4MVC
DW: Slanda, Miroslaw WSK
Temat: [External] Re: [AutoT4MVC] MissingTargetFrameworkException (#15)
I wasn't able to reproduce it (with VS 2015 RC Community Edition on Windows 10 Insider Preview), but I think I've found a solution. Can you try installing the VSIXhttps://github.com/bennor/AutoT4MVC/releases/download/v1.5.2/AutoT4MVC.vsix, from https://github.com/bennor/AutoT4MVC/releases/tag/v1.5.2 and let me know if it works.
—
Reply to this email directly or view it on GitHubhttps://github.com/bennor/AutoT4MVC/issues/15#issuecomment-100420751.


noTimes flag is set but never used

Fixed by @tatsushid with Pull Request #1657 in commit e989468.


fixed #827

Description of the change:
Added -update flag to sync the Gopkg.toml toGopkg.lock.
Motivation for the change:
The Gopkg.toml does NOT sync to Gopkg.lock automatically. Correct me if I'm wrong.
But, it will take more time to run if we add this -update flag.
Any comments are welcome！

Closes #827

Yes you are right according to the docs:
   -update       update the named dependencies (or all, if none are named) in Gopkg.lock to the latest allowed by Gopkg.toml (default: false)

Weird thing is that dep ensure -v works fine for me, so maybe we can add this as another make target and mention it in the docs, for example make dep-update. WDYT?

@jianzhangbjz I'd rather not use -update in make dep because it has side effects not apparent to users. We keep Gopkg.lock up to date by pushing revendor commits, so Gopkg.lock on master has been confirmed to work by CI,  and by myself and @LiliC locally. I'm fine with make dep-update.

@LiliC @estroz Thank you for your suggestion! Added make dep-update per your comments, please have a review!


Code refactoring of compiler with promises and async/await

Codecov Report

Merging #182 into master will increase coverage by 0.23%.
The diff coverage is 96.82%.

@@            Coverage Diff             @@
##           master     #182      +/-   ##
==========================================
+ Coverage   98.18%   98.41%   +0.23%
==========================================
  Files          62       62
  Lines        2310     2340      +30
==========================================
+ Hits         2268     2303      +35
+ Misses         42       37       -5

Impacted Files
Coverage Δ

...li-commands/compiler/etherlime-compile/profiler.js
100% <100%> (+0.62%)
:arrow_up:

...i-commands/debugger/etherlime-debug-utils/index.js
100% <100%> (ø)
:arrow_up:

...mands/compiler/etherlime-contract-sources/index.js
100% <100%> (ø)
:arrow_up:

cli-commands/compiler/etherlime-compile/parser.js
100% <100%> (ø)
:arrow_up:

cli-commands/flattener/flatten.js
100% <100%> (ø)
:arrow_up:

cli-commands/debugger/repl.js
100% <100%> (ø)
:arrow_up:

cli-commands/compiler/etherlime-resolver/npm.js
100% <100%> (ø)
:arrow_up:

cli-commands/compiler/etherlime-config/index.js
100% <100%> (ø)
:arrow_up:

cli-commands/debugger/index.js
100% <100%> (ø)
:arrow_up:

cli-commands/compiler/etherlime-resolver/index.js
100% <100%> (ø)
:arrow_up:

... and 12 more

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Paper 11b: The Swarm at the Edge of the Cloud

Reviewer: Alvaro Albero
Review Type: Analytical
Problem Domain
There is an increasing number of embedded devices that are connecting the cyber and the physical world. But so far these devices have been working as independent components instead of seamlessly integration.
Main Contributions
The authors propose a platform to wrap these devices and provide a way to deploy and operate them, they use the term tera-swarm. They use as a reference the mobile platform and they want to achieve a similar system to bring millions of developers to this platform where they can create and deploy applications, called swarmlets, that will recruit resources such as sensors or actuators from the swarm.
Questions

In Section C4, they talked about applications being dynamically composed and recomposed and they mention that optimizations cannot be done at design time, must be done at run time. What do they mean with this? Why is it different here than in other systems?

How will the swarmOS be able to interface with all the types of embedded devices and cloud providers in order to have a unique platform? Are they expecting everyone to accept and migrate to their solution?

This is a paper from 2014 where they are providing their vision. What has been the progress since then? Has this project kept evolving? Is work still being done in this direction or workshops like the one in 2013 still taking place?

Critiques

They make a comparison to the mobile ecosystem and say that they want to create a similar platform. I think that the way iOS and Android became the dominant platforms in the mobile world was not through decided or organized top down. Developers and consumers naturally moved towards those platforms because they were offering a better experience. This paper looks more like a top down organization where they explain that we should all move towards this one platform that does not exist yet.

They talk about this swarm where all embedded devices are interconnected and a swarmOS that controls the services and resources provided to swarmlets. This looks dangerous to me, you have this unique network that has access to all the imaginable sensors, actuators, etc. and you expose them through an OS to all the applications (swarmlet) that anyone can build. I feel this could be a huge platform with huge potential to do good things, but also bad things, and you are giving all this power to random developers and organizations without knowing what they will use it for.

Reviewer: Ratnadeep Bhattacharya
Review Type: Comprehension
Problem Domain
The boundary between the cyber and the physical world is becoming hazier due to the sheer number of sensors and actuators embedded in the physical world. The authors argue that this presents an opportunity to provide mega-scale services that involve multiple vendors and dynamic use of resources and available data.
Main Contributions
The authors list out the challenges towards this goal and make a strong case for a "SwarmOS", an all encompassing framework that includes the cloud backbone, the various sensors and actuators, all available data and data models. A further case is argued about seemingly uncontrolled access to all these resources by vendors aiming to provide these services. The paper then goes on to list challenges, possible technologies and research directions to solve those challenges and applications that could result.
Questions
In C2, the authors mention that virtualization of computing resources is not against real-time or time-sensitive services but more work is required to manage the quality of service in networks and temporal isolation is required in processors. I am not quite sure what exactly is meant by this. An example might have helped!
Critique

I am paranoid as far as the Internet and related privacy violations. As such this paper sends shivers down my spine. The sheer opportunity for privacy and security violations that could be created through the indiscriminate sharing of data with little control is scary. I don't think the paper addresses this subject in any seriousness.
The paper is sort of a "vision" paper and as such does not treat any particular topic to any depth. Their references section too is pretty thin and there are not many opportunities to dive down deeper in the context of this paper.

Contributor: Greg Kahl
Review Type: Comprehensive
Problem
There are more and more edge sensors and embedded systems being implemented in order to improve quality of life and collect data. However, these sensors and small systems are not all connected for an efficient use of the vast amount of data they are collecting.
Contribution
This paper suggest their TerraSwarm system to connect and manage all of these small devices on the system. They believe it will be a platform for future development to help bring all of the devices together for a better use and processing of the huge amount of data these edge sensors collect.
Questions
1 - They claimed that data doesn't need to be communicated or stored if they can predict it with models. What does this mean? How is the data useful if you are never actually using it and just trying to predict it?
2 - They discuss the use of the platform for autonomous vehicles, but I felt like they didn't really explain scheduling and critical systems such as cars on such a large system. How would they handle that to ensure the safety of the users?
3 - As we have read about in many other papers, security on the edge devices is very important. They briefly brush this off by saying they will develop energy efficient hardware support for security features what does this mean?

Reviewer: Niko Reveliotis
Review Type: Comprehension
Problem Being Solved
With the rise of IoT devices, there has been a "swarm" of sensors and actuators being introduced to these devices. The paper describes these sensors and actuators giving the cloud "eyes, ears, hands, and feet". This paper introduces "swarmlets" which will try to guarantee secure and proper operation of these sensors through an open and universal platform.
Main Contributions

TerraSwarm/"swarmlet" application tools/framework, named SwarmOS, which provide the ability to "dynamically recruit resources such as sensors, communication networks, computation, and information from the cloud; to aggregate and use that information to make or aid decisions; and then to dynamically recruit actuation resources — mediating their response by policy, security, and privacy concerns."

Three Questions

How would SwarmOS be able to get the market-share of both sensors and the cloud to become a player in the game? How do they expect to get everyone on board?
What tools are they referring to in needing to blur the distinction between "design time" and "run time"?
Were there any real-world test runs of these swarmlets conducted? They discuss possible applications of SwarmOS, but has this been extended into another paper with real-world testing?

Reviewer: Sam Hanna
Review Type: Critical
Problem Being Solved:
This paper talked about what could be accomplished if all of the IoT sensors and devices could be combined into the TerraSwarm. Currently, all IoT devices are disconnected and doing different projects for different purposes. They ask the questions of what could be accomplished if all IoT devices could be utilized to solve problems.
Important Areas:
This paper focuses on the idea of a TerraSwarm. This would focus on utilizing swarms and swarmlets in order to create more of a smart-city environment. They would create and utilize SwarmOS, a stable base operating system, in order to have access to all nodes and optimize the use of the swarms.
Questions:

If there are two nodes providing conflicting information, how does it choose which one to believe?
They mention briefly security being built in from the start, what steps are they taking to ensure that this can’t get hacked or a malicious application (swarmlet) does not purposely join the system?
What is the incentive for IoT device makers to join this? They use phone applications as a reference, but phones already had a huge use outside of the applications. How would this track with no strong user-base prior to getting developers?

Critiques:

They are vague on the details of a lot of the technical parts of how they are going to deal with large numbers of data, with nodes leaving the system, and with privacy concerns.
They talk very briefly about privacy and security, but really not enough considering the HUGE privacy implications of connecting the number of sensors they are talking about.
They talk about a lot of theoretical uses for this but do not have any real tests of the system or the different parts of the system.

Reviewer: Huachuan Wang
Review Type: Comprehension
Overview
This paper introduced the swarm which is an extension from the cloud to the physical world and enabling services that are directly embedded in the physical world. This paper also proposes swarmlets which is the adoption of an open and universal platform to enable a multiplicity of distributed sense and control applications.
Contribution
This paper proposed the swarmlets which are characterized by their ability to
(1) dynamically recruit resources such as sensors, communication networks, computation, and information from the cloud
(2) to aggregate and use that information to make or aid decisions
(3) and then to dynamically recruit actuation resources mediating their response by policy, security, and privacy concerns.
This paper also addressed the swarmlets's wide range of challenges and opportunities. This paper suggested a collaborative environment t to generate a broad range of innovative ideas and solutions.
Questions

I am confused about the dynamic hierarchical graph of TerraSwarm, a node can aggregate services to define new service, but could a node be part of several services at the higher level? Also, the edge has many representations, does that mean each edge has all the representations?

The author states that in order to fully achieve the potential of the swarm, they need a SwarmOS. However, given many existing operating systems already been successful, can we directly use or make modifications with these operating systems to implement the swarmlets? What are the special requirements that the existing operating system could not meet?

Reviewer: Becky Shanley
Review Type: Comprehension
Problem being addressed
The paper identifies an unexplored potential in using the "sensory swarm" as one uniform data aggregate of the physical world that could improve social problems and quality of life, called the TerraSwarm. They identify this as a useful field and then address the biggest problem standing between this reality: a lack of universal architecture/communication protocols that allow developers to create something useful on a large scale.
Main Contributions
This paper contributes to solving the problem of a lack of uniform development environment and architecture for the TerraSwarm by proposing a SwarmOS, which they compare to the idea of Android in that it is specific to IoT devices and their sensors.
Questions

I don't understand this paper's definition of Adaptive as it pertains to their system. What does it mean for the distinction between "design-time" and "run-time" to be blurred?
In section C3 it mentions that "Security-related technologies and techniques such as static analysis, hazard analysis, and elliptic curve cryptography will also prove useful" but didn't expand on what any of these will be useful in achieving other than a broad "security".

Reviewer: Pat Cody
Review Type: Comprehensive
Problem Being Solved:
As the number of sensors in the IoT explodes over the coming years, it will be important to find effective ways to utilize them. Many sensors currently only serve a single service or function, when there is much more power in re-using them and combining sensors for multiple services.
Main Paper Contributions
This paper establishes several abstractions, including "swarms", or groups of IoT sensors, and the "terraswarm", a global cyber-physical network (comprised of swarms and applications). By allowing multiple applications to utilize the same sensors, the collected data can be better used as less of it will be wasted. This also allows for more complete applications/services, as their idea of "SwarmOS" would give app developers a framework to build apps that utilize everything in the Terraswarm.
Questions

How do the paper authors envision maintaining privacy with this system? It's a pretty vague paper in all aspects, so I'm not surprised they didn't address this, but merging smart homes and smart cities into the same network means that there will be a lot of personal data available. How would app developers safely be able to access this? How would they prevent super sophisticated ad delivery (would they?)
Can we adapt other existing IoT abstractions to work with the swarm concept? For example, how does edge computing fit into all of this?
How are we moving away from "algorithms" and towards "dynamics", "distribution", etc.? Aren't these still algorithms?

Reviewer: Sean McBride
Review Type: Critical Review
Problem Being Solved:
This paper is Ted Nelson Xanadu levels of crazy, so it's hard to trace a coherent argument or problem. It is disturbing similar to the Radiohead song Fitter Happier.
I suppose the question is sort of meta or philosophical about how sensors and IOT devices should be organized given that:

sensors around to proliferate to 1000x per person
data is more valuable when accumulated

Main Contributions:

Tries to envision a very decentralized bazaar-not-Cathedral bottom-up approach to IOT, whereby arbitrary sensors, actuators, and edge resources share some common communications and control mechanisms ("SwarmOS") and can be composed together into graphs of services called "swarmlets." This is envisioned to be connected to seemingly everything across the world, creating a global network called the "TerraSwarm."
Provides sci-fi examples of "TerraSwarm Apps" such as smart jukeboxes that dynamically generate soundscapes based on the preferences of customers, but also have some sort of Orwellian knowledge of where the Doctors are, so it can bark orders at them when there are emergencies.
Gives me nightmares.

Questions:

How was this a peer-reviewed article that led to funding of a research institute and major corporations? Is one of the authors an eccentric genius or something?
Who own these sensors that can be arbitrarily enlisted? What mechanism actually manages scarcity among these competing TerraSwarm Apps?
What does it mean to have post-algorithmic computation?

Criticisms:

As mentioned above, this feels more Ted Nelson Xanadu than Tim Berners-Lee. Ideas and political philosophy just kinda swirled together without justification. The use of buzzwords and adjectives reminds me of the book House of Leaves, where there is nonsensical narrative with a hidden message that gives off a vague sense of dread. I haven't been able to discern the hidden message in this article. The paper mentions "battlefield management systems," "soundscapes," "control as a service," "Total Awareness," "swarm-in-the-loop simulation"
Different and contradictory statements are thrown out without much thought. Everything is decentralized, but unified. Everything is dynamic and arbitrarily composed, yet resilient to collapse. Things are dynamic and impromptu, yet somehow respect the time limitations of real-type systems. etc. etc. etc.
Figure 2 looks like something a mad scientist would draw.
The references mostly seem to be the authors' own works

Reviewer: Rachell Kim
Review Type: Critical
Problem Being Solved:
The increase in sensors and actuators in embedded devices, called the sensory swarm, poses concerns for deployment, operation, and access control. The author proposes a universal platform to mitigate these technical and non-technical challenges in swarm devices and their applications.
Main Contributions:
The authors propose an open, universal platform that swarm developers may leverage to develop applications (“Swarmlets”). They cite the need for an architecture (“SwarmOS”) that would efficiently manage the resources of a multitude of heterogeneous sensors and actuators. Moreover, they outline several possible approaches and key areas of research that could potentially contribute to the manifestation of the TerraSwarm system.
Questions:

The paper mentions that conventional methods of using cloud services to store data would not be enough to support the needs of TerraSwarm devices and applications and instead suggests using simulation models as a different, more scalable approach. I’m not sure if I understood this correctly, but is this implying that the system (specifically, the swarmlets) will rely heavily on mocked data simulated by swarm devices?
They mention that swarm technology would have “unprecedented robustness in the face of infrastructure collapse,” but how or on what basis/idea are they making this claim? I personally thought it would be the opposite.

Critique:

Perhaps because of the fact that we had just read a paper about the issues in trusting the physics in sensor data, I felt that the security issue was a much larger and serious problem than this paper took time to address, considering that they are proposing a system to handle a network of trillions of sensor devices.
This paper describes what needs to be done and what the TerraSwarm should be, but not much of the state of current research and efforts that have already been accomplished vs. what is lacking. I think that would have been nice information to include if it were possible.

Reviewer: Cuidi Wei
Review Type: Critique
Problem being solved
Most of sensor-based systems are targeting a single application or function. There is little technology to integrate the cyber and physical world. Therefore, sensory swarms offers an unprecedented ability to monitor and act on a range of evolving physical quantities.
Main contributions
This paper proposes the TerraSwarm, which dynamically recruits resources and information from the cloud, aggregates and use information to make decisions, and dynamically recruits actuation resources to mediate their response by policy, security, and privacy concerns.
Questions and Critiques

This paper gives little information how the TerraSwarm improve accuracy and security. We don’t know how the TerraSwarm achieves the security and provides the limited source for Swarmlets.
If a smarter approach can build and refine models of the data sources, how to define normal behavior of the data source? What’s the accuracy of checking the normal behavior? Are there any inaccurate results? If yes, how to prevent the inaccurate results?
I think this paper talks about many vague words, for example, the system theoretic formulation addresses privacy concerns by defining filters that release useful information. However, we know it difficult to filter the exact useful information. How to achieve this in this paper? The paper provides little results of testing the TerraSwarm.

@anguyen0204 Where is the summary of everyone's summaries?

@anguyen0204 Where is the summary of everyone's summaries?

updated


Implement a unified logging interface

For logging, we use LLVM's dbgs() extensively for debug output while the rest of logging is a mix of std, printf, and possibly LLVM's outs(). There were issues with output re-ordering depending on the different streams flushing. We need a better logger.
Originally posted by @ggeorgakoudis in https://github.com/ggeorgakoudis/proteus/pull/15#discussion_r1819959737

A good idea is to store LLVM IR files at different stages and use diff to make changes easy to see


Android support

Milestone 1 of Android Support
https://github.com/w3f/Grants-Program/pull/573

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

@splix the grant milestone pr has been merged.

great, so I can merge it too, right?

Yep!!
On Fri, Sep 10, 2021, 7:34 PM Igor Artamonov @.***>
wrote:

great, so I can merge it too, right?
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Mandatory change in licensing and legal documentation

Description
Due to a change in how we want to license Eclipse Tractus-X, there are a couple of changes
to legal documentation in our repositories.
This issue is created for every active repository in our GitHub org, to remind everyone
about the required changes and also to track the completion of if.
If there are any reasons, why you think this change should not be applied to this repository,
document them as comment on this issue, before closing it. Be aware, that there are most likely no
exceptions for our repositories.
If you have any questions, feel free to join the weekly Community Office Hour
and raise it there.
What has to be done?
The following steps have to be completed, to fully implement the licensing change:

[ ] Add a new file LICENSE_non-code in your repository root with the contents of the CC-BY-4.0 license
[ ] Remove the /LICENSES directory in case you previously stored the CC-BY-4.0 license there. Make sure there is no other CC-BY-4.0 License left, other than on root as LICENSE_non-code
[ ] Add the "Project Licenses" and "Terms of Use" sections to your CONTRIBUTING.md file. See eclipse-tractusx/sig-infra#476 for an example
[ ] Adapt "Declared Project License" section in NOTICE.md. See eclipse-tractusx/sig-infra#476 for an example
[ ] Please verify, your CONTRIBUTION.md does not have encoding issues. We found several occurences in repositories.

Additional information
You can find detailed information in our Release Guidelines section 7.
The changes have been introduces in eclipse-tractusx/eclipse-tractusx.github.io#856.
You can also see an example on how a repository was changed in eclipse-tractusx/sig-infra#476.
Overall progress tracked in eclipse-tractusx/sig-infra#477

bdrs
edc template
tutorials
tractus-x profiles
identity and trust

Done:

EDC Template Repo

PR:

EDC Repo
BDRS Repo

Open, due to open questions:

Identity and Trust Repo (Pure CC-BY-4.0 licensed stuff)
Tractus-X Profiles (JSON files licensed under Apache 2.0)

Done by @alexandrudanciu  and team:

Tutorial Repo


Update 7.3.2 release notes

Changing release notes back to what was automatically generated:

a. 55_pt was actually new this time (it was removed in a recent release): https://github.com/googlei18n/libphonenumber/commits/master/java/geocoder/src/com/google/i18n/phonenumbers/geocoding/data/55_pt
b. And we've always included the entire 1xxx numbers according to the file names - see libphonenumber-7.1.1 release notes for example.
We should generally leave the "metadata" section as is, and if it's wrong see why it was wrongly generated. Also if updating the release notes remember to update the PR description (https://github.com/googlei18n/libphonenumber/pull/1102 stayed the same).

Include the non-metadata change as "code changes", which slipped as it was added during the same PR as the release.

Good point about the PR description, sorry.
a) I thought we refer to the text file, not the binary, and the text file was a modification, not an add
b) We have done both. We should ideally fix the script, but it's too much effort. 5.1.3 and 5.9.1 just say 1 (en), and previously we did US and not country calling codes at all.
c) I don't think unit-test fixes count as code changes?

a) Well the text file and binary file are supposed to be doing the same thing, so the script is looking at only one of them and I guess we went wrong in release 7.2.4 when we removed the 55_pt binary while the text file was still there: https://github.com/googlei18n/libphonenumber/tree/libphonenumber-7.2.4/resources/geocoding/pt. Will investigate separately. You're right, in this change pt/55.txt was only edited.
b) OK I don't understand the 1 "country calling codes". So 1548 and 1743 are in https://github.com/googlei18n/libphonenumber/blob/master/resources/geocoding/en/1.txt but 1767 isn't and that's supposed to be Dominica (not US), right?
Why is it too much effort to fix in the script? It's also not ideal to remember to look at this manually or understand inconsistent release notes. If it makes it easier we can just say "prefixes" instead of "country calling codes" or something.
c) "Test changes" then?

a) I think best for script to look at txt files, don't remember why we made it look at the binary files instead and whether this is actually an oversight.
b) Everything for the US should be in the 1.txt file. The reason 1767 isn't is because we have nothing more detailed than 1767 itself, which we already know is Dominica without using the OfflineGeocoder at all. When building binary files, we split the US file (for performance reasons IIRC) into 1 per area code, and we have special "if 1" code that handles reading from them in the geocoder. I guess it's not too much effort to fix the script if we change it to look at the .txt files not the binary files, just don't remember why it wasn't like that to start with....
c) Sure, sounds good.

a) Probably to account for changes done in PRs :) Maybe 55_pt was added in a PR. b/29443300 to investigate later.
b) Thanks, I understand better. b/29441689
c) I don't have a strong opinion :) Thanks for helping me understand the issues, closing this PR.


Add support to images

@mateusnava thank you. I'm a bit swamped right now but will have a look when I got some time. The fact that the position in the images is relevant makes me think if we can maybe find a different solution. Also would be nice if the images only have to be in the context Hash and not passed on render.
The tricky part is to find a way to annotate the images in the document that we can match it against the passed context.

@senny thanks for the feedback :)
I will try to think about a different form for reference the images and after I will submit another pull request

@mateusnava would be awesome if we find a neat way to annotate the image somehow using the existing sablon expressions (eg = context.some.path). and then have context.some.path be a Image instance in your context hash.

Also thanks for working on this 💛

@senny man, thanks for the great GEM :)!
I did adjusts as your sugestions.
I created a recursive function for getting all images, so, is no more necessary pass the images in two points.
In theory, I didn't do the real tests, the user didn't have worry about the order, just put the images and the gem do the magic.
Ps. Sorry for my poor English.

I seem to get an error from MS Word on Mac saying "This file is corrupt and cannot be open" for the images samples / outputs. Version 15.24 of Word.

I'm a bit short on time at the moment. @Elektron1c97 can you give this PR a test run and review changes? Also, the corrupt file that @campbecf reported should be investigated. I can take a final look when things are ready.

@campbecf @senny I'm checking it in this moment

@campbecf, @senny I correct all the stuffs, please, test again :)))!
Thanks.

Sorry for the delay, I was on holidays last week.
I'll test it when I have time (maybe today or tomorrow)!

Does anyone can evaluate that? @senny @buenaventure @Elektron1c97 @campbecf

I left some comments in the code, the rest looks good to me 👍  When you're done, ping senny to take the last review

@mateusnava What I meant with the comment mentioning the breaks:

It is common practice to check the files into git with a break at the end of the file (as you can see in the screenshot above)

That definitely looks good to me now, @senny have a 👀  again 👍

@Elektron1c97 thanks :)), now I understood. I did do the adjusts!
@senny can you approve this PR?

@mateusnava Things are shaping up! I had a look and left some comments and open questions. Thanks a lot for working on this 💛

@senny I wiil do the changes on the next week :D

@senny I did almost all changes suggested by you, but, I have no time for do all things. Maybe in this moment you can approve this PR and in the future I will refactor the code, what do you think?

@buenaventure can you test again? I did the modifications about original file name

@senny is any possible you aprrove? If no, I will close this pull request and (try) mantain sablon images in other fork.
Thanks.

@mateusnava I definitely want to bring this in. I'm a bit short on time right now but will get back to you when I get time to have another look. Thanks a lot for your work and patience 💛

Thanks for working on this, looks promising.
I have 2 questions after I tried it:

Looks like the placeholder image has to be immediately after :start, and to do that I had to select "In line with text" as the image's "text wrap" option. Otherwise this line would return nil and the render would fail https://github.com/senny/sablon/pull/28/files#diff-c7915360210c6afe655fa399d7c43b5cR127. Can we at least mention how to format the placeholder image in the doc?

I am using Word 2016 for Mac. When I open the processed doc I got a warning:

Word found unreadable content in output.docx. Do you want to recover the contents of this document? If you trust the source of this document, click Yes.

It can be recovered automatically and the image was inserted correctly after I opened the doc. But still it looks like the output might be corrupted. I am able to reproduce the issue using the image_template.docx in this branch. Here is the output file.
output.docx
Please let me know if you need any more information.

@zhengjia man, I need to check this situation, I will do this :).
Thanks for your tests and comments.

Is more work needed here? What can be contributed to help out? Thanks!

@mateusnava I was looking into your solution and testing it. The test is written in image_test.rb works fine.
If I copy your table in image_template.Docx it works again fine. In the case when I created a table and tried to put my image it does not replace that. Over Document XML (unzipped docx) I didn't find the cNvPr node for my Picture. Is there any specific way to do that? Something In/Like mailmerge ?
I can put my sample template docx if required.

https://github.com/ivoke/sablon/commits/ADD_SUPPORT_TO_IMAGES_ALT is a fork of this branch which has been updated much more recently (~ 5 month difference) with some bug fixes it seems. Perhaps @ascyltos would be willing to rebase ivoke/sablon:ADD_SUPPORT_TO_IMAGES_ALT against the current master branch and submit a new PR to supersede this one?

I tried @ascyltos's solution, but it's not working as the same as @mateusnava's. The test case passes using the image_template.docx, but any other different image uploaded it won't work, as pointed out in this line, in which the node pic:cNvPr is not present.
After doing some debug, I realized the node cNvPr is not there for any image except the one provided on the test fixtures. The element drawing is not present. Even after changing the fixture file by using the same image (remove it then upload the same image again), I got the same problem. Seems like the problem is on Word version maybe? OS? Mine is Word for Mac 15.29.1.
I wonder how @mateusnava generated the image on the template, which Word version he is using, OS, etc...
Thanks guys for the great work on this!

Guys, sorry for my answer delay, in this moment I have no time for test or do the changes in this fork.
Sorry for this.

I came with a solution regarding the problem on pic_prop being nil. It happens because on some generated docx documents, the ancestor of ImageBlock is not found on the path .//w:p. I just changed to search across all ancestors instead:
class ImageBlock
  def self.parent(node)
    # node.ancestors('.//w:p') # it does not work for some documents
    node.ancestors
  end
end

And it works. Also I changed the regex for image name, from /(.*)\.[^.]+$/ to /(.*)\.*[^.]+$/ in order to get any content on the filename.
I'd like to submit another PR on behalf of @mateusnava as he has no time for that, with some fixes and more test coverage. I'll do it if I find some time in the next couple of days.
It would be nice to have this feature on master.


warn when using nested ternary

This will suggest engineers write code that is easier to read and more maintainable.


Delete a node then readd it in LB ingress has issue

/kind bug
What happened:
root@kvm-017407:~/go/src/k8s.io/cloud-provider-openstack# kubectl get ing
NAME            HOSTS         ADDRESS       PORTS   AGE
test-ingress1   foo.bar.com   <IP_ADDRESS>   80      44h
root@kvm-017407:~/go/src/k8s.io/cloud-provider-openstack# kubectl get nodes
NAME         STATUS   ROLES    AGE   VERSION
kvm-017407   Ready    master   49d   v1.12.1
kvm-017734   Ready       21m   v1.12.2
kubectl delete node
delete node (17734) but LB doesn't have any update, I think we should consider to update openstack member
Also
has following log
time="2018-12-05T02:53:36Z" level=info msg="Detected change in list of current cluster nodes. New node set: []"
time="2018-12-05T02:53:37Z" level=error msg="Failed to handle ingress" ingress=test-ingress1
means we should avoid doing up in this case (node = [])

I will submit some patches..


No thumbnail preview for .blend file

What's the Problem?
By default when using vanilla window file manager it should show the thumbnail preview for the file

but when using the Files its only show like this

Solution/Idea
apparently its a bug from blender itself but can be fixed with this

work on vanilla file explore but not on Files
Alternatives
im not sure if there alternative
Priorities

Capability
Priority

This proposal will allow developers to accomplish W
Must

This proposal will allow end users to accomplish X
Should

This proposal will allow developers to accomplish Y
Could

This proposal will allow end users to accomplish Z
Won't

Files Version
Version: <IP_ADDRESS> OS Version: 10.0.19043.1165
Windows Version
Edition	Windows 10 Pro Version	21H1 Installed on	20-Jul-21 OS build	19043.1165 Experience	Windows Feature Experience Pack 120.2212.3530.0
Comments
Your program were soo good btw. its just this small feature if implemented would benefit everyone who use blender

Merging with #2582


podman attach: missing --sig-proxy option

docker attach provides a --sig-proxy option, defaulting to true. podman does not offer the equivalent.
I'm not sensing an urgent need for this. Filing issue merely for sake of completeness.

We're also missing sig-proxy with podman run - the option is there, but it's not plugged into anything.


[YUNIKORN-2650]Complete or remove web_server_test#TestProxy

What is this PR for?
This PR completes web_server_test#TestProxy.
What type of PR is it?

[x] - Improvement

Todos

[ ] - Task

What is the Jira issue?
[YUNIKORN-2650]
How should this be tested?
It has been checked locally by make test.
Screenshots (if appropriate)
N/A
Questions:
N/A

@0lai0 please fix the linter warning.

Test failure is unrelated.

"make test" & "make lint" passed locally, will merge soon.


capture starts only after the scrollTop

With v6.0.2 (8536.26.17) of Safari the capture of $('body') starts only after the viewport.
Instead of the hole body, is starts in $(window).scrollTop(), goes to the end of the document and adds blank space to make the image the height of the document.
I have a demo in http://jsbin.com/ociriy/2 ,try not to have the browser bigger than the document height.
The bug doesn't work with http://jsbin.com/ociriy/2/edit , maybe because is in iframe?

Perhaps this is the same issue as #333 - look there for a workaround

@filipegarcia You using Safari on Mac OS or mobile Safari? Also, this is a very old bug.. Does the newest version from the master branch fix it for you?


Zone.js versions greater that 0.8.12 break dojo applications in IE11 only

When using zone.js with dojo, dropdown widgets (datepicker, combobox, etc) don't register click events when interacted with.
Simple reproduction steps: https://github.com/mcgraphix/zonejs-dojo-bug
That repo is currently using 0.8.26. If you revert to 0.8.12 in the script tag, the widget will start working.

@mcgraphix, thanks for posting the issue, I will check it.

Thanks @JiaLiPassion - I discovered that the issue only happens in IE11. I updated the defect title above

@mcgraphix, I think the issue related to this one, https://github.com/angular/zone.js/issues/589, the MSPointerUp vs pointerup changes from 0.8.12, I will do more research.

This just got a lot more critical with Angular 6. It seems that rolling back to an earlier version of zone.js doesn't work when running the tests. As you mentioned in this comment https://github.com/jasmine/jasmine/issues/1496#issuecomment-364190348 it the fix will be in a newer version of zone.js than the one we can currently use with dojo on the page

@mcgraphix, I created a branch for temp release.
Could you try to update your package.json and test the release is correct? Thanks.
"zone.js": "git://github.com/JiaLiPassion/zone.js#pointer-event-dist"

Thanks @JiaLiPassion - In my limited testing it does seem that that branch fixes the issue.

@mcgraphix, thanks for the confirmation!

I hit a similar issue with zone.js and angular-gridster component.
Events blacklisting solved the issue without zone.js downgrading:
(window as any).__zone_symbol__BLACK_LISTED_EVENTS = [   'MSPointerDown',   'MSPointerMove',   'MSPointerUp',   'MSPointerCancel' ];

@mobichel, thanks, this will also work if you don't need to update data in Pointer Event.

@JiaLiPassion Any ETA on when this fix will be released?

Hi @JiaLiPassion , are there any chances to have this fix in the main branch?


Using pretrained word embeddings

@dennybritz
Hi ,
First of all many thanks for sharing your code.  I am trying to use pretrained word embeddings instead of randomly initialized word embedings based on the vocabulary size.
My pretrained word embedding is numpy array  : ( N, 300, dtype=float.32) where N is indice of the word for which word embedding of dimension (300,) is stored.
However , unable to pass the step of
self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x) because tensorflow only allows int32,int64 as lookup indices.
Can you suggest how can i resolve this issue?
Many thanks

Sorry for the late reply, I was traveling. You need to set your pretrained embedding as the initializer of W when W is declared.

@sanjaymeena Can you share your code for the pre-training of word embeddings?

@fmaglia  I am posting snippet of code for  using pretrained word embeddings
'''
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops as array_ops_
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn
from tensorflow.python.ops import variable_scope as vs
class TextCNN(object):
"""
A CNN for text classification.
Uses an embedding layer, followed by a convolutional, max-pooling and softmax layer.
"""
def init(
self, sequence_length, num_classes, vocab_size,word_vector_map,
embedding_size, filter_sizes, num_filters, l2_reg_lambda=0.0,embedding_type='static'):
    # Placeholders for input, output and dropout
    self.input_x = tf.placeholder(tf.int32, [None, sequence_length], name="input_x")
    self.input_y = tf.placeholder(tf.float32, [None, num_classes], name="input_y")
    self.dropout_keep_prob = tf.placeholder(tf.float32, name="dropout_keep_prob")

    # Keeping track of l2 regularization loss (optional)
    l2_loss = tf.constant(0.0)

    #Embedding layer
    #with tf.device('/cpu:0'), tf.name_scope("embedding"):
    with tf.device('/cpu:0'), tf.name_scope("embedding"):

        # use pretrained word2vec embeddings
        if embedding_type in 'static':
            ids=self.input_x
            embeddings = vs.get_variable('w2v' + "_embeddings",
                                     [num_classes, embedding_size])
            name="embedding_lookup"
            ids = ops.convert_to_tensor(ids)
            params=tf.Variable(word_vector_map)

            # shape
            shape = array_ops_.shape(ids)

            # concatenates all the ids from all the sentences
            ids_flat = array_ops_.reshape(ids, math_ops.reduce_prod(shape, keep_dims=True))
            #
            embeds_flat = nn.embedding_lookup(params, ids_flat, name)
            embed_shape = array_ops_.concat(0, [shape, [-1]])
            embeds = array_ops_.reshape(embeds_flat, embed_shape)
            embeds.set_shape(ids.get_shape().concatenate(params.get_shape()[1:]))

            self.embedded_chars=embeds
            self.embedded_chars_expanded=tf.expand_dims(self.embedded_chars, -1)

        else:
            W = tf.Variable(
                tf.random_uniform([vocab_size, embedding_size], -1.0, 1.0),
                name="W")

            self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x)
            self.embedded_chars_ex

'''

Try initializing W from pre-trained vectors during the training session, not in the model definition.
First, make your embedding a self variable in __init__() in text_cnn.py
                self.W = tf.Variable(
                    tf.random_uniform([vocab_size, embedding_size], -1.0, 1.0),
                    name="W")

                self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x)
                self.embedded_chars_expanded = tf.expand_dims(self.embedded_chars, -1)

Second, just initialized the W matrix from the word2vec file in train.py like this:
        sess.run(tf.initialize_all_variables())

    # initial matrix with random uniform
    init_W = np.random.uniform(-0.25,0.25,(input_size, embedding_size))

    # load any vectors from the word2vec
    with open(word2vec_path, "rb") as f:
        header = f.readline()
        vocab_size, layer1_size = map(int, header.split())
        binary_len = np.dtype('float32').itemsize * layer1_size
        for line in xrange(vocab_size):
            word = []
            while True:
                ch = f.read(1)
                if ch == ' ':
                    word = ''.join(word)
                    break
                if ch != '\n':
                    word.append(ch)
            if word in vocab:
                idx = vocab[word]
                init_W[idx] = np.fromstring(f.read(binary_len), dtype='float32')
            else:
                f.read(binary_len)

           sess.run(cnn.W.assign(init_embedding))

hope this helps...

@sanjaymeena Thanks for the code.
I have 3 questions:

TypeError: __init__() takes at least 8 arguments (9 given)
In the train.py I add embedding_type in the class instantiation
How I can solve this error?
In your code there are no steps in which word2vec access to a dataset for the pre-training. Why?
What you are using as dataset for the pre-training? Can you share it?

Hi @dennybritz , thanks for sharing your code!
I am facing some issues when trying to use your CNN slightly modified using word2vec as an input, I will try to explain briefly what I have done:

In train.py I modified the method that obtains the data  as "x"  implementing "data_helpers.get_input_as_word2vec() " using gensim word2vec.
The dataset I am using IMDB as a dataset, being each row of "x" a movie review encoded as a word2vec vector with n_dim=300 (number of columns). After cross_validation, I obtain "x_train" ,finally getting the batches I obtain "x_batch".
"y_batch" is the label of the review: (1,0) or (0,1) same as you do.
Every call to  "train_step(x_batch, y_batch)" as you do, it trains a batch of [n_reviews_batch_size, n_features_word2_vec]. The run method inside "train_step" will make accessible x_batch inside TextCNN.py object as "input_x" (being this a batch of reviews)

After several tries I haven't been able to attach the word2vec embegging to the CNN. I am not really familiar yet with TensorFlow and its notation. Could you please give me some hint? Thanks in advance!
The error I get:   TypeError("List of Tensors when single Tensor expected")
Here is the TextCNN code in which I try to define W where "input_x" is a list of tensors (one for each review in the batch [n_review_batch, n_dim_word2_vec] ):
    def __init__(
       self, sequence_length, num_classes, vocab_size,
       embedding_size, filter_sizes, num_filters, l2_reg_lambda):

        # (embedding_size = n_dim_word2vec = sequence_length )
        # Placeholders for input, output and dropout
        self.input_x = tf.placeholder(tf.int32, [None, sequence_length], name="input_x")
        self.input_y = tf.placeholder(tf.float32, [None, num_classes], name="input_y")
        self.dropout_keep_prob = tf.placeholder(tf.float32, name="dropout_keep_prob")

        # Keeping track of l2 regularization loss (optional)
        l2_loss = tf.constant(0.0)

        # Embedding layer
        with tf.device('/cpu:0'), tf.name_scope("embedding"):
            W = tf.constant(self.input_x, name="W",shape=[self.input_x.get_shape()[0], embedding_size])

            self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x)
            self.embedded_chars_expanded = tf.expand_dims(self.embedded_chars, -1)

        # Create a convolution + maxpool layer for each filter size
        # ....

Hi @dennybritz
Thank you for your sharing your code!  I am having some issue trying to user word2vec as input:
I have a pretrained word2vec matrix "embedding_matrix" with one text sentence per row and n_dim(300) columns using gensim.

I assign it to "W" after defining it. However I get an error when processing "tf.nn.embedding_lookup(W, self.input_x)"
I followed your indications assining the pretrained word2vec matrix using W.assign(). Please, let me know if you how to solve it. thanks in advance!  (Please, note that I am not really familiar yet with TensorFlow)

   # Embedding layer
        with tf.device('/cpu:0'), tf.name_scope("embedding"):
           W = tf.Variable(tf.random_uniform([embedding_matrix.shape[0], embedding_size], -1.0, 1.0),name="W")
           W.assign(embedding_matrix)

            self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x)
            self.embedded_chars_expanded = tf.expand_dims(self.embedded_chars, -1)

        # Create a convolution + maxpool layer for each filter size
        #...

Error:

tensorflow.python.framework.errors.InvalidArgumentError: indices[0,10] = -1 is not in [0, 50000)
[[Node: embedding/embedding_lookup = Gather[Tindices=DT_INT32, Tparams=DT_FLOAT, _class=["loc:@embedding/W"], validate_indices=true, _device="/job:localhost/replica:0/task:0/cpu:0"](embedding/W/read, _recv_input_x_0)]]
Caused by op 'embedding/embedding_lookup', defined at:
File "cnn-text-classification-tf/text_cnn.py", line 46, in init
self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x)

@sanjaymeena what's the parameter "word_vector_map" mean, what's the format of it ?

Hi guys, I have the same problem with you guy. I tried to apply word2vec for Convolution Neural Network in Text Classification task. The code for pre_train is "word2vec_basic.py" in Tensorflow website. I really don't know how to feed it in the network. Here is the code I tried to do:
` W = tf.Variable(tf.constant(0.0, shape=[vocabulary_size, embedding_size]),
trainable=False, name="W")
embedding_placeholder = tf.placeholder(tf.float32, [vocabulary_size, embedding_size])
embedding_init = W.assign(embedding_placeholder) `

Here is how I load pre-trained word2vec into the model...
In text_cnn.py make W a self:

            self.W = tf.Variable(
                tf.random_uniform([vocab_size, embedding_size], -1.0, 1.0),
                name="W")

In train.py add something like this after "# Initialize all variables"

    sess.run(tf.initialize_all_variables())

    # initial matrix with random uniform
    initW = np.random.uniform(-0.25,0.25,(input_size, 300))
    # load any vectors from the word2vec
    with open("GoogleNews-vectors-negative300.bin", "rb") as f:
        header = f.readline()
        vocab_size, layer1_size = map(int, header.split())
        binary_len = np.dtype('float32').itemsize * layer1_size
        for line in xrange(vocab_size):
            word = []
            while True:
                ch = f.read(1)
                if ch == ' ':
                    word = ''.join(word)
                    break
                if ch != '\n':
                    word.append(ch)
            if word in vocab:
                idx = vocab_processor.vocabulary_.get(word)
                initW[idx] = np.fromstring(f.read(binary_len), dtype='float32')
            else:
                f.read(binary_len)

     session.run(cnn.W.assign(initW))

You'd need to run --embedding_dim=300 to match the word2vec

Hi j314erre, thanks for your code but I am quite don't understand it. Are all of your result stored in "GoogleNews-vectors-negative300.bin" ? My code is similar with "word2vec_basic.py" of Tensorflow. Could I use "cnn.W.assign" like you  ?

My code example assumes pre-trained vectors are stored in the Google format and you can get GoogleNews-vectors-negative300.bin here
I believe for pre-trained vectors it makes more sense to load them from a file.
I haven't used word2vec_basic.py buy it looks like the basic idea would be to assign 'final_embeddings' into session.run(cnn.W.assign(final_embeddings))

Yeah that is exactly what I did
`W = tf.Variable(tf.constant(0.0, shape=[vocabulary_size, embedding_size]),
trainable=False, name="W")
embedding_placeholder = tf.placeholder(tf.float32, [vocabulary_size, embedding_size])
embedding_init = W.assign(embedding_placeholder)
sess = tf.Session()
sess.run(embedding_init, feed_dict={embedding_placeholder: final_embeddings})
embedded_chars = tf.nn.embedding_lookup(W, data)
embedded_chars_expanded = tf.expand_dims(embedded_chars, -1)`
I used embedding_lookup for W and data (data is the variable store index of distionary) is It correct ? As @dennybritz wrote that "maps vocabulary word indices into low-dimensional vector representations"

Hi @j314erre ! Thanks for your code.
I followed your code and fix train.py.
But got a error with embedding size and vocab_size
I had fix the embedding size to 300
May I ask that do I fix anything about the # build vocabulary in train.py?

Here is a gist of modified text_cnn.py and train.py that loads pre-trained word2vec https://gist.github.com/j314erre/b7c97580a660ead82022625ff7a644d8
Note: you have to set --embedding_dim to be the same size as your pre-trained embeddings.
Also note:  it initializes the embedding with the pre-trained embeddings, but continues to learn and adapt the embeddings as you train further on your data...this is usually what you want.
I ran it like this:
$ ./train.py --embedding_dim=300 --word2vec=./GoogleNews-vectors-negative300.bin

Parameters:
ALLOW_SOFT_PLACEMENT=True
BATCH_SIZE=64
CHECKPOINT_EVERY=100
DROPOUT_KEEP_PROB=0.5
EMBEDDING_DIM=300
EVALUATE_EVERY=100
FILTER_SIZES=3,4,5
L2_REG_LAMBDA=0.0
LOG_DEVICE_PLACEMENT=False
NUM_EPOCHS=200
NUM_FILTERS=128
WORD2VEC=/mnt/hgfs/Temp/deeplearning/data/word2vec/GoogleNews-vectors-negative300.bin

Loading data...

I try your code to my fix version, it works!!
Thank you very much!!

Hey @j314erre, Thanks for this! What changes should I make to the code if I do not want the embeddings to continue to be trained along with the model? (i.e. I want to use static word2vec embeddings)

I have not tested this but try trainable=False when you define those parameters:
# Embedding layer
        with tf.device('/cpu:0'), tf.name_scope("embedding"):
            self.W = tf.Variable(
                tf.random_uniform([vocab_size, embedding_size], -1.0, 1.0),
                trainable=False,
                name="W")
            self.embedded_chars = tf.nn.embedding_lookup(self.W, self.input_x)
            self.embedded_chars_expanded = tf.expand_dims(self.embedded_chars, -1)

@ferfervi  hello,I meet the same problem with you ,have you solved it?

@j314erre
How much RAM you machine has to run this code ? I tried to load the Google binary file, but with 16 GB, I always get memory exhaustion errors :
root@f8d6a880db61:/mnt/chatbot/cnn/scripts# python3 train.py --embedding_dim=300 --version=1 --word2vec="/mnt/chatbot/data/GoogleNews-vectors-negative300.bin"

Parameters:
ALLOW_SOFT_PLACEMENT=True
BATCH_SIZE=64
CHECKPOINT_EVERY=100
DROPOUT_KEEP_PROB=0.5
EMBEDDING_DIM=300
EVALUATE_EVERY=100
FILTER_SIZES=3,4,5
L2_REG_LAMBDA=0.0
LOG_DEVICE_PLACEMENT=False
NUM_EPOCHS=100
NUM_FILTERS=128
WORD2VEC=/mnt/chatbot/data/GoogleNews-vectors-negative300.bin

Vocabulary Size: 2111
Training/Cross-validation/Test split: 7962/2654/2652
Writing to /mnt/chatbot/cnn/experiments/runs/1477599393

Load word2vec file /mnt/chatbot/data/GoogleNews-vectors-negative300.bin

Traceback (most recent call last):
 File "train.py", line 386, in <module>
   main(sys.argv[1:])
 File "train.py", line 239, in main
   word.append(ch)
MemoryError

My VM has 16 GB of RAM. I would like to know how much you have.
Thanks !

Hi @j314erre
Could you pls. let me know what's wrong with my code. I modified it in the same way and is running this way.
Traceback (most recent call last):   File "./train.py", line 141, in <module>     if FLAGS.word2vec:   File "/anaconda/lib/python3.5/site-packages/tensorflow/python/platform/flags.py", line 44, in __getattr__     raise AttributeError(name) AttributeError: word2vec papio:cnn-text-classification-tf-master compbio$

@dennybritz, @j314erre
Hi, thanks for the code!
I tried to run it with GloVe trained on the positive and negative examples, and I got an error from tf.nn.embedding_lookup():
`InvalidArgumentError (see above for traceback): indices[0,11] = 21161 is not in [0, 21161)
[[Node: embedding/embedding_lookup = Gather[Tindices=DT_INT32, Tparams=DT_FLOAT, _class=["loc:@embedding/W"], validate_indices=true, _device="/job:localhost/replica:0/task:0/cpu:0"](embedding/W/read, _recv_input_x_0)]]

21161 is the number of the pretrained vectors (and I use a 21161 x embedding_size - matrix in the embedding layer for the weights)

in the documentation of the tf.nn.embedding_lookup_sparse() they mention:  "It also assumes that all id values lie in the range [0, p0), where p0 is the sum of the size of params along dimension 0."
Why exactly should the id value be less than the size of params along dimension 0?
Is there any way to solve this?

@dennybritz what is advantage of pre-trainedembedding words ? I have  dataset(not very large). In test/validation dataset, I have some sentences with same meaning/context but sentence is not using exact same words. Then in that case acuuracy is not good. How to solve this issue ? Please help. I hope you have lots of ideas on this.

An interesting post written by mrry on Using a pre-trained word embedding (word2vec or Glove) in TensorFlow:

There are a few ways that you can use a pre-trained embedding in TensorFlow. Let's say that you have the embedding in a NumPy array called embedding, with vocab_size rows and embedding_dim columns and you want to create a tensor W that can be used in a call to tf.nn.embedding_lookup().

Simply create W as a tf.constant() that takes embedding as its value:
 W = tf.constant(embedding, name="W")

This is the easiest approach, but it is not memory efficient because the value of a tf.constant() is stored multiple times in memory. Since embedding can be very large, you should only use this approach for toy examples.

Create W as a tf.Variable and initialize it from the NumPy array via a tf.placeholder():
 W = tf.Variable(tf.constant(0.0, shape=[vocab_size, embedding_dim]),
                 trainable=False, name="W")

 embedding_placeholder = tf.placeholder(tf.float32, [vocab_size, embedding_dim])
 embedding_init = W.assign(embedding_placeholder)

 # ...
 sess = tf.Session()

 sess.run(embedding_init, feed_dict={embedding_placeholder: embedding})

This avoid storing a copy of embedding in the graph, but it does require enough memory to keep two copies of the matrix in memory at once (one for the NumPy array, and one for the tf.Variable). Note that I've assumed that you want to hold the embedding matrix constant during training, so W is created with trainable=False.

If the embedding was trained as part of another TensorFlow model, you can use a tf.train.Saver to load the value from the other model's checkpoint file. This means that the embedding matrix can bypass Python altogether. Create W as in option 2, then do the following:
 W = tf.Variable(...)

 embedding_saver = tf.train.Saver({"name_of_variable_in_other_model": W})

 # ...
 sess = tf.Session()
 embedding_saver.restore(sess, "checkpoint_filename.ckpt")

Thanks a lot @Franck-Dernoncourt! how does pretrained embedding is different from having the models' own embedding(created during training the model) ? Currently I have relatively small dataset to train on my model and wanted to get it generalized on new test examples in sense that chatbot understand different sentences carrying same semantic meaning(intents and entities in it). For example:

How can you help me?;  How can you assist me?; What assistance can you provide?; - Intent: help type
Make me laugh.; Crack some jokes  please.; Can you make me laugh?; Can you tell me something funny?; Can you entertain me? Please entertain me. ----> intent: Entertainment

What kind of embedding can help me on the above problem? Thanks.

@hariom-yadaw using pre-trained word embeddings, which are fine-tuned during the training phase, sometimes helps, e.g.  https://arxiv.org/pdf/1606.03475.pdf:

@Franck-Dernoncourt  Ok, Got it! Thanks. But again I have below two doubts

When we use pretrained embeddings(which should have millions of words), it works only for words which are in my dataset vocab(few thousands, suppose 1K). And I'm expecting new words(synonyms for words in my vocab) in my test set, its most likely to fail on those. How to tackle this?

We use pre-trained embeddings only when we rain the model or we use it during test? (I mean in serve mode- when chatbot is serving for the user)

Anyone facing a memory error while loading the word2vec model? Any suggestions on the amount of memory (RAM) i need to make sure things don't crash? I'm using the GoogleNews-vectors-negative300.bin for the word embeddings.

I was running the script eith Google's pre-trained word vectors on a server with 24 GB of RAM and pretty much all the RAM was filled up.

For Python3, you should code like this:
        if FLAGS.word2vec:
            # initial matrix with random uniform
            initW = np.random.uniform(-0.25,0.25,(len(vocab_processor.vocabulary_), FLAGS.embedding_dim))
            # load any vectors from the word2vec
            print("Load word2vec file {}\n".format(FLAGS.word2vec))
            with open(FLAGS.word2vec, "rb") as f:
                header = f.readline()
                vocab_size, layer1_size = map(int, header.split())
                binary_len = np.dtype('float32').itemsize * layer1_size
                for line in range(vocab_size):
                    print(line)
                    word = []
                    while True:
                        ch = f.read(1).decode('latin-1')
                        if ch == ' ':
                            word = ''.join(word)
                            break
                        if ch != '\n':
                            word.append(ch)
                    print(word)
                    idx = vocab_processor.vocabulary_.get(word)
                    if idx != 0:
                        initW[idx] = np.fromstring(f.read(binary_len), dtype='float32')
                    else:
                        f.read(binary_len)
            sess.run(cnn.W.assign(initW))

And it really cost me a lot of time to figure it out... 😞

Also running on a cluster and facing a MemoryError when loading the Google pre trained word vectors

Also MemoryError when loading Word2Vec.
Load word2vec file ./../../git_repo/style_transfer/data/GoogleNews-vectors-negative300.bin
Killed: 9

@j314erre The code in the train.py that you have created in your gist seems to be using the load_data_and_labels function from data_helpers, but you have not fed the path of the positive_data_file and negative_data_file flags as it has been done in the original trian.py. Why?

Anyone who is looking to Use Multi class classification with pre-trained Word2Vec, feel free to use this consolidated fork https://github.com/naveenjafer/cnn-text-classification-tf that builds on all the work done by the people here.

Has anyone tried to do visulization on cnn classification ? Which variable are you using to visualize


Add link to ETM Dataset Manager to front-end including text

We want to create a direct link / button from a dataset in the ETM to a dataset in the ETM Dataset Manager. This way users can check out the source data of that specific dataset. In https://github.com/quintel/etmodel/issues/3680 the data-specific link is created. This issue is about the location of the link in the ETM and the text supporting it.
Location
@noracato and I propose to add the link as a new sidebar-item underneath the 'Overview'-tab in the ETM. This would look something like this:

What do you think of this location @quintel/core ? Let us know when you have other ideas.
Country datasets
Something we have to think of is what you see here when you have opened a country dataset. Country datasets are not yet included in the ETM Dataset Manager, so not button should be shown then. There are a few options:

Only show this 'Source data' sidebar item for datasets on the ETM Dataset Manager
Always show the 'Source data' sidebar item and write a general story for country datasets about the generation process of country datasets (Energy Balances, etc)
Always show the 'Source data' sidebar item, write a general story for country datasets and link the users to the source analyses on GitHub (this is an Excel jungle though!)

I prefer option 2. If you have an opinion about this, let us know!

I think that adding it to the "Overview" tab would not fit entirely within the current process that a user goes through when opening the model. The users start with the Introduction to the model, which invites them to balance Supply and Demand. To then add this relatively advanced feature (in my opinion) to the "Overview" tab, seems to disrupt the user experience.
Currently most of our data is located at Results > Data export, so perhaps that would be a better location for the link to the Dataset manager?

I do think that showing source data fits the best at overview. Before someone starts they would like to see where the data comes from. It is input data and not result data, thus I would not show it at the end.
I prefer option 2, although I do have a remark. A general story (very short) about the main data sources voor countries and regions would be very helpful. The ETM Dataset Manager probably shows a of detail, but not the simple overall story:
Data sources:

Countries: Energy balance (IEA)
Dutch regions: Klimaatmonitor, Emissieregistratie and CBS.
Belgian regions: Burgemeestersconvenant, VITO

Also for the Dutch regions we have a word document describing the dataset process. It would be nice to have a link to this document too.

Currently most of our data is located at Results > Data export

True, but this is mostly data that is unique to your scenario; the results. In my opinion viewing the source data is not part of a result, it's what you are starting with. So for me it would not fit under that tab (or we would have to change the name).
Maybe we could name this new sidebar item 'Backgrounds' / 'Achtergronden' instead of 'Source Data' and also include a slide and link to our documentation there? Then it might become something like: if you want to learn more and go deeper, check this out.

I'm opposed to adding it under "Overview" and also believe it belongs in the "Results" section. I think we should rename "Results" to "Results and data".
@mabijkerk has already covered my reasoning for disliking adding it to "Overview". Users – especially new users – will view the intro, then proceed to the next page. The next page should be something which will capture their attention and introduce the features of the model, not send them off-site.

I agree with @mabijkerk and @antw

I agree with @mabijkerk and @antw

Me too

Thanks for all your input!
@mabijkerk & @antw you have convinced me. I think it's indeed better to included it in the "Results & data" section. I do think it's important to create a link from the "Introduction" section to the source data section, so users can find it.


Can I deploy to vercel?

Sorry I didn’t know what to choose so I just chose future request but if it’s not a feature pls make it one

Yes, you're free to use my code however you want.

Like make a button that says deploy to vercel I don’t know if you need like a special something but some people have like a deploy to vercel and deploy to heroku and type of stuff, if you need a screen shot I can upload one as an example

Ok, I understand your point now. I just did a little research, I know I will have to go through quite a trouble to make that, I'm very sorry to say no to your request.
You can deploy the server manually or make that feature, test if it works then contribute to this project since I'm not available to code the feature myself.
I recommend add a new code file (`deploy_vercel.py``) outside both versions, if the user wants to deploy then they will run that script along with the path to server.py that they choose to deploy.
For example: deploy_vercel.py "path_to_server.py"
It's been nice to chat with you. Close the issue if that's all.

Ok I’ll see, if you want to ask me if I’m done with it my discord is @qwertyhigkl


Date Range Partitioning by Month

According to the docs for projected partitioning, it looks like it's possible to partition a normal datetime column by arbitrary time intervals (1 month, in my case). However, the awswrangler code seems to only be able to generate partitions as datetimes or dates. For example, if I store a record with start_time = 2021-05-25T08:04:23.000000, I'd like this record to be stored in a partition, 2021-05. Right now, I'm turning start_time into a string and partitioning on that, but that means I can't use projection and I have to add an extra where clause to my sql to ensure the partitions are utilized.
Am I misunderstanding the docs for projected partitioning, or does awswrangler just not handle this? Also, this library is great, so thank you.

Could you please share a minimal example of what you are trying to achieve and the exact Wrangler call you are making? Perhaps with a dummy dataframe. Thanks


test: quick test for sending messages

Also started moving/refactoring tests
TIS21-1032: Synchronise and display placement data

Seems too stale to use


DefectDojo known security vulnerability in docker images w.r.t jquery

Hello Team,
We are trying to on board defectdeojo in our corporate, but as per our policy we have to perform container security scanning. While scanning we came up accross with jquery version used by defectdojo is vulnerable.
DefectDojo uses jquery version 2.1.* and from our scanning it shows that it should be upgraded to latest version 3.0.
So could you please provide some suggestion on upgrading jquery or can we get latest update on via docker image itself.

hi  @bilalk88 . on what branch are you? do you know where this dependency come from? from what I see in package.json on dev or master branch we're supposed to be using jquery 3:
 "@yarn_components/jquery": "jquery/jquery-dist#~3.3.1",

Hi @ptrovatelli . Thanks for the response.
I'm in the master branch. I'm not sure from where this old version of jquery came from. But when I checked in the nginx container under  " /usr/share/nginx/html/static/ " there all are older version of jquery there.

Those files are generated by (Dockerfile.nginx)
python3 manage.py collectstatic --noinput
they contain with other things, libraries pulled by yarn based on package.json.
this basically gets all static resources from django so that nginx can serve them.
I'm actually even seeing what seems to be jquery 1.7 and jquery 1.8. Can you point us to the files you're seing that are jquery 2.1?
docker exec -it django-defectdojo_nginx_1 bash
cd /usr/share/nginx/html/static
 find . -type f -name '*jquery*'
(...)
./font-awesome/src/3.2.1/assets/js/jquery-1.7.1.min.js
./fontawesome/src/3.2.1/assets/js/jquery-1.7.1.min.js
(...)
./jquery-ui/ui/jquery-1-7.js
(...)
./jquery.hotkeys/jquery-1.4.2.js
(...)
./rest_framework_swagger/lib/jquery-1.8.0.min.js
(...)
./tastypie_swagger/js/lib/jquery-1.8.0.min.js
./tastypie_swagger/js/lib/jquery.ba-bbq.min.js
./tastypie_swagger/js/lib/jquery.slideto.min.js
./tastypie_swagger/js/lib/jquery.wiggle.min.js

it's probably possible to improve the situation by tuning that package.json file.

@ptrovatelli. Thanks for the response.
Actually, jquery 2.* versions are inside the /usr/share/nginx/html/static/startbootstrap-sb-admin-2/bower_components/jquery/dist/jquery.js

Believe this is fixed: https://github.com/DefectDojo/django-DefectDojo/blob/414e10fd8b7aa51a27edfdce8a02ad3a512fe45c/components/package.json


Add Tarantool page

@totktonada, could you review changes?

@Totktonada, could you review changes?

Seems good, thanks!
I shared some thoughts around, but, please, don't consider them as blocking.


Support for jakarta.inject API

Since Bootique 3.0 introduces support for Jakarta APIs in various modules we may think about adding support for jakarta.inject to the Bootique DI

+1. And let's also try to do some research beyond jakarta.inject. I think we are still mostly ignorning JAXB and maybe a few more libs that are not used directly, but are imported by the integrated frameworks.

Closing, moved to https://github.com/bootique/bootique/issues/349


Score multiplier for Challenge creep sizes are incorrect

https://github.com/Praytic/youtd2/blob/4cd0b1f4069e055714da3796ee14a70753f1e02f/src/enums/creep_size.gd#L71
Hello, I'm new to godot and I've benefited a lot from the code of this project.
Can I get access to static resources?   :)

Hello.
Yes, those values are really incorrect. They are supposed to be as in the comment above. Thanks for reporting this!

Yes, that's exactly what I needed! thank


Installation problem: Ubuntu 16.04

Hi
I am running Ubuntu 16.04
and
cabal --version
cabal-install version <IP_ADDRESS>
using version <IP_ADDRESS> of the Cabal library
cabal build in the org-citeproc source directory I obtained:
Resolving dependencies...
Configuring org-citeproc-0.1...
cabal: At least the following dependencies are missing:
json -any, pandoc-citeproc -any
so I understand that I need to install pandoc-citeproc first?
Uwe Brauer

Hi Uwe,
Yes, this code is basically just a tiny wrapper around pandoc-citeproc.
What are you interested in doing with it?

HI Richard,
your code was recommended to me by John Kitchin. I want to do the following: I write an org document with references using John's org-ref package, but I want an html (or odt) file, which uses the classical LaTeX/bibtex/plain style like. For example
As shown by Einstein [1]
Generating the [1] in text needs, according to John some pre processing which pandoc provides. I realized that I even cannot  get pandoc citeproc to work. When I do, I might come back to you.
Reference

Albert Einstein Zur Elektrodynamik bewegter Körper.

Ah OK, well good luck! This code won't provide a drop-in solution for what you want to do; it isn't integrated with org-ref (so far as I know--maybe John did something on his side?). But it could provide a starting point for what you want to do.  If you're interested in making it work, I would happily lend you a hand, insofar as I am able.