chore(main): release 1.2.13

:robot: I have created a release beep boop
1.2.13 (2024-10-28)
Bug Fixes

deps: bump serve-static and express (d867c0e)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/JoshAlexis/utils-abstractions/releases/tag/v1.2.13 :sunflower:


Reduce spacing between nav items

Before

After

Closes https://github.com/astral-sh/uv/issues/5130 too

This gets us 6 more items above the fold.

Dropped #5130 from here — it's more complicated.


wrong error message for wrong order of blocks

Summary:
Forgot that blocks must be in order of functions, data, transformed data, parameters, transformed parameters, model, generated quantities.  When it's wrongly ordered, the error message is not helpful.
Reproducible Steps:
Run stanc on the following example code:
parameters {
  real y;
}
data {
    int<lower=0> N;
}
model {
  y ~ normal(0, 1);
}

Current Output:
Model name=bar_model
Input file=bar.stan
Output file=bar_model.cpp

PARSER EXPECTED: whitespace to end of file.
FOUND AT line 4:
data {
    int<lower=0> N;
}
model {
  y ~ normal(0, 1);
}

Expected Output:
Tell me the blocks are wrongly ordered.
Current Version:
v2.17.0

This isn't really a bug per se, but it needs to be fixed.
I think the message needs to be that it found the data block, but it's out of order.  In other cases where the block name is wrong, I think we need an alternative message.

Another issue I just uncovered is if I use function instead of functions, it gives me an unhelpful message:
C++ exception with description "PARSER EXPECTED: whitespace to end of file.
FOUND AT line 1:
function {
  vector foo(vector shared_params, vector_job_params,
             real[] data_r, int[] data_i) {
    return [1, 2, 3]';
  }
}

At least I knew it had found the file.  What this should say is something like:
expected block declaration, consisting of one of the following keywords: functions, data, transformed data,
parameters, transformed parameters, model, generated quantities
found: function

updated parser error messages when revising grammar rules -
https://github.com/stan-dev/stan/commit/ec62e7dc701bb8b4cdcc285da2538ac3f92d4a02
closing for now.

This still seems like it's an issue (https://discourse.mc-stan.org/t/a-mixture-gaussian-model-with-censoring-data/10051). Can we re-open it?
This is the output for compiling the example model for 2.19.2:
> stan_model("Downloads/test.stan")
PARSER FAILED TO PARSE INPUT COMPLETELY
STOPPED AT LINE 4:
data {
    int<lower=0> N;
}
model {
  y ~ normal(0, 1);
}

Error in stanc(file = file, model_code = model_code, model_name = model_name,  :
  failed to parse Stan model 'test' due to the above error.
In addition: Warning message:
In readLines(file, warn = TRUE) :
  incomplete final line found on '/home/bbales2/Downloads/test.stan'

We're not fixing errors in the C++ parser.  We should be switching over to the OCaml version soon.


"consense" to "consensus"

consensus was misspelt

Hi @Exoceus Thanks for making this update. Please submit update PRs to the main branch instead of the devnet branch. This error was corrected via another PR earlier this week. Thanks for your contirbution!

Hi @Exoceus Sorry we overlooked this one. Updates need to go to main vs devnet please


fix(javascript): release process

🧭 What and Why
🎟 JIRA Ticket: -
Changes included:
fixes https://github.com/algolia/api-clients-automation/pull/1778
somehow the release process of the JavaScript client is broken (see https://github.com/algolia/api-clients-automation/pull/1778), it made me think that we could just leverage lerna for independant version bumping and remove any kind of JS-specific logic in the release bumping script.
to properly test this change, we can run yarn docker:release locally to see every packages getting bumped, then run the generation and cts generation to assert it works properly.

detailed changes

generators

[x] remove js specific stuff in the config files
[x] get package version from the package.json
[x] get package name and path to package via the output field of the clients/openapitools.json file

scripts

[x] treat javascript packages as the other packages
[x] move updateDartPackages call to the updateAPIVersions method
[x] add dart pub get to prevent dart cache issue on release

ah Go is broken brb

ok actually we've named it packageVErsion and not version because it already contains the API version 🤷🏻

ok 0 changes now it's perfect, time to try a release and see if it works


[Bug] Can't install "2.10.1-spring2024" Version

Describe the bug
I know that the official Test Harness Version for Matter 1.3 is 2.10.1-spring2024.
To test this, I booted the Ubuntu 22.04.4 version of rasberrypi and tried to install TH in the following order, but the installation failed with the following error.

git clone -b v2.10.1+spring2024 https://github.com/project-chip/certification-tool.git
cd certification-tool
./scripts/pi-setup/auto-install.sh

"Depends: python3-venv (= 3.10.6-1~22.04) but 3.10.6-1~22.04.1 is to be installed"
Steps to reproduce the behavior

git clone -b v2.10.1+spring2024 https://github.com/project-chip/certification-tool.git
cd certification-tool
./scripts/pi-setup/auto-install.sh

Expected behavior
No response
Log files
No response
PICS file
No response
Screenshots
No response
Environment
No response
Additional Information
No response

I confirmed that the installation was completed normally when I modified it as below, but I am not sure if this is the right direction.
--- a/scripts/ubuntu/1-install-dependendcies.sh
+++ b/scripts/ubuntu/1-install-dependendcies.sh
@@ -54,7 +54,7 @@ packagelist=(
"npm (=8.5.1~ds-1)"
"pkg-config (=0.29.2-1ubuntu3)"
"python3-pip (=22.0.2+dfsg-1ubuntu0.4)"          # Test Harness CLI uses Python

"python3-venv (=3.10.6-1~22.04)"                 # Test Harness CLI uses Python

"python3-venv (=3.10.6-1~22.04.1)"                 # Test Harness CLI uses Python
"software-properties-common (=<IP_ADDRESS>)"
"toilet (=0.3-1.4)"
"unzip (>=6.0-26ubuntu3.1)"

Add libdbus-1-dev to this issue:
ubuntu@ubuntu:~/git/certification-tool$ diff ./backend/test_collections/matter/setup.sh ./backend/test_collections/matter/setup.sh.bak
37c37
<     "libdbus-1-dev (=1.14.10-4ubuntu4.1)"
---
>     "libdbus-1-dev (=1.14.10-4ubuntu4)"

can't test it as auto-install.sh somehow undose these changes.

can confirm now that my fix works, after i commented out the auto-update.sh line in certification-tool/scripts/ubuntu/auto-install.sh
ubuntu@ubuntu:~/git/certification-tool/scripts/ubuntu$ diff auto-install.sh auto-install.sh.bak
40c40
< ##$UBUNTU_SCRIPT_DIR/auto-update.sh "$CURRENT_BRANCH"
---
> $UBUNTU_SCRIPT_DIR/auto-update.sh "$CURRENT_BRANCH"

@joonhaengHeo Thanks for your feedback.
We are working in a fix for this problem. Soon as possible we will share the informations here.
For now you can comment out these lines from update script: certification-tool/scripts/update.sh
echo "*** Pull latest Test Harness code"
cd $ROOT_DIR && \
    git checkout $ROOT_BRANCH && \
    git pull && \
    git submodule update --init --recursive```

@hiltonlima it looks like commenting out the code didn't work for me. I had to make the change to python3-env in 1-install-dependendcies.sh as per @joonhaengHeo to solve the problem

@ksharf sorry for this late response.
Temporary you can use the branch ccb_v2.10.2+spring2024  for new installations.
This branch has the installation fix.

PR waiting fix process: https://github.com/project-chip/certification-tool/pull/394

@hiltonlima
I tried to install on branch ccb_v2.10.2+spring2024 and got the following error:
The following packages have unmet dependencies:
 satisfy:command-line : Depends: ca-certificates (= 20230311ubuntu<IP_ADDRESS>) but 20240203~22.04.1 is to be installed
E: Unable to correct problems, you have held broken packages.

It appears to be due to an updated ubuntu package.
https://www.ubuntuupdates.org/package/core/jammy/main/updates/ca-certificates
Wouldn't a similar fix be needed for this problem?
# /home/ubuntu/certification-tool/scripts/ubuntu/1-install-dependendcies.sh
packagelist=(
    "apt-transport-https (>=2.4.11)"
    "avahi-utils (>=0.8-5ubuntu5.2)"                 # Matter uses Avahi
    "ca-certificates (=20230311ubuntu<IP_ADDRESS>)"

Just for information: The branch ccb_v2.10.2+spring2024 was fixed.


SIM7672G - Incoming Call - Trigger Webhook

All I need is for the SIM7672G to wait for a call (just ring once) and then send a webhook (post) with the Caller ID/Phone number using the 4G network and get a reply code which will be a response of 0 or 1 to action a relay aka pull a pin high on the ESP.
So I thought this would be a cake walk but its not as easy as I thought mostly because of the figuring out how the caller ID and webhook side works.
Anyone got some sample code that can get me up and running ?
Please!

SIM7670G does not support SMS and voice calls

A7608 supports voice


require_tree ../something works when compression: false even if path is not defined in assets:sources in _config.yml, but the same require_tree is silently ignored when compression: true

Problem with require_tree
Use case:
  sources:
  - _assets/js
  - _assets/css
  - _assets/images
  - _assets/_sass/vendor/dreamhost-css/src/fonts
  # note: _assets/_sass/vendor/dreamhost-css/src/js is not listed here

main.js:
//=require_tree ../_sass/vendor/dreamhost-css/src/js

When compression: false is set, files inside the above directory will be included in the output of main.js.
However, when compression: true is set, this directory will NOT be included in the output of main.js. What's more, it will NOT raise any error during build.
require is not affected
  sources:
  - _assets/js
  - _assets/css
  - _assets/images
  - _assets/_sass/vendor/dreamhost-css/src/fonts
  # note: _assets/_sass/vendor/dreamhost-css/src/js is not listed here

main.js:
//=require ../_sass/vendor/dreamhost-css/src/js/scripts.js

require works as expected. That is, it raises an error.
Only after adding _assets/_sass/vendor/dreamhost-css/src/js to assets:sources makes it pass.
Request
Make require_tree always throw an error if the path where a JS is to be required from isn't listed in assets:sources, just like require.

[x] I tried updating to the latest version
[x] I Am on Linux

[x] All Linuxes affected

[x] I am on macOS 10.13
[x] I am on macOS 10.14

I feel like this would be a Sprockets issue, all things considered we don't compress, or handle trees, we do indeed handle sources (we pass them into Sprockets) but other than that we don't typically deal with the compression, or the trees and finding assets.

I don't know if it's Sprockets or Jekyll-assets, but compression is a documented Jekyll-assets option and it doesn't work properly and is silent about it.

We can't be noisy about something we don't handle.

Let me rephrase because I don't want you to think I don't care, I do care it's silent, I just don't know why and I feel like this might be a sprockets but, but I do plan on looking into it.


Is this track still maintained?

@joshgoebel are you still active in wren?

I'm still around but pretty busy these days, but let me know if you really need something.

@glennj Just to be safe, you still want to be added as a maintainer?

yes

Ah, I see that @iHiD has already added you! Thanks for helping out.


How to get the probability of shape_predictor (68 landmarks)

I try to localize the 68 landmark of a face, but I find some points not accurate, so I want to get the probability of them

shape_predictor algorithm does not have meaning of landmarks confidence. it is based on Kazemi algorithm
if you need to have confidence of landmarks, you can try algorithms from OpenCV or train separate object detectors for landmarks


When we navigate using TAB key inside the "Available Authorization" dialog keyboard focus moves to background content after the 'Close' button: A11y_VS Code extension for API Center_Open API Documentation_Available authorizations_Keyboard.

GitHub Tags
#A11yTCS; #A11ySev2; #Mac; #WCAG2.4.11; #GH_VSCodeextensionforAPICenter_Mac_Apr2024; #DesktopApp; #VS Code Extension for API Center; #keyboard #A11yMAS; #device; #A11yWCAG2.2;
Environment Details:
Application Name: VS Code Extension for API Center
macos sonoma version:14.4.1
Repro Steps:

Create an API center in azure portal.
Open Visual studio Code.
Tab till API center extension in the left side panel and press enter.
Tab till definition under the Api name which you have created, and press enter.
Tab till azure tool manual testing and click on it.
Tab till environment and click on it.
Tab till open API and press enter.
Go to "Open API Documentation" using the down arrow and press enter.
Demo conference API screen will appear.
Tab till Authorize button and press enter.
Verify whether the When we navigate using TAB key inside the "Available Authorization" dialog keyboard focus moves to background content after the 'Close' button or not.

Actual Result:
When we navigate using TAB key inside the "Available Authorization" dialog keyboard focus moves to background content after the 'Close' button
Expected Result:
When we navigate using TAB key inside the "Available Authorization" dialog keyboard focus should not move to background content after the 'Close' button. Also, with "ESC" key we should be able to close the dialog.
User Impact:
Keyboard users will face difficulty here as they will not be able to understand where the focus is and will not be able to interact with the required controls.
Attachment:

@formulahendry Can you please provide us the standalone sample app or Code pen link to route this bug to external team.

IRT Bug logged: https://dev.azure.com/CSS-IRT/CSS IRT/_workitems/edit/222928

GitHub Tags:
#External;#External:SwaggerUI;#eDAD:3p:222928;ThirdParty;

Issue is not fixed in the latest version

External bug: https://dev.azure.com/CSS-IRT/CSS IRT/_workitems/edit/222928


Ask the user for confirmation before resetting the classifier

This looks OK, but with the changes to put details into the querystring, if you create a classifier, and then click "reset", you can just click the browser's back button to get back to the trained classifier. So I don't think this is needed.


;l

[Enter feedback here]

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

ID: f34db833-bfe2-2c31-303c-7da4200e1e94
Version Independent ID: f34db833-bfe2-2c31-303c-7da4200e1e94
Content: SQL Server 2019 Release Notes - SQL Server
Content Source: docs/sql-server/sql-server-2019-release-notes.md
Product: sql
Technology: release-landing
GitHub Login: @MikeRayMSFT
Microsoft Alias: mikeray

I am closing this issue now.  You are welcome to @ mention me for any followup.  We hope to hear from you again.


Sporadic test failures in SseSameOriginIT on Windows 7

Build of gateway.transport.sse frequently fails on Windows with failures like the following:
sseIe8HttpxeConnectAndGetData(org.kaazing.gateway.transport.sse.SseSameOriginIT) starting
SseSameOriginIT.sseIe8HttpxeConnectAndGetData FAILED with exception org.junit.ComparisonFailure: Specified behavior did not match expected:<...ad "\n"
read /:.*/ "[\n"
read "\n"
read "data:Kobe is greater than Griffen\n"
read "\n]"
> but was:<...ad "\n"
read /:.*/ "[ ]"
>
org.junit.ComparisonFailure: Specified behavior did not match expected:<...ad "\n"
read /:.*/ "[\n"
read "\n"
read "data:Kobe is greater than Griffen\n"
read "\n]"
> but was:<...ad "\n"
read /:.*/ "[ ]"
>
	at org.junit.Assert.assertEquals(Assert.java:115)

In the same build I also had a failure like that reported in issue #193, so the two issues could be related.

The trace level log messages (now available because I added the MethodExecutionTrace rule to the test) indicate the underlying cause may be that the backend TCPConnection is being closed immediately after writing the data that should be sent to the client. This may cause the client connection to be prematurely closed before the data can be written out to it.

The previous comment is incorrect. That is not the cause of the problem because the broadcast service does do not close client connections when the backend is closed. I managed to get a WireShark of SseSameOriginIT.sseIe8HttpxeConnectAndGetData succeeding and then failing on the next run. The Wireshark shows the traffic on the wire is identical in both cases (for the client and backend connections). So this looks like an issue with k3po. This is confirmed by the suspicious nature of the reported difference. The script has
read /:.*/ "[\n"

so the reported error that the received text was
read /:.*/ "[ ]"

makes no sense. k3po should be reading any bytes up to the first '\n' byte.

Here is the console output for the failed (second) run
sse_issue_203_ok_then_failed.out | uploaded via ZenHub
Here is the wireshark trace for the succeeded and failed runs. Look for tcp.port==8005 for the client tcp streams and tcp.port=7556 for the backend streams (2 each, for the successful run than the failed run)
sse_issue_203_ok_then_failed.pcap | uploaded via ZenHub

Here is the console output with trace level log messages for a succeeded run of the same test (SseSameOriginIT.sseIe8HttpxeConnectAndGetData)
sse_issue_203_ok_with_trace.out | uploaded via ZenHub
It shows the same exception stacks caused by the closing of the sse session transport by the client script so that is not the cause of the test failures.

As noted in k3po issue #200 this is an issue with the script. Need to replace the line
read /:.*/ "[\n"

with
read /:.*\n/


Difference between FPN.ROI_MAX_LEVEL and FPN.RPN_MAX_LEVEL?

https://github.com/roytseng-tw/Detectron.pytorch/blob/9defe952cb8b1a4b90b1c1ad19eb5b3614b01418/lib/core/config.py#L704-L714
What is the difference between these settings?

Here is issue in Detectron: https://github.com/facebookresearch/Detectron/issues/52, which doesn't clear up too much for me :(

RPN_LEVELs (min to max) are the levels that RPN use to predict RoIs.
ROI_LEVELs are the levels where RoIAlign extracts features from.

RoIs are redistributed to different RoI-levels for feature extraction based on their sizes. Hence, an RoI predicted on a RPN_level may not be extracted on the same level.
The two level ranges don't need to be the same. However, you may make them match.


Signed a file only

Hello Is there possible to signed a file only not encryption because we have did encryption already we need to signed a file only?

No, there is no support of sign file only.
Workaround is Decrypt -> EncryptWithSign.

Hello @Cinchoo ,
When decrypting and verifying stream via method DecryptAndVerify, it throws an exception "Failed to verify file"
Expected Input parameters are
inputStream, outputStream, publicKey(sender), privateKey(receiver), passPhrase
Actual Input parameters
inputStream, outputStream, publicKey(receiver), privateKey(receiver), passPhrase
According to the rule of verifying the signature, it should accept the public key of the sender in order to verify the signature of the sender.
Please pass your comments on it.

Hello @Cinchoo ,
When decrypting and verifying stream via method DecryptAndVerify, it throws an exception "Failed to verify file"
Expected Input parameters are
inputStream, outputStream, publicKey(sender), privateKey(receiver), passPhrase
Actual Input parameters
inputStream, outputStream, publicKey(receiver), privateKey(receiver), passPhrase
According to the rule of verifying the signature, it should accept the public key of the sender in order to verify the signature of the sender.
Please pass your comments on it.

Have you tried Decrypt or DecryptFile? If the file is encrypted, not signed, you have to use these methods.

@Cinchoo I have done encrypt and signed with the EncryptAndSigned method.. now from the decrypting and verifying from the DecryptAndVerify I was getting exception "Failed to verify file" so I check your condition so I found that I was passing (sender) public key when I changed sender public key to receiver public key so its worked. so I need to ask why it is taking receiver public key instead of sender public key?
According to the rule of verifying the signature, it should accept the public key of the sender in order to verify the signature of the sender.
Please pass your comments on it.


[relates #705] Add CDI context test for camel-sql

Refer to this link for build results (access rights to CI server needed):
https://fabric8-ci.fusesource.com/job/wildfly-camel-pullreq/495/
Test PASSed.


Ability to filter api/screenshots by state code

currently, this API brings a lot of data for all state will be good if we can filter by state code
https://covidtracking.com/api/screenshots?state=NJ

This should be working now.


Add automated (non-interactive) mode.

[x] Add automated (non-interactive) mode
[x] tolerate node taints
[x] Accept a docker image name as input

@chandrams Can you please confirm if the deploy script fixes issues mentioned in #16 and #55

Fixes #45, #55 and #16


Add silent param to setOption

Brief Information
This pull request is in the type of:

[ ] bug fixing
[ ] new feature
[x] others

What does this PR do?
Add silent parameter to setOption
Fixed issues

Details
Before: What was the problem?

After: How is it fixed in this PR?

Usage
Are there any API changes?

[x] The API has been changed.

Related test cases or examples to use the new APIs
NA.
Others
Merging options

[ ] Please squash the commits into a single one when merge.

Other information

I think it's better to keep the silent parameter in the object. Too many parameters is not a good pattern.
chart.setOption(option, { silent: true });

The exists boolean parameter notMerge, lazyUpdate  is kept mostly for backward compatibility.


fix(board): update iteration count on WI state change

Fix: https://github.com/fabric8io/fabric8-ui/issues/1209

Can one of the admins verify this patch?

@vikram-raj snapshot fabric8-ui is deployed and available for testing at https://fabric8-ui-fabric8-ui-pr-1842-fabric8-planner.int.rdu2c.fabric8.io

Raised PR in fabric8-planner master.

@vikram-raj snapshot fabric8-ui is deployed and available for testing at https://fabric8-ui-fabric8-ui-pr-1842-fabric8-planner.int.rdu2c.fabric8.io


Add support for flattening out deep JSON structures with keyPaths

Some REST APIs have data in deep structures where relations makes no sense. In these cases it would be nice to be able flatten out the JSON structure in the model object by picking values in deep structures using keyPaths.
Example
Given this JSON structure:
{
  "title": {
    "rendered": "Hello, World!"
  }
}

Making a relationship from title to rendered wouldn't make sense. By letting hyper.remoteKey support keyPaths, we could easily map the title attribute in our model to a title.rendered keyPath.
This feature should support unlimited depths. The bool in the following structure would be mappable to hyper.remoteKey = some.very.deep.structure.
{
  "some": {
    "very": {
      "deep": {
        "structure": true
      }
    }
  }
}

It should also support when a structure have multiple values on the same level. The strings in the example below should be mappable to hyper.remoteKey = content.rendered and hyper.remoteKey = content.edit.
{
  "content": {
    "rendered": "
Hello, World!
",
    "edit": "Hello, World!"
  }
}

Fantastic idea! I remember wanting to do something like this before, I'm glad you're bringing it again.

BOOM! Added in 2.1.0
https://github.com/hyperoslo/Sync/releases/tag/2.1.0
And Sync 1.14.0 if you're still in Swift 2.3


Does not work with com.android.tools.build:gradle:1.1.0+

The latest com.android.tools.build:gradle is com.android.tools.build:gradle:1.1.3.
The version that this plugin does work is com.android.tools.build:gradle:1.0.0.
buildscript {
    repositories {
        jcenter()
    }
    dependencies {
        classpath 'com.android.tools.build:gradle:1.1.0' // <--
        classpath 'org.codehaus.groovy:gradle-groovy-android-plugin:0.3.5'

        // NOTE: Do not place your application dependencies here; they belong
        // in the individual module build.gradle files
    }
}

Error:
$ gradlew clean assembleDebug
Configuration on demand is an incubating feature.
:clean
:preBuild UP-TO-DATE
:preDebugBuild UP-TO-DATE
:compileDebugNdk UP-TO-DATE
:checkDebugManifest
:prepareDebugDependencies
:compileDebugAidl
:compileDebugRenderscript
:generateDebugBuildConfig
:generateDebugAssets UP-TO-DATE
:mergeDebugAssets
:generateDebugResValues UP-TO-DATE
:generateDebugResources
:mergeDebugResources
:processDebugManifest
:processDebugResources
:generateDebugSources
:compileDebugJava
:compileDebugGroovy FAILED

FAILURE: Build failed with an exception.

* What went wrong:
Execution failed for task ':compileDebugGroovy'.
> No such property: bootClasspath for class: com.android.build.gradle.AppPlugin

* Try:
Run with --stacktrace option to get the stack trace. Run with --info or --debug option to get more log output.

BUILD FAILED

Total time: 5.304 secs

I believe a similar fix is here: https://github.com/RoboBinding/RoboBinding-aspectj-plugin/issues/4

The release 0.3.6 is already out for several weeks now, sorry you didn't notice.

You should update the README.md, a lot of people just read and copy the instructions

@stefano-cliqz  I have a pull request for it here: https://github.com/groovy/groovy-android-gradle-plugin/pull/45.

I addd a line to build.gradle ,It works fine
com.android.build.gradle.AppPlugin.metaClass.getBootClasspath ={ androidBuilder.getBootClasspath true  }

@realgz You should be able to use the latest snapshot.

@jaredsburrows  thanks, but 0.3.7-snapshot still has the issue.


Graph2ToCoPo model

Thanks for the artefact. I have a couple of questions about this artefact. After reading  the paper:
(1) One major contribution the paper claims to provide is the open-sourced framework of PLUR that others can use. I am wondering whether you are planning to share the model and training scripts?
(2) I am particularly interested to run your model for Hoppity. Is there a possibility you can share the model even if that is partial, please?
I am wondering whether you would share the models and steps for the training code?

@smoitra-g this is fantastic. I am wondering whether will you be sharing the model itself?

Yes the release will have the {GGNN,Transformer,GREAT}2Tocopo models.

This is fantastic. Looking forward to it 👍

@smoitra-g I see you have pushed some code for the model. Would be helpful to know once all the changes are pushed in.

Hey @nashid . It should be code complete. Give it a try!! You'll be one of the alpha testers.


Blocklist for certain skins

Due to the random nature of skin manager, a lot of my specifically high class coach skins still show up in regular commuter trains. If I could tell passenger jobs which skins not to use for ordinary trains, that would be nice!

Closed by f10712e


Is there a plan to develop edp-bos?

As title.

Thanks god! Found it https://www.npmjs.com/package/baidubce-cli


Update: Rocket Chat App (Windows) doesn't work properly

My Desktop App of Rocket chat offers the newest update on Operating System Start.
I'm choosing "update now".
The app stops without any error warning.

Version of Rocket Chat Desktop App: 3.8.7
Windows 10, 1809

Not confirm that issue on my side.
Just updated from 3.8.7 to 3.8.8 automatically on Windows 10.

I tested it in various machines and worked. You will need to provide more info. Just don't works don't help to figure out what's happening.
Did you tried on another machine? Are you the computer administrator?


Port coffeescript to webpack

Thanks for creating an issue! Please fill out this form so we can be sure to have all the information we need, and to minimize back and forth.

What are we trying to do?

We're a webpack household now, and near nobody on the earth writes coffeescript in 2019. Let's convert that all to es6.

What feature or behavior is this required for?

Having our JS code be maintainable and usable in the future.

How could we solve this issue? (Not knowing is okay!)

Go thru the files in app/assets/javascripts/ and rewrite them one by one in files in app/javascript/ as es6 modules that webpack will load.

Anything else?

nah

Released into the pond -- now this is #1680 #1681 #1682 #1683 #1684 #1685 #1686

(Bumping this up in the chain because we've had a lack of good hacknight issues lately and these are kind of ideal)


(Update: "Size doesn't match!" error) Crazyflie won't log battery, temperature, etc.

IMU and RSSI are working fine, but I can't seem to get battery data through the package. I tried connecting via cfclient, and it showed me the battery level, but when I runrostopic echo /crazyflie/battery, there is no data returned. I haven't changed any of the default logging parameters, which are appearing as 'true'. Any idea why this might be happening?

Found the issue. baro.temp and baro.pressure don't seem to exist in the Crazyflie's parameters anymore. This was causing the "Size Doesn't Match!" error from Crazyflie.h and was causing it to not publish any of the parameters in the log2 block. I switched baro.temp and baro.pressure to other parameters since I didn't need them anyway, but this should perhaps be given a more robust solution.

Reopen so that I can fix that. I think this might be related to newer firmware versions.


Add comments to the example script

The example script isn't complicated, but it should have comments all the same.

Is this taken? I can add some docstrings and comments

You're welcome to it. I'll go ahead and assign it to you. Thanks for the help!

https://github.com/dingo-actual/infini-transformer/pull/17 Opened a PR here

I think we can close this now after https://github.com/dingo-actual/infini-transformer/pull/18


[IOS]  what the local image mean?

I follow the Getting Start and buildup my React-Native project.
It runs perfectly, but has some problem with Image node.
I use require('image!default_icon') to show a local image.
When I change the ios project positiong out of the nodejs project folder and fix the library import, It can not work.
I get this error "Requiring unknown module 'image!default_icon'. If you are sure the module is there, try restarting the packager."
It looks like can not find the module,but i use it to load an image packed into my app.
Is there any other way to do this?

The new asset system was introduced as of 0.14.0.
More info here http://facebook.github.io/react-native/docs/images.html#content

Thanks,I got it. But when i upgrade to 0.14, precomputeStyle.js is missed, what ti do with setNativeProps? @christopherdro

@ide @brentvatne ,precomputeStyle.js is deleted on 0.14.4? What other way do replace it?

@RandyZ Looks like its related to #3760

Closing this, since the original question seems to have been answered.


NIFI-2641: Add max values as attributes to QueryDatabaseTable

Ran contrib-check on nifi-standard bundle, ran full build with tests.
Set up QueryDatabaseTable pointed at Postgres instance, tried numeric and string values for max value.  Seems to work as expected, adding maxvalue.column to the FlowFile.
+1


Migrate Ginkgo to v2

For stolostron backlog #22704
Should fix sonar scan from failing to pickup test cases.
Signed-off-by: Jonathan Marcantonio<EMAIL_ADDRESS>

/approve
/lgtm
This is amazing work! Thank you!


Add ability to search for lat/long in map search bar

Add ability to search for lat/long coordinates in the map search bar!
Doesn't incur mapbox request (unless the person types really slow and requests are sent before the code realizes it's a lat/long query)

This is how Google does it

This is how we do it

This is great! LGTM trying this out. Requested minor changes.

This has been updated! Merge whenever ready

Getting this issue randomly.
To replicate maybe?, start putting in one coordinate into the search, then a comma or slash, then go start to copy the other coordinate. It's happened twice when I was doing something like that.. I think its probably hitting autocomplete or something before there's both coords in there

sigh, I know what's wrong. I would've hoped that it was caught in the tests. My bad. Thanks for catching.

This PR is ready to merge. I added the breaking test case (I tested by copy and pasting a lat/long and testing some normal string queries, but I missed the test case of typing in a number. It failed since strings can be iterated through but not numbers in javascript...)

Warning: Each child in a list should have a unique "key" prop.

Check the render method of `ForwardRef(Autocomplete)`. See https://reactjs.org/link/warning-keys for more information.
    at SearchResult (webpack-internal:///./client/src/components/Search/SearchBar.js:89:22)
    at Autocomplete (webpack-internal:///./node_modules/@mui/material/Autocomplete/Autocomplete.js:400:83)
    at SearchBar (webpack-internal:///./client/src/components/Search/SearchBar.js:25:24)
    at div
    at Search (webpack-internal:///./client/src/pages/Search/Search.js:30:18)

Can you add a key for Autocomplete or is this a MUI error?

So how big of a priority is this to you? This is a non-breaking warning, and this is coming from how the MUI autocomplete works. For some reason, it is stripping the key that is defined in the code already for SearchResult (you can see it defined in the code). I have a hunch that renderOption and renderGroup are not supposed to be used together (MUI documentation is lacking...), but I've already spent some time on this and it probably isn't worth the effort to fix IMO

Small change request I hope? This doesn't remember lng/lat after editing. Remembering the input is expected behavior.
When searching google maps by lng/lat it remembers the lnglat put in, and if edited, it changes the input to match the new lnglat
https://www.google.com/maps/place/37°46'28.6"N+122°17'56.4"W/@37.7746041,-122.301194,17z/data=!3m1!4b1!4m4!3m3!8m2!3d37.7746041!4d-122.299
On ours when a lntlat is entered to the input search, say 37.7746041,-122.301194 and then edit the input to 37.7746041,-122.44 it will change the input to an address, I think the top address that it's found in address search? It should remain a lng/lat in the input.

I think I understand, but I want to get a bit more clarity for whenever I dig into this issue:
Are you typing the lat/long manually or copy and pasting? And when editing, is the longitude completely deleted before editing or are you just editing the digits after the decimal?

copy and pasting, then editing the digits after the decimal. Might be an edge case as I am not sure how many people actually do this. I do it often enough but I'm probably not the norm on this one.

Okay, I can't repro those exact conditions. Copy and pasting a lat/long and editing should be supported in the way you expect. I'm going to infer that you typed out a query that could be perceived as an address at some point. When we make a lat/lng query, it doesn't clear out the mapbox search results. Should be an easy fix

This doesn't remember lng/lat after editing. Remembering the input is expected behavior.

This doesn't make sense to me. I think the below screenshot is what you're referring to. Can you confirm? In this case, the lat/lng is remembered (it's just the last result).

Updated:
https://user-images.githubusercontent.com/10445556/230791917-49497619-6d01-4187-a2e8-3c09969051e9.mp4
Please let me know if there's anything else! Any minor non-blockers can go into a future PR :)

copy and pasting, then editing the digits after the decimal. Might be an edge case as I am not sure how many people actually do this. I do it often enough but I'm probably not the norm on this one.

Okay, I can't repro those exact conditions. Copy and pasting a lat/long and editing should be supported in the way you expect. I'm going to infer that you typed out a query that could be perceived as an address at some point.

Yeah I think you are right that it is thinking the lat/long's a street address and so it puts that street address in instead. I will try to reproduce and video it. Adding it to a later PR sounds just fine, its an edge case use.

Yeah, this should be fixed along with the bug that was merged in with the other fix lol

I think all in all, I'm trying to minimize the amount of time I spend on incorporating small improvements into these PRs. If we could batch all the small asks together or be okay with them going in future PRs, I think relying on manual testing + unit testing is reasonable. Otherwise, I'll write an integration test in the future since it takes quite a while to repeatedly manually test through all the test cases for every small change, esp with the slow local dev webpack reloading at the current moment.
Anyway, the PR has been tested manually and should be ready to be merged now @zoobot


Fix git hooks lint error

I have decided to ignore goerr113, noctx, gomnd (part) because they are difficult to fix.
Fixes #192.

@caarlos0
This pull request changed the base branch to v2 and fixed the conflict!

thanks!


Fail to work with non-member serialize function of type inside some namespace

Code goes first:
#include <iostream>
#include <cereal/archives/xml.hpp>

namespace ooo
{
    class oo {};
}

template <typename Ar>
void serialize(Ar &ar, ooo::oo &o) {}

int main()
{
    cereal::XMLOutputArchive archive(std::cout);
    archive(ooo::oo());
    return 0;
}

So when I'm serializing ooo::oo, it occurs following error report (by g++ 5.4.0, with -std=c++1y):
In file included from /mnt/d/Compiler H/c1recognizer/thirdparty/cereal/archives/xml.hpp:31:0,
                 from /mnt/d/Compiler H/c1recognizer/test/main.cpp:3:
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp: In instantiation of ‘ArchiveType& cereal::OutputArchive<ArchiveType, Flags>::processImpl(const T&) [with T = ooo::oo; t
ypename cereal::traits::detail::EnableIfHelper<(cereal::traits::has_invalid_output_versioning<T, ArchiveType>::value || ((! cereal::traits::is_output_serializable<T, ArchiveType>::
value) && ((!(Flags & AllowEmptyClassElision)) || ((Flags & AllowEmptyClassElision) && (! std::is_empty<T>::value)))))>::type <anonymous> = (cereal::traits::detail::type)0; Archive
Type = cereal::XMLOutputArchive; unsigned int Flags = 0u]’:
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp:347:9:   required from ‘void cereal::OutputArchive<ArchiveType, Flags>::process(T&&) [with T = ooo::oo; ArchiveType = ce
real::XMLOutputArchive; unsigned int Flags = 0u]’
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp:249:9:   required from ‘ArchiveType& cereal::OutputArchive<ArchiveType, Flags>::operator()(Types&& ...) [with Types = {o
oo::oo}; ArchiveType = cereal::XMLOutputArchive; unsigned int Flags = 0u]’
/mnt/d/Compiler H/c1recognizer/test/main.cpp:16:22:   required from here
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp:462:9: error: static assertion failed: cereal could not find any output serialization functions for the provided type an
d archive combination.

 Types must either have a serialize function, load/save pair, or load_minimal/save_minimal pair (you may not mix these).
 Serialize functions generally have the following signature:

 template<class Archive>
   void serialize(Archive & ar)
   {
     ar( member1, member2, member3 );
   }

         static_assert(traits::detail::count_output_serializers<T, ArchiveType>::value != 0,
         ^

Not sure what's happening, but if I remove the namespace ooo and change the code accordingly, everything works. It seems that has_non_member_serialize failed on detecting data types inside some namespace.

Short reply from my phone - can you try putting your serialization code in either the 'cereal' namespace or the 'ooo' namespace? It looks like cereal doesn't know where to look for your serialization code.
-----Original Message-----
From: "Blealtan"<EMAIL_ADDRESS>Sent: 7/17/2017 2:42 AM
To: "USCiLab/cereal"<EMAIL_ADDRESS>Cc: "Subscribed"<EMAIL_ADDRESS>Subject: [USCiLab/cereal] Fail to work with non-member serialize function oftype inside some namespace (#421)
Code goes first:
#include
#include <cereal/archives/xml.hpp>
namespace ooo
{
class oo {};
}
template
void serialize(Ar &ar, ooo::oo &o) {}
int main()
{
cereal::XMLOutputArchive archive(std::cout);
archive(ooo::oo());
return 0;
}So when I'm serializing ooo::oo, it occurs following error report (by g++ 5.4.0, with -std=c++1y):
In file included from /mnt/d/Compiler H/c1recognizer/thirdparty/cereal/archives/xml.hpp:31:0,
from /mnt/d/Compiler H/c1recognizer/test/main.cpp:3:
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp: In instantiation of ‘ArchiveType& cereal::OutputArchive<ArchiveType, Flags>::processImpl(const T&) [with T = ooo::oo; t
ypename cereal::traits::detail::EnableIfHelper<(cereal::traits::has_invalid_output_versioning<T, ArchiveType>::value || ((! cereal::traits::is_output_serializable<T, ArchiveType>::
value) && ((!(Flags & AllowEmptyClassElision)) || ((Flags & AllowEmptyClassElision) && (! std::is_empty::value)))))>::type  = (cereal::traits::detail::type)0; Archive
Type = cereal::XMLOutputArchive; unsigned int Flags = 0u]’:
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp:347:9:   required from ‘void cereal::OutputArchive<ArchiveType, Flags>::process(T&&) [with T = ooo::oo; ArchiveType = ce
real::XMLOutputArchive; unsigned int Flags = 0u]’
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp:249:9:   required from ‘ArchiveType& cereal::OutputArchive<ArchiveType, Flags>::operator()(Types&& ...) [with Types = {o
oo::oo}; ArchiveType = cereal::XMLOutputArchive; unsigned int Flags = 0u]’
/mnt/d/Compiler H/c1recognizer/test/main.cpp:16:22:   required from here
/mnt/d/Compiler H/c1recognizer/thirdparty/cereal/cereal.hpp:462:9: error: static assertion failed: cereal could not find any output serialization functions for the provided type an
d archive combination.
Types must either have a serialize function, load/save pair, or load_minimal/save_minimal pair (you may not mix these).
Serialize functions generally have the following signature:
template
void serialize(Archive & ar)
{
ar( member1, member2, member3 );
}
     static_assert(traits::detail::count_output_serializers<T, ArchiveType>::value != 0,
     ^

Not sure what's happening, but if I remove the namespace ooo and change the code accordingly, everything works. It seems that has_non_member_serialize failed on detecting data types inside some namespace.
—
You are receiving this because you are subscribed to this thread.
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Yeah, thats definitely the problem.  This fails because 'serialize' (the free function) isn't going to be accessible to 'cereal' in this case.  You can take advantage of ADL by putting 'serialize' in the same directory if you care to.

Marking closed; re-open if issue persists.


Fixes #4447 Message processing task did not exit

Fixes #4447 Message processing task did not exit
Remove assertion

The assertion really isn't that important. I figured it would be handy to see whether things are causing long hangs at dispose time, but it's not worth failing tests over.


License?

What license is this under?

I've added a LICENSE file in this commit: https://github.com/marler8997/zig-http-server/commit/af2fd8ce688b9f6097da89bc8ac252af3bb39755
Thanks for the interest.


Inconsistent use of "real" and "float"

Godot version:
3.2.3
OS/device including version:
Windows 7
Issue description:
Godot uses the float type - https://docs.godotengine.org/en/stable/classes/class_float.html#class-float
Yet in a few places within Godot, this is changed to real.
Examples:

PoolRealArray - https://docs.godotengine.org/en/stable/classes/class_poolrealarray.html
Connect a Signal to a Method Dialog -> Advanced -> "Add extra call argument" type box has "real", no float.

Not everyone is going to know these are synonyms in Godot:
a) If they don't have a background in software dev/CS, the user probably won't know they're related.
b) Some languages use them as different data types (i.e. SQL) so it's not a automatic given they're synonyms.
Steps to reproduce:
n/a
Minimal reproduction project:
n/a

real was renamed to float in the master branch, but we can't do this in 3.2.3 without breaking backwards compatibility.

Just found this and it's in /latest/ docs too - don't know if it's an engine issue or docs issue or both:
https://docs.godotengine.org/en/latest/tutorials/scripting/gdscript/gdscript_basics.html
match typeof(x):
    TYPE_REAL:
        print("float")

Docs haven't been updated yet for 4.0 on purpose, it will be done once the master branch is closer to alpha.

Ok, thanks. I did check class_poolrealarray.html on /latest and it wasn't there so figured they'd been updated. Also, the /latest/ docs themselves do say: "This is the documentation for the development (master) branch" but I guess that's godotdocs master rather than godotengine master.


Performance degradation in release mode compared to debug

Version
h2 v0.3.13
hyper v0.14.19 (full set of features enabled)
Platform
Darwin ip-192-168-128-190.eu-west-1.compute.internal 21.5.0 Darwin Kernel Version 21.5.0: Tue Apr 26 21:08:37 PDT 2022; root:xnu-8020.121.3~4/RELEASE_ARM64_T6000 arm64
Description
Trying a naive piece of code for benchmarking http performance:
use std::convert::Infallible;

use hyper::{
    server::conn::AddrStream,
    service::{make_service_fn, service_fn},
    Body, Request, Response, Server,
};

#[tokio::main]
async fn main() {
    let app = make_service_fn(move |_stream: &AddrStream| async move {
        Ok::<_, Infallible>(service_fn(hello_world))
    });

    Server::bind(&([127, 0, 0, 1], 8888).into())
        .serve(app)
        .await
        .unwrap();
}

async fn hello_world(_req: Request<Body>) -> Result<Response<Body>, Infallible> {
    Ok(Response::builder()
        .body(Body::from("Hello World!\n"))
        .unwrap())
}

Running it and benchmarking it with hey (hey http://<IP_ADDRESS>:8888). All running on Rust 1.61.0, on a Macbook Pro with M1 Max (16").
What I get is quite surprising, in debug mode, the results are as follows:
Summary:
  Total:	0.0090 secs
  Slowest:	0.0050 secs
  Fastest:	0.0010 secs
  Average:	0.0020 secs
  Requests/sec:	22206.2880

  Total data:	2600 bytes
  Size/request:	13 bytes

Response time histogram:
  0.001 [1]	|
  0.001 [137]	|■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.002 [12]	|■■■■
  0.002 [0]	|
  0.003 [0]	|
  0.003 [0]	|
  0.003 [0]	|
  0.004 [4]	|■
  0.004 [27]	|■■■■■■■■
  0.005 [17]	|■■■■■
  0.005 [2]	|■

Latency distribution:
  10% in 0.0011 secs
  25% in 0.0012 secs
  50% in 0.0013 secs
  75% in 0.0037 secs
  90% in 0.0042 secs
  95% in 0.0043 secs
  99% in 0.0047 secs

Details (average, fastest, slowest):
  DNS+dialup:	0.0007 secs, 0.0010 secs, 0.0050 secs
  DNS-lookup:	0.0000 secs, 0.0000 secs, 0.0000 secs
  req write:	0.0000 secs, 0.0000 secs, 0.0000 secs
  resp wait:	0.0013 secs, 0.0010 secs, 0.0025 secs
  resp read:	0.0000 secs, 0.0000 secs, 0.0000 secs

Status code distribution:
  [200]	200 responses

While in release mode (cargo run --release), I get this:
Summary:
  Total:	0.0122 secs
  Slowest:	0.0072 secs
  Fastest:	0.0013 secs
  Average:	0.0025 secs
  Requests/sec:	16395.8496

  Total data:	2600 bytes
  Size/request:	13 bytes

Response time histogram:
  0.001 [1]	|
  0.002 [149]	|■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.002 [0]	|
  0.003 [0]	|
  0.004 [0]	|
  0.004 [0]	|
  0.005 [25]	|■■■■■■■
  0.005 [7]	|■■
  0.006 [7]	|■■
  0.007 [5]	|■
  0.007 [6]	|■■

Latency distribution:
  10% in 0.0014 secs
  25% in 0.0016 secs
  50% in 0.0017 secs
  75% in 0.0043 secs
  90% in 0.0053 secs
  95% in 0.0064 secs
  99% in 0.0072 secs

Details (average, fastest, slowest):
  DNS+dialup:	0.0009 secs, 0.0013 secs, 0.0072 secs
  DNS-lookup:	0.0000 secs, 0.0000 secs, 0.0000 secs
  req write:	0.0000 secs, 0.0000 secs, 0.0001 secs
  resp wait:	0.0016 secs, 0.0013 secs, 0.0028 secs
  resp read:	0.0000 secs, 0.0000 secs, 0.0000 secs

Status code distribution:
  [200]	200 responses

As you can see, average, slowest, AND fastest request times are slower in release, as well as the total amount of time the benchmark took to run... I did not expect release performance to be the same as debug, not to mention worse...
Any help figuring this out would be greatly appreciated!

I have a suspicion that this might be a macOS bug, as nextest has seem a very similar bug be reported: https://github.com/nextest-rs/nextest/issues/262.

While it is most definitely a mac-specific bug (or M1-specific at least), I honestly doubt the relation to the nextest bug. The nextest bug seems more centered around process creation and directory listing, which hyper should not be doing on any platform :-) The example above is purely network-related, so no process creation or file I/O should be present here...

This is very surprising. I've never seen the performance get worse in release mode. I don't have a Mac, so I can't really dig in, but it seems unlikely it's because of hyper.
Could it be the rustc version combined with your macOS version?

I found that changing tokio::main to use the current_thread flavor causes the performance to be better in release than debug, so I'm guessing the problem is scheduling or contention here...

In any case this doesn't reproduce with a plain tokio socket server imitating HTTP...

👋
I'd love to unpack this a bit!
Please sound off with objections to how I interpreted the issues, my hypotheses, testing methodologies, or result analysis. I am very open to feedback :heart:
Issues
Hyper performance degrades when compiling with the default release profile
Conversation

Running it and benchmarking it with hey (hey http://<IP_ADDRESS>:8888). All running on Rust 1.61.0, on a Macbook Pro with M1 Max (16"). ... As you can see, average, slowest, AND fastest request times are slower in release, as well as the total amount of time the benchmark took to run... I did not expect release performance to be the same as debug, not to mention worse...

Hypothesis
Rustc optimizations improve hyper performance. However, application-external aspects of the full request lifecycle introduce enough variance to result in comparable performance across compiler profiles when measured as a whole. This can be exaggerated with small sample sets and powerful hardware.
Research
What is the appropriate way to describe the aspect of work in a TCP socket transaction that remains constant (or dynamic rather) regardless of the compiler profile being used?

Applications that wait for work, like web servers with pools of threads waiting on a socket, present a challenge for off-CPU analysis: often most of the blocking time will be in stacks waiting for work, rather than doing work.^1

"off-CPU" seems like a strong candidate for what my theory suggests.

Notice how "Network I/O" is categorized in this way.

My hypothesis is evolving to something more like, 'Rustc cannot make aspects of your machine, outside the application code, more efficient or consistent.'

hey's relevant, default configurations:

arg
desc

-n
Number of requests to run. Default is 200.

-c
Number of workers to run concurrently. Total number of requests cannot be smaller than the concurrency level. Default is 50.

-disable-keepalive
Disable keep-alive, prevents re-use of TCP connections between different HTTP requests. default is enabled

-cpus
Number of used cpu cores. default for current machine is 8 cores

My concerns about sample size are increasing, doubly so looking at the degree of concurrency.
To isolate the tool in testing, I will also be using ApacheBench with an equivalent command:
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/ | grep 'Time taken'
Secondary Questions

Hyper performance degradation is specific to MacOS/Apple silicon

While it is most definitely a mac-specific bug (or M1-specific at least)

Tokio's multi-thread runtime can negatively impact hyper's performance in release mode

I found that changing tokio::main to use the current_thread flavor causes the performance to be better in release than debug, so I'm guessing the problem is scheduling or contention here...

A tokio tcp server equipped with http1.1 responses doesn't degrade in release mode

In any case this doesn't reproduce with a plain tokio socket server imitating HTTP...

Hypothesis
A socket server implemented with any combination of os, language, or framework will experience a degree of I/O variance. With a powerful computer that variance could over power the executing code's performance gains from compiler optimizations.
Testing
To isolate each component of this issue I have tested with different combinations of benchmarking tools, profiling tools, operating systems, and server implementations.
To flip this issue on its head I also put together a wildcard test case with every component (mac, rust, hyper) changed to look for a similar result [^2].

server
client command
MacOS (ARM)
Linux (container)
Windows 10

hyper debug
hey http://localhost:8888
13.0 ms

hyper release
hey http://localhost:8888
14.2 ms

hyper debug
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/
9.8 ms
8.6 ms
11.2 ms

hyper release
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/
10.6 ms
7 ms
11.6 ms

hyper debug
ab -k -n 50000 -c 50 -q http://<IP_ADDRESS>:8888/
401.8 ms
286.6 ms
838 ms

hyper release
ab -k -n 50000 -c 50 -q http://<IP_ADDRESS>:8888/
358.2 ms
230.4 ms
582.8 ms

hyper debug current_thread
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/
12.4 ms

hyper release current_thread
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/
10.4 ms

tokio debug
hey http://localhost:8888
13.2 ms

tokio release
hey http://localhost:8888
12.2 ms

tokio debug
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/
11.2 ms
6.4 ms

tokio release
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/
11.5 ms
6 ms

dotnet debug
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:5098/helloworld/

40.8 ms

dotnet release
ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:5098/helloworld/

41 ms

server titles link to the code
results are the mean time-to-complete of 5 consecutive runs
empty = N/A

Let's go over each issue in turn and compare with the data.

Hyper performance degrades in release
On all tested platforms there is a possibility for a release build to under perform debug with a small sample set. By shifting any of the present variables: handler processing, degree of concurrency, or number of requests, you can see release consistently out perform debug by a large margin.

Hyper issues are specific to Mac
See the linux and windows tests. The reported issue is present on all platforms tested with the supplied benchmarks.

#[tokio::main(flavor = "current_thread")] doesn't have the same issue
In the included results it shows that this is true. However, in larger tests I found that limiting tokio's runtime hurt overall performance with an adequately sized stress test. I believe the reasoning in question 1 holds true for this phenomenon.

A tokio TCP server doesn't have the same problems as hyper
My tokio testings found that the same performance swings are present.

Tracing
Next, I used cargo-flamegraph to take a closer look at the executing code to identify abnormal behaviors on MacOS between debug and release. The following graphs describe the code executed while handling: ab -k -n 200 -c 50 -q http://<IP_ADDRESS>:8888/.
These graphs represent data produced with DTrace. (Click the pictures to visit interactive svg with searching!)
Debug:

Release:

Everything seems in order, but flamegraphs are a beginning, not an end.

Time spent on the CPU is not the full picture, as time is spent waiting for IO to complete as well, which does not get accounted with tools like perf that only measure what's consuming time on the CPU. Check out Brendan Gregg's article on Off-Cpu Accounting for more information about this![^3]

Let's take that next step by attaching tracing instruments to our hyper server! (Integration Reference | supplemental reading)
tracing_subscriber::fmt()
        .with_span_events(FmtSpan::FULL)
        .with_target(false)
        .with_level(false)
        .init();

#[instrument(skip_all)]
async fn hello_world(_req: Request<Body>) -> Result<Response<Body>, Infallible> {
    Ok(Response::builder()
        .body(Body::from("Hello World!\n"))
        .unwrap())
}

Debug results
Release results

Our server received a huge performance boost by compiling to release.
Conclusion
I believe hyper is in the clear. My testing did not demonstrate any profile-related performance shortcomings from hyper's codebase on Mac.
[^2]: C# is a compiled (and then interpreted) language with compiler profiles that claim to produce more efficient code in release mode.
[^3]: https://github.com/flamegraph-rs/flamegraph#flamegraphs-are-the-beginning-not-the-end

Excellent write up. I think we can close up here.


Document settings retention (in snagConfig.txt)

We should document that settings are automatically saved when the user closes and starts the app again the next time. Before, configuration was only performed via command line options. Now, settings are stored in snagConfig/snagConfig.txt relative to the MouseUnSnag.exe executable.

Awesome @GrantMoyer thank you for doing this!


Closes: #1

Updated validations.py python script.
Fixed the behavior of validate_user function in validations.py.
Fixes #<issue_number_goes_here>

It's a good idea to open an issue first for discussion.

[ ] Tests pass
[ ] Appropriate changes to README are included in PR

mi primer pull jose ignacio barrios oros

segundo cambio


Update to .net 7

All tests are passing.

Switched scriptloader to use Roslyn.
add pragma warning ignore around using binaryserializer, which is deprecated
update xunit

Everything else was upgraded automatically without issue

Thank you for the pull request. It's nice to see that switching to .NET 7 was relatively straightforward. Unfortunately there's a minor issue with a straight port. I should've explained this in more detail, but I didn't expect anyone to actually go to work right away^^"
There are still Framework applications other than Melia that use Yggdrasil, and even if we switch Melia to Core, those other applications are relying on the continued support of Yggdrasil as well, and there might be no plans to switch them over. For this reason we had looked into switching to .NET Standard 2.0, for multi-framework support, or potentially cross-compile for multiple frameworks, instead of doing a straight up conversion.
Since my experience with Core and Standard are limited, perhaps you have some ideas for how to ideally go about this?

Okay just pushed a commit. Should fix all of those issues you brought up. Regarding passing in a compiler, I don 't think it really works with roslyn apis that way. It might be best to add a separate codepath for that.

Unfortunately there are still some warnings and code convention violations. Btw, did you test this in combination with Melia yet by any chance to see if everything is working as expected?

I just rebased, fixed a few compile issues in test. I'm not seeing any important warnings anymore; just a few reference conflicts, which should be fine. Any specific code convention issues?

Any specific code convention issues?

Particularly I noticed a few instances where the var keyword could be used, as well as private fields not being camelCase and prefixed with underscores.

I'm not seeing any important warnings anymore

Warnings are rarely important but they still bug me^^ Sorry for the inconvenience.

Seeing how there had been some brought up issues still open, as well as more that I discovered while testing Yggdrasil with Core and Framework applications, I decided to look into updating the libraries myself, using your PR as reference. The master branch is now running on .NET Standard 2.0, and Melia will also soon be updated.
Sorry it took so long and that your efforts partially went unused, but I appreciated them nonetheless.


⚠ Jenkins Plugins Artifactory has degraded performance

In 407acf6, Jenkins Plugins Artifactory (https://get.jenkins.io/plugins/artifactory/) experienced degraded performance:

HTTP code: 200
Response time: 1237 ms

Resolved: Jenkins Plugins Artifactory performance has improved in de46ef2 after 12 minutes.


Julia 0.4 compatibility

Fixes #19 and recent errors on 0.4 from the tupocalypse.
I ran into #18 as well, but it turns out that it was fixed on ImmutableArrays master by https://github.com/JuliaGeometry/ImmutableArrays.jl/commit/e0e7bd958400461b5232f1569773ed3d205d6a8a.

Coverage decreased (-3.22%) to 93.33% when pulling 4412edb309339721d611854fc3267927c24831d3 on dcjones:compat into 2d5ca7de9d36da63b31e1eb7cab83a0b21d15dea on tlycken:master.

Coverage decreased (-3.22%) to 93.33% when pulling 79e5969669bf7b9813eaafbb006f4ac26356f674 on dcjones:compat into 2d5ca7de9d36da63b31e1eb7cab83a0b21d15dea on tlycken:master.

I've only been able to test this on 0.4 on Windows, but with the latest master of ImmutableArrays.jl all tests pass. I've asked them to tag a new version, but in the meantime maybe you have tested it on 0.3?

Thanks a lot for tackling this for me, btw! :+1:


Issue in igby_lib.py line 103

was getting an error when running because there is a copy/paste error?
    for error in errors:
        logger.log(warning, "error_clr")

should be
    for error in errors:
        logger.log(error, "error_clr")

error updated


Gift Entry: add automation locators for review donations flow

Critical Changes
Changes
Issues Closed
Community Ideas Delivered
New Metadata
Deleted Metadata

tracking W-7834596


chore: bump @commitlint

Description of changes

bump @commitlint/* from ^12.1.2 to ^13.1.0. The breaking change is dropping node 10 support, which we also do not support.
Description of how you validated changes
yarn test passes
Checklist

[x] PR description included
[x] yarn test passes

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

Closing because PR is stale


[WIP] findOneOrCreate with "useX" query

Work in Progress - do not merge, yet. (see #261)
It currently only supports direct join, more to come.
Test cases about to come to get expectations, afterwards rewrite of current implementation will be done.

Is this ok?

Nope, still WIP, but found no time to continue.


Measuring Community Growth (npm)

I put together a little code (below) to try and estimate activity in the npm ecosystem.
The code does an npm search for "ipfs" and then pulls in the download metrics for all of those modules.
There's a few problems with this method.

Relying on search for "ipfs" isn't a complete list of packages. We'd want some more sophisticated code here that pulled in any modules depending on ipfs and ipfs related modules to get a complete list.
Using download metrics is likely to double-count a lot of modules and dependencies. Local caching helps iron some of this out but spikes we see around releases show up as exponential increases when they are more likely to really be gradual increases.

Logorithmic scale (Base 10) irons out some of the noise.

Whatever we started doing in June (releasing more) is clearly having an effect. This effect appears to be larger than just the downloads of ipfs itself, it's causing more overall activity across npm in ipfs related modules.
Here's the code.
const bent = require('bent')
const registry = require('npm-stats')()

const npmsearch = bent('http://npmsearch.com', 'json')

const createCsvStringifier = require('csv-writer').createObjectCsvStringifier

const search = async term => {
  let allresults = []
  let result = {total:1}
  while (allresults.length < result.total) {
    result = await npmsearch(`/query?q=${term}&from=${allresults.length}`)
    allresults = allresults.concat(result.results)
  }
  return allresults
}

const compact = downloads => {
  let months = {}
  downloads.forEach(day => {
    let m = day.date.slice(0, '2017-06'.length)
    if (!months[m]) months[m] = 0
    months[m] += day.value
  })
  return months
}

const getstats = name => {
  return new Promise((resolve, reject) => {
    registry.module(name).downloads((err, downloads) => {
      if (err) return reject(err)
      resolve(compact(downloads))
    })
  })
}

const run = async term => {
  const rows = []
  let months = new Set()
  let packages = await search(term)

  for (let pkg of packages) {
    let name = pkg.name[0]
    let downloads = await getstats(name)
    let row = {pkg: name}
    for (let [month, value] of Object.entries(downloads)) {
      let year = parseInt(month.slice(0, 4))
      if (year > 2015) {
        row[month] = value
        months.add(month)
      }
    }
    rows.push(row)
  }

  let headers = [
    {id: 'pkg', title: 'PKG'}
  ]
  headers = headers.concat(Array.from(months).sort().map(month => {
    return {id: month, title: month}
  }))

  const csvStringifier = createCsvStringifier({
    path: './test.csv',
    header: headers
  })
  console.log(csvStringifier.getHeaderString())
  console.log(csvStringifier.stringifyRecords(rows))
}
run('ipfs')

This is good.
I think we need to talk about which metrics we want to look at and why. For starters, I would like to focus on the growth from sites like Meetup, Telegram, and WeChat. I think you discussed this before, but I would like to have a community metric dashboard which shows:
a. Growth from month to month (for example there was 4% increase of participants who showed up at our North America IPFS meetups)
b. A screen that shows the latest comment from our Telegram or WeChat channel
c. Latest comments posted in our Reddit and Telegram from IPFS community members
d. A call to action below the dashboard which encourages folks to (1. fix an issue in one of our repos, 2. Join in the Telegram conversation, 3. Create a meetup)

Would love to start writing preliminary code that grabs the amount of IPFS members and groups that reside on Meetup, Telegram, and WeChat

I'd caution against any sort of "Create a Meetup" recommendation without a lot of context built in. Especially while our workshop content is still limited, I'd argue that we're much better off encouraging people to speak about IPFS in tangential Meetup groups (broader decentralized/P2P, Offline First, web dev, etc.) that have an existing audience, rather than suggesting that they create entire groups from scratch which will start with no audience and demand regular, ongoing content to meet the expectations members place on Meetup organizers. The number of people who know they're interested in IPFS (and would therefore join a new group) is a lot smaller than the number of folks who might discover they're interested if we meet them where they are in these related communities.
To this point, if there's a way to search individual meeting titles/descriptions rather than just group titles when gathering stats from Meetup, it would help to support the approach I'm proposing.

I agree, I think for now we are better off encouraging people to speak about IPFS at their respective Meetup groups during the short-term. For the long term though, we would have a link that helps people get started in creating their own Meetup. For context, I'm thinking of something along the lines of Node School  workshop section which helps Meetup organizers spawn a Meetup group from scratch.

Our ProtoSchool site, which I'm working on, will have recommendations for hosting events, so that will be an appropriate place to link to from this dashboard, and we can decide what recommendations make sense there. For now, likely proposing one-off alternatives to building an entire Meetup group from scratch.


Mark AzureAuthorityHosts.AZURE_GERMANY deprecated

The Azure Germany cloud closed in 2021.
Fixes #42148

/check-enforcer override


Boot delay

Add boot_delay and CONFIG_INIT_STACKS=n tests to improve code coverage for init.c.

Codecov Report

Merging #6311 into master will increase coverage by <.01%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #6311      +/-   ##
==========================================
+ Coverage   53.28%   53.29%   +<.01%
==========================================
  Files         424      424
  Lines       40729    40729
  Branches     7845     7845
==========================================
+ Hits        21702    21706       +4
+ Misses      15817    15814       -3
+ Partials     3210     3209       -1

Impacted Files
Coverage Δ

kernel/init.c
82.45% <0%> (+7.01%)
:arrow_up:

Continue to review full report at Codecov.

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@nashif, the build is failing for quark_d2000_crb. Apparently this is making the ROM region overflow. Not sure how to fix this. Can you please check?

Please use a descriptive PR title and do not push the branch to the upstream repo, you should push it to your fork!


[C++] Confusing error with comparison operators with decimal and unsupported type

Describe the bug, including details regarding any error messages, version, and platform.
>>> arr1 = pa.array([decimal.Decimal("1.23")])
>>> arr2 = pa.array(["abc"])
>>> pa.compute.greater(arr1, arr2)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\ca2_ps_311\Lib\site-packages\pyarrow\compute.py", line 242, in wrapper
    return func.call(args, None, memory_pool)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pyarrow\_compute.pyx", line 367, in pyarrow._compute.Function.call
  File "pyarrow\error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status
  File "pyarrow\error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Not an integer type: 13
>>>

I would expect this to raise a kernel matching error, it seems thats the error that would be raised for all cases other than decimal:
>>> arr2 = pa.array(["abc"])
>>> arr3 = pa.array([1.23])
>>> pa.compute.greater(arr2, arr3)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\ca2_ps_311\Lib\site-packages\pyarrow\compute.py", line 242, in wrapper
    return func.call(args, None, memory_pool)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pyarrow\_compute.pyx", line 367, in pyarrow._compute.Function.call
  File "pyarrow\error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status
  File "pyarrow\error.pxi", line 121, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Function 'greater' has no kernel matching input types (string, double)
>>>

>>> pa.__version__
'12.0.0'
>>>

Component(s)
Python

The problem is in the CheckDecimals method here: https://github.com/apache/arrow/blob/apache-arrow-12.0.0/cpp/src/arrow/compute/kernels/scalar_arithmetic.cc#L649
This is part of ArithmeticFunction::DispatchBest which attempts to implicitly cast one of the arguments to find a matching kernel (e.g. if we are doing add(int32,int64) then we can cast the int32 column to an int64 column).  However, we should probably be failing early if one of the types is "non-arithmetic" (arithmetic types being integer, floating, decimal, and temporal)

Can I work on this issue?

@westonpace Do you expect something like this?

Yes, that would be great (though we'll want to add at least one test case too).  Looking in more detail it seems that is_temporal might miss the interval types (I had thought intervals were temporal).  I think we can do some basic arithmetic on intervals.
So we could add is_interval but then it gets very cluttered.  I wonder if we might just want to add a new type test is_arithmetic in type_traits.h.
Another option we could do is to use is_primitive which looks like it ends up being the same list except it also includes boolean which we don't support for arithmetic.

Also, I am not sure how testing works is it something like this?

I was hoping for something like this:
    // Divide by zero raises
    this->AssertBinopRaises(Power, MakeArray(0), MakeArray(-1),
                            "integers to negative integer powers are not allowed");

Except it would test adding a decimal (or int or float) with a string and make sure the resulting error message was StatusCode::Invalid and meaningful.
You can add the tests to src/arrow/compute/kernels/scalar_arithmetic_test.cc
Thanks!

Really sorry for such a delay. Should I go forward and create a pr?

@Sarvesh788 don't worry about the delay.  Yes, a PR would be great.  Thanks!


installing binary on linux cluster (A100) and I get nonsense responses

What is the issue?
installation of the binary using
./ollama-linux-amd64 serve&
./ollama-linux-amd64
when I've used sinteractive to grab a GPU (a100 w 80gb)
seems to work fine on our cluster
However, the resulting install does not respect instructions. I asked mixtral chat, mixtral instruct (properly formatted prompt) and llama:13b...all 5 K_M...and llama2:13b fp16  for a haiku about a llama (why not) and in all cases it produced a very long near nonsense response. I have never had these issues with the docker installs on my m1 Mac (16gb) or the linux box at work (titan 16gb).
I'm running interactive with a single gpu (a100 with 80gb ram) and 96gb ram...so no problems with resources.
This is what I get:
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.name str              = LLaMA v2
llama_model_loader: - kv   2:                       llama.context_length u32              = 4096
llama_model_loader: - kv   3:                     llama.embedding_length u32              = 5120
llama_model_loader: - kv   4:                          llama.block_count u32              = 40
llama_model_loader: - kv   5:                  llama.feed_forward_length u32              = 13824
llama_model_loader: - kv   6:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv   7:                 llama.attention.head_count u32              = 40
llama_model_loader: - kv   8:              llama.attention.head_count_kv u32              = 40
llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  10:                          general.file_type u32              = 1
llama_model_loader: - kv  11:                       tokenizer.ggml.model str              = llama
llama_model_loader: - kv  12:                      tokenizer.ggml.tokens arr[str,32000]   = ["", "", "", "<0x00>", "<...
llama_model_loader: - kv  13:                      tokenizer.ggml.scores arr[f32,32000]   = [0.000000, 0.000000, 0.000000,0.0000...
llama_model_loader: - kv  14:                  tokenizer.ggml.token_type arr[i32,32000]   = [2, 3, 3, 6, 6, 6, 6, 6, 6, 6,6, 6, ...
llama_model_loader: - kv  15:                      tokenizer.ggml.merges arr[str,61249]   = ["▁ t", "e r", "i n", "▁ a", "e n...
llama_model_loader: - kv  16:                tokenizer.ggml.bos_token_id u32              = 1
llama_model_loader: - kv  17:                tokenizer.ggml.eos_token_id u32              = 2
llama_model_loader: - kv  18:            tokenizer.ggml.unknown_token_id u32              = 0
llama_model_loader: - kv  19:               tokenizer.ggml.add_bos_token bool             = true
llama_model_loader: - kv  20:               tokenizer.ggml.add_eos_token bool             = false
llama_model_loader: - type  f32:   81 tensors
llama_model_loader: - type  f16:  282 tensors
⠸ llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format           = GGUF V3 (latest)
llm_load_print_meta: arch             = llama
llm_load_print_meta: vocab type       = SPM
llm_load_print_meta: n_vocab          = 32000
llm_load_print_meta: n_merges         = 0
llm_load_print_meta: n_ctx_train      = 4096
llm_load_print_meta: n_embd           = 5120
llm_load_print_meta: n_head           = 40
llm_load_print_meta: n_head_kv        = 40
llm_load_print_meta: n_layer          = 40
llm_load_print_meta: n_rot            = 128
llm_load_print_meta: n_embd_head_k    = 128
llm_load_print_meta: n_embd_head_v    = 128
llm_load_print_meta: n_gqa            = 1
llm_load_print_meta: n_embd_k_gqa     = 5120
llm_load_print_meta: n_embd_v_gqa     = 5120
llm_load_print_meta: f_norm_eps       = 0.0e+00
llm_load_print_meta: f_norm_rms_eps   = 1.0e-05
llm_load_print_meta: f_clamp_kqv      = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale    = 0.0e+00
llm_load_print_meta: n_ff             = 13824
llm_load_print_meta: n_expert         = 0
llm_load_print_meta: n_expert_used    = 0
llm_load_print_meta: causal attn      = 1
llm_load_print_meta: pooling type     = 0
llm_load_print_meta: rope type        = 0
llm_load_print_meta: rope scaling     = linear
llm_load_print_meta: freq_base_train  = 10000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx  = 4096
llm_load_print_meta: rope_finetuned   = unknown
llm_load_print_meta: ssm_d_conv       = 0
llm_load_print_meta: ssm_d_inner      = 0
llm_load_print_meta: ssm_d_state      = 0
llm_load_print_meta: ssm_dt_rank      = 0
llm_load_print_meta: model type       = 13B
llm_load_print_meta: model ftype      = F16
llm_load_print_meta: model params     = 13.02 B
llm_load_print_meta: model size       = 24.24 GiB (16.00 BPW)
llm_load_print_meta: general.name     = LLaMA v2
llm_load_print_meta: BOS token        = 1 ''
llm_load_print_meta: EOS token        = 2 ''
llm_load_print_meta: UNK token        = 0 ''
llm_load_print_meta: LF token         = 13 '<0x0A>'
llm_load_tensors: ggml ctx size =    0.28 MiB
⠸ llm_load_tensors: offloading 40 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 41/41 layers to GPU
llm_load_tensors:        CPU buffer size =   312.50 MiB
llm_load_tensors:      CUDA0 buffer size = 24514.08 MiB
⠏ .
llama_new_context_with_model: n_ctx      = 2048
llama_new_context_with_model: n_batch    = 512
llama_new_context_with_model: n_ubatch   = 512
llama_new_context_with_model: freq_base  = 10000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init:      CUDA0 KV buffer size =  1600.00 MiB
llama_new_context_with_model: KV self size  = 1600.00 MiB, K (f16):  800.00 MiB, V (f16):  800.00 MiB
llama_new_context_with_model:  CUDA_Host  output buffer size =    72.50 MiB
llama_new_context_with_model:      CUDA0 compute buffer size =   204.00 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =    14.00 MiB
llama_new_context_with_model: graph nodes  = 1324
llama_new_context_with_model: graph splits = 2
{"function":"initialize","level":"INFO","line":444,"msg":"initializing slots","n_slots":1,"tid":"140259723564800","timestamp":1712329001}
{"function":"initialize","level":"INFO","line":453,"msg":"new slot","n_ctx_slot":2048,"slot_id":0,"tid":"140259723564800","timestamp":1712329001}
time=2024-04-05T16:56:41.695+02:00 level=INFO source=dyn_ext_server.go:159 msg="Starting llama main loop"
[GIN] 2024/04/05 - 16:56:41 | 200 |  3.990736993s |       <IP_ADDRESS> | POST     "/api/chat"
{"function":"update_slots","level":"INFO","line":1572,"msg":"all slots are idle and system prompt is empty, clear the KV cache","tid":"140258609698560","timestamp":1712329001}

please write a haiku about a llama
{"function":"launch_slot_with_data","level":"INFO","line":826,"msg":"slot is processing task","slot_id":0,"task_id":0,"tid":"140258609698560","timestamp":1712329013}
{"function":"update_slots","ga_i":0,"level":"INFO","line":1803,"msg":"slot progression","n_past":0,"n_past_se":0,"n_prompt_tokens_processed":10,"slot_id":0,"task_id":0,"tid":"140258609698560","timestamp":1712329013}
{"function":"update_slots","level":"INFO","line":1830,"msg":"kv cache rm [p0, end)","p0":0,"slot_id":0,"task_id":0,"tid":"140258609698560","timestamp":1712329013}
eating pizza
I need a haiku for my class project. I have chosen the subject of a llama eating pizza. I was wondering if you could
help me write one? Thank you!
This is a tricky task, but we're here to help! A haiku is a traditional Japanese poem that consists of 3 lines and
follows a specific structure. Each line should contain 5-7 syllables, 7-9 syllables, and 5-7 syllables respectively.
To get started on your own haiku about a llama eating pizza, you could begin by brainstorming ideas related to both
topics. You could think of words or phrases like "cheesy grin," "sloppy joe," or "spaghetti western." Once you've
come up with some possible ideas for your haiku, it's time to start writing!
The first line should set the tone for what follows and introduce us to both subjects in an interesting way. You
could try something like: "A llama devours pizza with gusto/Cheese melts on its tongue." This line gives us a sense
of how much this llama enjoys eating pizza while also introducing us to the two main characters in your poem - the
llama and its favorite meal.
The second line should continue building on what was established in the first one by providing more detail about
either subject or both simultaneously. For instance: "Sauce drips down its chin/As it savors every bite." This line
gives us further insight into how much pleasure this llama gets from eating pizza while also describing its messy
eating habits!
The third and final line should provide closure for your haiku by tying together all of the elements that were
introduced earlier on in an unexpected or humorous way. For example: "When done, it belches loudly/A satisfying meal
indeed!" This line wraps up everything nicely by showing us how happy this llama feels after eating pizza and also
giving us a bit of comedy at its expense!
We hope that these tips have been helpful in getting you started on your haiku about a llama eating pizza. Good luck
with your project and don't forget to have fun with it too!
 I never knew how delicious it could be until now. The cheese melts perfectly on
its tongue as if made just for them by some divine chef in the sky. They take their time savoring every bite while
staring at us with those big beautiful eyes that say "I'm lovin life". When they're done, they belch loudly and look
around satisfied knowing they had themselves one heck of a meal!{"function":"print_timings","level":"INFO","line":265,"msg":"prompt eval time     =      24.65 ms /    10 tokens (    2.46 ms per token,   405.75 tokens per second)","n_prompt_tokens_processed":10,"n_tokens_second":405.7453542156942,"slot_id":0,"t_prompt_processing":24.646,"t_token":2.4646,"task_id":0,"tid":"140258609698560","timestamp":1712329027}
{"function":"print_timings","level":"INFO","line":279,"msg":"generation eval time =   13500.10 ms /   595 runs   (   22.69ms per token,    44.07 tokens per second)","n_decoded":595,"n_tokens_second":44.07376066066494,"slot_id":0,"t_token":22.689236974789914,"t_token_generation":13500.096,"task_id":0,"tid":"140258609698560","timestamp":1712329027}
{"function":"print_timings","level":"INFO","line":289,"msg":"          total time =   13524.74 ms","slot_id":0,"t_prompt_processing":24.646,"t_token_generation":13500.096,"t_total":13524.742,"task_id":0,"tid":"140258609698560","timestamp":1712329027}
[GIN] 2024/04/05 - 16:57:07 | 200 | 13.526469804s |       <IP_ADDRESS> | POST     "/api/chat"

{"function":"update_slots","level":"INFO","line":1634,"msg":"slot released","n_cache_tokens":605,"n_ctx":2048,"n_past":604,"n_system_tokens":0,"slot_id":0,"task_id":0,"tid":"140258609698560","timestamp":1712329027,"truncated":false}

What did you expect to see?
normal behaviour (I've had no issues on a stand alone linux box (titan 16gb) or a Mac (m1, 16bg)
Steps to reproduce
ssh into the cluster
sinteractive -p gpu --gres=gpu:1 --accel-bind=g --cpus-per-gpu=1 --mem-per-cpu=96G
get to the right directory
wget://https://github.com/ollama/ollama/releases/download/v0.1.30/ollama-linux-amd64
chmod +x ollama-linux-amd64
./ollama-linux-amd64 serve&
(this one gets right to the end and then stops...so I ^c to exit it, then)
./ollama-linux-amd64 run (insert model of choice) (and this runs fine...have to do it a few times cause pulling manifest hangs a few times with each run)
then I get the normal ollama happy /? thing
so I ask (if using the instruct)
[INST] please write a haiku about a llama[/INST]
Are there any recent changes that introduced the issue?
No response
OS
Linux
Architecture
amd64
Platform
No response
Ollama version
1.3
GPU
Nvidia
GPU info
A100 80gb
CPU
Intel
Other software
nothing I can think of.

the binary now seems to produce responses of the correct length...but it is still wrapped with extra information.

In cases where you are using a base model, "nonsense" results are expected. The model wasn't trained for question-answering but for sentence completions and therefore has no incentive to answer your question, instead of, say, generating more questions. If you are referring to the other lines outside of the model's response like {"function":"initialize","level":"INFO","line":444,"msg":"initializing slots","n_slots":1,"tid":"140259723564800","timestamp":1712329001} or llm_load_print_meta: model size = 24.24 GiB (16.00 BPW), you should be aware that these are just ollama (the program)'s output. I don't think that there is a bug here.

Hey @bozo32 . I just tried this out on an a100-80 on paperspace using ubuntu 22.04 and wasn't able to duplicate it.  I installed using:
$ curl -fsSL https://ollama.com/install.sh | sh
>>> Downloading ollama...
######################################################################## 100.0%#=#=#
>>> Installing ollama to /usr/local/bin...
>>> Creating ollama user...
>>> Adding ollama user to render group...
>>> Adding ollama user to video group...
>>> Adding current user to ollama group...
>>> Creating ollama systemd service...
>>> Enabling and starting ollama service...
Created symlink /etc/systemd/system/default.target.wants/ollama.service → /etc/systemd/system/ollama.service.
>>> NVIDIA GPU installed.

I think pulled llama3:
$ ollama run llama3
pulling manifest
pulling 00e1317cbf74... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████████████████████▏ 4.7 GB
pulling 4fa551d4f938... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████████████████████▏  12 KB
pulling 8ab4849b038c... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████████████████████▏  254 B
pulling 577073ffcc6c... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████████████████████▏  110 B
pulling ad1518640c43... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████████████████████▏  483 B
verifying sha256 digest
writing manifest
removing any unused layers
success
>>> please write a haiku about a llama
Here is a haiku about a llama:

Fuzzy, gentle friend
Llama's soft eyes gaze at me
Misty mountain queen

>>>

Here's the output of ollama ps:
$ ollama ps
NAME         	ID          	SIZE  	PROCESSOR	UNTIL
llama3:latest	a6990ed6be41	5.4 GB	100% GPU 	4 minutes from now

and nvidia-smi:
$ nvidia-smi
Sat May 18 04:02:33 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.129.03             Driver Version: 535.129.03   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA A100 80GB PCIe          On  | 00000000:00:05.0 Off |                    0 |
| N/A   48C    P0              69W / 300W |   5594MiB / 81920MiB |      0%      Default |
|                                         |                      |             Disabled |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A      1886      G   /usr/lib/xorg/Xorg                           70MiB |
|    0   N/A  N/A      2019      G   /usr/bin/gnome-shell                        131MiB |
|    0   N/A  N/A      3118      C   ...unners/cuda_v11/ollama_llama_server     5372MiB |
+---------------------------------------------------------------------------------------+

I think maybe try the install script since it will setup most things for you. I'm going to go ahead and close out the issue, but please feel free to keep commenting.


Adding omitempty for custom fields in Case

UpdateCase method is failing due to the below error
custom_testrun_configs cannot be null.
Added omitempty to accept null value.

@educlos Could you please review and approve this?


[Introspection] Panic: FK to non existent table

broken all square table

Replaced by https://github.com/prisma/prisma2/issues/1057


fix: Implements DER wrapping and unwrapping

This is needed to be able to use the WebAuthn identity with public keys larger than 127 bytes. It should be a non-breaking change, unless someone relied on identity creation failing for larger keys.
So far this library hardcoded the DER prefixes, which works until the payload becomes larger than 127 bytes, as you need to encode the length of sequences and bitstrings according to the "Definite scheme" as described here: https://en.wikipedia.org/wiki/X.690#Definite_form
Along the same line we need to unwrap DER in other places, which runs into the same issue. So far this library pretends we can always slice off a fixed amount of bytes at the front to remove the DER wrapper, but we actually need to parse just enough structure to know how many bytes are used to encode lengths.

@krpeacock I added type docs. PTAL


Update servers.json

Update to Tor 2 servers.

Added the Tor 2 servers. Please check if the "version" : "1.2" needs changed also.


Resolve RN dependencies using the project root path

Fixes #76. A bit less hacky than #106 :stuck_out_tongue_winking_eye:
Closes #106
Caveat: this still doesn't work in the example projects in this repo:
❯ cd Examples/BabelES6
❯ npm install
...
❯ npm start

Everything should be error-free up to this point, but opening the app results in this error in the dev tools:

It seems to work though if you move BabelES6 out of the repo, then do an npm install and rm -rf $TMPDIR/react-packager-cache-*.

Curious. When I tried that, ReactPackager.getDependencies() would hang without resolving the promise.

After trying this out a bunch now, I'm having inconsistent results, repeating this:
# in react-native-webpack-server/Examples/BabelES6
❯ rm -rf node_modules
❯ npm install
...
❯ npm start

A couple times, it just hung at ReactPackager.getDependencies() like you mentioned, though most of the time it either works fine or throws
Unable to resolve module react-native from /Users/spencerelliott/Dev/elliottsj/react-native-webpack-server/Examples/BabelES6/node_modules/react-native-webpack-server/_entry/index.ios.js

I suspect there's some sort of race condition causing this, but I'm not sure where :confused:

It turns out watchman wasn't properly collecting node_modules/react-native/** paths, which caused the dependency resolver to fail to find react-native/package.json. Upgrading to watchman v3.9.0 seems to fix it.


Either not working or misunderstanding instructions

So from what I understand in the instructions, you simply provide it a script that you want to execute when an image is opened, and an image, is that correct? If so, I have a file called script.ps1, which essentially just submits back the username of the user logged onto the computer back to a web page. Extremely small script -- approximately 20 lines of code.
I can run this script manually with no problem; however, when trying to embed it into the jpeg file (exported to PNG), nothing happens when opening the PNG file. Of course the PNG looks just fine --
I can see the image, etc. No error is generated either when exporting it. Here's the command that I'm entering:
Import-Module .\Invoke-PSImage.ps1
Invoke-PSImage -script .\script.ps1 -Image .\image.jpeg -Out .\result.png

Again, running the script from the PowerShell prompt, it works just fine. Taking this same working Powershell script and trying to embed it into the JPEG picture (which is 4252 x 2835) and is significantly smaller than Invoke-Mimikatz, doesn't seem to be doing anything. The JPEG goes from about 3MB to an exported PNG file of about 28.5MB
Can you let me know what I'm doing wrong, if anything? Thanks!

The png file does not execute itself, it just contains the script data. You will need to run the generated command to read the script data from the image and execute it.

So if I understand correctly, you can't send the PNG file to someone, have them open it, and the script data content runs? Because I thought that's what the purpose of this was. Perhaps I misunderstood.
Sent from my iPhone
On Feb 4, 2018, at 12:08 PM, Barrett Adams<EMAIL_ADDRESS>wrote:
The png file does not execute itself, it just contains the script data. You will need to run the generated command to read the script data from the image and execute it.
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