[API] Ability to name flow branches

Migrated over from https://github.com/lumio-medical/lumio-flow/issues/2
Consider the addition of a feature enabling the developer to name a flow.
This can be especially useful for more complex flows with multiple sections and joins.
Eg. the following flow:
var sourceFlow = Flow
    .from(() -> 1)
    .pipe(i -> i + 1)
    .sink(i -> i * 2)
;

var branchA = sourceFlow.pipe(i -> i ^ 2);
var branchB = sourceFlow.pipe(i -> i * 5);

var merge = branchA
    .join(branchB, (a, b) -> a + b)
    .sink(System.out::println)
;

...can produce the following output:
[main] DEBUG com.noleme.flow - Collected 1 flow entry nodes
[main] DEBUG com.noleme.flow - Flow execution graph contains 7 nodes
[main] DEBUG com.noleme.flow - Launching flow source #98e1f353-e819-4338-a1ac-842833079751 of extractor MyTest$$Lambda$15/0x0000000800b62c40
[main] DEBUG com.noleme.flow - Launching flow pipe #fb16046e-961d-45f1-96e0-e9add7d1943f of transformer MyTest$$Lambda$22/0x0000000800b66040
[main] DEBUG com.noleme.flow - Launching flow pipe #606d5192-f1cb-4d10-b243-87a5a820fc91 of transformer MyTest$$Lambda$23/0x0000000800b66440
[main] DEBUG com.noleme.flow - Launching flow pipe #fac31507-a2c7-40fa-a475-778c9b85c644 of transformer MyTest$$Lambda$25/0x0000000800b65c40
[main] DEBUG com.noleme.flow - Launching flow pipe #e9cd3c88-b05b-4c85-aa40-a1e8f0186fb7 of transformer MyTest$$Lambda$24/0x0000000800b65840
[main] DEBUG com.noleme.flow - Launching flow join #93692897-dbad-47d3-8d16-1a83f9c71ade of upstream flows #e9cd3c88-b05b-4c85-aa40-a1e8f0186fb7 and #fac31507-a2c7-40fa-a475-778c9b85c644
[main] DEBUG com.noleme.flow - Launching flow sink #c8cbc1d9-3b40-46f3-b277-ebdb5da8a6c5 of loader MyTest$$Lambda$27/0x0000000800b65440
26

The more complex the flow, the more difficult it can become to read its execution trace, especially if like in the example above, we rely on a lot of lambdas or anonymous classes.
One (possibly bad or technically problematic) idea would be to name flow branches.
For instance, the code above could become:
var sourceFlow = Flow
    .from("source", () -> 1)
    .pipe(i -> i + 1)
    .pipe(i -> i * 2)
;

var branchA = sourceFlow.pipe("branch_a", i -> i ^ 2);
var branchB = sourceFlow.pipe("branch_b", i -> i * 5);

var merge = branchA
    .join("joined", branchB, (a, b) -> a + b)
    .sink(System.out::println)
;

...and could produce the following output:
[main] DEBUG com.noleme.flow - Collected 1 flow entry nodes
[main] DEBUG com.noleme.flow - Flow execution graph contains 7 nodes
[main] DEBUG com.noleme.flow - [source] Launching flow source #98e1f353-e819-4338-a1ac-842833079751 of extractor MyTest$$Lambda$15/0x0000000800b62c40
[main] DEBUG com.noleme.flow - [source] Launching flow pipe #fb16046e-961d-45f1-96e0-e9add7d1943f of transformer MyTest$$Lambda$22/0x0000000800b66040
[main] DEBUG com.noleme.flow - [source] Launching flow pipe #606d5192-f1cb-4d10-b243-87a5a820fc91 of transformer MyTest$$Lambda$23/0x0000000800b66440
[main] DEBUG com.noleme.flow - [branch_b] Launching flow pipe #fac31507-a2c7-40fa-a475-778c9b85c644 of transformer MyTest$$Lambda$25/0x0000000800b65c40
[main] DEBUG com.noleme.flow - [branch_a] Launching flow pipe #e9cd3c88-b05b-4c85-aa40-a1e8f0186fb7 of transformer MyTest$$Lambda$24/0x0000000800b65840
[main] DEBUG com.noleme.flow - [joined] Launching flow join #93692897-dbad-47d3-8d16-1a83f9c71ade of upstream flows [branch_a]#e9cd3c88-b05b-4c85-aa40-a1e8f0186fb7 and [branch_b]#fac31507-a2c7-40fa-a475-778c9b85c644
[main] DEBUG com.noleme.flow - [joined] Launching flow sink #c8cbc1d9-3b40-46f3-b277-ebdb5da8a6c5 of loader MyTest$$Lambda$27/0x0000000800b65440
26

One downside is that once we start naming flows, it might make it impossible to evade naming downstream flows due to the naming being preserved unless told otherwise (which is pretty much the whole point). As a result, it could create confusion for cases where the designer of one branch or joined flow forgot to properly tag the section.
One way to partially address this could be to add a Node.unname() method, but it still requires downstream flows to acknowledge the existence of a name, which is not always possible and thus could lead to making unname() calls almost mandatory, which we definitely do not want.

Addressed by https://github.com/noleme/noleme-flow/commit/6e2774ad1184099f6d1aae5d1478bd9294b8ee24 delivered in v0.14 ; works only as a single node tagging feature to enable better identification of actor usage.


all the ui changes as well as updating the home page have been done

the code is easily maintainable not much changes are made u can easily add additional features like dark mode and light mode now easily and can improve the home page

@MadhurimaNayak can you tell me what type of design would be great? My design is not good, You guys can discuss about design part.
I am adding you as a Reviewer, please review this PR.

HEY @MadhurimaNayak  SO BASICALLY INSTEAD OF HAVING ONLY SINGLE DARK THEME IF WE HAVE IT IN LIGHT THEME IT WOULD BE BETTER TO TOGGLE TO DARK ALSO
AND HAVING A HOME PAGES GIVES US MORE OPPURTUNITIES TO ADD MORE FEATURES ALSO IN THE FUTURE WHERE YOU CAN JUST HAVE THE DETAILS OF THEM IN THE HOME AND THE FEATURE PART IN SEPERATE PAGES.


[minor issue] Roadblock setup condition

Version: 1.0.3
Mods: CBA, TFAR, ACE(no-medical), RHS
Environment: SP, MP LAN, MP host, MP dedi.
.rpt attatched? No
have you edited the missionfile?: No
Issue:

Roadblock setup is considered successful if driver arrive with or without the vehicle (so player tie up the guy bring him to  roadblock location and a vehicle will appear. can the check be on the alive and  position vehicle instead?
the roadblock vehicle is a truck and at the roadblock there will be the armed offroad can line 20 of crearpuestofia be replaced with vehSDKLightArmed ?

(optional) request:

create roadblock and OP are separated and just create the HC group, no position on map or task.
shift ctrl Y on roadblock group selected = check if is on road and then deploy
remove roadblock create a group in RB position and send the eventual added garrison back to HQ

As it is a mix of AT squad and armed vehicle, I chose one, :9


Mocks(?) won't generate on mocks-dir but on root-dir

I'm working on my project, on this branch https://gitlab.com/shackra/goimapnotify/-/tree/35-make-key-structs-more-testable?ref_type=heads
I noticed that running mockigo (I'm running latest version) generates a file on the root of the project, this is my configuration:
root-dir: .
mocks-dir: ./mocks
walk:
  - "!."
  - "idleClient"

the file generated is called mocks_test.go, but I was expecting to be generated on mocks/ as indicated in the configuration. What is going on?

In the latest version config file is not used anymore. You just call mockigo for each folder where you want to have the mocks, see the updated readme. The changed is was done to fix this issues: https://github.com/subtle-byte/mockigo/issues/10.


Add .Capabilities.APIVersions.Has on non k8s core resources

We should add .Capabilities.APIVersions.Has to non k8s core resources

will be fixed by https://github.com/stakater/application/pull/226


openpgp: gpg-agent fails for ed25519 keys with ssh certificates

It's not clear if this is a firmware issue or the openssh protocol itself.
firmware: v1.5.0-test.20230704
gnupg: 2.4.3
openssh: OpenSSH_for_Windows_9.2p1, LibreSSL 3.7.2
os: Windows 11 Pro, fully updated
Here is the scenario:

Create a ed25119 authentication subkey and transfer to the nk3 device using gpg.
Create a ssh certificate for this subkey using default ssh-keygen options.
Try to connect to server using certificate. We get the following error:

sign_and_send_pubkey: signing failed for ED25519 "~/.ssh/ed25519.pub": agent refused operation
NIIBE Yutaka, author of Gnuk and Nitrokey Start, has a good explanation of the root cause of the problem and a possible workaround [1].
It would be awesome if the NK3 firmware could expand the memory to handle the new ssh protocol features.
[1] https://dev.gnupg.org/T6250

Hi, thank you for the report.
In the GnuPG ticket you mention that the signed data is around 700 bytes, but are you sure that it's the Nitrokey 3 that rejects such large data? After some manual checking with Ed25519 it can sign up to 1024 bytes. (actually I also noticed that it crashes for 1025 https://github.com/Nitrokey/opcard-rs/issues/173 :worried: ).
So if it's only 700 bytes as you say I don't think the error comes directly from the Nitrokey 3 (and if it did you would have noticed a crashing key). I think we could bump it to a bit less than 2KB but that doesn't seem like the proper way to fix this problem.

Thank you for the quick response.
So far I have had no issue signing ed25519 keys with either gpg or openssh.
I agree with you that this solution is not optimal. There is definitely a protocol issue here as NIIBE mentions. However, it would make NK3 a bit more robust to poorly specified protocol.

I will leave this open for documentation. If anyone encounters this issue, the recommended solutions are to either use another protocol that can do pre-hashing (P256 or RSA), or to use the OpenSSH integration with FIDO if you are using a sufficiently recent version of OpenSSH.


Session Timeout

What feature do you want?
Session's should end after a specified amount of time
Why do you want this feature?
It would save computation power. Also it would prevent the user from accidentally running a session for too long or forgetting about it

How much time are we thinking for the timeout?

How much time are we thinking for the timeout?

How much time do you think is appropriate?

How much time are we thinking for the timeout?

How much time do you think is appropriate?

Maybe like 30mins to 1hr?

How much time are we thinking for the timeout?

How much time do you think is appropriate?

Maybe like 30mins to 1hr?

30 minutes sounds good to me


Update visibility tags

Add some tags to the bazel build that we can leverage internally to help
control visibility in the Google build system.

Can I ask the reason on making grpc++_test private?  My team in Verily had made use of that target.

We make strong guarantees about compatibility for our public APIs, and we do not make those guarantees for these afaik.

Thanks for the clarification.  It doesn't look like grpc++_test was used inside of grpc, except for their own test, at least for the mocks.
They were a useful helper classes that had been effectively public for several years.  Given that they're google test mocks of the public API, I would hope they could continue to be provided with a less strong guarantee (that one needed to match google test versions).


offering help upgrading between MC+LL versions

I've had a lot of experience with updating mods that had fallen behind on updating, and this mod looks like it would be really useful if it were updated to the most recent versions of Minecraft. I don't know how much support you'll find for 1.7.10, 1.8, or 1.8.9, especially since Mumfrey switched the LiteLoader project to gradle starting with 1.8.9, but I can help update it to any of those later versions for liteloader if you'd like

I expect the hardest parts will be finding personal motivation and not wanting to backport features/fixes to 1.7.10. The mc18 branch has some early work from a few years ago, but since then it's always been "just have to finish that one thing first". There was a HTML export feature that got a tiny bit of initial development (but will probably join recipe docking in the "abandoned code; maybe someday" pile), then later playing a skyblock modpack (and creating an extension mod for recipe support) drove multithreading and some API refinement.
I think I'll settle for implementing a spinner while recipes load (the icon's already there, it just needs to be placed into the GUI and have theme XML support added), then finally abandon 1.7.10 development.


[DOC] add springmvc auto set port doc

see https://github.com/apache/incubator-shenyu-website/pull/494


Add reference catalog loader notebook

The PR provides an example of loading a reference catalog with color terms and proper motions applied.
Not yet ready for review.

Expanded documentation. Also, it appears that the reference catalog loader is not incorporated in the main branch of lsst.pipe.tasks so I think this is now ready for review.

I was able to run the notebook successfully on the NCSA RSP.  This was the first time I encountered butler.getDirect and butler.getDeferred.  Maybe some additional description of these two functions could be added in a future update.


migration to spring boot 2.0.0.release breaks val

After migrating from spring boot 1.5.10 to spring boot 2.0.0 all vals got broken with message "Cannot use 'val' here because initializer expression does not have a representable type: Type cannot be resolved"
lombok version 1.6.20

[INFO] --- lombok-maven-plugin:<IP_ADDRESS>:delombok (default) @ rest-api ---
D:\zielen-project\rest-api\src\main\java\api\ApiApplication.java:5: error: package org.springframework.boot.autoconfigure.security.servlet does not exist
import org.springframework.boot.autoconfigure.security.servlet.SecurityAutoConfiguration;
^
D:\zielen-project\rest-api\src\main\java\api\product\domain\exception\ProductException.java:7: error: cannot find symbol
import org.springframework.lang.Nullable;
^
symbol:   class Nullable
location: package org.springframework.lang
D:\zielen-project\rest-api\src\main\java\api\ApiApplication.java:7: error: cannot find symbol
@SpringBootApplication(exclude = {SecurityAutoConfiguration.class})
^
symbol: class SecurityAutoConfiguration
[INFO] Delombok complete.
I have also these bugs after updating to 2.0.0

@pedegie @mmczhukov Are you two still having this problem?
Some more details are needed: what version of Java and Spring Boot are you on? A pom.xml example would also be helpful.


Fold edit validation failures into a single class

In preparation for defining a planting site map validation API, replace the
individual classes for validation problems with a single class that uses an enum
to identify the problem type. This will be easier to map to an API response with
a fixed payload format.

#2042
#2041
#2040
#2039  👈
main

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fix compile errors on avr-gcc 5.4.0

Modifications in commit 0a43712 seem to be working (haven't tested on a board yet, but compiles with avr-gcc 5.4.0)
You should modify the function WriteProgmemArray in Katiana.c/.h to accept a "const uint8_t *" to remove warnings:
warning: passing argument 1 of  discards ‘const’ qualifier from pointer target type [-Wdiscarded-qualifiers]
Katiana.h, line 262: static void  __attribute__((noinline)) WriteProgmemArray(const uint8_t*, uint8_t);
Katiana.c, line 727: static void WriteProgmemArray(const uint8_t *Response, uint8_t Count)

Modifications in commit 7428ded doesn't compile (with LUFA v.170418)
Type CDC_DTYPE_CSInterface is unknown.
Probably a LUFA version problem, haven't tested with a newer version though.


Why parameters from codes and those of the paper are quite different?what is better?

Why parameters (and network struct) from codes and those of the paper are quite different?what is better? Thank you
boolings are all commented, why ?  Such as
#h_pool2 = max_pool_2x2(h_conv2)

Hello, I will update the code recently!
However, this project did not accurately follow the DQN paper, so I did it only because it work.


Added dust particles when the player walks or jumps.

To test it walk and jump around!
Jump around!
Jump around!
Jump around!
Jump up, jump up and get down! 🎶

Can you update the player prefab before we merge please? Its possible that the level breaks and then we have an easy way to recover it

Sure!


Latex to particle?

sympy.parsing.latex can parse latex equations into sympy code. Can we take that and turn it into a kernel somehow?

I very briefly investigated this today. There are some compilcations making sure the correct version of various things is installled, but, the basic premise could be something like:
from sympy.parsing.latex import parse_latex
expr = parse_latex("\sqrt{a+b}")

from sympy.codegen.pyutils import render_as_module
render_as_module(expr)
'import math\n\nmath.sqrt(a + b)'

The challenge is therefore:

Find a good way for user's to specify their expressions, kernel names etc.
Use sympy's latex parsing functionality to parse the latex into a sympy expression.
Convert this expression into a HartreeParticleDSL interaction, that can be fed into backends the same as before. Since sympy has already functionality to output sections of the functionality this is ok - however the complications exist where nodes such as sqrt and similar exist, as these should probably be backend math functions instead of sympy ones.


[Enemy In Shadows] Malthusius token missing

After update cant find token for MalthusiusFrom: Zedkerd#1828foundry: 10.291wfrp4e: 6.3.0wfrp4e-archives1: 2.4.1wfrp4e-core: 3.0.4wfrp4e-dotr: 2.3.4wfrp4e-eis: 3.0.0wfrp4e-horned-rat: 2.0.1wfrp4e-pbtt: 2.2.3wfrp4e-rnhd: 3.0.2wfrp4e-starter-set: 3.0.2Active Modules: color-picker, combat-carousel, dice-so-nice, easy-target, foundry-combat-focus, foundryvtt-simple-calendar, image-hover, lib-wrapper, monks-active-tiles, monks-little-details, popout, settings-extender, smalltime, token-action-hud, wfrp4-wfrp4e-npc-generator, wfrp4e-character-details, wfrp4e-gm-toolkit, wfrp4e-laws-pet-shoppe

Non reproduceable


Add location of auto auth setting to ecomm documentation.

Adding a bit more info about how to enable auto auth on LMS. @srpearce thoughts? Perhaps a review? :)

@srpearce I went with your second suggestion. Let me know if this looks good.

👍

just looked at this.  Perhaps you would like to poke @edx/ecommerce ?


fix: disable link check for flaky link

Attempts to mitigate https://github.com/celestiaorg/celestia-app/issues/1887

Codecov Report

:exclamation: No coverage uploaded for pull request base (main@7989d88). Click here to learn what that means.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main    #1955   +/-   ##
=======================================
  Coverage        ?   21.21%
=======================================
  Files           ?      121
  Lines           ?    13704
  Branches        ?        0
=======================================
  Hits            ?     2907
  Misses          ?    10509
  Partials        ?      288

how did these errors get on main? https://github.com/celestiaorg/celestia-app/actions/runs/5316456140/jobs/9626005256?pr=1955#step:4:231


[core] Add a fast path when no files exist

This can be a bit faster than binary searching over all files
every time we emit a fake 'piece hashed' event indicating
data which does not exist has 'failed' a hash check.

Let's skip a fast path. It's only a tiny bit noticeable for torrents with 32k pieces.


MNT: rerender

Hi! This is the friendly automated conda-forge-webservice.
I've started rerendering the recipe as instructed in #15.
If I find any needed changes to the recipe, I'll push them to this PR shortly. Thank you for waiting!
Here's a checklist to do before merging.

[ ] Bump the build number if needed.

Fixes #15

@conda-forge-admin , please re-render

This is passing! 🎉
@conda-forge/theseus-ai this is ready for review 🙂


fix(core): Skip all transformations for 3rd party modules

Hopefully fixes https://github.com/getsentry/sentry-javascript-bundler-plugins/issues/194
It seems like injecting into 3rd party modules may cause them to be bundled/resolved differently and this will fail some builds.
It could be that this is just an incompatibility with another plugin but I say it is worth just making this exemption.

Were you able to reproduce?

@AbhiPrasad  Yup will leave a comment in the original issue!


Fixes to "Save"

Changes:

Configuration defaults work again (apparently broke at some point, including no longer defaulting SaveOptions.format_csv to True on new enlighten.ini)
Warn user if "saving" spectra but no formats selected

this fixed #160


Support Transform for moving and positioning bodies

Currently, the only way to move and position bodies after initialization is to use the Position and Rotation components. Using these separate components has many benefits over using Transform for physics, as discussed in #16.
However, if we want Bevy XPBD to feel as integrated into Bevy as possible, it would make sense to allow using Transform directly for moving bodies, as it is what Bevy and the rest of its ecosystem typically uses. This would also allow third party crates to move bodies in a more backend-agnostic way without having to have explicit support for Bevy XPBD.
This PR adds a new synchronization system for SyncPlugin that updates Position and Rotation based on changes in GlobalTransform. This does not replace the separate components, but rather adds another way to position bodies in a more familiar and native way.
The new behaviour is entirely optional, and there is a new SyncConfig resource for disabling syncing features.
Caveats
Transform changes are only handled if they happen before physics
To only detect user changes in GlobalTransform, I use a PreviousGlobalTransform component that stores the global transform from the very beginning of each frame. If the transform has changed before physics is run, transform_to_position is run.
This avoids unnecessary runs of the system and circumvents some change detection problems, but it also means that Transform updates are only handled if they happen before physics is run.
Additional transform propagation
To handle hierarchies, I also need to run a copy of Bevy's transform propagation before physics. I don't think it's particularly expensive, but it does seem to go through all entities and their hierarchies, so it would probably be nice to find a way to avoid it.
Best practices for positioning bodies
There are now two ways to position bodies, either using Transform or using Position and Rotation. The best practises are unclear here; should people use transforms, which is considered to be a more native way, or should they continue to use Position and Rotation, which is currently the more robust option?
For now, I think it's enough to just mention both ways in the docs and let people make their own conclusions. Later on, we can maybe make clearer recommendations, and maybe even revisit #16 in some capacity.

Would this also add support for scaling colliders using bevy's Transform?

Not yet, but I will soon add some Scale or ColliderScale component that syncs with Transform scale.


Topology update broadcasts are sent once per route calculation

Topology updates, either sent directly or received from other peers, are sent via
GossipChannel.relayBroadcast().  It calls routes.ensureRecalculated(), which has three possible behaviours:

if no recalculation is pending, it returns straight away
if a recalculation is pending and nobody else is waiting, it will wait for that recalculation to start then finish
otherwise it will queue for an opportunity to do 1 or 2

This means that, when recalculations are plentiful, e.g. when a large cluster is forming, each update waits for one recalc.  We saw this when trying to get #106 to work.
I believe the idea was that ensureRecalculated() would wait for any previously-requested recalc to finish, but not wait for any future recalcs that might become necessary.

Fixed by #110


Add new extractor(bh,pt) and update author name in sb extractor

Please follow the guide below

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Use Preview tab to see how your pull request will actually look like

Before submitting a pull request make sure you have:

[x] Searched the bugtracker for similar pull requests
[x] Read adding new extractor tutorial
[x] Read youtube-dl coding conventions and adjusted the code to meet them
[x] Covered the code with tests (note that PRs without tests will be REJECTED)
[x] Checked the code with flake8

In order to be accepted and merged into youtube-dl each piece of code must be in public domain or released under Unlicense. Check one of the following options:

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[ ] I am not the original author of this code but it is in public domain or released under Unlicense (provide reliable evidence)

What is the purpose of your pull request?

[x] Bug fix
[ ] Improvement
[x] New extractor
[ ] New feature

Description of your pull request and other information

Added new extractors for baddiehub and porntrex
Fixed author name extraction in spankbang and add updated tests

Explanation of your pull request in arbitrary form goes here. Please make sure the description explains the purpose and effect of your pull request and is worded well enough to be understood. Provide as much context and examples as possible.

@rautamiekka please review again


Cannot get the exact match if another match matches

run("2017/easurvey") runs the wrong file.
This is because there is a more recently modified wildcard match that trumps the exact match:
> syberia_models("2017/easurvey")
[1] "2017/lean_analysis/lgsurvey" "2017/easurvey"
[3] "2017/lean_analysis/easurvey"

An exact match gets it:
> syberia::active_project()$find("2017/easurvey", base = "models", method = "exact")
[1] "models/2017/easurvey"

But syberia_models and run cannot pass the method parameter.

@peterhurford Try firing up the latest modeling.sy -- the run function should respect the method parameter now.


Decide what to do if a single event exceeds the maximum request size

My suggestion is to skip saving it in the localStorage queue and try sending it once immediately.

I think that suggestion sounds sane! Let's discuss further in due course

Should we do the same thing for GET requests that are too long?
The setting in the argmap is called "maxPostBytes" so we can't really use it for GETs as well.

Hmm - potentially yes. Could you create a ticket for 2.5? Let's not rush this GET issue...

Here it is: #362

Thanks Fred!


signin-signup form navigation

signup and signup navigation added user now toggle.

share screenshots or screen recording to support your resolution

please add tag gssoc-ext hacktoberfest-accepted and also add a level of problem.
https://github.com/user-attachments/assets/629c118b-03c2-48a8-ac93-c71874ff0ae4

This close
Signup page login page no toggle button for switch signup and login text error in login page #15

@ChandelAnish please check above attached document

Your Branch has Conflicts So Resolve Conflicts otherwise it will not be Merged

Your Branch has Conflicts So Resolve Conflicts otherwise it will not be Merged

Thanks I will resolve as soon as possible

signup and signup navigation added user now toggle.

please assign to me unfortunately i will discord commits

There was conflict with some branch did you resolved that issue?


Remove whitespaces from end of lines in Bridge code

Sometimes copypaste and even Visual Studio operations makes empty whitespaces in lines and line ends.
This issue is intended to wipe them out from current Bridge version.

Wipeout complete. :)
Hope it didn't wipe actual code. (no, it didn't!)


[plugin-propelo-job-reporter] ADD: Ashish @ harness as a developer for the propelo-job-reporter plugin. DEL: amit as a developer

Approved @ivan-levelops
Link to GitHub repository
https://github.com/jenkinsci/propelo-job-reporter-plugin
When modifying release permission
If you are modifying the release permission of your plugin or component, fill out the following checklist:
### Release permission checklist (for submitters)
- [x] The usernames of the users added to the "developers" section in the .yml file are the same the users use to log in to [accounts.jenkins.io](https://accounts.jenkins.io/).
- [x] All users added have logged in to [Artifactory](https://repo.jenkins-ci.org/) and [Jira](https://issues.jenkins.io/) once.
- [x] I have mentioned an [existing team member](https://github.com/orgs/jenkinsci/teams) of the plugin or component team to approve this request.

### Reviewer checklist
- [ ] Check that the `$pluginId Developers` team has `Admin` permissions while granting the access.
- [ ] In the case of plugin adoption, ensure that the Jenkins Jira default assignee is either removed or changed to the new maintainer.
- [ ] If security contacts are changed (this includes add/remove), ping the security officer (currently `@Wadeck`) in this pull request. If an email contact is changed, wait for approval from the security officer.

There are IRC Bot commands for it.

cc: @maxime_propelo @viraj_propelo @sid_propleo


Re-Implement Launchpad Pad Brightness Control

I have 2 Launchpad Minis (both Mk.2 models), connected to 2 PER|FORMER modules.
There seems to be a noticeable brightness difference between the two Launchpads, and the brighter unit intermittently looses communication with the PER|FORMER it is connected to.
I can't be sure that the higher LED brightness of my 2nd LP Mini is the reason it occasionally disconnects, but if (as seems to be the case), there is significant variation in brightness between Launchpad units, would it be worth re-implementing the brightness-adjustment setting from 0.1.11?

I can't seem to edit the first post, annoyingly. I meant to say my Launchpads are both Mk.1 units.

Also, the page created a duplicate Issue when I tried to edit this issue. I've closed the issue (#67), but can't seem to delete it.
Sorry about that. I'm using an unsupported Safari version on my old iMac, so perhaps that's the reason (though I haven't seem these issues before, on the same system).

The brighter launchpad is likely in "Full Power" mode and not "Low Power". When the launchpad first turns on, it will respectively display a letter F or L depending on the mode it's in:
https://customer.novationmusic.com/sites/customer/files/novation/downloads/6961/launchpad-s-and-mini-advanced-features-guide_0.pdf
Novation recommends using a powered USB hub for the Full Power mode.

Ah.. that was it! I've set it to Low Power mode, and so far, so good.
Thank you, Michel!

Before I close the issue, could I recommend that the Launchpad Low Power mode is documented in the manual, @westlicht?

@sneak-thief good catch, I remember reading about that a long time ago.
@toneburst good idea to mention this in the manual!

Manual is updated. Closing this.


ARROW-13872: [Java] ExtensionTypeVector does not work with RangeEqualsVisitor

This adds the ExtensionTypeVector to the VectorVisitor interface and implements that method for the existing visitors. Now when visitor like RangeEqualsVisitor that uses another ExtensionTypeVector, they can both use the visitor on the underlying storage vector.

@BryanCutler Thanks for working on this.
Mostly LGTM, with a few minor comments. Please check if they are reasonable.

Thanks for reviewing @liyafan82. Good catches with the comments, I updated to address them.

Merging. Thanks.


404 not found - when try to install nginx-proxy-manager in proxmox

Script
nginx-proxy-manager
https://raw.githubusercontent.com/ej52/proxmox-scripts/main/lxc/nginx-proxy-manager/setup.sh
Describe the bug
The script "https://raw.githubusercontent.com/ej52/proxmox-scripts/main/lxc/nginx-proxy-manager/setup.sh" which is used during the installation process can not find the dependend script "https://raw.githubusercontent.com/ej52/proxmox-scripts/main/lxc/nginx-proxy-manager/install".
The called script ist missing.
System info:

Proxmox Version: 7.0-8
Alpine Version: [e.g. 3.12]

Screenshots
Code from install Script:
`[info] Creating LXC container...

_pct_options=(-arch $_arch -cmode shell -hostname $_host_name -cores $_cpu_cores -memory $_memory -net0 name=eth0,bridge=$_bridge,ip=dhcp -onboot 1 -ostype $_os_type -rootfs $_rootfs,size=$_disk_size -storage $_storage -swap $_swap -tags npm)
pct create 101 local:vztmpl/alpine-3.12-default_20200823_amd64.tar.xz -arch amd64 -cmode shell -hostname nginx-proxy-manager -cores 1 -memory 512 -net0 name=eth0,bridge=vmbr0,ip=dhcp -onboot 1 -ostype alpine -rootfs local-lvm:vm-101-disk-0,size=2G -storage local-lvm -swap 0 -tags npm
cat
info 'Setting up LXC container...'
echo -e '\e[32m[info] Setting up LXC container...\e[39m'
[info] Setting up LXC container...
pct start 101
sleep 3
pct exec 101 -- sh -c 'wget --no-cache -qO - https://raw.githubusercontent.com/ej52/proxmox-scripts/main/lxc/nginx-proxy-manager/setup.sh | sh'
wget: can't connect to remote host (<IP_ADDRESS>): Connection refused
popd
rm -rf /tmp/tmp.q6KuRJCpdk
`

@kpleines I think whats happening here is that the container does not have internet connectivity,  please make sure you are using the correct --bridge for the setup


Understanding spend-exposure fitting warning

Project Robyn
Describe issue
After running robyn_inputs I get the following message/warning:
"Michaelis-Menten fitting for PAID_MEDIA_VAR out of range. Using lm instead
Warning message:
In fit_spend_exposure(dt_spendModInput, mediaCostFactor[i], paid_media_vars[i]) :
Spend-exposure fitting for PAID_MEDIA_VAR has rsq =  0.323570148129739 To increase the fit, try splitting the variable. Otherwise consider using spend instead."

What does it mean that the PAID_MEDIA_VAR is out of range? What is the expected range?
Can you provide more details about the warning message? Why is it recommended to split the variable use spend to increase fit?

Environment & Robyn version
R version (4.1.2)

Hi,

The out of range error relates to the starting values for the nonlinear fitting for the spend exposure model are somehow not working. It usually happens when the relationship is very linear, in which case it will use a linear model as fall-back.
Imagine you have two different campaigns on FB, one is optimised towards conversions and thus has higher conversion rate, but more expensive CPM. The other is optimised towards awareness and thus has lower CPM, but also worse CVR. When using one single variable to represent FB, the difference above is ignored. When splitting it, not only the spend exposure fitting will become better, but also the total model will benefit from the two new variables that can potentially explain your dependent better.

Hope it helps.

feel free to reopen if necessary


Tests: Via protocol stack test.

Test that the VIA string has the correct protocol stack data.

clang format successful! https://ci.trafficserver.apache.org/job/clang-format-github/149/

RAT check failed! https://ci.trafficserver.apache.org/job/RAT-github/164/

AU check successful! https://ci.trafficserver.apache.org/job/autest-github/147/

FreeBSD11 build successful! https://ci.trafficserver.apache.org/job/freebsd-github/1845/

Linux build successful! https://ci.trafficserver.apache.org/job/linux-github/1736/

Intel CC build successful! https://ci.trafficserver.apache.org/job/icc-github/275/

clang-analyzer build successful! https://ci.trafficserver.apache.org/job/clang-analyzer-github/407/

clang format successful! https://ci.trafficserver.apache.org/job/clang-format-github/150/

RAT check successful! https://ci.trafficserver.apache.org/job/RAT-github/165/

FreeBSD11 build successful! https://ci.trafficserver.apache.org/job/freebsd-github/1846/

AU check successful! https://ci.trafficserver.apache.org/job/autest-github/148/

Intel CC build successful! https://ci.trafficserver.apache.org/job/icc-github/276/

Linux build successful! https://ci.trafficserver.apache.org/job/linux-github/1737/

clang-analyzer build successful! https://ci.trafficserver.apache.org/job/clang-analyzer-github/409/

@SolidWallOfCode Please remember to set tags / versions ... ;-P

One small update - I changed the hooks to use attributes instead of strings so that typos weren't quite so annoying.

clang format successful! https://ci.trafficserver.apache.org/job/clang-format-github/155/

RAT check successful! https://ci.trafficserver.apache.org/job/RAT-github/170/

FreeBSD11 build successful! https://ci.trafficserver.apache.org/job/freebsd-github/1851/

AU check failed! https://ci.trafficserver.apache.org/job/autest-github/152/

Intel CC build successful! https://ci.trafficserver.apache.org/job/icc-github/281/

Linux build successful! https://ci.trafficserver.apache.org/job/linux-github/1741/

clang-analyzer build successful! https://ci.trafficserver.apache.org/job/clang-analyzer-github/414/

clang format successful! https://ci.trafficserver.apache.org/job/clang-format-github/159/

RAT check successful! https://ci.trafficserver.apache.org/job/RAT-github/174/

FreeBSD11 build successful! https://ci.trafficserver.apache.org/job/freebsd-github/1855/

AU check failed! https://ci.trafficserver.apache.org/job/autest-github/156/

Intel CC build successful! https://ci.trafficserver.apache.org/job/icc-github/285/

Linux build successful! https://ci.trafficserver.apache.org/job/linux-github/1745/

clang-analyzer build successful! https://ci.trafficserver.apache.org/job/clang-analyzer-github/418/


To many Total mult-adds nums.

Thank you for great research!
model_t = timm.create_model('rdnet_tiny.nv_in1k', pretrained=False)
summary(model_t, input_size=(1, 3, 224, 224), device='cpu')
Total params: 23,541,024
Trainable params: 23,541,024
Non-trainable params: 0
Total mult-adds (Units.GIGABYTES): 78.87
Input size (MB): 0.60
Forward/backward pass size (MB): 2651.23
Params size (MB): 94.15
Estimated Total Size (MB): 2745.99

your paper assert that tiny model's FLOPs is 5GB. but it has 78GB.
Of course, i might not estimate right method.
But, i compare FLOPs with another models. than rdnet has much more.
I think, this code has some junk behavior. What do you think about this cause?
Thanks.

Thank you for your interest in our work.
https://github.com/naver-ai/rdnet/blob/7bc6b007fe13f3474ee32baf1ed07eadd37d9b97/benchmark.py#L44-L48
I checked FLOPs with deepspeed 0.12.6 with a following command :
python benchmark.py -b 128 --num-bench-iter 1000 --img-size=224 --fuser te --channels-last --bench infer -m rdnet_tiny

Please refer to TRAINING.md

Thank you for your response.
I got the result by benchmark.py, too
Actually, my big problem is memory costs in my custom training.
I can't understand why using timm.models.create_model has different memory costs
python benchmark.py -b 128 --num-bench-iter 100 --img-size=224 --fuser te --channels-last --bench train -m rdnet_tiny
memory cost is :

but, when i use timm.models.create_model('rdnet_tiny) in custom training, memory cost is :

Thank you for reading my question!

It is challenging to provide a definitive answer based solely on the described images. It would be beneficial to verify whether the input image size has increased, if any fusing-related configurations have been applied (fuser te), and if the channel-last feature has been adapted.
Thank you.

Based on the provided information, it seems that the size value of Estimated Total Size is much smaller compared to the value shown by nvidia-smi. This seems a bit unusual.
However, the results from nvidia-smi are highly reliable, this discrepancy may not pose a critical issue.
Noticing the output format of the summary you have shown closely resembles torchinfo (formerly torch-summary), I carried out some tests as follows.
import rdnet
import timm
from torchinfo import summary

model = timm.create_model("rdnet_tiny", pretrained=True)
batch_size = 128
summary(model, input_size=(batch_size, 3, 224, 224))

==============================================================================================================
Total params: 23,863,008
Trainable params: 23,863,008
Non-trainable params: 0
Total mult-adds (Units.GIGABYTES): 646.23
==============================================================================================================
Input size (MB): 77.07
Forward/backward pass size (MB): 21213.95
Params size (MB): 95.44
Estimated Total Size (MB): 21386.46
==============================================================================================================

In my trsult, the value of Estimated total size is similar to nvidia-smi value.
Please check a summary method (or package) once more :)
Thank you.


embed_bqm refactor

I was making some changes that might take some time to get approval.  Along the way I found some low-bar performance improvements (on the order of 10x for a K64 embedding, significantly more in the case of FixedEmbeddingComposite and the like) which are less controversial.

Codecov Report

Merging #321 into master will decrease coverage by 2.11%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #321      +/-   ##
==========================================
- Coverage   92.80%   90.69%   -2.12%
==========================================
  Files          22       22
  Lines        1167     1171       +4
==========================================
- Hits         1083     1062      -21
- Misses         84      109      +25

Impacted Files
Coverage Δ

dwave/system/composites/embedding.py
95.83% <100.00%> (-1.12%)
:arrow_down:

dwave/system/samplers/dwave_sampler.py
70.66% <0.00%> (-15.34%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
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marked as draft because I just discovered the existence of immutabledict which might make for a cleaner implementation... but I have other work to do and I've already refactored this twice


try catch

Is there a way to specify an exception handler function for a given asyncResult block?
Currently I am manually putting a try catch inside the asyncResult, but it would be cool if I could specify a built-in try catch that would wrap maybe the bind (or run).

Never mind! I found a catch function that works well enough.


Cannot Get setTimeout snippet to work

Trying to write a snippet for setTimeout in JS and getting errors.
s(
	"setTimeout",
	fmt(
		[[
                setTimeout(() => {
                    {1}
                 }, {2})
                ]],
	         rep(1), rep(2) }
	)
),

Here is the error when I start Neovim
Error detected while processing /Users/jcostanzo/.dotfiles/files/.config/nvim/init.lua:
E5113: Error while calling lua chunk: ...ck/packer/start/impatient.nvim/lua/impatient/profile.lua:148: ...
ite/pack/packer/start/LuaSnip/lua/luasnip/extras/fmt.lua:137: Found unescaped { inside placeholder; format
[18:22]="{
  {"
stack traceback:
        [C]: in function 'error'
        ...ck/packer/start/impatient.nvim/lua/impatient/profile.lua:148: in function 'require'
        /Users/jcostanzo/.config/nvim/init.lua:24: in main chunk

There's a few small mistakes in that snippet:

by default any occurence of {some_text} is replaced by a node. It complains about the unescaped { in "setTimeout (() => { and first } in "}, {2})"
fmt's prototype is fmt(format: string, nodes: table), all nodes passed to it have to be wrapped into a table.
rep(n) mirrors/repeats the nth jumpable node, but there are no nodes to mirror.

s(
	"setTimeout",
	fmt(
		[[
		setTimeout(() => {{
			{1}
		}}, {2})
		]], {
			i(1), i(2)
		}
	)
)

, where i is ls.insertNode, should work.

Thanks. Still trying to grasp the documentation. Thank you


Automatically create a TLS certificate for secure access of Rancher UI

By default, rancher is only available unencrypted by HTTP. An automatically created self signed TLS certificate for HTTPS access of rancher is much better than the unencrypted default. Of course, an integration of Let's Encrypt would be much better…
Rancher Versions:
Server: 1.5.5
Docker Version:
17.03.1-ce, build c6d412e
OS and where are the hosts located? (cloud, bare metal, etc):
CentOS Linux release 7.3.1611 (Core)
bare metal
Setup Details: (single node rancher vs. HA rancher, internal DB vs. external DB)
single node rancher
Environment Type: (Cattle/Kubernetes/Swarm/Mesos)
cattle
Steps to Reproduce:
Start a fresh new rancher instance.
Results:
The rancher UI is only available using unencrypted HTTP requests.

This would be absolutely great +1

As a new user of Rancher, I was trying to figure out why on earth nothing's listening on port 80,443... Having Rancher be insecure out of the box is pretty devastating when it's supposed to be a secure orchestration tool.

I think this can be closed, because it's supported in 2.0 :)

Thanks!


Simple bitwise operations

Simple bitwise operations as primitives. Useful for bitset operations and also the theory of bitvectors. See commented out section of test for bitset operations. Should supporting things like that be something in the surface language?

I feel like those should be primitives, no? What is the advantage of them being functions instead?


stepper_move() freezes when "moving" to the current position

Instead, the C-code should detect this harmless condition and issue a callback immediately.

Likewise, rp2.adc(blocks_to_send=0) freezes (i.e. also fails to send a callback immediately).


Include client id in traces

LTTng trace entries should include client id, to allow correlation libpaf trace entries with pafd syslog entries and other debugging facilities.

Implemented in 8b798ed.


Implement different order strategy

Partial orders
New order after 60s if not filled
Withdraw functionality

I should probably mention that I have not tested the partial fills as it was kind of difficult with little money :D


Brew Option / Disabling Automatic Modification of bashrc

Hey, is there anyway we can install this without having it automatically modify shared configs like ~/.bashrc? I manage these files seperately. Also, any chance you can publish this as a Homebrew package? If you need help creating this as a brew package, please let me know!

Thanks for the issue! This makes perfect sense, I'll work on a PR to make it possible to install without modifying the shared configs. If you're interested in helping get this published to homebrew, I'd definitely appreciate any help you can give with that!

Hey @ddworken -- sure, I can open a PR with a GoReleaser config and you can include it in your Makefile to automatically publish to a variety of platforms. Here's a sample config https://gitlab.com/megabyte-labs/go/cli/task-dash/-/blob/master/.config/goreleaser.yml?ref_type=heads

Awesome! The latest version of hishtory now supports installing without modifying shell configs via ./hishtory install --skip-config-modification.

Thank you!
On Fri, Jun 14, 2024, 12:46 AM David Dworken @.***>
wrote:

Awesome! The latest version of hishtory now supports installing without
modifying shell configs via ./hishtory install --skip-config-modification.
—
Reply to this email directly, view it on GitHub
https://github.com/ddworken/hishtory/issues/212#issuecomment-2167202878,
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You are receiving this because you authored the thread.Message ID:
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Errors without default "derive" feature

I'm playing with the library not using iced (seeing if it works nicely for an imgui-rs based UI), and came into this minor problem:
The example in the README doesn't build as
[dependencies]
anim = { version="0.1", default-features = false }

..will error because the derive feature is currently required (I get lots of errors of things not being defined due).
Workaround is easy enough - just need to define the derive feature then it builds nicely:
anim = { version="0.1", default-features = false, features = ["derive"] }

features were not configured correctly.


⚠ Bofrost.at has degraded performance

In 2861e82, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 1320 ms

Resolved: Bofrost.at performance has improved in 2ca9b3b.


QAT model to TFLite strict int8 quantisation - big performance gap

1. System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 18.04
TensorFlow installation (pip package or built from source): pip package
TensorFlow library (version, if pip package or github SHA, if built from source): 2.5.0-dev20201210

2. Code
import numpy as np

import tensorflow as tf
print("TENSORFLOW VERSION:", tf.__version__)
from tensorflow.python.keras.engine.input_layer import Input
import tensorflow_model_optimization as tfmo

from tensorflow.keras.layers import Input, Conv2D
from tensorflow.keras.layers import ReLU
from tensorflow.keras import Model

def calc_mse(target, pred, dtype="float"):

    if dtype=="float":
        scale = 255 ** 2
    elif dtype=="int":
        scale = 1
    else:
        raise NotImplementedError("dtype must be float or int.")

    mse = tf.reduce_mean(tf.pow(target - pred, 2)) * scale
    return mse

def validate_tflite(interpreter, dataset):
    mse = 0

    for img, img in dataset:

        # Preprocess image
        input_details = interpreter.get_input_details()[0]
        scale, zero_point = input_details['quantization']
        tflite_integer_input = img / scale + zero_point
        tflite_integer_input = tf.cast(tflite_integer_input, input_details['dtype'])
        interpreter.set_tensor(input_details['index'], tflite_integer_input)

        interpreter.invoke()

        output_details = interpreter.get_output_details()[0]
        tflite_integer_output = interpreter.get_tensor(output_details['index'])

        tflite_integer_input = tf.cast(tflite_integer_input, "float32")
        tflite_integer_output = tf.cast(tflite_integer_output, "float32")

        mse += calc_mse(tflite_integer_input, tflite_integer_output, dtype="int")

    return mse / len(dataset)

if __name__ == "__main__":

    tfmodel_old = tf.keras.models.load_model("simpleconv")

    tfmodel = tf.keras.Sequential([
        Input((32, 32, 3)),
        Conv2D(128, 3, padding="same", name="Conv1"),
        ReLU(name="Act1"),
        Conv2D(3, 3, padding="same", name="Conv2")])

    tfmodel.set_weights(tfmodel_old.get_weights())

    cifar = tf.keras.datasets.cifar10
    (train_images, _), (test_images, _) = cifar.load_data()
    train_images = train_images[:1000].astype(np.float32) / 255.0
    test_images = test_images[:1000].astype(np.float32) / 255.0

    cifar_train = tf.data.Dataset.from_tensor_slices((train_images, train_images)).map(
        lambda x, y: (tf.expand_dims(x, axis=0), tf.expand_dims(y, axis=0)))

    tfmodel.compile(optimizer="adam", loss=calc_mse)
    mse = tfmodel.evaluate(cifar_train)

    print(f"tf savedmodel mse: {mse}")

    # Finetune tensorflow model with QAT
    quantise_model = tfmo.quantization.keras.quantize_model
    qa_model = quantise_model(tfmodel)
    adam = tf.keras.optimizers.Adam(learning_rate=1e-6)
    qa_model.compile(optimizer=adam, loss=calc_mse)

    # NOTE: check mse here
    qa_model.fit(cifar_train)

    # Convert to TFLite and quantise
    converter = tf.lite.TFLiteConverter.from_keras_model(tfmodel)

    # Quantise to int8 without float fallback
    converter.optimizations = [tf.lite.Optimize.DEFAULT]

    def create_repr_data_gen(data):

        def representative_data_gen():
            for input_arr, target in data:
                yield [input_arr]
        return representative_data_gen

    converter.representative_dataset = create_repr_data_gen(cifar_train)
    converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
    converter.inference_input_type = tf.uint8
    converter.inference_output_type = tf.uint8

    quantised_qa_model = converter.convert()
    print("TFLite conversion done!")

    # Validate TFLite model and check mse again
    interpreter = tf.lite.Interpreter(model_content=quantised_qa_model)
    interpreter.allocate_tensors()
    input_details = interpreter.get_input_details()
    output_details = interpreter.get_output_details()

    print(input_details, "\n", output_details)
    mse_tflite = validate_tflite(interpreter, cifar_train)
    print(f"TFLite mse: {mse_tflite}")

3. Failure after conversion
I have a pretrained tensorflow model (just a simple Conv2D + ReLU + Conv2D trained with MSE) that I load, do quantisation aware training on (with the CIFAR dataset), then quantise to int8 in tensorflow lite.
MSE of the original tensorflow model is 139.7, and MSE of the QAT model is 193.9, which is reasonable given that I'm doing QAT on a 1000 images only.
However, MSE of the int8 quantised tensorflow lite model is much higher at 1620.5. The representative dataset I provide for quantisation calibration is the same, so I don't understand how performance could degrade this much.
5. (optional) Any other info / logs
Below is the console output of the program:
2021-02-10 14:17:33.598712: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:33.598730: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
TENSORFLOW VERSION: 2.5.0-dev20201210
2021-02-10 14:17:34.496241: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-02-10 14:17:34.520408: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:34.520885: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1727] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: TITAN RTX computeCapability: 7.5
coreClock: 1.77GHz coreCount: 72 deviceMemorySize: 23.64GiB deviceMemoryBandwidth: 625.94GiB/s
2021-02-10 14:17:34.520962: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:34.521347: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1727] Found device 1 with properties:
pciBusID: 0000:02:00.0 name: TITAN RTX computeCapability: 7.5
coreClock: 1.77GHz coreCount: 72 deviceMemorySize: 23.65GiB deviceMemoryBandwidth: 625.94GiB/s
2021-02-10 14:17:34.521474: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:34.521603: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublas.so.11'; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:34.521709: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublasLt.so.11'; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:34.524210: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-02-10 14:17:34.524500: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-02-10 14:17:34.527516: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-02-10 14:17:34.527711: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcusparse.so.11'; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:34.527835: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:34.527845: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1764] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2021-02-10 14:17:34.528075: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-02-10 14:17:34.528483: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-02-10 14:17:34.528492: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1273]
WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.
2021-02-10 14:17:35.448465: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:127] None of the MLIR optimization passes are enabled (registered 2)
2021-02-10 14:17:35.449007: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency:<PHONE_NUMBER> Hz
1000/1000 [==============================] - 1s 588us/step - loss: 140.2766
tf savedmodel mse:<PHONE_NUMBER>2070312
1000/1000 [==============================] - 3s 3ms/step - loss: 193.8917
2021-02-10 14:17:40.852032: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
2021-02-10 14:17:41.087654: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:41.087979: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:41.088209: I tensorflow/core/grappler/devices.cc:69] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 2
2021-02-10 14:17:41.088302: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session
2021-02-10 14:17:41.321745: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:41.322082: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1727] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: TITAN RTX computeCapability: 7.5
coreClock: 1.77GHz coreCount: 72 deviceMemorySize: 23.64GiB deviceMemoryBandwidth: 625.94GiB/s
2021-02-10 14:17:41.322177: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:41.322633: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1727] Found device 1 with properties:
pciBusID: 0000:02:00.0 name: TITAN RTX computeCapability: 7.5
coreClock: 1.77GHz coreCount: 72 deviceMemorySize: 23.65GiB deviceMemoryBandwidth: 625.94GiB/s
2021-02-10 14:17:41.322751: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.322817: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublas.so.11'; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.322874: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublasLt.so.11'; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.322891: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-02-10 14:17:41.322903: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-02-10 14:17:41.322915: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-02-10 14:17:41.322968: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcusparse.so.11'; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.323021: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.323032: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1764] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2021-02-10 14:17:41.323050: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-02-10 14:17:41.323058: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1273]      0 1
2021-02-10 14:17:41.323065: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1286] 0:   N N
2021-02-10 14:17:41.323070: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1286] 1:   N N
2021-02-10 14:17:41.324051: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:933] Optimization results for grappler item: graph_to_optimize
  function_optimizer: function_optimizer did nothing. time = 0.005ms.
  function_optimizer: function_optimizer did nothing. time = 0.001ms.

2021-02-10 14:17:41.341282: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:330] Ignored output_format.
2021-02-10 14:17:41.341306: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:333] Ignored drop_control_dependency.
2021-02-10 14:17:41.345935: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:41.346306: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1727] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: TITAN RTX computeCapability: 7.5
coreClock: 1.77GHz coreCount: 72 deviceMemorySize: 23.64GiB deviceMemoryBandwidth: 625.94GiB/s
2021-02-10 14:17:41.346397: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-02-10 14:17:41.346725: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1727] Found device 1 with properties:
pciBusID: 0000:02:00.0 name: TITAN RTX computeCapability: 7.5
coreClock: 1.77GHz coreCount: 72 deviceMemorySize: 23.65GiB deviceMemoryBandwidth: 625.94GiB/s
2021-02-10 14:17:41.346839: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.346902: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublas.so.11'; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.346958: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcublasLt.so.11'; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.346974: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-02-10 14:17:41.346987: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-02-10 14:17:41.346999: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-02-10 14:17:41.347050: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcusparse.so.11'; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.347105: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: :/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib:/usr/local/QT_5_13_2/lib:/usr/local/OpenCV_4_1_1/lib:/opt/intel/lib/intel64:/opt/intel/mkl/lib/intel64:/usr/local/magma/lib
2021-02-10 14:17:41.347115: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1764] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2021-02-10 14:17:41.347135: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-02-10 14:17:41.347141: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1273]      0 1
2021-02-10 14:17:41.347147: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1286] 0:   N N
2021-02-10 14:17:41.347152: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1286] 1:   N N
TFLite conversion done!
[{'name': 'input_1', 'index': 7, 'shape': array([ 1, 32, 32,  3], dtype=int32), 'shape_signature': array([-1, 32, 32,  3], dtype=int32), 'dtype': <class 'numpy.uint8'>, 'quantization': (0.003921568859368563, 0), 'quantization_parameters': {'scales': array([0.00392157], dtype=float32), 'zero_points': array([0], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}]
 [{'name': 'Identity', 'index': 8, 'shape': array([ 1, 32, 32,  3], dtype=int32), 'shape_signature': array([-1, 32, 32,  3], dtype=int32), 'dtype': <class 'numpy.uint8'>, 'quantization': (0.007350581232458353, 30), 'quantization_parameters': {'scales': array([0.00735058], dtype=float32), 'zero_points': array([30], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}]
TFLite mse: 1620.45458984375

Forgot to add, here's the pretrained model as a SavedModel directory (zipped).
simpleconv.zip

hello, any updates?

tfmodel does not seems to be able to correctly classify images into 10 classes. also, note that you're not using class label during training. Please refer to this page for CNN basics: https://www.tensorflow.org/tutorials/images/cnn

Apologies, I didn't explain myself clearly in the original post.
This model is not trained as a classifier, it's trained to reconstruct the original image and it's trained using MSE. So, it takes an image of shape (1,H,W,3) and outputs (1,H,W,3). Hence why I'm discarding the CIFAR labels.

Oh, I see. Will take a look. Meanwhile, this could happen if the original range is too broad so that the quantization error goes large. For example, you can try applying ReLU6 to narrow the quantization range. For now it doesn't seem like a bug, but some technical issue in the model structure itself.

QA-trained a simple classifier with the same code (doing the necessary modifications) and it doesn't incur any accuracy loss.
Also tested the autoencoder swapping ReLU with ReLU6, and the mse of the quantised model does decrease compared to ReLU, although it's still nowhere close to the mse of the non-quantised model.

I tried training the autoencoder without normalising the images to the 0-1 range. I kept them in the 0-255 range (converting to float of course), since I noticed that some pre-trained models used in the AI-Benchmark app have been trained in this way.
However, no dice. Once I quantise and convert to tensorflow lite, mse is terrible. Any updates on your end?

I was able to reproduce this issue in TF 2.11. Please find the gist here. Thank you.

Hi @Cy-r0,
Thanks for point this out,
I reproduced this on TF 2.12 with some modifications in this gist
Some things to note:

Since this is an integer quantized model and your mse calculations are a little different depending on float or int representations, I dequantized the output of the converted model and used the same float calculations for mse (calculating the mse of the original img tensor with the dequantized output) to ensure a fair comparison. This reduces the mse to 1240.

I modified the validate_tflite function to print out the individual mse's for each example. If you look through it, you will see that most mse's are completely reasonable and aligned with the original model's mse. However there are some examples with extremely high mse's such as 36351.508 which brings the average up quite high. This is due to a couple of things:
a. Reduced precision from the quantization processes will increase the chances of higher errors
b. The squared error nature of mse calculations will make these errors more pronounced and increase the average quite a bit
c. Most use cases are log loss calculations across expected probabilities and an actual class label rather than direct mse differences between expected tensors vs. actual tensors, which are less likely to suffer from these issues.

As such we think this case exhibits normal reduced precision errors rather than emblematic of a bug.
Let us know if you are satisfied with this conclusion. Thank you.

although I'm not working on this project anymore, I'm satisfied by your explanation, thank you!

Closing as not an issue, as verified by original author.


Change in method name of Browser Class

there is no Browser.RequestAsync method available. It should be Browser.OpenAsync

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

ID: 0e1cc45d-67d0-81bf-918f-85da4c143c93
Version Independent ID: 9143201f-a3a5-d283-ba8a-e84c471e9a0b
Content: Xamarin.Essentials Open Browser - Xamarin
Content Source: docs/essentials/open-browser.md
Service: xamarin
GitHub Login: @jamesmontemagno
Microsoft Alias: jamont

Thanks @Im-PJ. A fix for this should be published soon.


WYSIWYG editing replaces linked images relative path to absolute path

Edit a notebook with image in WYSIWYG editor
Save the notebook
Check the diff
eg. "",
gets converted to
""

@rajeshka can you please put some more info here besides empty strings

@chlafreniere Fixed it (if you go into edit mode usually the content is still there, in this case he just hadn't escaped it properly so it thought it was actual markdown 😆 )


Enhancement: add a method to retrieve MinCount/MaxCount properties

Please refer to what has been discussed in issue 71
That may also apply to other properties, in addition to MinCount/MaxCount.

See also getFieldDefinition in autoform pkg. This and get and such should be combined into a sensible solution.

Closing since the PR for this was merged some time ago


typescript-stryker: Compilation fails, but tsc through npm does not

tsconfig
{
  "compilerOptions": {
    "target": "es5",
    "allowJs": true,
    "module": "commonjs",
    "importHelpers": true,
    "moduleResolution": "node",
    "emitDecoratorMetadata": true,
    "experimentalDecorators": true,
    "sourceMap": true,
    "declaration": false,
    "pretty": true,
    "removeComments": false,
    "skipLibCheck": true,
    "strictNullChecks": true,
    "suppressExcessPropertyErrors": true,
    "suppressImplicitAnyIndexErrors": false,
    "isolatedModules": false,
    "outDir": "dist",
    "lib": [
      "dom",
      "esnext"
    ]
  },
  "include": [
    "src/**/*.ts"
  ],
  "exclude": [
    "node_modules"
  ]
}

part of stryker.conf
    config.set({
        files: [
            { pattern: 'src/spec.module.js', mutated: false, included: true },
            { pattern: 'src/**/app.component.ts', mutated: true, included: false },
            { pattern: 'src/**/*.service.ts', mutated: false, included: false },
            { pattern: 'src/**/*.{ts,scss,html,json,png}', included: false, mutated: false },
            { pattern: 'src/app/testing/**/*.ts', included: true, mutated: false },
        ],
        testRunner: 'karma',
        testFramework: 'jasmine',
        coverageAnalysis: 'off',
        // coverageAnalysis: 'perTest',
        mutator: 'typescript',
        transpilers: ['typescript'],
        tsconfigFile: 'tsconfig.json',
        reporter: ['progress', 'html'],
        htmlReporter: {
            baseDir: '.testresults/mutation'
        },
        logLevel: 'trace',
        // maxConcurrentTestRunners: 1,
        clearTextReporter: {
            maxTestsToLog: 0
        },

When I run tsc
Everything compiled ok, without errors.
When stryker run it produce a tons of errors:
core.module.ts(26,12): error TS2304: Cannot find name 'window'.
core.module.ts(30,12): error TS2304: Cannot find name 'localStorage'.
x.service.ts(35,129): error TS2339: Property 'includes' does not exist on type 'Type[]'.

In tsconfig lib dom, esnext is specified, but looks like stryker ignores it.

In trace mode, I do not see message that lib.dom.d.ts is loaded
Like
[DEBUG] TranspilingLanguageService - Pulling file into memory...

@unlight thanks very much for testing out our new TypeScript support.
Your assumption is correct in that you should see a Pulling file into memory message. Take Stryker itself as an example:
[2017-09-25 22:48:40.943] [DEBUG] TranspilingLanguageService - Resolving lib file lib.es5.d.ts to C:\z\github\stryker-mutator\stryker\node_modules\typescript\lib\lib.es5.d.ts
[2017-09-25 22:48:40.943] [DEBUG] TranspilingLanguageService - Pulling file into memory: lib.es5.d.ts
[2017-09-25 22:48:40.962] [DEBUG] TranspilingLanguageService - Resolving lib file lib.es2015.promise.d.ts to C:\z\github\stryker-mutator\stryker\node_modules\typescript\lib\lib.es2015.promise.d.ts
[2017-09-25 22:48:40.963] [DEBUG] TranspilingLanguageService - Pulling file into memory: lib.es2015.promise.d.ts

Do you see any lib files at all?
Could you run in debug once more and look at the top for "[DEBUG] Stryker - Using config:". There you should also see your typescript config (read using the stryker-typescript ConfigEditor plugin). Could you verify that the lib file is displayed there?
Finally: what versions are you using for typescript and stryker?

Versions:
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>
I see only this typescript related definition files:
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.core.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.collection.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.generator.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.promise.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.iterable.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.symbol.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.proxy.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.reflect.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es2015.symbol.wellknown.d.ts
[DEBUG] TranspilingLanguageService - Pulling file into memory: C:/xxx/node_modules/typescript/lib/lib.es5.d.ts

No esnext which is specified in tsconfig.
But es2015 was specified explicitly in one of the my spec file by triple comment reference
/// <reference path="../../../node_modules/typescript/lib/lib.es2015.d.ts" />

This pushed me to an idea, and finally I was able to solve it by creating empty ts file with content:
/// <reference path="../node_modules/typescript/lib/lib.dom.d.ts" />
/// <reference path="../node_modules/typescript/lib/lib.esnext.d.ts" />

@unlight ok, so the finger clearly points to Stryker not loading lib files correctly. I tried to reproduce the problem in this small sample: https://github.com/nicojs/stryker-typescript-issue394
I did come across an other bug #396 , but other than that the lib files seems to be loaded fine.
Could you try out this small sample and try to reproduce the problem there?

I've just tried and issue is not reproducible there, esnext definition is loading ok.
I will continue investigation in my project.

Figure out the problem.
Need remove all 'path' triple reference <reference path="node_modules/typescript/lib/lib.es2015.d.ts"
due to <reference no-default-lib="true"/>   it prevents loading what is defined in tsconfig.lib

@unlight ok, cool you found the problem. Just to be clear, you had <reference no-default-lib="true"/> somewhere in your code? If so, how could typescript itself compile?
Are you now able to run stryker on typescript code? Or is there some other issue your running into?

I had several references to 'lib.es2015' in my code.
'lib.es2015' contains 'reference no-default-lib'.
I suspect that it was the reason.


Any chance on getting the sample weights? Drive, Dropbox...

Can someone please share the old weights files?
rdn-C6-D20-G64-G064-x2_ArtefactCancelling_epoch219.hdf5
and
rdn-C6-D20-G64-G064-x2/PSNR-driven/rdn-C6-D20-G64-G064-x2_PSNR_epoch086.hdf5

Could you please share the weight files?

batch response: This repository is over its data quota. Purchase more data packs to restore access.
error: failed to fetch some objects from 'https://github.com/idealo/image-super-resolution.git/info/lfs'

Hi,
the same for me, the repo is over its data quota :(

I thought maybe someone had it saved in hard drive from previous pulls or clones.

Maybe some one will donate a gift card? https://github.com/nabla-c0d3/nassl/issues/17

I'll be happy to front the the cost of a few data packs @nabla-c0d3 just drop me a line.

Cool project! To be honest I don't quite understand how nassl has anything to do with it... Can you explain?

Whoops, followed the link assuming you were the owner. My offer still stands for @cfrancesco or @datitran  though; I've already bought a gift card.

sorry my fault... it was me linking a possible solution to the problem... thought not permanent... still thinking that just putting them in git is more than enought...

Hi everyone,
sorry for the troubles and thank you very much @CPritch for your very kind offer. @datitran and I will look into a proper solution.
For now, here there are:
https://drive.google.com/drive/folders/1cJLPgGfEuFAQzBKbXQtSGXxLXssw1D9f?usp=sharing
Let me know if there is any further issue (I'm not sure how this google drive solution will work out in the long run)/

I work for ovh.com and we will provide you something on a cloud storage as it be downloadable form CLI which is not the case for gdrive. I’ve been putting a lot of weights files on public cloud storage just because gdrive doesn’t allow direct download and it’s a pain...

Hi @CPritch and @jqueguiner, thanks for your offer and we're happy to take it if your offers still stand. You can send me a PM to my mail<EMAIL_ADDRESS>Thanks.

We have bandwidth again. Thanks to @CPritch for the gift card. Will close the issue for now.

The repo now includes direct download from S3 at model creation, like so:
model = RRDN(weights='gans')


Use bot in description of logs command

lets keep the naming to "agents" for now. we have this ticket to track the renaming work. ideally we do it all in one major release


python3Packages.aio-geojson-client: 0.15 -> 0.16

Motivation for this change
https://github.com/exxamalte/python-aio-geojson-client/releases/tag/v0.16
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 160450 run on x86_64-linux 1

16 packages built:

home-assistant-component-tests.geonetnz_quakes
home-assistant-component-tests.geonetnz_volcano
home-assistant-component-tests.ign_sismologia
home-assistant-component-tests.nsw_rural_fire_service_feed
python310Packages.aio-geojson-client
python310Packages.aio-geojson-geonetnz-quakes
python310Packages.aio-geojson-geonetnz-volcano
python310Packages.aio-geojson-nsw-rfs-incidents
python310Packages.georss-ign-sismologia-client
python310Packages.georss-nrcan-earthquakes-client
python39Packages.aio-geojson-client
python39Packages.aio-geojson-geonetnz-quakes
python39Packages.aio-geojson-geonetnz-volcano
python39Packages.aio-geojson-nsw-rfs-incidents
python39Packages.georss-ign-sismologia-client
python39Packages.georss-nrcan-earthquakes-client


Submission for Coding Challenge

https://people.sap.com/edwin_sendjaja34

https://people.sap.com/edwin_sendjaja34

Thanks a lot for your contribution. The solution looks great and I'll close this PR now!
You should receive your badge soon.


Use spawn_local with bazel to work around path include issue.

Likely ref. https://github.com/microsoft/TypeScript/issues/29221

This doesn't seem to have been sufficient. @cromwellian sees a few other flags we might want to try here: https://docs.bazel.build/versions/master/command-line-reference.html#flag--experimental_sandboxfs_map_symlink_targets
There are many docker/sandbox related experimental flags there.


GH-37720: [Format][Docs][FlightSQL] Document stateless prepared statements

documents changes for stateless management of FlightSQL prepared statement handles based on the design proposal described in apache/arrow#37720

GitHub Issue: #37720

PRs for language implementations:

Rust: apache/arrow-rs#5433
Go: apache/arrow#40311

Mailing list discussion: https://lists.apache.org/thread/3kb82ypx99q96g84qv555l6x8r0bppyq

Will we need to extend the schema of the PutResult message in order to encapsulate the DoPutPreparedStatementResult payload?
This is the spec right now:
service FlightService {
  rpc DoPut(stream FlightData) returns (stream PutResult) {}
}

message PutResult {
  bytes app_metadata = 1;
}

I don't think the response would be considered app_metadata.

The "app" in this case is Flight SQL. (Someday I would like to fuse Flight SQL/Flight RPC to avoid these odd distinctions, and so that we aren't multiplexing a dozen different calls into the same endpoint...)

With that framing it makes sense, thanks @lidavidm.

This proposal was approved on the Arrow dev mailing list. See thread here

Thank you everyone for your feedback and participation in the process


Give a heads-up e-mail to all the section leaders to tell them they will start getting follow-up e-mails so they are not surprised

Hey @mathias-gibson can you handle this? I think sending them an e-mail letting them know will be a good heads up so they don't see a foreign e-mail and then just get sent to spam.

Happy to, though you'll be going to the pic in person to tell them about it
this week, right? I'll email Donna and ask her how she wants to notify the
section leaders, what's the email address and subject line for the email
they'll be receiving?
On Nov 2, 2015 8:26 AM, "Ernie Hsiung"<EMAIL_ADDRESS>wrote:

Hey @mathias-gibson https://github.com/mathias-gibson can you handle
this? I think sending them an e-mail letting them know will be a good heads
up so they don't see a foreign e-mail and then just get sent to spam.
—
Reply to this email directly or view it on GitHub
https://github.com/codeforamerica/mdc-feedback/issues/490.

So in THEORY I am going to PIC. I haven't heard anything from Donna yet. I'm heads down writing a doc for Camilo so we can pair program together tomorrow. We can customize the subject line for the e-mail to whatever.

but will the emails continue to come from<EMAIL_ADDRESS>or is
that going to change? I will email Donna and get that conversation rolling.
when is email routing  expected to go live?
On Mon, Nov 2, 2015 at 10:02 AM, Ernie Hsiung<EMAIL_ADDRESS>wrote:

So in THEORY I am going to PIC. I haven't heard anything from Donna yet.
I'm heads down writing a doc for Camilo so we can pair program together
tomorrow. We can customize the subject line for the e-mail to whatever.
—
Reply to this email directly or view it on GitHub
https://github.com/codeforamerica/mdc-feedback/issues/490#issuecomment-153102765
.

Will the emails continue to come from<EMAIL_ADDRESS>or is that going to change?
That's a question we need to have; I know Pittsburgh has had difficulties getting it working. We should start it up with Donna on what her preferences are if we can do it easily.

When is email routing  expected to go live?
E-mail routing can go live literally now if we wanted to, but it depends on if we want to give a heads up to staff or not. It's as simple as going to http://mdc-feedback-stage.herokuapp.com/users/manage (after logging in) and plugging the e-mails in.

Well, I was there in person to tell them how the section leaders would get e-mail follow-ups. It's safe to say they won't be surprised, I suppose.


Releasing 2.0.0

Microsoft Json Schema Packages
2.0.0 Pointer | Schema| Schema.ToDotNet| Schema.Validation

Loosen Newtonsoft.JSON minimum version requirement from v13.0.1 to v9.0.1 Newtonsoft.Json. #157
FEATURE: Add support for JSON Schema type uuid. #132
FEATURE: Add new option for specifying .NET type to express Json integers: --generate-json-integer-as = int | long | biginteger | auto with a default of int. #158

The update to 2.0.0 was based on my offline feedback. Between the Newtonsoft changes and adding a new command line argument; this project has been overdue for a major version release.

Refers to: src/ReleaseHistory.md:7 in 5fe7f3f. [](commit_id = 5fe7f3fa77e579e0cb145304d7bee7578bc8e7c1, deletion_comment = False)

@michaelcfanning, I've reviewed and approve the versioning for this release. If you could merge,@shaopeng-gh will be unblocked to proceed with updating dependent projects.


timestamp_ms() truncates on python 2

Different resolution on python 2 and 3 since 0.12.0. Not sure if this is intentional.

@kisom
>>> pkt.timestamp_us
232646
>>> pkt.timestamp_ms
232

or
>>> pkt.timestamp_ms
232.646

That is not intentional. This bug was introduced when I fixed #12.
I'm going to create a PR to fix this. I'm only running code on py3 and forgot the difference.


Pukcc: GF(p)'s ECDSA signature generation/validation + full C-style ABI

This PR provides easy to use, high-level API for a small subset of PUKCC capabilities. Namely, ECDSA signature generation and validation over prime fields.

@twitchyliquid64
There's also a question of how to deal with CNS. Documentation, as far as I can read, does not require CNS parameter filled in for these specific services. Yet, without it, it produces bogus results: signatures are scrambled; all signatures are invalid. Probably it is preferable to generate this constant everytime? As far as I understand, it should be constant against a specified P modulus, so having it as a part of curve parametrization should be fine (I guess). Also I'm pretty convinced I messed up endianness in CNS but it gives correct results so I left it there as it is :D I'll create a test vector in my spare time.

There's also a question of how to deal with CNS. Documentation, as far as I can read, does not require CNS parameter filled in for these specific services. Yet, without it, it produces bogus results

From what I can tell CNS is a fixed parameter used for doing modulus arithmetic in fast mode, but only for some services. Other services seem to specify the CNS parameter as working memory for other computations?
Maybe a safe starting point would be to always initialize CNS to stack memory with the correct value for the current curve?


Made Josh Smith page

Test steps:
Open joshsmithpage.html
Verify it opens
Text is on page

Good stuff!

Be sure to sign up at https://hacktoberfest.digitalocean.com and do your four pull requests before the end of October to get your free t-shirt!


[$125] Upgrade mapbox and remove patch

This issue is just a tracker to upgrade mapbox and remove the patch we added in https://github.com/Expensify/App/pull/45289/files#diff-7ae45ad102eab3b6d7e7896acd08c427a9b25b346470d7bc6507b6481575d519R102
Looks like the build issues are being address upstream in https://github.com/rnmapbox/maps/issues/3593 and we can upgrade to https://github.com/rnmapbox/maps/releases/tag/v10.1.30 and remove the patch.
Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~01ed1b0e1397924f45
Upwork Job ID:<PHONE_NUMBER>455065976
Last Price Increase: 2024-08-27
Automatic offers:

suneox | Reviewer | 103729434
abzokhattab | Contributor | 103729436

Issue OwnerCurrent Issue Owner: @suneox

For the sake of this proposal, let's lay out the test steps we'll follow to ensure that the new version works as expected

Still waiting @abzokhattab change PR status

Could we also bump pod for rnmapbox/maps?
CC: @abzokhattab @roryabraham

good catch @MrRefactor

Created https://github.com/Expensify/App/pull/48925 to clean that up

Sorry for the difficulty with automations not working in this case. Growing pains in the deploy systems.
The PR for this was deployed to prod on 2024-09-11

Which PR fixed the bug on this GH @roryabraham?
It looks like this one wasn't deployed to prod yet: https://github.com/Expensify/App/pull/48436

https://github.com/Expensify/App/pull/48436. It was deployed to prod on 2024-09-11, the deploy comment just didn't work. Sorry for the confusion

Payment summary:

Contributor: @abzokhattab $125 (paid in Upwork)
Reviewer: @suneox $125 (paid in Upwork)


Drag and select time to create event with options

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Describe the solution you'd like
A clear and concise description of what you want to happen. Preferably with a code example or even the API you would
like to see.
We need feature that we can create event with the drag and select timing on timeline for week and day view similar to Google Calendar.
I am adding reference here.
https://github.com/user-attachments/assets/665ac1d2-5a07-4271-9ec0-91578f385ca5
Additional context
Add any other context or screenshots about the feature request here.
Things that could speed up the process

[ ] I can picture implementing at least parts of this feature
[ ] I believe I know how to do this, and am willing to implement the whole thing.
[x] I have a Schedule-X premium license

Thanks for opening this issue. This is something I definitely want to build, and try to release during Q1 in 2025.


Hosts ux

No, it wont be deleted, but I added it to git ignore.


Adds some initial guides + FAQs, and shows Dangerfiles on the front page

I love/hate that the title font doesn't have any chars other than UPPER CASE letters. No punctuation or anything. Hah


Feature/add initcode size check

This PR aims to solve Issue 4783
described in the Additional Context of this comment
Motivation
Prior to EIP-3860 there was no size limit on creation code (initcode), and just a 24576 byte size limit on runtime code.
EIP-3860 went live in Shangai so now there is both:

a 24576 byte size limit on runtime code
a new 24576 * 2 = 49152 byte size limit on initcode.

Currently, forge build --sizes does not account for this new size limit.
Solution

This PR adds a new column pair to the table displayed by forge build --sizes for the contract init code size (bytes) and the margin left counting towards the limit (bytes).
Also, the existing check for the deployed contract size is complemented with a new check for the init code size, making the process exist with status code 1 if the check fails.
Finally, a new option --ignore-eip-3860 allows to ignore the check mentioned in the previous point. This is aimed to users deploying to chains that do not enforce this limit.

Testing

Two tests were adjusted to account for the new structure of the table.
Two new tests were introduced to verify both failing and ignoring the new init code size limit.

Finally! Thank you ser 🫡
Tested and worked to me!

@DaniPopes Please let me know if this needs any further improvements before it can be merged. Thank you!


Roll engine to 08b660ed12e89ef4e600df9ff5fe029acead505e

flutter/engine@08b660e Roll Dart to 1ac34f151363958a11bb2997611acc2a1d54ed01
flutter/engine@2d9a0a7 Roll src/third_party/skia 177742435e52..faeef7837210 (1 commits)
flutter/engine@b3e866e Call drawPath without clip if possible
flutter/engine@7e0bb3b Allow freezing a texture.
flutter/engine@3cbb5e2 Persist DartCallbackCache contents across launches
flutter/engine@953570a libtxt: truncate paragraph width to an integer in order to match Blink's behavior

This roll includes and supersedes https://github.com/flutter/flutter/pull/20312. Updated version of golden files was taken from https://github.com/flutter/flutter/pull/20312.


All SGB palettes copy the first color from Background Palette 7

Describe the bug
The first color of Background Palette 7 is used for all the other SGB palettes when played on a SGB/emulator.
To Reproduce
Steps to reproduce the behavior:

Create a new scene that uses the lightest color.
Set the first color of Background Palette 7 to something easily noticeable, such as red.
Run this scene of the game on a SGB/emulator.
See that what should have been the first color of Background Palette 5 is now red.

Expected behavior
The SGB palettes should be able to each have their own unique first color.
Screenshots

Platform (please complete the following information):

OS: Windows 10
App version 3.0.1

SGB palettes work differently: https://gbdev.io/pandocs/SGB_Color_Palettes.html#color-0-restriction

@untoxa The first color should probably be copied from Background Palette 5 instead then.