Fix bug with collateral selection for KeyWallet, Add SignMultiple example for KW (was #709)

Replay of https://github.com/Plutonomicon/cardano-transaction-lib/pull/709 | Closes https://github.com/Plutonomicon/cardano-transaction-lib/issues/668
Pre-review checklist

[x] All code has been formatted using our config (make format for Purescript, nixpkgs-fmt for Nix)
[x] All Purescript imports are explicit, including constructors
[x] All existing examples have been run locally against a fully-synced testnet node
[x] The integration and unit tests have been run (npm run test) locally
[x] The changelog has been updated under the ## Unreleased header, using the appropriate sub-headings (### Added, ### Removed, ### Fixed)

Please resolve the conflicts, all great!


fix: array schema is not being parsed correctly

Description
Fixes array schema parsing with the following caveats:

If 'items' is defined as an array of schemas, it will continue to be parsed as an Arraylist (like before).
Once we have some clarity on whether we should be using 'prefixIems', or returning a list of schemas, we can implement it.

In the meantime, with this fix, if 'items' is a json schema, then it will get parsed to a 'Schema' object, instead of the LinkedHashmap which we get right now.
We are a bit blocked due to this, and this fix will allow us to proceed with using this library in our project to validate messages with array schemas
Related issue(s)
#154

@jaydeepk please switch to 1.0.0-EAP-3-SNAPSHOT branch. It contains bunch of changes

Merged - https://github.com/asyncapi/jasyncapi/pull/159


Navigating file explorer Quirks

@bryphe given you're looking to get the file explorer into the next release wanted to give some feed back on issues I've noted (following on from the gitter conversation).
As I mentioned with my own init.vim enabled I find that pressing j or k causes the cursor to occasionally jump over nodes in the tree. I've tried deactivating my config which actually results in an error which crashes oni.

Will do some more digging and add a screen cast to illustrate the issue shortly.

Just tried again with my config disabled and was able to get the full navigation. I'm thinking that it might be a good idea to temporarily remove a user's default h,j,k,l binding whilst in the file explorer so their mappings don't override the explorer's then restore them afterwards which Is what loads of vim ui plugins like NERDTree do, wasn't able to reproduce the crash 😟

I ended up implementing the functionality to temporarily save, remove then restore a users bindings only to discover that the bug persists despite this 😭 , I was so sure it was due to the bindings I didn't try a simple unmap to see if that helped. Anyway It seems like potentially very useful functionality to have for many reasons like a user using an oni config to set their vim keybindings etc. so can make PR if you'd like to see the work that entailed.
Re. this bug ill keep looking but if you have any ideas re the movement issues, I'm having the same on the welcome screen i.e. I'm unable to use the onivim navigation

Thanks for all your help here, @Akin909 ! It's helpful to know that turning off the config made it work (there were some other bugs related to navigation that I thought I fixed, so I wasn't sure if it was still those or something else).

I'm thinking that it might be a good idea to temporarily remove a user's default h,j,k,l binding whilst in the file explorer so their mappings don't override the explorer's then restore them afterwards which Is what loads of vim ui plugins like NERDTree do, wasn't able to reproduce the crash 😟

Seems reasonable. We actually use a second Neovim instance for these 'extra-UI' pieces, like the sidebar, panes, and welcome screen - we could switch that to not load the users init.vim at all. Might be safer to minimize conflicts in those cases!

I ended up implementing the functionality to temporarily save, remove then restore a users bindings only to discover that the bug persists despite this 😭 , I was so sure it was due to the bindings I didn't try a simple unmap to see if that helped

Oh man sorry you went to those lengths! I'm guessing this might not have worked if it was run against the main Neovim instance.


update copy + graphic for WebAssembly card; add WebVR card; reorder cards

r+ per https://github.com/mozilla/moz-games/issues/131#issuecomment-322837282


Feature/hardware concurrency demo

Hardware concurrency demo project

@addyosmani
https://adaptive-loading.web.app/cra-hardware-concurrency-considerate-code-splitting/
This is the firebase deployed URL.


ci: fix flaky test_pyobject_drop_without_gil_doesnt_decrease_refcnt

Closes #2723
I think @adamreichold is correct in what causes the flakiness, and the solution in this case seems straightforward enough - just pass reference off to another thread to drop it (as that thread won't have the GIL), no events needed.

Yet Clippy can never be appeased...

bors r=adamreichold

@bors r=me

(I suspect bors does not listen to me since I could not push to the protected branch any way, but let's try nevertheless.)
bors r+

I suspect bors does not listen to me

Hmm looks like just worked here, can check its config if you think there's an issue?
Thanks for fixing up this one 😁


componentwise config

enable vae.encode compile:
A100 speedup

original VAE: 1 step LCM sdv1.5 - 24ms speedup! (0.062s -> 0.038s) (I think it doesn't actually work though)
taesd: (4step LCM sdv1.5) - 2ms (0.058s -> 0.056s)

@jon-chuang vae.encode now is compiled through https://github.com/chengzeyi/stable-fast/commit/c152145a4fe3061afc21cc58bf892eeae60c142f


Include create-env secrets in credhub

Hi, we had some trouble in the past maintaining our secrets files for the bosh directors. Most of the time we keep them on our jumphost and in 1Password. But its hard to keep the secrets up to date in the 1Pass and not to lose it on the jumphost by an accidental rm.
What do you think about a feature in bosh-deployment that checks after create-env is finished if a credhub is deployed with the director and then imports all the director secrets there?
Think about it, after i made a bosh create-env, i only have to remember my credhub credentials. This will also give me an easy solution for updating the bosh director with Concourse since the credentials are available from within the director.
We are facing the same problem with bosh state file. For me it would be great if we could either move it into credhub as well, or if the director is able to generate it with an cli command.
best,
Dennis

Have a look at https://github.com/cloudfoundry/bosh-cli/pull/407 as one possible path forward.
I don't think you want the credentials for your BOSH stored inside the same BOSH VM. If anything goes wrong with your BOSH VM you can't get the credentials back out to redeploy it?
One idea I've had is to resurrect the Binary BOSH idea [1] for BOSH/UAA/Credhub - where your BOSH is deployed by a 2nd "meta" BOSH, and in return the meta BOSH is deployed by the primary BOSH. The secrets for each BOSH is held in the alternate BOSH's credhub.
[1] https://starkandwayne.com/blog/resurrecting-bosh-with-binary-boshes/


fix distrbute sdk code example missing brace

and emphasize calling DontCheckForUpdatesInDebug BEFORE LoadApplication()

@ichpuchtli thanks, I'll have the PM take a look at the changes and merge.


Added call-bind-apply folder

Issue:- #63
I created chapter on call(), apply(), and bind() methods under "Advanced Functions & Concepts".
Here is the output
https://github.com/user-attachments/assets/9d9d7b10-9106-4b6f-98e5-3e87e6c603f8
If any improvements are needed, please let me know.

@Arushi-N4 can you add your all changes in single commit because after merging, all your 5 commits will show in main branch which can be cumbersome?
Follow these steps -

take new fork of this repository in new folder or take a new clone.
copy all your changes and combine them all in single commit.

then push your changes and create new PR
I hope you understand this and if you have any doubts then tell me.

I got it
Check this out
https://github.com/neerajrathore/javascript-handbook/pull/117


feat: add local faucet for the create-fuels app

Closes #1852
https://github.com/FuelLabs/fuels-ts/assets/39617427/d2889151-92fe-40af-ac1e-72a63c173491
The create-fuels template app now provides a local faucet and uses a local burner wallet to execute transactions.
Previously, the app was using a hardcoded key to sign all transactions. This key is now being used as the key for the faucet, and the burner wallet is being used to execute transactions.
For convenience, the burner wallet is persisted in local storage so that it can be used across multiple sessions.
The burner wallet is also topped up with 10,000 coins on first load.
This is an important step towards adding support for the Fuel Wallet SDK, which will allow users to sign transactions using their own wallets. Having a faucet of some sort that would let users fund their own wallets was necessary.

@arboleya

I think we should keep this the only template for now since you this template does not really introduce a lot of overhead that you might want to opt out of as a user. The original template was 'incomplete' and this PR is one step towards making it 'complete' - is how I see it. Once the template is deployment-ready with wallet connections etc, then we should explore the possibilities of different templates using different frameworks and environments. I think almost everyone would want wallet connections and burner wallets/faucets for local development baked in. The difference of choices might come down to what frameworks/development tooling people prefer like Next, Vite, Svelte, or something else.

I don't think so actually. I think it's still a template that lets you build your own Fuel applications. It just gives you a solid development environment and other tools to make things easier. Yes, it should be using wallet connections using the Wallet SDK and that's what I'm gonna add next once this PR is merged. This PR is a precursor to that.


Versions disappeared on conda-forge

Comment:
Hi @jan-janssen,
I just realized that all versions but 2.1.0 and 1.8.0 have disappeared (see https://anaconda.org/conda-forge/pylops/labels).
Do you know why this happened and if we can restore it?

@mrava87 I am confused, for me they are still listed under https://anaconda.org/conda-forge/pylops/files?page=2

Interesting, I see them too :) one of my students was trying to install pylops 1.18.3 in conda-forge and was getting an error (version not found). Let me try to trouble shoot.
Thank for the quick reply!

@mrava87 It could depend on your students hardware, for example if they have an Apple ARM Mac and try to build an all ARM conda environment than this fails, because we only added Apple ARM support for 2.1.0

Indeed, I see :)


frequently print warn log cause cpu using increase

Please answer these questions before submitting your issue.
2020-08-29 07:32:06,113 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-1] WARN  [] - Pick up system reserved threshold 500ms because of config missing

Why do you submit this issue?
[x] Question or discussion
[ ] Bug
[ ] Requirement
[ ] Feature or performance improvement

Question

What do you want to know?

Bug

Which version of SkyWalking, OS and JRE?
skywalking 7.0，os linux，jre jdk8

Which company or project?

What happened?
If possible, provide a way to reproduce the error. e.g. demo application, component version.

Requirement or improvement

Please describe your requirements or improvement suggestions.

2020-08-29 07:32:02,777 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-7] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,458 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-9] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,487 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-14] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,531 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-9] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,593 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-11] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,638 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-6] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,640 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-7] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,742 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-12] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,866 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-5] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:03,867 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-14] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:04,040 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-3] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:04,106 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-10] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:04,106 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-7] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:04,356 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-15] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:04,356 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-2] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,138 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-15] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,139 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-3] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,217 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-13] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,218 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-5] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,247 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-10] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,248 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-1] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,409 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-4] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,412 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-14] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:05,645 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-1] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:06,113 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-1] WARN  [] - Pick up system reserved threshold 500ms because of config missing
2020-08-29 07:32:06,138 - org.apache.skywalking.oap.server.core.analysis.ApdexThresholdConfig - 64 [grpcServerPool-1-thread-6] WARN  [] - Pick up system reserved threshold 500ms because of config missing

Put this file https://github.com/apache/skywalking/blob/master/oap-server/server-core/src/test/resources/service-apdex-threshold.yml in the config folder.
This has been fixed in the 8.x release.

Put this file https://github.com/apache/skywalking/blob/master/oap-server/server-core/src/test/resources/service-apdex-threshold.yml in the config folder.
This has been fixed in the 8.x release.

我在apache-skywalking-apm-bin-8.x版本仍然遇到同样的问题，我的service-apdex-threshold.yml中包含了链接拥有的配置。我应该如何解决？
I still had the same problem with the Apache-Skywalk-apm-bin-8.x version, and my service-apdex-threshold-yml included the link-owned configuration. How can I solve it?


Form: filled? fails to validate

require 'bundler/setup'
require 'dry-validation'

form = Dry::Validation.Form do
  required(:foo).maybe(:filled?)
end

result = form.call('foo' => ['23'])
puts result.success?
puts result.messages[:foo].inspect

__END__

Expected:
  true
  nil

Actual:
  false
  ["is missing"]

GIT
  remote: git://github.com/dry-rb/dry-logic.git
  revision: e649fad58546e8e53a048d310c554ad910466a93

GIT
  remote: git://github.com/dry-rb/dry-types.git
  revision: 394fa8b62966fd398f84b83cc712e5b1355f4af7

GIT
  remote: git://github.com/dry-rb/dry-validation.git
  revision: 59fb0a09c4997db95076b49082dc68445ead4630

Similar case:
required(:foo).maybe(:filled?)

result = form.call('foo' => ['23'])

On the opposite side, it fails to return an error in case of blank input:
required(:foo).maybe(:filled?)

result = form.call('foo' => '')

__END__

Expected:
  false
  ["is missing"]

Actual:
  true
  nil

Wrong error message:
required(:foo).maybe(:filled?)

result = form.call('foo' => [])

__END__

Expected:
  false
  ["must be filled"]

Actual:
  false
  ["is missing"]

Similar to: https://github.com/dry-rb/dry-validation/issues/130#issuecomment-216463576
optional(:foo).maybe(:filled?)

result = form.call('foo' => '')

__END__

Expected:
  false
  ["must be filled"]

Actual:
  true
  nil

Similar to: https://github.com/dry-rb/dry-validation/issues/130#issuecomment-216463925
optional(:foo).maybe(:filled?)

result = form.call('foo' => [])

__END__

Expected:
  false
  ["must be filled"]

Actual:
  true
  nil

Looks like more issues with maybe (especially re: the wrong error messages), but I think there may be a few cases of misunderstanding here.
In the cases where you say "it fails to return an error in case of blank input", e.g. with:
required(:foo).maybe(:filled?)
result = form.call('foo' => '')

and
optional(:foo).maybe(:filled?)
result = form.call('foo' => '')

and
optional(:foo).maybe(:filled?)
result = form.call('foo' => [])

In all these cases, it seems to me like maybe(:filled?) behaving in the right way. It expands in that case to none? | filled?, which means that blank input is actually valid, and therefore the validation should succeed and return no error messages. Does that make sense to you?

@timriley Yes, it makes sense. I'm sorry for this false alarm. 😄


Decide what to do with property tserver.last.location.mode

The property tserver.last.location.mode can have a value of assignment or compaction. When its compaction it sets the tablets last location when a tablet compacts on a tserver.  However since tablet servers no longer compact tablets this property may no longer be have a reason to exists.
Noticed this while working on #3592

If tservers and compactors are running on the same host, this it's possible that compaction could still have an effect.

While it may still have an effect, and could still be useful, I would like to point out that the reason the property exists was mainly to change the default assignment behavior to the assignment mode. Prior to this property existing, the default behavior was hard-coded in the compaction mode. The compaction mode itself was a best-effort to achieve data locality. It's not clear that the benefits were very substantial, though. Tablets can migrate around, and the location where data was most recently compacted may not even be the location where most of the tablet's data is stored. It's also possible that none of the user's data is local, even with the mode set to compaction... as that's dependent on very specific assumptions about HDFS behavior that may not hold (the assumption that there's a local copy made for each block replica). A lot of those assumptions fall through when you consider erasure coding instead of replication, data S3 instead of HDFS, differences in user configuration for replication, the fact that a data node might not even be running on the same node as the tserver, etc.
I think this property could be removed if users have more metrics about where tablet files are being compacted, and could use that information to exercise fine-grained control over tablet assignments by some other means. Then again, in a world where most of Accumulo is offline and hosted only ondemand, I'm not sure it's really going to matter, because we're no longer going to care as much about balancing thrashing or churn on assignment locations due to rebooting a cluster.


Error code 'forwarding'

Describe the bug

In the case where a client makes a request to server A, and an exception is thrown in server A because of an error response from server B, we should try to preserve error codes where they make sense in the response to the ultimate client

For example: Client calls plookup on Server A; Server A  calls lookup on Server B; server B returns "error:AT0015-Key not found : ..."

@sitaram@lookup:phone@murali
error:null-null : Request to remote secondary @murali at vip.ve.atsign.zone:7001 received error
  response 'error:AT0015-key not found : @sitaram:phone@murali does not exist in keystore'

Server A will currently throw an AtConnectException with the error response it got from B, providing the additional information that it came from B

The "null-null" is caused by https://github.com/atsign-foundation/at_tools/issues/152

Expected behaviour

When returning to the client we would like to preserve that AT0015 (key not found) as it is most correct, but provide the additional context of the full error message from the other end. For example:

   @sitaram@lookup:phone@murali
   error:AT0015-key not found : Request to remote secondary @murali at vip.ve.atsign.zone:7001 received error
     response 'error:AT0015-key not found : @sitaram:phone@murali does not exist in keystore'

This can be achieved in outbound_message_listener, for example, by having it

When there's an error code from remote server, inspect it and match it to its corresponding AtException

If there is a matching Exception then throw that, adding the entire message received from remote
Else do what's being done now (throw AtConnectException)

Consider extending at_commons error_message.dart with a way to create (not throw, just create) the correct exception given an error code. (We currently have mapping from exception to error-code but not the other way around)

The changes are completed in the following PR: https://github.com/atsign-foundation/at_server/pull/841

Dependent issue
https://github.com/atsign-foundation/at_server/issues/691

The changes are merged to trunk branch: json_encode_error_message

@kalluriramkumar is this ticket complete, should it be closed?

@gkc : The changes are yet to released into canary. Hence the ticket is open.
Currently facing issue in releasing code to canary. Following is the issue:
Run sed -i '0,/version/ s/version\:.*/&+${GITHUB_REF#refs/tags/}/' pubspec.yaml
  sed -i '0,/version/ s/version\:.*/&+${GITHUB_REF#refs/tags/}/' pubspec.yaml
  shell: /usr/bin/bash -e {0}
  env:
    working-directory: at_server
    VERSION: c3.0.[2](https://github.com/atsign-foundation/at_server/actions/runs/3082036906/jobs/4981321618#step:4:2)[3](https://github.com/atsign-foundation/at_server/actions/runs/3082036906/jobs/4981321618#step:4:3)c
sed: -e expression #1, char [4](https://github.com/atsign-foundation/at_server/actions/runs/3082036906/jobs/4981321618#step:4:4)[7](https://github.com/atsign-foundation/at_server/actions/runs/3082036906/jobs/4981321618#step:4:8): unknown option to `s'

The same command works fine in e2e_test_prep action.

The changes are related to canary servers in v3.0.23

The changes are released to production. Hence closing the git issue.


[Android] Transfer-Encoding: chunked' header can not be used when content object is not specified.

Please check all of the platforms you are having the issue on (if platform is not listed, it is not supported)

[ ] iOS
[x] Android
[ ] UWP
[ ] watchOS
[ ] tvOS
[ ] Tizen
[ ] .NET Standard

Feature Library

[ ] Core
[ ] BluetoothLE
[ ] Beacons
[ ] Locations
[x] HTTP Transfers
[ ] Notifications
[ ] Sensors

Version of Library
<IP_ADDRESS>0-beta
Version of OS(s) listed above with issue
All
Steps to Reproduce

Create an Android app with Shiny
Try to download a file

Expected Behavior
File should be downloaded
Actual Behavior
Error thrown as title

Please provide the entire stack trace as well as a device & android version.  I use the android download manager, so this likely isn't a bug, but I would like to be sure.

Hi @aritchie ,
I created an instance of HttpClientHttpTransferManager, and my sample code was use TransferJob, not the Android download manager.
Regards.

That isn't even done or documented.  You should be using the default stuff for now.  Please make sure to include these details in the future.


Types align on M5

Adapt some imports, add shims for change to Growable/Shrinkable, where += is now final and addOne is the template method. Shims should be cleaned up and tested.
Tried it out on House of Mirrors, which I couldn't get to compile on 2.9.x any more, but with an import tweak and workaround XML code that was made private in 2011, it runs. Will check how much it exercises.
Fixes scala/scala-swing#84

Failure due to MIMA. What does compatible mean on 2.0.x?

Maybe the changes can be made in a binary compatbile way?

Maybe the maintainers would prefer 2.13 on 3.0, without shims.

Next major version would be 2.1.x; I don't think binary compat is a major point now. People could probably just just 2.1.x source compatible, or otherwise use 2.0.x for Scala <= 2.12 and 2.1.x for Scala >= 2.13. Anyway, I agree with @lrytz that at least we should look into the possibility of having compatible return types. I will see if I can clone the PR and look into that.

Thanks @som-snytt for doing a great chunk of the work. Im happy to call this 2.1.x for 2.13+ if that clears the mima hurdle, haven't yet looked at the error in detail.

I'm trying, based on your work, a version that puts the shims directly into the places, splitting BufferWrapper into two source code dirs. Hopefully another PR soon.

@Sciss Thanks for the opportunity to help a bit.

Thank you - I basically created the new PR based on your work and the understanding I gathered from it. If you find time to look at it, it will be very much appreciated.


Fix #576

See #576 - Combining props and children via append leads to a children property being added to props.
I observed this when working on the dynamic toolbar when passing props via reference and adding a child via append at the same time.
E.g.
$$(StrongTool, toolState.strong).append($$(Icon, {icon: 'fa-bold'}))

leads to toolState.strong.children being set. In debug mode I even get two VirtualComponent entries here as the manipulated props object is used for the second render.
@oliver---- Can you have a look?

Wrong base.


Add SimpleTransformer model to transformer ensemble

Describe your changes

Checklist before requesting a review

[ ] I have performed a self-review of my code

Check the correct box. Does this PR contain:

[ ] Breaking changes
[ ] New functionality (new method, new metric, ...)
[ ] Major changes
[ ] Minor changes
[ ] Bug fixes

[ ] Proposed changes are described in the CHANGELOG.md

[ ] CI Tests succeed and look good!

only used for testing


Increase test coverage for completion providers, fix found bugs

This increases test coverage for the completion providers and fixes a few bugs found during that process:

4c0d60cc8ad17f42ce09fbd5ac0d370dad316da9 - Corrects the detection of the tag name while performing event completions
8c143522aaf6e12102ba42d426dcc238ef7fc3c2 - Fixes the path detection in getTargetPath
08c9f99d5c49713777d5a8c2ccd2aeaa2d8679e2 - Fixes detection of view tags when providing suggestions in view controllers
a8087e28374ded38667507a41bc86e799bb09bef - Explicitly ignore Alloy.CFG in controller completions as we want to fall through
92e411aaff2c0daef32c44c070bc3d9574edcb5f - Corrects the alloy assets path for images
b89d13b2ed486f3bdb8d3bee59e04106222c5d4b - Correctly formats the controller/lib filenames when returning results on Windows

Messages

:book:

:white_check_mark: All tests are passing
Nice one! All 54 tests are passing.

:book:

:floppy_disk: Here's the built vsix for this change.

  Generated by :no_entry_sign: dangerJS against b89d13b2ed486f3bdb8d3bee59e04106222c5d4b


Mutations/Input types break schema creation in AWS

Describe the bug
Adding mutations/input types to the schema causes the schema creation to fail when deployed to AWS lambda. The stack trace/error message don't contain any details:
module initialization error: Error at invariant (/var/task/node_modules/graphql/jsutils/invariant.js:21:11) at typeMapReducer (/var/task/node_modules/graphql/type/schema.js:299:57) at typeMapReducer (/var/task/node_modules/graphql/type/schema.js:295:12) at Array.reduce (<anonymous>) at typeMapReducer (/var/task/node_modules/graphql/type/schema.js:327:38) at Array.reduce (<anonymous>) at new GraphQLSchema (/var/task/node_modules/graphql/type/schema.js:145:28) at Function.generateFromMetadataSync (/var/task/node_modules/type-graphql/dist/schema/schema-generator.js:31:24) at Object.buildSchemaSync (/var/task/node_modules/type-graphql/dist/utils/buildSchema.js:22:55) at Object.<anonymous> (/var/task/src/graphql.js:1:2604)
To Reproduce
See repo with instructions how to reproduce https://github.com/orantwolinkme/type-graphql
Expected behavior

Schema creation in AWS lambda should work correctly with mutations/input types
A descriptive error message

Enviorment (please complete the following information):

AWS Lambda
Node 8.10
Package version 0.17.4
TypeScript version 3.4.5

I bet that the problem is with transpiliing the code using a webpack.
Are you able to reproduce the issue not using the AWS but only the webpack config used by it?
Without debugging possibility I'm afraid I can do nothing about it 😞

It is a webpack issue. In the code I uploaded in webpack.config.js there are settings for mode and devtool:
    mode: slsw.lib.webpack.isLocal ? 'development' : 'production',
    devtool: slsw.lib.webpack.isLocal
        ? 'cheap-module-eval-source-map'
        : 'source-map',

The setting that's breaking it is devtool using 'source-map' when not deployed locally
Changing devtool setting to:
    devtool: 'cheap-module-eval-source-map',

works

The call stack when it fails is:
"[
  "Error: Schema must contain uniquely named types but contains multiple types named \"c\".",
  "at invariant (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\graphql\\jsutils\\invariant.js:21:11)",
  "at typeMapReducer (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\graphql\\type\\schema.js:299:57)",
  "at typeMapReducer (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\graphql\\type\\schema.js:295:12)",
  "at Array.reduce (<anonymous>)",
  "at typeMapReducer (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\graphql\\type\\schema.js:327:38)",
  "at Array.reduce (<anonymous>)",
  "at new GraphQLSchema (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\graphql\\type\\schema.js:145:28)",
  "at Function.generateFromMetadataSync (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\type-graphql\\dist\\schema\\schema-generator.js:31:24)",
  "at Object.buildSchemaSync (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\type-graphql\\dist\\utils\\buildSchema.js:22:55)",
  "at Object.<anonymous> (C:\\Dev\\Learning\\type-graphql-minimal\\.webpack\\service\\src\\graphql.js:1:2604)",
  "at n (C:\\Dev\\Learning\\type-graphql-minimal\\.webpack\\service\\src\\graphql.js:1:220)",
  "at C:\\Dev\\Learning\\type-graphql-minimal\\.webpack\\service\\src\\graphql.js:1:1019",
  "at Object.<anonymous> (C:\\Dev\\Learning\\type-graphql-minimal\\.webpack\\service\\src\\graphql.js:1:1028)",
  "at Module._compile (internal/modules/cjs/loader.js:701:30)",
  "at Object.Module._extensions..js (internal/modules/cjs/loader.js:712:10)",
  "at Module.load (internal/modules/cjs/loader.js:600:32)",
  "at tryModuleLoad (internal/modules/cjs/loader.js:539:12)",
  "at Function.Module._load (internal/modules/cjs/loader.js:531:3)",
  "at Module.require (internal/modules/cjs/loader.js:637:17)",
  "at require (internal/modules/cjs/helpers.js:22:18)",
  "at Object.createHandler (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\serverless-offline\\src\\functionHelper.js:192:17)",
  "at handler (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\serverless-offline\\src\\index.js:624:40)",
  "at Object.internals.handler (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\handler.js:101:51)",
  "at request._protect.run (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\handler.js:32:23)",
  "at module.exports.internals.Protect.internals.Protect.run (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\protect.js:60:12)",
  "at exports.execute (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\handler.js:26:22)",
  "at each (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\request.js:401:16)",
  "at iterate (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\items\\lib\\index.js:36:13)",
  "at done (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\items\\lib\\index.js:28:25)",
  "at internals.Auth.payload (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\auth.js:235:16)",
  "at each (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\request.js:401:16)",
  "at iterate (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\items\\lib\\index.js:36:13)",
  "at done (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\items\\lib\\index.js:28:25)",
  "at onParsed (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\route.js:341:20)",
  "at Subtext.parse (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\hapi\\lib\\route.js:380:20)",
  "at next (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\subtext\\lib\\index.js:46:26)",
  "at Wreck.read (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\subtext\\lib\\index.js:243:16)",
  "at finish (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\wreck\\lib\\index.js:374:20)",
  "at wrapped (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\wreck\\node_modules\\hoek\\lib\\index.js:879:20)",
  "at module.exports.internals.Recorder.onReaderFinish (C:\\Dev\\Learning\\type-graphql-minimal\\node_modules\\wreck\\lib\\index.js:449:16)",
  "at Object.onceWrapper (events.js:277:13)",
  "at module.exports.internals.Recorder.emit (events.js:194:15)",
  "at module.exports.internals.Recorder.EventEmitter.emit (domain.js:459:23)",
  "at finishMaybe (_stream_writable.js:641:14)",
  "at endWritable (_stream_writable.js:649:3)",
  "at module.exports.internals.Recorder.Writable.end (_stream_writable.js:589:5)",
  "at IncomingMessage.onend (_stream_readable.js:651:10)",
  "at Object.onceWrapper (events.js:277:13)",
  "at IncomingMessage.emit (events.js:194:15)",
  "at IncomingMessage.EventEmitter.emit (domain.js:441:20)",
  "at endReadableNT (_stream_readable.js:1125:12)"
]"

Ok, so the problem is with production webpack and code minification. You have to disable it.

That's what I'm doing for now. Is there going to be a fix for this or is it outside the scope of this project?

@19majkel94 I got similar issue with sequelize and type-graphql during schema creation
(node:3715) UnhandledPromiseRejectionWarning: Error: Cannot determine GraphQL output type for genres
    at Function.getGraphQLOutputType (/SYS/PROJECT/WEB/PROJECT/node_modules/type-graphql/dist/schema/schema-generator.js:394:19)
    at objectType.fields.reduce (/SYS/PROJECT/WEB/PROJECT/node_modules/type-graphql/dist/schema/schema-generator.js:174:44)
    at Array.reduce (<anonymous>)
    at fields (/SYS/PROJECT/WEB/PROJECT/node_modules/type-graphql/dist/schema/schema-generator.js:168:56)
    at resolveThunk (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/definition.js:381:40)
    at defineFieldMap (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/definition.js:563:18)
    at GraphQLObjectType.getFields (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/definition.js:518:27)
    at typeMapReducer (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/schema.js:320:61)
    at typeMapReducer (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/schema.js:295:12)
    at typeMapReducer (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/schema.js:330:22)
    at typeMapReducer (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/schema.js:295:12)
    at typeMapReducer (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/schema.js:330:22)
    at Array.reduce (<anonymous>)
    at new GraphQLSchema (/SYS/PROJECT/WEB/PROJECT/node_modules/graphql/type/schema.js:145:28)
    at Function.generateFromMetadataSync (/SYS/PROJECT/WEB/PROJECT/node_modules/type-graphql/dist/schema/schema-generator.js:31:24)
    at Function.<anonymous> (/SYS/PROJECT/WEB/PROJECT/node_modules/type-graphql/dist/schema/schema-generator.js:16:33)
    at Generator.next (<anonymous>)
    at /SYS/PROJECT/WEB/PROJECT/node_modules/tslib/tslib.js:110:75

Is there going to be a fix for this

You can place the full name in the decorator - @ObjectType("fullName") - so it won't use the minified class names.

Closing for a housekeeping purposes 🔒

@leonetosoft I think that only class names are minified.


Show created at and/or updated at timestamp in telegraf config table

Breaking this out of https://github.com/influxdata/influxdb/issues/11527

The telegrafs api doesn't come back with created at/updated at timestamp. Blocked on API.


some items have no description, even though they do have in DC

see: http://www.oldnyc.org/#711945f-a
and: http://digitalcollections.nypl.org/items/510d47dc-fdf7-a3d9-e040-e00a18064a99
among many others

I dropped the image description when it was just cross-streets. You can already get them from the map (and presumably you just clicked on the location), so they're redundant & in very large type.

we would like them there if that's ok with you. we do not mind that redundancy

It's a pretty big waste of space, especially on small screens.
As an alternative, I could include the location text above the image grid, where it would be shared between all images.
Or under the map in the left gutter.

if you prefer to do that... as long as there is some title text applicable to the photos... and as long as "1945" or "No Date" doesn't look like the title of the photo

Closing in favor of #82.


Pass Group ID for Workspace

Certain workspaces (particularly those with spaces in their names) seem to have issues. This could be avoided if there were a way to specify the group/workspace ID instead of the group name in the actions settings. Thoughts?

I discovered an additional possible bug while looking into this. It looks like the check for conflicts on publish only reviews reports. This can cause problems in situations where one would want to publish an updated dataset for "mydata.pbix", and there is no report in the workspace for "mydata.pbix". Because there is no report, the process assumes there's no conflict and no overwrite. Once it attempts to publish a dataset, it seems to encounter a conflict it did not expect and fail.

I can also see this problem, I tried using groupId instead and it worked.

Hi @jknix,
Do these issues still appear? At the moment I'm working on a updated version with some large changes. Are you able to check when the release is done?


Planner: UI in some cases shows target charging start start in the past

Describe the bug
UI shows charging planner start in the past, when target SoC is already reached but target time is not.
See image:

Time of Screenshot 6:30
Charging target time 7:00
Charging target 95% reached
Text shows: "Zielladen geplant. Ladung startet heute 02:45"

Steps to reproduce

Set a SoC Target
Use either dynamic tarif or CO2 data (I did CO2)
Set a target time in the future
The planner uses charging slots except at least the last hour slot of the target time
Open the UI in such a slot close to the end where SoC is reached but time is not

Configuration details
Nothing special

Log details
Might not be required, can be provided if needed

What type of operating system are you running?
Linux
Version
0.115.0

@DerAndereAndi debug Log wäre super- das darf egtl (tm) schon im Backend nicht passieren.

Hier das entsprechende Log. Das Laden wurde um 2:46 beendet.
log.txt


[MINOR] made some optimisation

Motivation
Made some optimization in file.
Modifications
removed the repetition of function call.
Documentation

Does this pull request introduce a new feature? (no)

The current pr has a duplicate fix with pr #3599.

okay, thanks for helping.


Deleting prod domain fails

I tried to delete the prod domain after archiving it: This results in a strange Git error:
[aquilon@vm-79119 /]$ aq del domain --domain prod --justification emergency --reason "remove domain created for unit tests"
Bad Request:
Cloning into 'trash'...
fatal: Remote branch trash not found in upstream origin
fatal: The remote end hung up unexpectedly

Attempt to create the trash branch (does not really make sense) triggers another error referring to missing identity configuration in Git which is also strange (as it is done and not reported for other commands):
[aquilon@vm-79119 /]$ aq del domain --domain prod --justification emergency --reason "remove domain created for unit tests"
Bad Request:
error: duplicate parent 705efacbfcc749cf681f618c9f9cbf3230b2ba0d ignored

*** Please tell me who you are.

Run

  git config --global user.email<EMAIL_ADDRESS>  git config --global user.name "Your Name"

to set your account's default identity.
Omit --global to set the identity only in this repository.

fatal: empty ident name (for<EMAIL_ADDRESS>not allowed

@jouvin
Creating a trash branch should be a part of intial quattor aquilon setup and should be added to the docs here: http://www.quattor.org/aquilon/00-install.html (in the Git Daemon Configuration section).
Not sure how you added the 'trash' branch, it would be forbidden to create the trash branch using add domain command as this name is 'reserved':
https://github.com/quattor/aquilon/blob/upstream/lib/aquilon/worker/dbwrappers/branch.py#L144
Anyway, why not setting up git config --global user.email<EMAIL_ADDRESS>& git config --global user.name "Your Name"? Especially, if it is in the set up documentation for quattor aquilon anyway:
http://www.quattor.org/aquilon/00-install.html (at section Git Daemon Configuration).
Let me know if after setup of user and email there are still issues with deleting domain.
Btw, one can change the 'trashs' domain name specifying it in the settings (so potentially it can be changed to any existing branch):
[broker]
trash_branch = unittest_trash

@urbonegi thanks for your answer. I have not payed enough attention to the fact that the failure may have been caused by the missing Git configuration. I'll try again and let you know if this is enough to remove the error. If you don't mind, let this is issue open but I am not sure I'll be able to do a test anytime soon. May be later in July.

@jouvin Have you looked at this one? You should create trash branch manually using git commands. Setting git username and email also should be done as part of Application setup. Maybe we could close it?

This is the file that needs amending: https://github.com/quattor/quattor.github.com/blob/master/_aquilon/00-install.md

Discussed at RAL workshop: missing step from documentation, probably should be scripted, but at least documented.

https://github.com/quattor/quattor.github.com/pull/225


Fix integer overflow bug

@kohkaixun there's merge conflict, can try and resolve?

I have posted a query on the forum to check if such a fix is allowed. Let's wait for Prof's reply before proceeding?

Oh no, ok we can implement it in the dg instead @eugenetangkj .

Cannot fix, but explained in developer guide at #202.


Fixed possible XSS bug in md-loader style binding

Got some Ember deprecation warnings in my console about a possible XSS bug. Found it was in md-loader, computed property barStyle.

This is failing tests
https://travis-ci.org/sgasser/ember-cli-materialize/jobs/60497134#L452-L461

I think all you'll need to do here is something like
return Ember.String.htmlString(`width: ${parseInt(this.get('percent'), 10)}%`);

The reason your PR is failing tests is because we have prototype extensions disabled for this addon


Audio does not work in Mobile Safari, iOS WKWebView, and Android Browser

@bfirsh, sound emulation via Web Audio API does not work in iOS 10 Mobile Safari, iOS WKWebViews, or Android browsers. Unlocking the audio context on a touchend event before loading a ROM from the list might resolve the issue. Sound is working fine in my Chrome and Firefox desktop browsers, though.
https://jsnes.fir.sh/ (open web ui in mobile browser)
Originally reported here:
https://github.com/bfirsh/jsnes/issues/52

Thanks for the report!

With iOS 14.5 I am able to get sound in Mobile Safari as long as  this.Emulator.speakers.start(); is called in a button handler for a client touch or click event (thus unlocking the AudioContext via direct interaction)


Arduino code with ROS

This issue has the system main codes which is divided for two  codes the first one is the movement code and the second one is for the sensor code.

Movement code:
Handles the speeds of the motors as inputs and the feedback from sensors to be used in the motion control system.
Sensors code:
Handles the sensors libraries and calculations to be sent later to the movement code.
PS: Documentation hasn't been finished yet

I made a pull request to the main not embedded


.Net: When adding AzureOpenAI chat completion with a custom credential add additional override that accepts a HttpClient

One thing we noticed looking at the solution for SK to work with Substrate's LLMApi
When using this pattern.
var services = new ServiceCollection();
// Add the kernel and plugins to the service collection.
services.AddKernel();
services.AddAzureOpenAIChatCompletion("gpt-4-turbo", "[https://es365-aoai-eastus2.openai.azure.com/"](https://es365-aoai-eastus2.openai.azure.com/%22), new DefaultAzureCredential(includeInteractiveCredentials: true));

There is not an override that accepts the httpClient.

There is not an override that accepts the httpClient.

With DI, you typically expect the HttpClient to come from the DI system.  Is that not appropriate for their scenarios? i.e. why would they be getting the SK-related types from DI but not want the HTTP-related components to also come from DI?

With DI, you typically expect the HttpClient to come from the DI system. Is that not appropriate for their scenarios? i.e. why would they be getting the SK-related types from DI but not want the HTTP-related components to also come from DI?

I agree, I also created unit test that verifies that this scenario works as expected:

Closing this issue as this is by design. See: https://github.com/microsoft/semantic-kernel/issues/5065.


Is there a link to KeyVault after import?

I miss information about the behavior when imported a certificate from KeyVault.
Will there be a link to KeyVault or is it just a one-time operation? (not in sync with new versions of the certificate)

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

ID: 36657265-6c54-f354-9e09-51f5f23d6ba5
Version Independent ID: bad1c0d1-b706-107a-3f15-e3e8d46b7e28
Content: Tutorial - Import a certificate in Key Vault using Azure portal
Content Source: articles/key-vault/certificates/tutorial-import-certificate.md
Service: key-vault
Sub-service: certificates
GitHub Login: @msmbaldwin
Microsoft Alias: sebansal

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

@martinoss
Can you clarify what you mean by is there a link to the Key Vault after import.
For more information on certificates:
Importing Azure Key Vault certificates FAQ
About Azure Key Vault certificates
Import Certificate - Import Certificate
If you have any other questions, please let me know.
Thank you for your time!

Hi @JamesTran-MSFT
I wondered, if the imported certificate (form KV) on the AppService will update too, when I add a new version of the certificate in KeyVault.

@martinoss
When it comes to certificate rotation I found a Stack Overflow post that will answer your question.

"The Web App service runs a background job that periodically (once a day ) that syncs all App Service certificate..."

Thank you for your time and patience.


[tflite][quantization][deeplabv3] Constant array MobilenetV2/expanded_conv_7/depthwise/depthwise_weights lacks MinMax information

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):no
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):Ubuntu 16.04
TensorFlow installed from (source or binary):Source
TensorFlow version (use command below):1.9.0
Python version:2.7.12
Bazel version (if compiling from source):0.12.0
GCC/Compiler version (if compiling from source):5.4.0
CUDA/cuDNN version:cuda-9.0/7.0
GPU model and memory:GeForce GTX 1080/8105MiB
Phone:xiaomi5 (Snapdragon 820)
Exact command to reproduce:
bazel run --config=opt //tensorflow/contrib/lite/toco:toco --
--input_file=/external_home/data/model/deeplabv3_mnv2_pascal_train_aug/frozen_inference_graph.pb
--output_file=/external_home/data/model/deeplabv3_mnv2_pascal_train_aug/kanul.tflite
--inference_type=QUANTIZED_UINT8
--input_shape=1,513,513,3
--input_array=sub_7
--output_array=ResizeBilinear_3

Describe the problem
I have tried to quantize MobileNetV2 for deeplabV3+ with TFlite. But I fail to convert the model.
From the following issue, I saw that the operations were not supported for the option of quantization.
https://github.com/tensorflow/models/blob/master/research/deeplab/g3doc/model_zoo.md
Checkpoint name: mobilenetv2_coco_voc_trainaug
As we can see graphs from the tensorboard, there is one big problem.
In "import/MobilenetV2/expanded_conv_7/depthwise/depthwise",
the operation of depthwise consists of the subgraph with 3 nodes: (depthwise) and BatchToSpaceND, SpaceToBatchND.
But, in "import/MobilenetV2/expanded_conv_6/depthwise/depthwise",
the operation of depthwise is DepthwiseConv2dNative itself.
From the difference, we can not quantize deeplabv3 based on mobilenetv2.
The one thing is that MobilenetV2/expanded_conv_7~16 does not have min/max value to be needed for quantization with tflite.
Although I implement the needed min/max value in hardcode_min_max.cc,
This model does not run well in mobile environments.
The ultimate problem is caused by the fact that depthwise_conv_7~16 consist of 3 nodes including BatchToSpaceND and SpaceToBatchND.
I request you to notify the method to resolve above issues.
Source code / logs
bazel run --config=opt //tensorflow/contrib/lite/toco:toco --
--input_file=/external_home/data/model/deeplabv3_mnv2_pascal_train_aug/frozen_inference_graph.pb
--output_file=/external_home/data/model/deeplabv3_mnv2_pascal_train_aug/kanul.tflite
--inference_type=QUANTIZED_UINT8
--input_shape=1,513,513,3
--input_array=sub_7
--output_array=ResizeBilinear_3
2018-07-11 04:40:01.330069: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] Before pre-quantization graph transformations: 166 operators, 340 arrays (1 quantized)
2018-07-11 04:40:01.330711: W tensorflow/contrib/lite/toco/graph_transformations/hardcode_min_max.cc:339] Tweaking the MinMax of array ResizeBilinear_1, which is an input to {Concatenation operator with output concat}, because we want all inputs and outputs of a Concatenation operator to have the same MinMax so that it can be implemented as a pure byte-copy, no arithmetic.
2018-07-11 04:40:01.332983: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] After pre-quantization graph transformations pass 1: 111 operators, 285 arrays (1 quantized)
2018-07-11 04:40:01.335731: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] Before quantization graph transformations: 111 operators, 285 arrays (1 quantized)
2018-07-11 04:40:01.337575: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_7/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.337670: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.337695: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_7/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.338553: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_8/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.338711: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.338786: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_8/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.339777: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_9/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.339918: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.339985: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_9/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.340933: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_10/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.341034: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.341059: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_10/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.342497: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_11/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.342593: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.342620: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_11/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.344311: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_12/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.344422: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.344452: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_12/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.345978: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_13/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.346094: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.346122: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_13/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.349163: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_14/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.349318: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.349351: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_14/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.353356: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_15/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.353511: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.353545: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_15/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.357264: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_16/depthwise/depthwise_weights lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.357400: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm_mul_0_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.
2018-07-11 04:40:01.357432: W tensorflow/contrib/lite/toco/graph_transformations/quantize.cc:92] Constant array MobilenetV2/expanded_conv_16/depthwise/BatchNorm/FusedBatchNorm_add_param lacks MinMax information. To make up for that, we will now compute the MinMax from actual array elements. That will result in quantization parameters that probably do not match whichever arithmetic was used during training, and thus will probably be a cause of poor inference accuracy.

@tatianashp
How can I get a help to resolve above issues?

@aselle, @andrehentz Can you help?

I also kept on getting similar errors with using a MobileNetV2 backbone for my network.
To solve my issue, I made sure to create the training quantization nodes (tf.contrib.quantize.create_training_graph(quant_delay=quant_delay)) in my training graph with MobileNetV2 training scope:
with tf.contrib.slim.arg_scope(mobilenet_v2.training_scope()):
    <create mobilenetv2 based network>

Where when I created my eval graph with quantization nodes (tf.contrib.quantize.create_eval_graph()), I made sure to load my MobileNetv2 model without the above training scope. This solved all of my errors of having nodes without having min/max information.
I separated my training and evaluation into different scripts/functions in order to make it easier to separate the two graphs.
I then froze my saved checkpoint weights from training with the graph from evaluation, then optimized them for inference, and finally converted to TFLite with TOCO to get a quantized tflite file.
Hope this helps.

Hi @G-mel
Thank you for your comments
I have developed the segmentation based on mobilnetv2.
How could I edit train.py and eval.py to reflect you proposal.
Where should I add the training scope in train.py?
Your suggestion is very helpful
https://github.com/tensorflow/models/tree/master/research/deeplab

I've looked around at the deeplab source code and the code for training scope already appears on lines 58, 85 and 318 in feature_extractor.py.
It also looks like the training scope in DeepLab is handled properly if is_training=False is being passed into the training scope in feature_extractor.py.
you can take a look at mobilenet.py to see how is_training is handled in the scope.
If the train.py and the eval.py training scopes are being handled properly, then you have to add tf.contrib.quantize.create_training_graph(quant_delay=quant_delay) into train.py to rewrite its graph with fake quant nodes, and add tf.contrib.quantize.create_eval_graph() into eval.py in order to rewrite the deeplab graph without training nodes into the eval graph with quant nodes.
Then following the other steps I provided above hopefully converts your deeplab model into a quantized tflite format.

Hi, @G-mel , @kanul ,
I got the same error.
bazel-bin/tensorflow/contrib/lite/toco/toco   --input_file=${MODEL_PATH}/frozen_inference_graph_stripped.pb   --output_file=${MODEL_PATH}/deeplabv3+_quan.lite   --input_format=TENSORFLOW_GRAPHDEF   --output_format=TFLITE   --inference_type=QUANTIZED_UINT8   --input_shapes=1,513,513,3   --input_arrays=sub_7   --output_arrays=ResizeBilinear_3   --std_values=128   --mean_values=127   --dump_graphviz=${MODEL_PATH} 2018-07-24 13:39:12.271875: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 639 operators, 1220 arrays (0 quantized) 2018-07-24 13:39:12.293302: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 639 operators, 1220 arrays (0 quantized) 2018-07-24 13:39:12.537359: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] After general graph transformations pass 1: 166 operators, 340 arrays (1 quantized) 2018-07-24 13:39:12.541454: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] Before pre-quantization graph transformations: 166 operators, 340 arrays (1 quantized) 2018-07-24 13:39:12.541764: W tensorflow/contrib/lite/toco/graph_transformations/hardcode_min_max.cc:105] Tweaking the MinMax of array ResizeBilinear_1, which is an input to {Concatenation operator with output concat}, because we want all inputs and outputs of a Concatenation operator to have the same MinMax so that it can be implemented as a pure byte-copy, no arithmetic. 2018-07-24 13:39:12.543031: I tensorflow/contrib/lite/toco/graph_transformations/graph_transformations.cc:39] After pre-quantization graph transformations pass 1: 111 operators, 285 arrays (1 quantized) 2018-07-24 13:39:12.544625: F tensorflow/contrib/lite/toco/tooling_util.cc:1607] **Array MobilenetV2/expanded_conv_7/depthwise/depthwise/SpaceToBatchND, which is an input to the DepthwiseConv operator producing the output array MobilenetV2/expanded_conv_7/depthwise/depthwise, is lacking min/max data, which is necessary for quantization.** Either target a non-quantized output format, or change the input graph to contain min/max information, or pass --default_ranges_min= and --default_ranges_max= if you do not care about the accuracy of results. Aborted (core dumped)
@suharshs,
It seems that SpaceToBatchND is an unsupported operation in mobilenetv2 ?
@G-mel ,
How do you avoid SpaceToBatchND used in mobilenetv2 ?
I add with tf.contrib.slim.arg_scope(mobilenet_v2.training_scope()): to feature_extractor.py#L60, there will be the same errors!!
Thanks!

Hi all, I had a chance to look into this. The issue is that dilated depthwise convolution isn't yet supported. The contrib/quantize rewrite supports this at HEAD but TOCO/TFLite doesn't have the inference transformations and quantized dilated depthwise convolution kernels implemented. This is something I am trying to complete soon so will keep you posted.
Thanks for your patience!

Hi @suharshs
I saw the commit id: 06228fb70858ef50f31cc8cdf909121c80e100b2
I have checked that quantizing atrous convolutions were already supported from above commit id.
Then, Is this very hard to add quantized dilated depthwise convolution kernels in TOCO/TFlite?

Hi @suharshs
How is your status for the above issue?

Hi sorry for the delay, I have a work in progress change, but need to make time to implement the necessary optimized kernels, but we are actively working on this issue. Thanks for your patience!

Nagging Assignee @suharshs: It has been 14 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.

@suharshs When dilated depthwise convolution will be supported? Thanks for your hard work!

Hi sorry for the delay responding. I am working on it as we speak and I
expect all the necessary code to be done within 2 to 3 weeks. Thanks!
On Mon, Sep 10, 2018, 8:36 PM raninbowlalala<EMAIL_ADDRESS>wrote:

@suharshs https://github.com/suharshs When dilated depthwise
convolution will be supported? Thanks for your hard work!
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/20684#issuecomment-420135055,
or mute the thread
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Hi all, thanks for your patience.
I have submitted optimized dilated depthwise conv support and better handling in TOCO of dilations. Everything should be available at the lastest nightly release, so please give it a try and create a new separate issue if you encounter problems with dilated depthwise conv support.
Here are the list of commits, in case you are curious:
Reference implementations: https://github.com/tensorflow/tensorflow/commit/fb50c8e9a3cb2ccfac9cf4a847d5841cba80b524#diff-c748d758eb53ac58d70a13e07e02c6db
Optimized implementations: https://github.com/tensorflow/tensorflow/commit/3365cd1cc7bf3dcb781c76652132119bf82133e6#diff-c748d758eb53ac58d70a13e07e02c6db
TOCO transformations: https://github.com/tensorflow/tensorflow/commit/0ab89a599bdb9885532785a5e7b6bfe346e09ee3#diff-c748d758eb53ac58d70a13e07e02c6db
Thanks!

Hi @suharshs
I have a question for the meanings of optimized implementations.
How about your strategy to implement the optimized dilated conv?
Could I obtain a clue from the function of Fast3x3FilterKernelSupported?


NOISSUE - Add info default value to log levels

Signed-off-by: Darko Draskovic<EMAIL_ADDRESS>What does this do?
Adds default "info" log level environment variables.
Have you included tests for your changes?
No.
Did you document any new/modified functionality?
No need for docs.

Codecov Report

Merging #422 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #422   +/-   ##
=======================================
  Coverage   89.29%   89.29%
=======================================
  Files          46       46
  Lines        1634     1634
=======================================
  Hits         1459     1459
  Misses        119      119
  Partials       56       56

Continue to review full report at Codecov.

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@darkodraskovic I agree with @chombium's remarks - add MF_LOG_LEVEL=info ./run.sh in Makefile.
@chombium this make run is running microservices natively and is for now for development purposes, this is why @darkodraskovic proposed to add some more logs useful during development stage.
I would propose that we change also run target into rundev (for development native run with logs), and use make run to run docker containers.

@drasko I understand that that's for development purposes, but even then, because of the missing flexibility to set the log level from outside, it can happen that someone changes the log levels to and unintentionally commits the changed shell script.
We could also add a new rundev.sh file to the git ignores and everyone can configure the log levels as he/she wants. That would also do the trick

@drasko I understand that that's for development purposes, but even then, because of the missing flexibility to set the log level from outside, it can happen that someone changes the log levels to and unintentionally commits the changed shell script.
We could also add a new rundev.sh file to the git ignores and everyone can configure the log levels as he/she wants. That would also do the trick

@drasko I understand that that's for development purposes, but even then, because of the missing flexibility to set the log level from outside, it can happen that someone changes the log levels to and unintentionally commits the changed shell script.

Closing this one, will be implemented through https://github.com/mainflux/mainflux/pull/427


Deny todo!() macro in product code

Let's employ the help of clippy to prevent todo!() call sites from sneaking into product code. Do so from CI, which is expected to check all crates in the workspace.

See https://github.com/danielocfb/blazesym/actions/runs/6672484997/job/18136482706 for example run.


Decouple converter for stand-alone use

This is part of the work for #378. Right now, lib/converter/converter.ts uses a "component" architecture via decorators to register handlers to convert from the TypeScript compiler's representation of the code to typedoc's reflections. This architecture is very difficult to follow and know for sure how everything works together and directly couples the converter to the Application and Options classes. This pull request simplifies the converter by removing the concept of "components", eschews the use of decorators, and changes the constructor to accept an options object.

I would love to merge this if we can get an additional set of eyes. Aside from that, my only question is - do you want to delete that commented out code instead?

Not to put a damper on this, but I made some discoveries in the TypeScript APIs today and I'm looking into a way to simplify the converter more than what I've done here. I should have a proof of concept tomorrow.

Was there ever any update on this @bryanforbes ? Would be great to get it merged, TypeDoc is awesome, but is real hard to hack on currently, partially due to this stuff :)


[zh] Updated /access-authn-authz/service-accounts-admin.md

Clear differences found by ./scripts/lsync.sh
content/zh-cn/docs/reference/access-authn-authz/service-accounts-admin.md

Preview: https://deploy-preview-36524--kubernetes-io-main-staging.netlify.app/zh-cn/docs/reference/access-authn-authz/service-accounts-admin/

/lgtm


Is this project alive?

[✅ ] Question

Hi,
Is this project alive? Seems like there is lot's of open pull requests and very few changes in code lately.
Thanks

It's alive in the sense that I am using it in production, as are a few other organizations, but it is not actively being improved or developed at this time as my day job now takes up nearly all my time. See #573.

Closing in favor of #573.


[INlONG-2791][Manager] Optimize manager client APIs

Title Name: [INlONG-2791] Optimize Inlong manager client apis
where XYZ should be replaced by the actual issue number.
Fixes #2791
Motivation
optimize methods in client
Modifications
Verifying this change

[ ] Make sure that the change passes the CI checks.

(Please pick either of the following options)
This change is a trivial rework / code cleanup without any test coverage.
(or)
This change is already covered by existing tests, such as (please describe tests).
(or)
This change added tests and can be verified as follows:
(example:)

Added integration tests for end-to-end deployment with large payloads (10MB)
Extended integration test for recovery after broker failure

Documentation

Does this pull request introduce a new feature? (yes / no)
If yes, how is the feature documented? (not applicable / docs / JavaDocs / not documented)
If a feature is not applicable for documentation, explain why?
If a feature is not documented yet in this PR, please create a followup issue for adding the documentation

only modify SinkPageRequest and SourcePageRequest will cause some problem.
StreamSinkServiceImpl
 public PageInfo<? extends SinkListResponse> listByCondition(SinkPageRequest request) {         if (LOGGER.isDebugEnabled()) {             LOGGER.debug("begin to list sink page by " + request);         }         Preconditions.checkNotNull(request.getInlongGroupId(), Constant.GROUP_ID_IS_EMPTY);         String sinkType = request.getSinkType();         Preconditions.checkNotNull(sinkType, Constant.SINK_TYPE_IS_EMPTY);
StreamSourceServiceImpl
 public PageInfo<? extends SourceListResponse> listByCondition(SourcePageRequest request) {         if (LOGGER.isDebugEnabled()) {             LOGGER.debug("begin to list source page by " + request);         }         Preconditions.checkNotNull(request.getInlongGroupId(), Constant.GROUP_ID_IS_EMPTY);         String sourceType = request.getSourceType();         Preconditions.checkNotNull(sourceType, Constant.SOURCE_TYPE_IS_EMPTY);


Drawing not showing

There is no indication of anything happening on the screen after configuring the field

What drawing program are you using?

I tried it with onenote

Try Paint and see if it works.

Paint doesn't work either, im using a surface laptop studio with windows 11


⚠ Bofrost.nl has degraded performance

In a249fb2, Bofrost.nl (https://www.bofrost.nl) experienced degraded performance:

HTTP code: 200
Response time: 2406 ms

Resolved: Bofrost.nl performance has improved in ce4e435 after 6 minutes.


Exposing mas_commonSuperviewOfViews

In the class NSArray+MASAdditions.h
There is a method named mas_commonSuperviewOfViews. If we can use it when setting constraints for an array it could be useful having this method exposed in the corresponding .h file.

@TiagoVeloso I'm not sure I fully understand why you need this? Also if you're using iOS 8.0 or above Masonry no longer installs constraints on the closest common superview but defers this to UIKit via the activate and deactivate APIs

Closing this due to inactivity.


Expected Completion Date of Full Code Refactoring

Hi AutoDAN Team,
Fantastic work! Thank you for open-sourcing the code and proceeding with the refactoring of version 0.2.
Could you please share more details on when you plan to complete the full refactor? I was attempting to run some experiments and noticed that the code still lacks a few minor details. Do you happen to know an expected completion date?
Thanks!

Hi @abhaypuri98, we expect to complete the code update by the end of this December. Thank you for your interest in our work!


Simplify jumpLoc and add cycled next diagnostic feature

Thanks a lot! That seems really helpful! However, maybe adding jumpPrevLocationCycle will be better? Since user might want to jump back after jumping to the start of a cycle.

@haorenw1025 I can definitely add that too

@haorenW1025 good to go


Large number of line breaks after text copy

happens when selecting and copying text using ctrl-a or dragging below the final line

dont think this is fixable


feat: Add typescript

Closes #19
This does several things :

Use only vite instead of vite for dev and rollup for build
Install typescript
Add types where needed
Use eslint config that supports typescript
Remove prettier (the eslint preset I use does not need it)
Refactor dev files into the playground folder
Use script setup

It's seems work perfectly.
Just i need to find a proper solution to config the bundle worker instead use a CDN before publish a new package. By the way, thanks a lot.


Setup a auth proxy to have an external based authentication

As api catalog is targeted towards a standalone mode, we are gonna make the authentication first type as an auth proxy so that anyone can accommodate the auth process. The decision for server being node or go haven't finalized.
But auth proxy will act as the user management. It will be based on a config setuo

Using authy setup completed for setting any oauth clients needed in server


Migrate Possible GraphQL Tests to Use the GraphQL Client

Description:
Currently, the GraphQL tests are using an HTTP client to test the GraphQL services. We should check the possibility of using the GraphQL client implemented in the GraphQL package to test the services. This will increase the test coverage of the client as well.
With this effort, it is better to check the test util functions that are there for some time now and improve them and remove possible duplicates occurring during this time.

With this effort, the testing approach should also be reviewed. We should keep some of the tests in the ballerina-tests submodule and move to unit tests inside the ballerina submodule.
Most of the methods in the GraphQL engine should have designated unit tests instead of having them tested via integration tests. This way, we might be able to solve #3610


generators: support customising output path

This PR adds support for customising the output path through either;

an optional -o flag for the generate command.
an optional sdk-destinations section under the defaults key in cpm.json, specifically

  "defaults": {
    ...
    "sdk-language": "python",
    "sdk-destinations": {
      "onchain": {
        "csharp": "csharp_out_dir",
        "golang": "golang_out_dir",
        "java": "java_out_dir",
        "python": "python_out_dir"
      }
    }
  }

All paths are relative. You only have to specify the key for the language defined in sdk-language. In the example above the csharp, java and golang keys are ignored and could be omitted.

Do we need to use an output folder instead of a file?

Not sure I understand the question. You have 2 options

you do not specify sdk-destinations, then the sdk will automatically be put under /cpm_out/<language>/<contractname>/
you do specificy sdk-destinations, then the sdk will be put under <your_path>/<contractname>/

The new structure looks as follows (note that the main branched moved to use yaml over json) which is reflected here
defaults:
  contract-source-network: mainnet
  contract-destination: neo-express
  contract-generate-sdk: false
  # settings related to SDK generation for on chain contracts
  on-chain:
    # both languages and destinations take the same keys values: csharp, go, java or python
    languages:
    - python
    # if not destination is given for a specific language it will output to ./cpm_out/<language>/<sdk name>
    destinations:
      python: <python_sdk_output_dir>
      java: <java_sdk_output_dir>

We have an on-chain key for all generation settings related to smart contract SDKs (that can be included by other smart contracts). Its counter part off-chain is for the future where we will read the settings for frontend/backend SDK generation (i.e. if a website wishes to easily invoke contract methods through an SDK)


Test hacl-packages CI

This is a test  for https://github.com/hacl-star/hacl-star/pull/719

@pnmadelaine should we close this or do you need it open still for testing?


Restarting blinking cursor

After rebooting (from terminal or otherwise), everything appears to shutdown correctly but then left with a blinking cursor on a black screen on the Pi.
Cycling power will start everything again as normal.  Any clues as to what may be causing this?

Are you using the Touchscreen (in SETTINGS)? Should be fixed if you deactivate it.

Thanks will take a look


python311Packages.starlette-wtf: 0.4.3 -> 0.4.5

Automatic update generated by nixpkgs-update tools. This update was made based on information from passthru.updateScript.
meta.description for python311Packages.starlette-wtf is: A simple tool for integrating Starlette and WTForms
meta.homepage for python311Packages.starlette-wtf is: https://github.com/muicss/starlette-wtf
meta.changelog for python311Packages.starlette-wtf is: https://github.com/muicss/starlette-wtf/blob/v0.4.5/CHANGELOG.md
Updates performed

Ran passthru.UpdateScript

To inspect upstream changes
Impact
Checks done

built on NixOS
The tests defined in passthru.tests, if any, passed
found 0.4.5 with grep in /nix/store/sx7i7qmww5px0fzv9ynqiyllp6pbhlf4-python3.11-starlette-wtf-0.4.5
found 0.4.5 in filename of file in /nix/store/sx7i7qmww5px0fzv9ynqiyllp6pbhlf4-python3.11-starlette-wtf-0.4.5

Rebuild report (if merged into master) (click to expand)

3 total rebuild path(s)

3 package rebuild(s)

First fifty rebuilds by attrpath
irrd
python311Packages.starlette-wtf
python312Packages.starlette-wtf

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/sx7i7qmww5px0fzv9ynqiyllp6pbhlf4-python3.11-starlette-wtf-0.4.5 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A python311Packages.starlette-wtf https://github.com/r-ryantm/nixpkgs/archive/e8b228437c5bbe48c16e4549815b59578d1fe67f.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/e8b228437c5bbe48c16e4549815b59578d1fe67f#python311Packages.starlette-wtf

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/sx7i7qmww5px0fzv9ynqiyllp6pbhlf4-python3.11-starlette-wtf-0.4.5
ls -la /nix/store/sx7i7qmww5px0fzv9ynqiyllp6pbhlf4-python3.11-starlette-wtf-0.4.5/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review --extra-nixpkgs-config '{ allowInsecurePredicate = x: true; }' run on x86_64-linux 1

2 packages failed to build:

irrd
irrd.dist

4 packages built:

python311Packages.starlette-wtf
python311Packages.starlette-wtf.dist
python312Packages.starlette-wtf
python312Packages.starlette-wtf.dist

Maintainer pings
cc @n0emis @vidister @johannwagner @yu-re-ka for testing.

Result of nixpkgs-review pr 303777 run on aarch64-darwin 1

2 packages marked as broken and skipped:

irrd
irrd.dist

4 packages built:

python311Packages.starlette-wtf
python311Packages.starlette-wtf.dist
python312Packages.starlette-wtf
python312Packages.starlette-wtf.dist


⚠ Bofrost.at has degraded performance

In d4eb758, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 1603 ms

Resolved: Bofrost.at performance has improved in a0924d4 after 312 days, 8 hours, 49 minutes.


Fixes the relative links for the OSLP messages.

All is well.

All is well.

@rlemmers can you have a look if my fix works?
See: http://<IP_ADDRESS>/view/Pull Request Builder/job/OSGP_Documentation_pr/89/artifact/_book/index.html


Handle deleted episodes which where automatically created by iCal Importer

This happens, if an episode which was created by the iCal Importer is deleted by an user.
Decide what to do in this case. Options:

Skip this episode as the user does not want it
Recreate the episode
Recreate, if some condition is met (start time is in far future (1-2 days))

https://app.getsentry.com/xnis/frontend/issues/119878531/
RelatedObjectDoesNotExist: ICalEpisodeSource has no episode.
  File "radioportal/messages/receive.py", line 557, in dispatch_message
    return getattr(self, '%s_%s' % (keys[0], keys[1]))(data)
  File "radioportal/messages/receive.py", line 405, in importer_ical
    ep = source.episode

Maybe it is a good idea to not allow deleting episodes which are imported via ical. This creates consistency for the user. He has to delete the episode at the source: In his ical calendar.

Solution Idea:

Add flag recreateIfDeleted to ICalEpisodeSource with default of False.
If an episode is linked with an ICalEpisodeSource then change the confirmation page for episode deletion to contain three buttons: "Abort", "Delete without recreation", "Delete with recreation"
If "Delete with recreation" was choosen, then set the flag "recreateIfDeleted" to True
During iCal import: Check if ICalEpisodeSource has episode attached, if not evaluate flag


Doesn't work in latest xcode

I have recently updated my Xcode and the library doesn't work in interface builder.
Sample Error
"IB Designables: Ignoring user defined runtime attribute for key path "maskType" on instance of "UIButton". Hit an exception when attempting to set its value: [<UIButton 0x7f946aeb9e50> setValue:forUndefinedKey:]: this class is not key value coding-compliant for the key maskType.
"

Did you update to Xcode 7.3? It's working well in the demo app. Could you share more information that could help? Screenshots? Setup of your UIButton? Maybe a sample project?
Thanks!

@pixelbendr could you please provide more details as @tbaranes mentioned?
Do you use CocoaPods, Carthage or SPM?
Did the project used to work before your upgrade to Xcode 7.3?
Which pod did you install? 1.2/2.0/2.1
Did you try to re-open Xcode?
Did you try to clear derived data?
Did you check Identity Inspector, make sure your Button is using AnimatableButton, Module field is good?
Please let me know if you have any questions? Thanks

@JakeLin @tbaranes its working now. :) The only issue is when I copy and paste from the example project it doesn't work. I had to restart my Mac before it started working. Regards.


Update config.yaml

Added erouvas as an other maintainers at businessautomation-cop

/aprove

/approve

/lgtm


(PA-4218) Updates macOS tests

Adding support for macOS 12 Monterey surfaced some issues with existing tests for macOS specifically. This PR

Removes macOS tests that are no longer relevant and
Expands an existing test to cover macOS 12 Monterey

@joshcooper thanks for the review, I made a minor change (changed the regex in ticket_8740_should_not_enumerate_root_directory.rb to simply exclude Mac altogether), would you mind taking another quick look when you have the chance?
Thank you!


HIVE-21200: Vectorization: date column throwing java.lang.UnsupportedOperationException for parquet

What changes were proposed in this pull request?
The date type should be treated as int instead of long.
Why are the changes needed?
otherwise exception will be thrown when read parquet files with date column when vectorization is enabled.
Does this PR introduce any user-facing change?
no.
How was this patch tested?
add a unit test for date.

@sunchao Could you please help review this?

Merged. Thanks!


:fire: Remove EFCore.Relational.Design.Specification.Tests

This removes Design.Specs.tests
filed #9352 to remove dependency on SqlServer.

Updated & rebased on latest dev.
@AndriySvyryd  - included "faster cleanup" change.


OCPBUGS-17827: e2e: refactor checkPodsHaveLabel to be allowlist rather than exact match

We have painted ourselves into a corner with the current EnsureComponentsHaveNeedManagementKASAccessLabel check.
It is currently implemented as a match list, not an allowlist.  The list of components that have the NeedManagementKASAccessLabel must exactly match the list of components.
This leads to a situation where there is no workable way to add or remove the label from components, as the e2e binary image is update immediately upon merge and will be used to test against older CPOs.
This PR converts the check into an allowlist such that if a component is on the allowlist but doesn't have the NeedManagementKASAccessLabel, it does not fail the test.
After this change, removing the label from a component can be done in 2 steps:

remove the label from the component and wait for sufficient promoting of the change in the CI release stream (at least 2 promoted release images with the change)
remove the component from the allowlist in the e2e test

Adding the label to a new/existing component can be done in a single PR changing both the CPO and e2e test.

/test e2e-aws

/test unit
/test verify

e2e-aws failure seems to be a infra flake

/lgtm


BCL API review: Rename "source" to "provider"

Currently each of the specific components that can be chained to provide configuration data from a different source is an IConfigurationSource. The proposal is to change this to be an IConfigurationProvider which is believed to be more consistent with how we have use these words in the past and across the stack.

e3f4e5d87d3abe26493b702b510d21a6fb666470


Update CONTRIBUTING.md

Hi Seth! 👋
Was perusing and noticed a couple things in need of copy edits.
Cool project!

oh hey thanks! it felt like there was something i'd missed lol.


You created github issue by this, can't even open directly.

You created github issue by this, can't even open directly.

Thanks for your reply, now people can click the reply to get in

we are just following implementation rules

\0

\n