Release new version

It seems a lot of work has been done since 0.7 was released. Can you release a new version onto PyPi, so it can easily be included in a requirements.txt file?

Ah yes, I was stuck with Django 1.8 compat and forgot to make a release when it was done. Working on it :)

Done, 0.8.1 is on PyPI.


Remove restricted area "R160" at EGLL

Thanks @tedrek for pointing out that R160 applies to helicpoters only!

:+1:


Vulnerability roundup 99: docker-18.09.9: 2 advisories [6.8]

search, files

[ ] CVE-2021-21284 CVSSv3=6.8 (nixos-20.09)
[ ] CVE-2021-21285 CVSSv3=6.5 (nixos-20.09)

Scanned versions: nixos-20.09: 95ce0f52ec1.
Cc @nequissimus
Cc @offlinehacker
Cc @periklis
Cc @tailhook
Cc @vdemeester

See also: #109156

NixOS 20.09 is EOL, so this issue isn't actionable anymore.


Use DirectX instead of CUDA

Hi, Is it possible to use DirectX as an alternative to CUDA? If so, could you please provide guidance on how to implement this?

@ZCOREP I have tried the Vulkan backend on my computer, and it works very well. The version of llamasharp I am currently using is 0.19.0.


Usermin > Delete Spam

I just installed version 19.05 and while it addresses many pressing issues with 19.04, I've discovered that when you press "Delete Spam" button on either the message list, or within a message, it triggers a new window to be launched instead of changing the right panel of the current window.
I've not checked other buttons in the UI, but I suspect it may affect other buttons so might want to check just in case.

Hi, Peter. It's not going to affect other buttons. It's just for those specifically.
It will be changed on mail rework completely.


Update docs per new implementation

no creating acr by default, only attaching through role assignment
@mlearned Can you please quickly run through this doc and approve. Please make sure you run the actual commands.. I did but i want someone else to do as well

@sauryadas : Thanks for your contribution! The author(s) have been notified to review your proposed change.

@sauryadas : Thanks for your contribution! The author(s) have been notified to review your proposed change.

#sign-off


Added support for Python 3.12.

No review needed.

coverage: 25.0%. remained the same when pulling b60176bf3487b8f4710fba93a13e9fa421a55797 on andy/add-py312 into 3619918ed7dae02a6c98b45d574d324c50cac541 on master.


input value changes by JQ code ,v-model variable don't changes ?

HTML

  <input type="text" id="input" v-model="value"/>

  Vue-model: {{value}}

  input value changed, but model value didn't changed?

  can model value auto updated by other JS code that change input value?

JS
new Vue({
	data:{"value":"one"},
  el:"#vue"
})

setTimeout(function(){
	$("#input").val("two")
 },1000)

here is run code: https://jsfiddle.net/monkong/xmdpksa5/9/

Hello ...,
thank you for your interest in this project.
Please follow the guidelines on how to report an issue. In particular, provide an example on www.jsfiddle.net (or a similar service) that reproduces the problem.
Thank you.

This is the second time today. Please - use the forum or gitter.


Fix Embedded objectmeta

https://github.com/kubernetes-sigs/controller-tools/issues/448
https://github.com/kubernetes-sigs/controller-tools/pull/539

@regadas  This fixes a bug that we have in Rook https://github.com/rook/rook/issues/7629. Is it possible for us to request a new build of controller-gen so that we can start using a released version of this fix in our build environment?

@BlaineEXE I was checking if this fix is in the recent release and stumble upon your comment ... sorry I completely missed it!


Add fwd implementation for Phi_approx

Summary:
Because the primitive version of Phi_approx is templated, the fwd and mix cases can be currently handled. However, in order to vectorize the function, we will need to implement the fwd version.
Description:
We need to create stan/math/fwd/scal/fun/Phi_approx.hpp to handle the fwd and mix cases when we untemplate the primitive version.
Reproducible Steps:
I found this while trying to vectorize the function.
Current Output:
There are two implementations of Phi_approx: one in stan/math/prim/scal/fun and one in stan/math/rev/scal/fun.
Expected Output:
There will be three implementations of Phi_approx: one in stan/math/prim/scal/fun, one in stan/math/rev/scal/fun, and one in stan/math/fwd/scal/fun.
Current Version:
v2.9.0

Please don't do this.  Instead, you should figure out how to get the vectorization to work with what it has.
You don't list here what the problem is with not having the fwd and rev versions.


Restful API /paths/{path}/exists return 200 with empty content

Alluxio Version:
2.9.3
Describe the bug
Restful /paths/{path}/exists API return 200 with empty content, for example 'exists' should return true or false and never expected to have an empty bytes as return value
To Reproduce
make a call using curl or any sdk (based on result api)
references:
https://docs.alluxio.io/os/restdoc/2.9.3/proxy/index.html
https://docs.alluxio.io/os/user/stable/cn/api/Clients-Python.html
Expected behavior
Get expected response content
e.g. using the latest alluxio python client
with V2.9.3, I get

with V2.8.0, I get

or

Urgency
NOTE! not only 'exists' has such issue, 'ls'  turn out the same behavior, 'create-direcotry' not work but still return 200
Are you planning to fix it
Additional context

it seems like a bug, If alluxio.proxy.s3.v2.version.enabled and alluxio.proxy.s3.v2.async.processing.enabled are set false proxy rest api functionality can be restored. you can have a try.

is this issue being tracked?

@xiaohu-liu thank you a lot!
this workaround works with 2.9.5 version :+1:


Version is still at 2.1.3 in bignumber.js file

https://github.com/MikeMcl/bignumber.js/blob/master/bignumber.js#L1
:shipit:

Corrected, thanks.

Thank you @MikeMcl :beers:


Consistant card corruption on power loss

Stratux version:

Stratux config:
SDR

[ ] single
[x] dual

GPS

[x] yes
[ ] no
type:

AHRS

[ ] yes
[ ] no

power source: 2A
usb cable: Anker

EFB app and version: Foreflight
EFB platform: iOS
EFB hardware: iPad Mini 4

Description of your issue:

On first power up, everything is great and works as expected.  If you unplug the unit without going into the web interface and selecting "shutdown" however, the SD card becomes corrupted and the stratux application will not open the access point on subsequent startups.  Did not have this issue in 1.0 for whatever reason but it's been a significant issue in 1,2.

Do you have errors on the console/fsck output? Is the only symptom you're seeing that the access point does not come up? What SD card type, speed, brand, and source?

I'll do some testing when I get a chance.  Currently in the middle of IFR training so it's hard find time to have my system down.
I can tell you that I've tried both SanDisk (32GB UHS-1) and Lexar (32GB UHS-1) cards and both failed the same way.  Both were purchased through amazon and have not had issues with other devices.
Currently the only symptom I'm seeing is a failure to bring up the access point.  I connected to a display and was able to log in and poke around without issue.  Systemd didn't appear to report any issues on startup but I didn't do a thorough examination of dmesg or any other logs.

I'm having this issue as well. Card isn't "corrupted" persay but no AP is started.
I'm using a Pi Zero W.

Different issue - the default image isn't configured for the Pi Zero W.

@cyoung Okay, well I opened #579 anyhow

@pdelbarba - try v1.2r2 and reopen if you have the issue again.


Got rid of vertical scroll

horizontal too? <3

Why, though?
Eventually scrolling vertically will be necessary. Horizontal scrolling is already needed now, since the map won't fully fit in some displays.

True


Dataclass problem with redefined field

Environment data

Language Server version: 2021.7.4
Python version (& distribution if applicable, e.g. Anaconda): Python 3.8.5

Expected behaviour
No problem detected when the field creation is inside an other method.
Independent on where the field method is called.
It seams to me that Pylance is not aware, that prop_a is not a init parameter anymore, when it is not overwritten directly but indirectly.
Actual behaviour
For example class C there is no problem linted but for class B:
Fields without default values cannot appear after fields with default
Logs

[Info  - 11:55:44 AM] Pylance language server 2021.7.4 (pyright 209f9621) starting
[Info  - 11:55:44 AM] Server root directory: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist
[Info  - 11:55:44 AM] No configuration file found.
[Info  - 11:55:44 AM] No pyproject.toml file found.
[Info  - 11:55:44 AM] Setting pythonPath for service "code": "/home/me/anaconda3/bin/python"
[Warn  - 11:55:44 AM] stubPath /home/me/my/code/typings is not a valid directory.
[Info  - 11:55:44 AM] Assuming Python version 3.8
[Info  - 11:55:44 AM] Assuming Python platform Linux
Search paths for /home/me/my/code/
  /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib
  /home/me/my/code/
  /opt/ros/melodic/lib/python2.7/dist-packages
  /home/me/my/code/typings
  /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stubs/...
  /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/bundled/stubs
  /opt/ros/melodic/lib/python2.7/dist-packages
  /home/me/anaconda3/lib/python3.8
  /home/me/anaconda3/lib/python3.8/lib-dynload
  /home/me/anaconda3/lib/python3.8/site-packages
  /home/me/anaconda3/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg
[Warn  - 11:55:45 AM] Exception received when installing recursive file system watcher: TypeError [ERR_FEATURE_UNAVAILABLE_ON_PLATFORM]: The feature watch recursively is unavailable on the current platform, which is being used to run Node.js
[Warn  - 11:55:45 AM] Exception received when installing recursive file system watcher: TypeError [ERR_FEATURE_UNAVAILABLE_ON_PLATFORM]: The feature watch recursively is unavailable on the current platform, which is being used to run Node.js
[Warn  - 11:55:45 AM] Exception received when installing recursive file system watcher: TypeError [ERR_FEATURE_UNAVAILABLE_ON_PLATFORM]: The feature watch recursively is unavailable on the current platform, which is being used to run Node.js
[Warn  - 11:55:45 AM] Exception received when installing recursive file system watcher: TypeError [ERR_FEATURE_UNAVAILABLE_ON_PLATFORM]: The feature watch recursively is unavailable on the current platform, which is being used to run Node.js
[Warn  - 11:55:45 AM] Exception received when installing recursive file system watcher: TypeError [ERR_FEATURE_UNAVAILABLE_ON_PLATFORM]: The feature watch recursively is unavailable on the current platform, which is being used to run Node.js
[Info  - 11:55:45 AM] Searching for source files
[Info  - 11:55:45 AM] Found 16 source files
[FG] parsing: /home/me/my/code/folder/test.py (20ms)
[FG] parsing: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/builtins.pyi [fs read 3ms] (93ms)
[FG] binding: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/builtins.pyi (28ms)
[FG] binding: /home/me/my/code/folder/test.py (1ms)
[Info  - 11:55:45 AM] Background analysis(1) root directory: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist
[Info  - 11:55:45 AM] Background analysis(1) started
Background analysis message: setConfigOptions
Background analysis message: ensurePartialStubPackages
Background analysis message: setTrackedFiles
Background analysis message: markAllFilesDirty
Background analysis message: setFileOpened
Background analysis message: getSemanticTokens full
[BG(1)] getSemanticTokens full at /home/me/my/code/folder/test.py ...
[BG(1)]   parsing: /home/me/my/code/folder/test.py (23ms)
[BG(1)]   parsing: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/builtins.pyi [fs read 2ms] (89ms)
[BG(1)]   binding: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/builtins.pyi (30ms)
[BG(1)]   binding: /home/me/my/code/folder/test.py (0ms)
[BG(1)]   parsing: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/typing.pyi [fs read 2ms] (27ms)
[BG(1)]   binding: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/typing.pyi (10ms)
[BG(1)]   parsing: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/_typeshed/__init__.pyi [fs read 0ms] (7ms)
[BG(1)]   binding: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/_typeshed/__init__.pyi (1ms)
[BG(1)]   parsing: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/typing_extensions.pyi [fs read 1ms] (3ms)
[BG(1)]   binding: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/typing_extensions.pyi (1ms)
[BG(1)]   parsing: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/dataclasses.pyi [fs read 0ms] (6ms)
[BG(1)]   binding: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/dataclasses.pyi (2ms)
[BG(1)]   parsing: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/abc.pyi [fs read 0ms] (1ms)
[BG(1)]   binding: /home/me/.vscode/extensions/ms-python.vscode-pylance-2021.7.4/dist/typeshed-fallback/stdlib/abc.pyi (0ms)
[BG(1)] getSemanticTokens full at /home/me/my/code/folder/test.py (243ms)
Background analysis message: analyze
[BG(1)] analyzing: /home/me/my/code/folder/test.py ...
[BG(1)]   checking: /home/me/my/code/folder/test.py (7ms)
[BG(1)] analyzing: /home/me/my/code/folder/test.py (7ms)
Background analysis message: getSemanticTokens range
[BG(1)] getSemanticTokens range 0:0 - 25:0 at /home/me/my/code/folder/test.py (3ms)
Background analysis message: resumeAnalysis

Code Snippet / Additional information

# %%
from dataclasses import dataclass, field

def result():
    return field(init=False, repr=False, hash=False, compare=False)

@dataclass
class A():
    prop_a: str

@dataclass
class B(A):
    prop_a: str = result()
    prop_b: int

    def __post_init__(self):
        self.prob_a = str(self.prop_b)

@dataclass
class C(A):
    prop_a: str = field(init=False, repr=False, hash=False, compare=False)
    prop_b: int

    def __post_init__(self):
        self.prob_a = str(self.prop_b)

B(2)

This is expected behavior. The field type must be created within the dataclass so its argument types can be statically analyzed. Mypy (another Python type checker) has the same limitation here and emits the same errors.

Since it's still valid Python code, what would be the best way, to ignore the error?
type: ignore in the following lines?
I have a lot of properties of this type, so I'd prefer to not write  field(init=False, repr=False, hash=False, compare=False) for every property

If you want to use static type checking, you will need to replicate field(init=False, repr=False, hash=False, compare=False) for each property. If you don't care about static type checking, you can disable it by setting  typeCheckingMode to off.


Simplify metadata handling and make it more performant

Use MetadataCommand instead of rewriting it
Use no_deps() to avoid downloading packages from the internet

Oh thanks ! I don't know much about "cargo-metadata" so I would never have caught it !

It's ok, I only recently found this myself :laughing: https://github.com/deadlinks/cargo-deadlinks/pull/98


misc things

@Shnupbups mind fix the tiny problems real quick? Then this is good to go.

@modmuss50 Feel free to check out this one, given you are a bit more available than player :smiley:


Change source to . when calling startup scripts in shell runner

Update the startup script shell runner invocation from source, which is specific to bash, to . which is compatible with more shells.
A set of new test_configs have been added that test startup scripts against different OS images. This change has been deployed and tested against these new test_configs.

[x] Is unit test coverage still above 80%?
[x] Have you updated all applicable documentation?
[x] Have you followed the guidelines in our Contributing document?

I think we also need to add documentation that is very explicit about what type of shell scripts we support. I never interpreted it to mean "POSIX" but that is the status quo.

A note as I'm running through some tests:

Using . to source within sh -c in ubuntu (and probably debian) means arguments aren't passed to the script.
Using . to source without sh -c can have some odd effects with commands like exit 1. The entire process will exit with a failure in this case. That may be what we want, but it's worth noting as I ran into it during testing.

I think we also need to add documentation that is very explicit about what type of shell scripts we support. I never interpreted it to mean "POSIX" but that is the status quo.

The recent change removed the sh -c, so the shell used will be the default shell, and not strictly a POSIX shell.

The integration test failure is one that has been exposed by this change, Omnia is not installing properly anymore ands needs to be updated to a more recent version.


[BUG] RKE2/K3S registration command not working on airgap setup

Rancher Server Setup

Rancher version: v2.8.3-rc2
Installation option (Docker install/Helm Chart): docker airgap

If Helm Chart, Kubernetes Cluster and version (RKE1, RKE2, k3s, EKS, etc):

Proxy/Cert Details:

Information about the Cluster

Kubernetes version: v1.28.6+rke2r1/v1.28.6+k3s2
Cluster Type (Local/Downstream):

If downstream, what type of cluster? (Custom/Imported or specify provider for Hosted/Infrastructure Provider): Custom

User Information

What is the role of the user logged in? (Admin/Cluster Owner/Cluster Member/Project Owner/Project Member/Custom) Admin

If custom, define the set of permissions:

Describe the bug

In Airgap setup RKE2 and K3s custom clusters registration command on nodes is failing with below error:

curl: (22) The requested URL returned error: 500

To Reproduce

Create v2.8.3-rc2 docker airgap setup.
Create nodes on AWS for RKE2 or K3s custom cluster.
SSH into bastion node and then SSH into node created for custom cluster above.
Run the registration command and observe that it fails with curl: (22) The requested URL returned error: 500

Result

Cluster registration command fails.

Expected Result

Cluster registration command should run successfully.

system-agent-install.sh Request Chronology

The system-agent-install.sh file is fetched from Rancher Server by the custom node during registration in the Airgap setup.
The request lands on the server.go file in the installer package, triggering the LinuxInstallScript function. This, in turn, calls the installScript function.
An If condition within the installScript function checks if setting.Get() is equal to setting.Default.
Here setting.Get() is CATTLE_SYSTEM_AGENT_INSTALL_SCRIPT and setting.Default is SystemAgentInstallScript
Upon the success of the above if condition, the system-agent-install.sh is searched locally at /usr/share/rancher/ui/assets/. If the condition fails, the script is searched at the URL provided by the environment variable CATTLE_SYSTEM_AGENT_INSTALL_SCRIPT

Cause of issue

The introduction of PR #43776 removes the URL for system-agent-install.sh from SystemAgentInstallScript. Reference diff
This breaks the if condition logic which looks for the system-agent-install.sh locally and is essential for registration of custom nodes in Airgap setup.

Fix

@chiukapoor
To resolve this issue in the short term, let's do this:

Re-add the system-agent install script asset URL to the default value in pkg/settings/settings.go, you are already doing that in the PR here: https://github.com/rancher/rancher/pull/44688/files
Enhance that PR 44688 with granular in the codebase in pkg/settings/settings.go with a comment to indicate why we are duplicating the value of the install script asset
Add a comment in the Dockerfile where we define the environment variable CATTLE_SYSTEM_AGENT_INSTALL_SCRIPT that indicates that the value should match the value in pkg/settings/settings.go to reference the local version that we download during build/package time
Backport/forward port the PR once approved/merged across our actively maintained release lines (2.7, 2.9)

@chiukapoor
To resolve this issue in the short term, let's do this:

Re-add the system-agent install script asset URL to the default value in pkg/settings/settings.go, you are already doing that in the PR here: https://github.com/rancher/rancher/pull/44688/files
Enhance that PR 44688 with granular in the codebase in pkg/settings/settings.go with a comment to indicate why we are duplicating the value of the install script asset
Add a comment in the Dockerfile where we define the environment variable CATTLE_SYSTEM_AGENT_INSTALL_SCRIPT that indicates that the value should match the value in pkg/settings/settings.go to reference the local version that we download during build/package time
Backport/forward port the PR once approved/merged across our actively maintained release lines (2.7, 2.9)

Will PR https://github.com/rancher/rancher/pull/44688 suffice as a fix, considering we do not need to duplicate the value of the install script asset across the codebase?

Thank you, @Oats87 .
@chiukapoor @rishabhmsra , FYI created https://github.com/rancher/rancher/issues/44713 / https://github.com/rancher/rancher/issues/44714 for back/forwardporting so please link back/forwardport PRs to those issues.

@chiukapoor
To resolve this issue in the short term, let's do this:

Re-add the system-agent install script asset URL to the default value in pkg/settings/settings.go, you are already doing that in the PR here: https://github.com/rancher/rancher/pull/44688/files
Enhance that PR 44688 with granular in the codebase in pkg/settings/settings.go with a comment to indicate why we are duplicating the value of the install script asset
Add a comment in the Dockerfile where we define the environment variable CATTLE_SYSTEM_AGENT_INSTALL_SCRIPT that indicates that the value should match the value in pkg/settings/settings.go to reference the local version that we download during build/package time
Backport/forward port the PR once approved/merged across our actively maintained release lines (2.7, 2.9)

Will PR #44687 suffice as a fix, considering we do not need to duplicate the value of the install script asset across the codebase?

I don't believe it's a satisfactory permanent fix. I would prefer we do minimal changes (i.e. revert what was changed) and then revisit the topic when we have time to thoroughly test it.

The workaround for this issue before the code fix is available is to set CATTLE_SYSTEM_AGENT_INSTALL_SCRIPT env var to empty.

v2.8 PR
v2.7 backport PR
v2.9 forward port PR

Reopening this issue as we will need to ensure proper QA validations have been handled.

Reopening for QA validations again, somehow it got closed again.

The workaround for this issue before the code fix is available is to set CATTLE_SYSTEM_AGENT_INSTALL_SCRIPT env var to empty.

Please note that the workaround listed in the issue only applies for new nodes. The issue is that the delivered system-agent-install script to the nodes (in both custom and provisioned cases) is rendered incorrectly before the workaround is applied. Once the workaround is applied, any new retrieval of the installation script will have be rendered correctly; however, notably, in the case of a provisioned cluster (where machines are created by Rancher), the data will be outdated.


check data size before encoding

copy_from_slice (used in write_image_data) panics if the line length is not as expected.
This patch checks if the data_size is as expected.

Thanks! Merging.


snpguest: 0.6.0 -> 0.7.0; snphost: 0.4.0 -> 0.5.0

Description of changes
https://github.com/virtee/snpguest/releases/tag/v0.7.0
https://github.com/virtee/snphost/releases/tag/v0.5.0
Things done

Built on platform(s)

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

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

Result of nixpkgs-review pr 341008 run on x86_64-linux 1

2 packages built:

snpguest
snphost


Icon: Add support for new semantic colors

Summary
What changed?
Add new semantic color options to Icon in preparation for deprecating the old options.
Why?
We want to limit icons in Pinterest to semantic, purposeful options that allow for dark mode support.
New colors:

Links

Jira

Checklist

[x] Added unit and Flow Tests
[x] Added documentation + accessibility tests
[x] Verified accessibility: keyboard & screen reader interaction
[x] Checked dark mode, responsiveness, and right-to-left support
[x] Checked stakeholder feedback (e.g. Gestalt designers)

I see an issue with color dark

@AlbertCarreras yeah the combination cmp needs some updates, but it will be easier to do when we remove the old colors, so I'm waiting a bit to refactor that component


Issues downloading postgresql

Hi
I keep getting the following error:
Downloading postgress JDBC driver...
--2016-07-19 12:17:57--  https://jdbc.postgresql.org/download/postgresql-9.3-1103.jdbc41.jar
Resolving jdbc.postgresql.org (jdbc.postgresql.org)... <IP_ADDRESS>, 2001:4800:1501:1::228
Connecting to jdbc.postgresql.org (jdbc.postgresql.org)|<IP_ADDRESS>|:443... connected.
ERROR: The certificate of ‘jdbc.postgresql.org’ is not trusted.
ERROR: The certificate of ‘jdbc.postgresql.org’ hasn't got a known issuer.
running docker run  sjoerdmulder/teamcity
Not sure but maybe it is somehow proxy related. Without configuring proxy for docker i was not able even to pull any image. Now i can, but with this particular one  facing the issue descibed above.
UPDATE:
When run wget  https://jdbc.postgresql.org/download/postgresql-9.3-1103.jdbc41.jar
inside my docker machine it runs just fine.
Thanks

Not sure what causes that issue, looks like it has some outdated dependencies

Please check your network connection, could it be that you are behind some proxy?
Try to check SSL certificates by running command openssl s_client -showcerts -connect jdbc.postgresql.org:443

Try pulling a new version using docker pull
If building yourself make sure you use the --pull option with docker build

Closing this issue now since its not related with Teamcity docker image but outdated enviroment


Fix test loading

This PR fixes a couple of bugs related to tests loading in the api:

when there are multiple test corpora with the same prefix but the difference between them is not the date (i.e. we cannot pick one by sorting by date), e.g. covid19_curated_tests, covid19_curated_tests_c19dm.
when the stats are generated with refreshed hash but the test objects are stored with old hash and there's no match to load evidence (need to force hash refresh).

Great! Unrelated to this PR, looks like the Gromet package structure changed so there is a test failing.

Great! Unrelated to this PR, looks like the Gromet package structure changed so there is a test failing.


Trading Bot - first attempt (2-8-23)

The beginning of my first trading bot in the Python programming language with the assistance of AI
In light of the entrance of ChatGPT and soon to be others, my goal of creating an incredibly successful, automated trading bot will be marked by three milestones:

The creation of a simple, Python-based trading bot that can turn a profit in both paper and live trading.
The integration of additional Python-based strategies, signals, trade secrets, etc. for greater profit potential.
The conversion of strategies from other programming languages (e.g., Pine Script) into viable Python code for a trading bot that is both strategic and comprehensive in scope and design for maximum profitability in live trading, specifically.

Milestone 1:
I will initially utilize this YouTube video:  https://www.youtube.com/watch?v=-1B2cxSjeGw
How to use ChatGPT to get started building my trading bot:

Go to this URL:  https://chat.openai.com/chat
We’re going to be using the following library:  backtrader.py
Backtrader.py will allow us to do backtesting, as well as live trading.
In ChatGPT, we must start with the following prompt:  Do you know what backtrader.py is?
It has an obvious response and I won’t bore you w/ that here.
For the next prompt, I asked:  Can you please create a trading strategy in Python by using backtrader.py to trade Apple stock, based on 5 years historical data?

ChatGPT generated the following code and response:
import backtrader as bt
import backtrader.indicators as btind

class SmaCross(bt.Strategy):
    params = (("fast", 50), ("slow", 200),)
    def __init__(self):
        sma_fast = btind.SimpleMovingAverage(self.data.close, period=self.params.fast)
        sma_slow = btind.SimpleMovingAverage(self.data.close, period=self.params.slow)
        self.crossover = btind.CrossOver(sma_fast, sma_slow)

    def next(self):
        if not self.position:
            if self.crossover > 0:
                self.buy()
        else:
            if self.crossover < 0:
                self.sell()

cerebro = bt.Cerebro()

data = bt.feeds.YahooFinanceData(dataname='AAPL', fromdate='2018-01-01', todate='2023-01-01')

cerebro.adddata(data)
cerebro.addstrategy(SmaCross)
cerebro.run()

In this example, the SmaCross strategy buys when the fast simple moving average crosses above the slow simple moving average and sells when the fast simple moving average crosses below the slow simple moving average. The params class attribute is used to specify the values of the fast and slow moving average periods. The next method implements the logic for making trades based on the crossover of the fast and slow moving averages. The Cerebro class is used to manage the trading strategy and data, and the YahooFinanceData class is used to import the data.

The code (and written response) generated above differs in a few ways from the video at the YouTube URL, however I will continue on w/ the basic strategy given, and will adjust, accordingly.

Next prompt:  YahooFinanceData is not available anymore, do you have other options for historical data sources for Apple stock?
We were offered Quandl, as one of the sources, but a code was generated for another source.  I asked ChatGPT to change the data source to Quadl.  It generated the following code:
import backtrader as bt
import backtrader.indicators as btind

class SmaCross(bt.Strategy):
    params = (("fast", 50), ("slow", 200),)
    def __init__(self):
        sma_fast = btind.SimpleMovingAverage(self.data.close, period=self.params.fast)
        sma_slow = btind.SimpleMovingAverage(self.data.close, period=self.params.slow)
        self.crossover = btind.CrossOver(sma_fast, sma_slow)

    def next(self):
        if not self.position:
            if self.crossover > 0:
                self.buy()
        else:
            if self.crossover < 0:
                self.sell()

cerebro = bt.Cerebro()

data = bt.feeds.Quandl(dataname='EOD/AAPL',
                       fromdate='2018-01-01',
                       todate='2023-01-01',
                       api_key='<YOUR_API_KEY>',
                       compression=1)

cerebro.adddata(data)
cerebro.addstrategy(SmaCross)
cerebro.run()

Note: You'll need to replace <YOUR_API_KEY> with your own API key obtained from Quandl.

At this point, we must open account w/ Quandl, which was recently acquired by NASDAQ.
5:29 Mark in the Video:  Signup for an account at:  https://data.nasdaq.com/
I will be provided w/ my API key immediately upon account creation.
6:50 Mark in the Video:  Get Visual Studio Code and let’s run the code there.
7:33 Mark in the Video:  Copy/paste my API key into Visual Studio Code, as directed.
Be advised, the video says to add the Python extension to our version of Visual Studio Code.  The latest version of Visual Studio Code, instead, will prompt us to be installed the moment we add the main.py file to our folder.
With the Python extension successfully installed into VS Code, a play-button appear towards the top-right corner of the VS Code platform.  It makes it more convenient for us to test code.
8:26 Mark:  Press the PLAY button.

8:35 Mark:  We need to install backtrader module, but before we do…
8:40 Mark:  We must create the virtual environment.
In VS Code at the prompt, type “python3 –m venv chatgpt_env”.
Note:  We can use any name for the environment.  Now we have our environment.
And this last command is where I ran into a problem.
See directly below:

first error is the module error, you'll something like:
create a requirements.txt file in the root directory of the project.
# requirements.txt
backtrader

run pip install -r requirements.txt


MNT: rerender

Hi! This is the friendly automated conda-forge-webservice.
I've rerendered the recipe as instructed in #7.
Here's a checklist to do before merging.

[x] Bump the build number if needed.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

xref: https://github.com/conda-forge/conda-forge.github.io/issues/1237
@isuruf how do I disable appveyor? The provider is set to azure for win...

xref: https://github.com/conda-forge/conda-forge.github.io/issues/1237
@isuruf how do I disable appveyor? The provider is set to azure for win...

I disabled appveyor. It looks like we don't need to rerender as this was fixed in an earlier PR.

I disabled appveyor. It looks like we don't need to rerender as this was fixed in an earlier PR.


Hold for Release Downgrade Warning

Updating for downgrade warning, when ready.
Description of the change:
Reason for the change:
Link to original source:

Closes #

Hello @sendgrid-ryan,Thanks again for the PR! We appreciate your contribution and look forward to                                              continued collaboration. Thanks!                                             Team SendGrid DX


Ability to add target for Service secrets

Please add the ability to add target parameter to secrets:
docker service update
--secret-add source=mysql_password,target=old_mysql_password
--secret-add source=mysql_password_v2,target=mysql_password
mysql

This should be extended to all options :
docker service create --name redis \
    --secret source=ssh-key,target=ssh \
    --secret source=app-key,target=app,uid=1000,gid=1001,mode=0400 \
    redis:3.0.6

I think we should only focus on target here to avoid cluttering the UI? @ncresswell thoughts?

Agree
Rgds,
Neil Cresswell
On 10/10/2017, at 6:18 PM, Anthony Lapenna <notifications<EMAIL_ADDRESS>wrote:
I think we should only focus on target here to avoid cluttering the UI? @ncresswellhttps://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_ncresswell&d=DwMCaQ&c=euGZstcaTDllvimEN8b7jXrwqOf-v5A_CdpgnVfiiMM&r=0fx0h4vB56iTLpw2McH1ZD6TqG_QGpbggVOB-PfMJpM&m=rM1PIft2dahu5c3p1TfWS2WcLHML0_Wk8QRkcltfhqc&s=AOmU4C6_m3d4DPHOi72jqzT4GM8exEVjPqRcbXoxGqk&e= thoughts?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHubhttps://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_portainer_portainer_issues_1254-23issuecomment-2D335363474&d=DwMCaQ&c=euGZstcaTDllvimEN8b7jXrwqOf-v5A_CdpgnVfiiMM&r=0fx0h4vB56iTLpw2McH1ZD6TqG_QGpbggVOB-PfMJpM&m=rM1PIft2dahu5c3p1TfWS2WcLHML0_Wk8QRkcltfhqc&s=qyTvjk77KZfZh3kPtAAEmH3lxaaJbTMeWv2E7TAcjZQ&e=, or mute the threadhttps://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_notifications_unsubscribe-2Dauth_AWGrlZWphRMAYELMbtvpZrKJP7pCwV0Sks5sqv4ggaJpZM4Poznv&d=DwMCaQ&c=euGZstcaTDllvimEN8b7jXrwqOf-v5A_CdpgnVfiiMM&r=0fx0h4vB56iTLpw2McH1ZD6TqG_QGpbggVOB-PfMJpM&m=rM1PIft2dahu5c3p1TfWS2WcLHML0_Wk8QRkcltfhqc&s=DLCP5wQzDVsgi64nqAdmx8BsvyrvKsj1d6-fkLtMjtM&e=.

Also, When docker config functionality is implemented, can target be added to them as well?

@jjesudassbah this will be part of another issue :-)


[Hold for merge] Upgrade to DS-2.0.2

Description and Motivation
Upgrade Remote Monitoring to use the latest version of Device Simulation.
The PR for local deployments can be found here:
https://github.com/Azure/remote-monitoring-services-dotnet/pull/209
Hold merge for the Simulation template to be added.
https://github.com/Azure/device-simulation-dotnet/pull/330
Change type

[ ] Bug fix
[ ] New feature
[x] Enhancement
[ ] Breaking change (breaks backward compatibility)

Checklist:

[x] All tests passed
[x] The code follows the code style and conventions of this project
[x] The change requires a change to the documentation
[x] I have updated the documentation accordingly

This change is

Someone should fix the "IOHUB" typo rather than carrying it over


17.10 is causing MissingMethodException exceptions on upgrade

A number of customers reported the following error when moving to 17.10.
Unhandled Exception: System.MissingMethodException: Method not found: ‘System.Collections.Generic.IEnumerator1<Microsoft.CodeAnalysis.NodeStateEntry1<System.ValueTuple2<System.__Canon,System.__Canon>>> Microsoft.CodeAnalysis.NodeStateTable1.GetEnumerator()’.	... C:\Program Files\Microsoft Visual Studio\2022\Enterprise\MSBuild\Current\Bin\Roslyn\Microsoft.CSharp.Core.targets	85

This is caused by using the 7.0.4xx NET SDK in VS 17.10. Those SDKs are not technically supported in this release but the feedback on this bug is strong enough that we're going to try and move forward with a patch to this problem.
In the meantime customers who hit this can work around it in a few different ways. The preferred work around is moving to a newer .NET SDK which is supported like 8.0.2xx or 8.0.3xx. If that is not possible then customers can do the following for individual projects hitting this issue:
dotnet add package Microsoft.Net.Compilers.Toolset --version 4.9.2

For larger solutions it’s likely easier to set that in a Directory.Build.props file so that impacts all projects:
<Project>
  <ItemGroup>
    <PackageReference Include="Microsoft.Net.Compilers.Toolset" Version="4.9.2">
      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
      <PrivateAssets>all</PrivateAssets>
    </PackageReference>
  </ItemGroup>
</Project>

Note This is a temporary solution. Please uninstall this package after the fix is in 17.10 otherwise you will end up hitting issues with future Visual Studio updates.

@danroth27 reading that page I would not have been able to figure out that 8.0.1xx was not supported in 17.10.
I know 7.xx is not supported any more but it would have been nice seeing a warning telling what SDK's were no longer supported in 17.10
Thanks for your time.

So, I updated our global.json file to use version "8.0.300" of the SDK and that resolved the initial issue.  However, we are now getting a ton of these errors during compilation (mostly in our test projects):
error CA1861: Prefer 'static readonly' fields over constant array arguments if the called method is called repeatedly and is not mutating the passed array
There are a handful of other errors, too. Yet, we have an .editorconfig file at a higher level with the following statement:
## Avoid constant arrays as arguments
dotnet_diagnostic.CA1861.severity = warning

It is like the build process is now ignoring our .editorconfig file and treating the diagnostic as an error instead of a warning. This might be a separate issue, which I'm still investigating, but it only started happening once we moved to a newer .NET SDK as recommended in this thread.

@paul-schroeder-msft believe that you're running into this issue with editorconfig priorities
https://github.com/dotnet/roslyn/issues/72889

So, to solve this in the near term, what I did in order to get things compiling via Visual Studio, my local command line, and our build pipeline is:

Change the SDK version in our global.json file to 8.0.300

Add this to the .csproj files for affected projects (because of the new compilation errors mentioned in a prior comment above):

	<PropertyGroup>
		<AnalysisLevelStyle>9.0</AnalysisLevelStyle>
		<NoWarn>CA1861,SA1101,SA1200,SA1629,SA1633</NoWarn>
	</PropertyGroup>

Thanks @jaredpar for the assistance!

Closing as 17.10.2 is now released

#10411

C# interactive window stop working on 17.10.2, it does not open at all, even after clean installation for windows & visual studio community


(PUP-871) deprecate key face

The key face is (self-described) not intended to be used - per PUP-871 it
should be removed.
From key.rb:
"it should not be necessary to use this subcommand directly"
Signed-off-by: Moses Mendoza<EMAIL_ADDRESS>

This passed a local ad-hoc acceptance run against ubuntu 16.04:
https://gist.github.com/MosesMendoza/bae542255371f8b092b3f01e2ac05b70

CLA signed by all contributors.

Confirmed that the faces listed match up with the discussion in the attached tickets and spec tests validate the behaviour. As this is a deprecation message only, this is a low risk change. LGTM.


RabbitMQ regex - No matching metrics found

Report
regex with rabbitmq scaler is unable to get metrics - error is: No matching metrics found (screenshots are provided).
the httpConnectionString environment variable in deployment takes its value from a secret and its of this format:
http://username:password@:/host
Strangly it also complains in keda-metrics pod logs about being unable to resolve secret "for env AUTHZ_CLIENT_ID". AUTHZ_CLIENT_ID environment variable that is not mentioned and not related to rabbit / scaling so I'm confused why its in the logs.

maybe I misconfigured something?
I was following this documentation:
https://keda.sh/docs/2.5/scalers/rabbitmq-queue/
Expected Behavior
get queues and scale on sum of messages
Actual Behavior
error getting metrics to scale
Steps to Reproduce the Problem

install keda 2.5.0
apply rabbitmq scaler with regex

Logs from KEDA operator
E1222 14:15:51.999441       1 provider.go:124] keda_metrics_adapter/provider "msg"="error getting metric for scaler" "error"="error resolving secrets for ScaleTarget: error resolving secret name &SecretKeySelector{LocalObjectReference:LocalObjectReference{Name:piper-auth0,},Key:clientId,Optional:nil,} for env AUTHZ_CLIENT_ID in namespace default"  "scaledObject.Name"="niffler" "scaledObject.Namespace"="default" "scaler"={}
E1222 14:15:51.999498       1 status.go:71] apiserver received an error that is not an metav1.Status: &errors.errorString{s:"No matching metrics found for s0-rabbitmq--5eniffler-28-3f-21--2a-5b--5derrors-24-29--2a-24"}: No matching metrics found for s0-rabbitmq--5eniffler-28-3f-21--2a-5b--5derrors-24-29--2a-24

KEDA Version
2.5.0
Kubernetes Version
1.20
Platform
Google Cloud
Scaler Details
rabbitmq
Anything else?
No response

hi @alegmal
Are the ScaledObject and the deployment in the same namespace?

it's weird because I think that we don't use any variable AUTHZ_CLIENT_ID in the code :/
is it variable in your workload?

@JorTurFer

just double checked and its in the same namespace.
yes - this is env of the workload it should scale (niffler). As I wrote, I have no clue why its in the logs as the hostFromEnv is set to "MQ_CONNECTION_STRING" env

Hi @alegmal
It's weird, I have at least 20-25 SO scaling in base of RabbitMQ with regex :(
Could you try using TriggerAuthentication instead of getting the value from the pod?
Please, to ensure that this problem is not affecting you, be sure that you update the ScaledObject instead of deleting and creating it again, or if you cannot do that, modify the name of the SO (one character is enough)

@JorTurFer thanks for quick responses
I checked and generation of SO seems to be updated with new changes.
I created a new SO with different name and same regex configuration and I got the same erors.
I'll try triggerauthentication and update.

@JorTurFer unfortunately triggerauthentication did not help solve the issue
E1222 14:15:51.999441       1 provider.go:124] keda_metrics_adapter/provider "msg"="error getting metric for scaler" "error"="error resolving secrets for ScaleTarget: error resolving secret name &SecretKeySelector{LocalObjectReference:LocalObjectReference{Name:piper-auth0,},Key:clientId,Optional:nil,} for env AUTHZ_CLIENT_ID in namespace default"  "scaledObject.Name"="niffler" "scaledObject.Namespace"="default" "scaler"={}

This is the is what puzzles me in this error: LocalObjectReference{Name:piper-auth0,},Key:clientId
We have a secret piper-auth0 with key clientId but nowhere its reffered to in scaledobject as seen in a screenshot.
This also happens when using triggerAuthentication.
Maybe I need to clear some cache or something?

Hi @alegmal
I guess that you already tried updating the SO instead of deleting and creating it, but you could try also a simple restart of KEDA's pods, that will refresh the cache. (I know that it's not the best solution, but I propose it only for troubleshooting stuff)

@JorTurFer so funny story happened... apparently "kubectl describe scaledobjects.keda.sh " is important in process of debugging... who knew facepalm
when using describe here is the problem:
error inspecting rabbitMQ: regex matches more queues than can be recovered at once
I would expect keda-metrics to output error that is as clear and relevant as the one when describing scaledobject
How much can be recovered and can I configure it?

oh 🤦
If the error is that, it should be shown also in the metrics server logs. The default value is 100 ,and you could modify it using the tigger value pageSize

pageSize - This parameter allows setting page size. (Default: 100, Optional, Only applies when useRegex is true)

but be careful because the rabbitmq cluster usually has its own limit ( usually 500).

thanks, issue is solved, closing.


Create formal deprecation process

As suggested by @RomanDzhabarov, we should have a clearer way to track deprecated features (e.g. #994, #979). We agreed to add a DEPERECATED.md to track deprecations in the Envoy source root.
In addition, maybe we can consider flag protection of deprecated features so we can turn them off easily on the CLI and validate behavior. This would be easy with gflags, not sure about using tclap.

Another idea: have a log().warning requirement to appear once only the first time a deprecated feature is used.

Also, require commit messages to mention deprecation.

#988 DEPRECATED  http_codec_options config.

covered by https://github.com/lyft/envoy/pull/1019 and https://github.com/lyft/envoy/pull/1026

There is one open question on whether we should have soft deprecation in place.
"I'm still wondering about flag protection for deprecated features. Not to restart the tclap vs. gflags discussion, but with gflags it's fairly cheap to add CLI startup flags to enable/disable deprecated features, it might allow us to perform a softer deprecation. WDYT?"
"Having soft deprecation would mean for us to keep all of the if/else (sometimes messy) code around forever.
But obviously, it eases migration to a newer version. Let's bring this up once mattklein123 back if he has strong opinion on those options."

I'm not advocating we keep flags around forever. Instead, we can flag protect the deprecated feature in master up to the next release X, turn the flag off at release X, and then remove the flag and deprecated code at X+1.

IMO it's not worth the effort to have CLI options to control the deprecation. It will just lead to more tests needing to be written and more code complexity during the deprecation interval. IMO it's simpler to just have tests for both paths, then just nuke the old code and tests when we snap the next release as one of the first work items. I think we should start with the simple approach, and then if it becomes clear that CLI options are necessary for some reason we can do that? I will try to codify all of this in the contributing guide this week.

Sounds reasonable. However, I think that we still may see surprises at the point a release gets cut when features that were relied upon disappear, I don't expect everyone to pay close attention to DEPRECATED.md. But, let's see how this goes, the simplest thing is not to add it yet.


Tweaks required to compare dragnet to skimit's model

This is one of several bits of code that we need in order to compare Dragnet to our content model. List of changes:

change makefile so dragnet's C extensions build on OSX (a recent version of gcc is required, eg. 7, but OSX has 4 by default). Install a new one with home-brew, then tell make to use it.
add a little script that wraps our content model (run locally as an API) in the interface required by dragnet's evaluation
make sure dragnet's eval does not include the training set

Two more PRs coming soon, one to prepare our data so dragnet can be trained on it, and one to train our model on the same data our model was trained on.

Apologies, I submitted this PR to the wrong upstream :) I am comparing dragnet to a tool we have in house. I'll let you know how it goes.


Write higher quality fuzzer

We should test all transcoding routines for adversarial cases to check that we do not need generate buffer overflows. We already have some fuzzing as part of the tests, but we should extend the fuzzing.

cc @NicolasJiaxin

@NicolasJiaxin If you are interested, you could help find bugs... A fuzzer that catches buffer overflows would be fantastic. :-)

I will look into that!

Note that we would not normally run it as part of our tests. It would be something that we let run for a long time with sanitizers on…

I'm sure my code has at least a few bugs the fuzzer will find!  Looking forwards to it.


Month view in DatePicker does not change on date change.

If the date that is bound is changed from another source, the month (and maybe year) does not change according to the change that happened to the date.
Month stays the same.

Should be fixed in v2.5.5, thanks for the report!

Should be fixed in v2.5.5, thanks for the report!

Did you mean v2.2.5 by any chance? If so, do you have any ETA on when it will be released?
Appreciate the work <3

Yes, v2.2.5. It's already out, just forgot to create the GitHub release

This is still happening to me in v2.10.0, I'm using a writable date and changing it in another place, the date picker stays on the same view and doesn't update to show the new date.

@FearsomeFlyingJacob Please provide a REPL

Here is the REPL: https://svelte.dev/repl/b7f78a985fe44f0cbb136eea6d86383a?version=4.2.8
The two date pickers start with 2021-01-01 and today as selected dates.
Clicking the "last xyz" buttons correctly update the selection in the stores and in the date pickers, but the date pickers don't change view to show the currently selected date.

Fixed in v2.10.1


No error code is returned when the contract does not exist

No error code is returned when the contract does not exist

commit 42991db1e1e14fd5b2fc897202f95163691b5f0d
commit 848018c525fc9db689da24fd6b881eb0667e34cd
commit 1bd1ccc6b05feb610bce04d9c103f4c1d8463640
problem fixed


Remove noDataFound template on autorun hook

Closes https://github.com/Digipalvelutehdas/APIKA/issues/55

@jykae Could you please review it?


PR Test

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.:x: justinroy89 sign nowYou have signed the CLA already but the status is still pending? Let us recheck it.


Rendering issues in Alacritty terminal

I'm observing rendering issues in Alacritty. In the recording I am running the example program with CharSets[11] (the default of 9 works okay). I do not have this issue in iTerm2 on the same computer.
https://user-images.githubusercontent.com/15056719/162021378-e56f6366-08da-4e47-8acb-0c22fdae26b5.mov

OS: MacOS Big Sur 11.6.5
Terminal: Alacritty
Font: FiraCode Nerd Font Mono (also tried Monaco and Menlo, but it seems to be the terminal)

I just remembered I'm not using standard Alacritty, but a fork that adds support for ligatures. This issue is not present in standard Alacritty, so I blame that. Closing the issue for now.


What is the best convention for sharing a cache between cores in Monoio?

For example, say you want to cache an expensive IO operation. How would one want to do that in Monoio?

You can use something like RwLock or Mutex. Runtime does not provide data structures for that.


About maxPayload

Hi nats team,
i am getting started on cnats by using the example named pubstr.c . However i got a mistake while using natsConnection_PublishString(conn,"foo","hello") and i find that the natsStatus is NATS_MAX_PAYLOAD. When i debug i find that the maxPayload is zero,but i am pretty sure that the maxPayload on my nats server is not zero.Thus i decide to find where the zero came from, but i failed.So i would like to know why my maxPayload on nats client is zero and the value of maxPayload come from where. Could you please give me some advise?
By the way, i am using cnats client on AndroidStudio3.0 for a Android App.

Which version of server and C NATS are you using? Note that there were some LOCALE issues fixed in 1.7.4, so if you are not using the latest (1.7.6, or master), I would recommend you to try with that first. If the problem still persists, you could run the test suite (at least the JSON test):
From your build directory:
ctest -R JSON -V

and send the output for review.
I am assuming an issue with parsing of the INFO protocol received from server. I don't use a library and do manual parsing. You could add this printf directive here like this:
    _clearServerInfo(&(nc->info));
    printf("INFO: %.*s\n", len, info);

    s = nats_JSONParse(&json, info, len);

Hi ,i find something new.
i try to connect nats server by using C++ socket, and my server log that
2018/07/31 11:30:48.423506 [ERR] <IP_ADDRESS>:56934 - cid:45 - Error reading from client: Client Parser ERROR, state=0, i=0: proto='"Hlo from C+"...'
When i use cnats client to connect my server ,nothing happend. But i can capture some TCP request by using wireshark. It seems that TCP request from my AVD can find the host but cant find my server. In addition the natsStatus remains NATS_MAX_PAYLOAD.

When you connect to a NATS Server, there is a protocol, you can't simply send data otherwise the server will as shown above close the connection with a parser error.
Using the library, the TCP connect is followed by NATS protocol, which is to parse the incoming INFO from the server and then send a CONNECT protocol: https://www.nats.io/documentation/internals/nats-protocol/
Start the server with the -DV flag and try to connect your cnats client. See if server is reporting anything.
Could it be that you have firewall that prevents data from flowing from server to client?
Not sure why the connection reports NATS_MAX_PAYLOAD.

:),i make a progress.
There may be something wrong when call _jsonGetNum.
I think it begin with this warning when i built it:
warning: implicit declaration of function 'strtold_l' is invalid in C99 [-Wimplicit-function-declaration]
lval = nats_strtold(*ptr, &tail);
So the nats_strtold return zero.Thus numbers get from json all become zero, such as port and max_payload.
Should i use C89? or There may be other solutions.
Looking forward to your reply.

In addition , nats_strtold is in<n-unix.h> line 74 :)
#define nats_strtold(p, t)  strtold_l((p), (t), (natsLib_getLocale()))

Sorry for the delay. Can you look for strtold_l in android header files if you can find it? If you find the version strtod_l instead, then for test modify nats_strtold definition in unix.h to (long double) strtod_l(... and see if that works for you.

@yhslln Any update on this? Was it resolved?


Systems Admin page

[x] #27
[x] #86
[x] #87
[x] #88
[x] #89

All tasks complete. Closing this issue.


How to build DLL for WP8?

Hello,
I followed the guide on how to build dll, that is, edit the path to Unity's install location, re-reference the WinRTLegacy.dll in project, but after hitting F6, the dll for WinRT doesn't show up in build folder. Instead, there are some errors displayed in the console, which, I believed, is because it can't include some namespace but I can't seem to figure out which is.
The errors are as follow:
Error	CS1061	'Type' does not contain a definition for 'IsInterface' and no extension method 'IsInterface' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\fsSerializer.cs	288	Active
Error	CS1061	'Type' does not contain a definition for 'IsAbstract' and no extension method 'IsAbstract' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\fsSerializer.cs	288	Active
Error	CS1061	'Type' does not contain a definition for 'IsGenericType' and no extension method 'IsGenericType' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\fsSerializer.cs	291	Active
Error	CS1061	'Type' does not contain a definition for 'IsInterface' and no extension method 'IsInterface' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\fsSerializer.cs	409	Active
Error	CS1061	'Type' does not contain a definition for 'IsAbstract' and no extension method 'IsAbstract' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\fsSerializer.cs	409	Active
Error	CS1061	'IEnumerable<TypeInfo>' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'IEnumerable<TypeInfo>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	17	Active
Error	CS1061	'IEnumerable<Attribute>' does not contain a definition for 'Length' and no extension method 'Length' accepting a first argument of type 'IEnumerable<Attribute>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	112	Active
Error	CS0021	Cannot apply indexing with [] to an expression of type 'IEnumerable<Attribute>'	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	113	Active
Error	CS1061	'IEnumerable<ConstructorInfo>' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'IEnumerable<ConstructorInfo>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	222	Active
Error	CS1061	'IEnumerable<MethodInfo>' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'IEnumerable<MethodInfo>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	306	Active
Error	CS1061	'IEnumerable<PropertyInfo>' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'IEnumerable<PropertyInfo>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	314	Active
Error	CS1061	'IEnumerable<FieldInfo>' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'IEnumerable<FieldInfo>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	322	Active
Error	CS1061	'IEnumerable<MemberInfo>' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'IEnumerable<MemberInfo>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	330	Active
Error	CS1061	'IEnumerable<Type>' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'IEnumerable<Type>' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	400	Active
Error	CS1061	'Type[]' does not contain a definition for 'ToArray' and no extension method 'ToArray' accepting a first argument of type 'Type[]' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsPortableReflection.cs	404	Active
Error	CS1061	'Type' does not contain a definition for 'GetGenericArguments' and no extension method 'GetGenericArguments' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsTypeExtensions.cs	53	Active
Error	CS1061	'Type' does not contain a definition for 'GetGenericArguments' and no extension method 'GetGenericArguments' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsTypeExtensions.cs	65	Active
Error	CS1061	'Type' does not contain a definition for 'GetGenericArguments' and no extension method 'GetGenericArguments' accepting a first argument of type 'Type' could be found (are you missing a using directive or an assembly reference?)	FullSerializer - Unity - WinRT	D:\Documents\gits\fullserializer\Assets\FullSerializer\Source\Internal\fsTypeExtensions.cs	66	Active

Interestingly, these error also shown up if I choose to add source code into Unity project and build to WP8.1 in .NET framework.
Does anybody know how to solve this issue?

These errors are also present when doing non-dll builds for Windows Universal 10 with the .NET backend. It works if the I2CPP backend is used. Unfortunately for me, I have other plugins which aren't compatible with I2CPP.

These errors should be fixed with #136. Can you test against the latest code in master?


Doc(Prefect-Fivetran): Added Disclaimer section

Added disclaimer to specify discontinued coverage
Per this height ticket: https://fivetran.height.app/T-619592
And per this Slack discussion: https://fivetran.slack.com/archives/C01CE97SJPP/p1704951108107569
Fivetran no longer officially supports this repo

Would I be able to get a review from @desertaxle or @PubChimps ?

@desertaxle It is not clear to me why all the checks are failing for this documentation update. Could you offer insight there?
Also, I would not be able to merge this PR. If/when it passes tests, could you merge it?
Thank you.


feat: azure support

Added handling of Azure Container Registry

Replaced by https://github.com/humanitec-architecture/backstage/pull/15


Is heavy usage possible?

Hi all, I'm making a Chrome extension that saves all text content that a user looks at. Next I want to use voy to create embeddings and write an algorithm to make context for gpt. Can you tell me what difficulties I might encounter? Perhaps too much data, or will the speed be slow? Also, is it works fine in web/service workers?

Hey @maxbaluev thanks for reaching out! It's possible. Voy works with workers. Data storage will depend on the limitation of the storage you choose, for example local storage, and the transformer model you choose.
Currently Voy only support embedding index. It doesn't store the embeddings but instead use the embeddings as coordinates to locate data and enable faster retrievals, like database index conceptually.
I'm currently looking for sponsors to kickoff the project to provide native Wasm transformers in Voy to tackle the performance issue in most of the JavaScript based transformers. At the mean time, libraries like transformers.js or web-ai are great options for web to handling the text feature extraction.

Is it true that indexes are only stored in memory, and the storage layer is managed by me ? Will it work with embeddings from openai?

That's correct. Voy doesn't store embeddings and you have full control over the storage solution. Voy also exposes serialize and deserialize functions so you can also store the serialized indexes in your storage layer.
Looking at OpenAI's documentation, the embeddings should work with Voy just fine. I think you're the first to experiment Voy with OpenAI. I'm very excited about what you're about to build!


[Gally]: master <- dev

Automatically created by Git-Ally

:tada: This PR is included in version 6.3.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


[Docker] Permanently store custom workflows in the simple tab

Expected Behavior
Custom workflows added to the simple tab should survive a rebuild of a docker image / spinning up a new container just like they remain available in ComfyUI tab and how models persist
Actual Behavior
Every time I rebuild a fresh container from the image, these workflows are gone from the simple tab. They remain accessible in the ComfyUI tab, so they are persisted.
Steps to Reproduce

Create a custom workflow in the ComfyUI tab
Use the exposed UI functionality to add it to the simple tab
Stop and remove the container
Spin up a new container based on the same run / docker-compose command
See how they are gone

Debug Logs
----

Other
I'm using the official docker image and created some ComfyUI workflows, which I added to the Simple tab through the functionality exposed in the ComfyUI tab.

Haven't tested but should be fixed

Not for me, even after a fresh build.


NVRTCError: NVRTC_ERROR_COMPILATION (6)

Hi,
I run into  NVRTC compilation errors when trying to run cupyimg.
I have an otherwise working cupy environment with cupy version 9.0.0b3.
Cudatoolkit version is 11.2. This has been installed from conda forge.
I verified that I can create cupy arrays and do basic operations on them.
When trying to run the example code snippet from your README.md file the
line yg = uniform_filter(xg, size=5) generates the following error:
yg = uniform_filter(xg, size=5)

---------------------------------------------------------------------------
NVRTCError                                Traceback (most recent call last)
~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/cuda/compiler.py in compile(self, options, log_stream)
    624                     nvrtc.addAddNameExpression(self.ptr, ker)
--> 625             nvrtc.compileProgram(self.ptr, options)
    626             mapping = None

cupy_backends/cuda/libs/nvrtc.pyx in cupy_backends.cuda.libs.nvrtc.compileProgram()

cupy_backends/cuda/libs/nvrtc.pyx in cupy_backends.cuda.libs.nvrtc.compileProgram()

cupy_backends/cuda/libs/nvrtc.pyx in cupy_backends.cuda.libs.nvrtc.check_status()

NVRTCError: NVRTC_ERROR_COMPILATION (6)

During handling of the above exception, another exception occurred:

CompileException                          Traceback (most recent call last)
<ipython-input-5-e3ce52cf8d9c> in <module>
----> 1 yg = uniform_filter(xg, size=5)

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupyimg/scipy/ndimage/filters.py in uniform_filter(input, size, output, mode, cval, origin, dtype_mode)
    650     if len(axes) > 0:
    651         for axis, size, origin, mode in axes:
--> 652             uniform_filter1d(
    653                 input,
    654                 int(size),

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupyimg/scipy/ndimage/filters.py in uniform_filter1d(input, size, axis, output, mode, cval, origin, dtype_mode)
    595         raise ValueError("invalid origin")
    596     weights = cupy.full((size,), 1 / size, dtype=dtype_weights)
--> 597     return correlate1d(
    598         input, weights, axis, output, mode, cval, origin, dtype_mode=dtype_mode
    599     )

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupyimg/scipy/ndimage/filters.py in correlate1d(input, weights, axis, output, mode, cval, origin, backend, dtype_mode)
    256             input.ndim, weights, origin, axis
    257         )
--> 258         return _correlate_or_convolve(
    259             input, weights, output, mode, cval, origins, dtype_mode=dtype_mode
    260         )

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupyimg/scipy/ndimage/filters.py in _correlate_or_convolve(input, weights, output, mode, cval, origin, convolution, dtype_mode)
    490     offsets = _filters_core._origins_to_offsets(origins, weights.shape)
    491     kernel = _get_correlate_kernel(mode, weights.shape, int_type, offsets, cval)
--> 492     output = _filters_core._call_kernel(
    493         kernel, input, weights, output, weights_dtype=weights_dtype
    494     )

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupyimg/scipy/ndimage/_filters_core.py in _call_kernel(kernel, input, weights, output, structure, weights_dtype, structure_dtype)
    150         output, temp = _util._get_output(output.dtype, input), output
    151     args.append(output)
--> 152     kernel(*args)
    153     if needs_temp:
    154         temp[...] = output[...]

cupy/core/_kernel.pyx in cupy.core._kernel.ElementwiseKernel.__call__()

cupy/core/_kernel.pyx in cupy.core._kernel.ElementwiseKernel._get_elementwise_kernel()

cupy/_util.pyx in cupy._util.memoize.decorator.ret()

cupy/core/_kernel.pyx in cupy.core._kernel._get_elementwise_kernel()

cupy/core/_kernel.pyx in cupy.core._kernel._get_simple_elementwise_kernel()

cupy/core/_kernel.pyx in cupy.core._kernel._get_simple_elementwise_kernel()

cupy/core/core.pyx in cupy.core.core.compile_with_cache()

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/cuda/compiler.py in compile_with_cache(source, options, arch, cache_dir, extra_source, backend, enable_cooperative_groups, name_expressions, log_stream, jitify)
    432             name_expressions, log_stream, cache_in_memory)
    433     else:
--> 434         return _compile_with_cache_cuda(
    435             source, options, arch, cache_dir, extra_source, backend,
    436             enable_cooperative_groups, name_expressions, log_stream,

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/cuda/compiler.py in _compile_with_cache_cuda(source, options, arch, cache_dir, extra_source, backend, enable_cooperative_groups, name_expressions, log_stream, cache_in_memory, jitify)
    509     if backend == 'nvrtc':
    510         cu_name = '' if cache_in_memory else name + '.cu'
--> 511         ptx, mapping = compile_using_nvrtc(
    512             source, options, arch, cu_name, name_expressions,
    513             log_stream, cache_in_memory, jitify)

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/cuda/compiler.py in compile_using_nvrtc(source, options, arch, filename, name_expressions, log_stream, cache_in_memory, jitify)
    271                 cu_file.write(source)
    272
--> 273             return _compile(source, options, cu_path,
    274                             name_expressions, log_stream, jitify)
    275     else:

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/cuda/compiler.py in _compile(source, options, cu_path, name_expressions, log_stream, jitify)
    255                              name_expressions=name_expressions)
    256         try:
--> 257             ptx, mapping = prog.compile(options, log_stream)
    258         except CompileException as e:
    259             dump = _get_bool_env_variable(

~/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/cuda/compiler.py in compile(self, options, log_stream)
    635         except nvrtc.NVRTCError:
    636             log = nvrtc.getProgramLog(self.ptr)
--> 637             raise CompileException(log, self.src, self.name, options,
    638                                    'nvrtc' if not runtime.is_hip else 'hiprtc')
    639

CompileException: /home/hilsenst/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/core/include/cupy/complex/complex.h(94): warning: __host__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/home/hilsenst/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/core/include/cupy/complex/complex.h(94): warning: __device__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/home/hilsenst/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/core/include/cupy/complex/complex.h(101): warning: __host__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/home/hilsenst/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/core/include/cupy/complex/complex.h(101): warning: __device__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/home/hilsenst/miniconda3/envs/cupy/lib/python3.8/site-packages/cupy/core/include/cupy/carray.cuh(4): catastrophic error: cannot open source file "type_traits"

1 catastrophic error detected in the compilation of "/tmp/tmppb62rtd7/1077d7e392f07f825d24a432298f6244_2.cubin.cu".
Compilation terminated.

Note that I got the same error with every filter that I tried, so it is not specific to the example in the README.
I assume that this has something todo with the compiler used for compiling Cuda kernels (which I guess is part of cudatoolkit ?).
I observed this error a couple of months back when I first got  this machine (DELL XPS 15, GTX 1650, Ubuntu 20.04). Back then I thought this had something to do with the version of cudatoolkit I was using (there was no cudatoolkit 11.2 on conda-forge at the time). I had also tried installing cupyimg inside a RAPIDS docker container back then and got the same error. (other RAPIDS stuff seemed to be working).
At the time I thought this may be due to some cudatoolkit version mismatch and I decided to wait for cudatoolkit 11.2. Now that it is available the error ist still here.
Any pointers would be appreciated.
In case it is important:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.39       Driver Version: 460.39       CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| 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  GeForce GTX 165...  Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   54C    P8     3W /  N/A |   2141MiB /  3914MiB |     22%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

@VolkerH Thanks for testing it out and for reporting.
@grlee77 This is due to the CuPy bug just introduced recently: https://github.com/cupy/cupy/issues/4875. The temporary solution is to add --std=c++11 to compiler options of RawKernel/RawModule, if it's used in cupyimg. I think this is a regression and should be fixed asap.

Thanks for that @leofang. If that is the case,  I will try reverting to an earlier version of cupy until the issue you mentioned is fixed upstream.

Ok, I just downgraded to cupy version 8.3.0 from conda-forge with python 3.7 and I also get an NVRTCError, but not the exact same one:
(also caused by the uniform_filter call in the snippet of the README.md file in this repo).
If these errors are related this would not be consistent with a recent regression in cupy, but  maybe these errors have different causes.
---------------------------------------------------------------------------
NVRTCError                                Traceback (most recent call last)
~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/cuda/compiler.py in compile(self, options, log_stream)
    553                     nvrtc.addAddNameExpression(self.ptr, ker)
--> 554             nvrtc.compileProgram(self.ptr, options)
    555             mapping = None

cupy_backends/cuda/libs/nvrtc.pyx in cupy_backends.cuda.libs.nvrtc.compileProgram()

cupy_backends/cuda/libs/nvrtc.pyx in cupy_backends.cuda.libs.nvrtc.compileProgram()

cupy_backends/cuda/libs/nvrtc.pyx in cupy_backends.cuda.libs.nvrtc.check_status()

NVRTCError: NVRTC_ERROR_COMPILATION (6)

During handling of the above exception, another exception occurred:

CompileException                          Traceback (most recent call last)
<ipython-input-1-63e2addd1a0a> in <module>
     14 # separable 5x5x5 convolution kernel on the GPU
     15 xg = cupy.asarray(x)
---> 16 yg = uniform_filter(xg, size=5)
     17 # %timeit yg = uniform_filter(xg, size=5); d.synchronize()
     18 #    -> 6.23 ms ± 24.8 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupyimg/scipy/ndimage/filters.py in uniform_filter(input, size, output, mode, cval, origin, dtype_mode)
    658                 cval,
    659                 origin,
--> 660                 dtype_mode=dtype_mode,
    661             )
    662             input = output

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupyimg/scipy/ndimage/filters.py in uniform_filter1d(input, size, axis, output, mode, cval, origin, dtype_mode)
    596     weights = cupy.full((size,), 1 / size, dtype=dtype_weights)
    597     return correlate1d(
--> 598         input, weights, axis, output, mode, cval, origin, dtype_mode=dtype_mode
    599     )
    600

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupyimg/scipy/ndimage/filters.py in correlate1d(input, weights, axis, output, mode, cval, origin, backend, dtype_mode)
    257         )
    258         return _correlate_or_convolve(
--> 259             input, weights, output, mode, cval, origins, dtype_mode=dtype_mode
    260         )
    261     else:

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupyimg/scipy/ndimage/filters.py in _correlate_or_convolve(input, weights, output, mode, cval, origin, convolution, dtype_mode)
    491     kernel = _get_correlate_kernel(mode, weights.shape, int_type, offsets, cval)
    492     output = _filters_core._call_kernel(
--> 493         kernel, input, weights, output, weights_dtype=weights_dtype
    494     )
    495     return output

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupyimg/scipy/ndimage/_filters_core.py in _call_kernel(kernel, input, weights, output, structure, weights_dtype, structure_dtype)
    150         output, temp = _util._get_output(output.dtype, input), output
    151     args.append(output)
--> 152     kernel(*args)
    153     if needs_temp:
    154         temp[...] = output[...]

cupy/core/_kernel.pyx in cupy.core._kernel.ElementwiseKernel.__call__()

cupy/core/_kernel.pyx in cupy.core._kernel.ElementwiseKernel._get_elementwise_kernel()

cupy/_util.pyx in cupy._util.memoize.decorator.ret()

cupy/core/_kernel.pyx in cupy.core._kernel._get_elementwise_kernel()

cupy/core/_kernel.pyx in cupy.core._kernel._get_simple_elementwise_kernel()

cupy/core/_kernel.pyx in cupy.core._kernel._get_simple_elementwise_kernel()

cupy/core/core.pyx in cupy.core.core.compile_with_cache()

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/cuda/compiler.py in compile_with_cache(source, options, arch, cache_dir, extra_source, backend, enable_cooperative_groups, name_expressions, log_stream)
    374             source, options, arch, cache_dir, extra_source, backend,
    375             enable_cooperative_groups, name_expressions, log_stream,
--> 376             cache_in_memory)
    377
    378

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/cuda/compiler.py in _compile_with_cache_cuda(source, options, arch, cache_dir, extra_source, backend, enable_cooperative_groups, name_expressions, log_stream, cache_in_memory)
    440         ptx, mapping = compile_using_nvrtc(
    441             source, options, arch, cu_name, name_expressions,
--> 442             log_stream, cache_in_memory)
    443         if _is_cudadevrt_needed(options):
    444             # for separate compilation

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/cuda/compiler.py in compile_using_nvrtc(source, options, arch, filename, name_expressions, log_stream, cache_in_memory)
    210
    211             return _compile(source, options, cu_path,
--> 212                             name_expressions, log_stream)
    213     else:
    214         return _compile(source, options, '', name_expressions, log_stream)

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/cuda/compiler.py in _compile(source, options, cu_path, name_expressions, log_stream)
    193                              name_expressions=name_expressions)
    194         try:
--> 195             ptx, mapping = prog.compile(options, log_stream)
    196         except CompileException as e:
    197             dump = _get_bool_env_variable(

~/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/cuda/compiler.py in compile(self, options, log_stream)
    564             log = nvrtc.getProgramLog(self.ptr)
    565             raise CompileException(log, self.src, self.name, options,
--> 566                                    'nvrtc' if not runtime.is_hip else 'hiprtc')
    567
    568

CompileException: /home/hilsenst/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/core/include/cupy/complex/complex.h(94): warning: __host__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/home/hilsenst/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/core/include/cupy/complex/complex.h(94): warning: __device__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/home/hilsenst/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/core/include/cupy/complex/complex.h(101): warning: __host__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/home/hilsenst/miniconda3/envs/cupy830/lib/python3.7/site-packages/cupy/core/include/cupy/complex/complex.h(101): warning: __device__ annotation is ignored on a function("complex") that is explicitly defaulted on its first declaration

/tmp/tmpkc7qafah/1e83c354aece002849c8a6558ec6f5b2_2.cubin.cu(9): catastrophic error: cannot open source file "math_constants.h"

1 catastrophic error detected in the compilation of "/tmp/tmpkc7qafah/1e83c354aece002849c8a6558ec6f5b2_2.cubin.cu".
Compilation terminated.

That's another bug that we've fixed in v8.4 or v8.5 😆

Thanks for linking those issues, @leofang.
@VolkerH: CuPy 9.0 will have most, if not all, things that were under the cupyimg.numpy and cupyimg.scipy namespaces here.
The things currently unique to this repository are in the cupyimg.skimage namespace, although these are also in the process of moving to a new home where they will be better tested and should hopefully be more reliable long term. I will put a link to that repository and probably archive this one once everything is public (mid-to-late April). The API will remain the same as what is here (matching scikit-image), but the top-level package name will change.

I merged #18 which should make things compatible with CuPy 9.0.0b3 again. It will likely still not work with 8.x, although that apparently already wasn't working.
We will be targeting the new repository to CuPy >= 9 only so that we don't have to duplicate a lot of the functionality that was already ported upstream.

Hi @grlee77,
I installed the latest master following #18, but unfortunately I still get the same compilation error as in the original post in this issue. Not sure whether this is expected (i.e. waiting for upstream fix as indicated by @leofang) or whether there is something wrong with the toolchain on my machine (or in my conda env).

BTW, nice to hear about a lot of the scipy and numpy functionality here moving into cupy.

I installed the latest master following #18, but unfortunately I still get the same compilation error as in the original post in this issue.

I tried running the tests again today (on CUDA 11.0) using the conda-forge 9.0.0b3 package instead of a local build and did get some compilation errors related to math_constants.h. I just merged 4f5b458 which backports the fix for this from upstream CuPy. This would require a fairly recent CuPy as I don't think older versions had a local copy of the necessary constants.
Also, the new package I mentioned should be public by the time of this GTC presentation related to it

Hooray. After cloning the repo and installing from the latest master no more error message with cupy 9.0.0b3 from conda-forge.
Thanks for fixing this.
It took me two attempts though, on first attempt I was installing like this:
pip install https://github.com/mritools/cupyimg/archive/master.zip

and either some local caching on my machine or some caching at github (zipfile generation) threw a spanner in the works.
I guess this issue can be closed now, and once the new package becomes public it will probably be obsolete anyway.
I'll leave the decision up to you.

The fix is merged upstream: https://github.com/cupy/cupy/pull/4922.

To follow up on my previous comment:
The newer version of this repository is now a RAPIDS project called cuCIM. The cucim.skimage module there is an updated version of cupyimg.skimage from this repository. In addition, new image I/O functionality mirroring the OpenSlide API is available via a cucim.clara module (initially supporting TIFF files, but more formats are planned in the future).
Currently, it should be possible to install for CUDA 11.x via conda from the rapidsai-nightly channel. For example, to create a new conda environment with it:
conda create -n cucim -c rapidsai-nightly -c conda-forge/label/cupy_rc -c conda-forge cucim
conda activate cucim

In a few days it should be ready on the main rapidsai channel as well. If you try it and encounter any problems, please let us know over at the cuCIM issues page.
One known issue at the moment is that cuCIM requires a newer version of CuPy than other RAPIDS projects. For a future RAPIDS 0.20 release, I think the whole RAPIDS ecosystem will have updated to CuPy 9.0, making things easier to install together in the same environment.

Thank you for the update, @grlee77! Glad to hear it lands in a new home! Congrats for you 🙂

@grlee77
Hello, I have also encountered the same problem. This error occurred when I was running other people's demo examples. This problem has bothered me for many days.
error：
Number of threads used:  32
Loading models parameters...
./models/trained/disparity-estimation-no-mask.tar
Model disparity loaded succesfully.
./models/trained/disparity-refinement.tar
Model refine loaded succesfully.
./models/trained/inpainting-color.tar
Model inpaint loaded succesfully.
Traceback (most recent call last):
File "/usr/local/python39/lib/python3.9/site-packages/cupy/cuda/compiler.py", line 681, in compile
nvrtc.compileProgram(self.ptr, options)
File "cupy_backends/cuda/libs/nvrtc.pyx", line 139, in cupy_backends.cuda.libs.nvrtc.compileProgram
File "cupy_backends/cuda/libs/nvrtc.pyx", line 151, in cupy_backends.cuda.libs.nvrtc.compileProgram
File "cupy_backends/cuda/libs/nvrtc.pyx", line 67, in cupy_backends.cuda.libs.nvrtc.check_status
cupy_backends.cuda.libs.nvrtc.NVRTCError: NVRTC_ERROR_COMPILATION (6)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/DATA/jupyter/share/haodawei/improved-kbe/kbe.py", line 182, in
ken_burn_pipe((tensorImage+1)/2, zoom_settings, output_path, pretrained_estim=pretrained_estim)
File "/DATA/jupyter/share/haodawei/improved-kbe/utils/pipeline.py", line 112, in call
numpyResult = process_kenburns({
File "/DATA/jupyter/share/haodawei/improved-kbe/utils/common.py", line 208, in process_kenburns
tensorRender, tensorExisting = render_pointcloud(objectCommon['tensorInpaPoints'] + tensorShift,
File "/DATA/jupyter/share/haodawei/improved-kbe/utils/common.py", line 435, in render_pointcloud
launch_kernel('kernel_pointrender_updateZee', preprocess_kernel('''
File "cupy/_util.pyx", line 67, in cupy._util.memoize.decorator.ret
File "/DATA/jupyter/share/haodawei/improved-kbe/utils/common.py", line 380, in launch_kernel
return cupy.cuda.compile_with_cache(strKernel, tuple([ '-I ' + os.environ['CUDA_HOME'], '-I ' + os.environ['CUDA_HOME'] + '/include' ])).get_function(strFunction)
File "/usr/local/python39/lib/python3.9/site-packages/cupy/cuda/compiler.py", line 460, in compile_with_cache
return _compile_module_with_cache(*args, **kwargs)
File "/usr/local/python39/lib/python3.9/site-packages/cupy/cuda/compiler.py", line 488, in _compile_module_with_cache
return _compile_with_cache_cuda(
File "/usr/local/python39/lib/python3.9/site-packages/cupy/cuda/compiler.py", line 566, in _compile_with_cache_cuda
ptx, mapping = compile_using_nvrtc(
File "/usr/local/python39/lib/python3.9/site-packages/cupy/cuda/compiler.py", line 317, in compile_using_nvrtc
return _compile(source, options, cu_path,
File "/usr/local/python39/lib/python3.9/site-packages/cupy/cuda/compiler.py", line 301, in _compile
compiled_obj, mapping = prog.compile(options, log_stream)
File "/usr/local/python39/lib/python3.9/site-packages/cupy/cuda/compiler.py", line 698, in compile
raise CompileException(log, self.src, self.name, options,
cupy.cuda.compiler.CompileException: /tmp/tmpl94lnfh3/6335edf91d36e122532b0e6f44001e82f777db6a.cubin.cu(2): catastrophic error: cannot open source file "/home/s182169/Master_thesis/GAN-Burns-effect/utils/helper_math.h"
1 catastrophic error detected in the compilation of "/tmp/tmpl94lnfh3/6335edf91d36e122532b0e6f44001e82f777db6a.cubin.cu".
Compilation terminated.
————————————————
my env:
OS                           : Linux-4.9.0-8-amd64-x86_64-with-glibc2.27
Python Version               : 3.9.2
CuPy Version                 : 10.1.0
CuPy Platform                : NVIDIA CUDA
NumPy Version                : 1.20.1
SciPy Version                : 1.6.1
Cython Build Version         : 0.29.24
Cython Runtime Version       : None
CUDA Root                    : /usr/local/cuda
nvcc PATH                    : /usr/local/cuda/bin/nvcc
CUDA Build Version           : 10020
CUDA Driver Version          : 10020
CUDA Runtime Version         : 10020
cuBLAS Version               : 10203
cuFFT Version                : 10102
cuRAND Version               : 10102
cuSOLVER Version             : (10, 3, 0)
cuSPARSE Version             : 10301
NVRTC Version                : (10, 2)
Thrust Version               : 100907
CUB Build Version            : 100800
Jitify Build Version         : 60e9e72
cuDNN Build Version          : 8300
cuDNN Version                : 8101
NCCL Build Version           : 21104
NCCL Runtime Version         : 2804
cuTENSOR Version             : None
cuSPARSELt Build Version     : None
Device 0 Name                : Tesla V100-SXM2-32GB
Device 0 Compute Capability  : 70
Device 0 PCI Bus ID          : 0000:18:00.0
Device 1 Name                : Tesla V100-SXM2-32GB
Device 1 Compute Capability  : 70
Device 1 PCI Bus ID          : 0000:3B:00.0
Device 2 Name                : Tesla V100-SXM2-32GB
Device 2 Compute Capability  : 70
Device 2 PCI Bus ID          : 0000:AF:00.0

Did you try https://github.com/rapidsai/cucim or cupyimg (which has been superseeded by cucim)?

@VolkerH
Thank you for your reply. I have not tried cucim. If I want to use cucim, do I need to modify some codes under CUPY before?

If you have existing code that is based on cupyimg and cupy you may have to change imports as the package is now called cucim and some functions have been moved to cupy itself. See the top of the README.md here in this repo.

@VolkerH
I was just looking at my code, and THERE's a reference in there：
launch_kernel('kernel_pointrender_updateZee', preprocess_kernel('''
extern "C" global void kernel_pointrender_updateZee(
const int n,
const float* input,
const float* data,
const float* zee
) { for (int intIndex = (blockIdx.x * blockDim.x) + threadIdx.x; intIndex < n; intIndex += blockDim.x * gridDim.x) {
const int intSample = ( intIndex / SIZE_2(input) ) % SIZE_0(input);
const int intPoint  = ( intIndex                 ) % SIZE_2(input);
		assert(SIZE_1(input) == 3);
		assert(SIZE_1(zee) == 1);

		float3 dblPlanePoint = make_float3(0.0, 0.0, {{dblFocal}});
		float3 dblPlaneNormal = make_float3(0.0, 0.0, 1.0);

		float3 dblLinePoint = make_float3(VALUE_3(input, intSample, 0, intPoint), VALUE_3(input, intSample, 1, intPoint), VALUE_3(input, intSample, 2, intPoint));
		float3 dblLineVector = make_float3(0.0, 0.0, 0.0) - dblLinePoint;

		if (dblLinePoint.z < 0.001) {
			return;
		}

		float dblNumerator = dot(dblPlanePoint - dblLinePoint, dblPlaneNormal);
		float dblDenominator = dot(dblLineVector, dblPlaneNormal);
		float dblDistance = dblNumerator / dblDenominator;

		if (fabs(dblDenominator) < 0.001) {
			return;
		}

		float3 dblIntersection = dblLinePoint + (dblDistance * dblLineVector); // https://en.wikipedia.org/wiki/Line%E2%80%93plane_intersection

		float dblOutputX = dblIntersection.x + (0.5 * SIZE_3(zee)) - 0.5;
		float dblOutputY = dblIntersection.y + (0.5 * SIZE_2(zee)) - 0.5;

		float dblError = 1000000.0 - (({{dblFocal}} * {{dblBaseline}}) / (dblLinePoint.z + 0.0000001));

		int intNorthwestX = (int) (floor(dblOutputX));
		int intNorthwestY = (int) (floor(dblOutputY));
		int intNortheastX = intNorthwestX + 1;
		int intNortheastY = intNorthwestY;
		int intSouthwestX = intNorthwestX;
		int intSouthwestY = intNorthwestY + 1;
		int intSoutheastX = intNorthwestX + 1;
		int intSoutheastY = intNorthwestY + 1;

		float dblNorthwest = (intSoutheastX - dblOutputX)    * (intSoutheastY - dblOutputY);
		float dblNortheast = (dblOutputX    - intSouthwestX) * (intSouthwestY - dblOutputY);
		float dblSouthwest = (intNortheastX - dblOutputX)    * (dblOutputY    - intNortheastY);
		float dblSoutheast = (dblOutputX    - intNorthwestX) * (dblOutputY    - intNorthwestY);

		if ((dblNorthwest >= dblNortheast) & (dblNorthwest >= dblSouthwest) & (dblNorthwest >= dblSoutheast)) {
			if ((intNorthwestX >= 0) & (intNorthwestX < SIZE_3(zee)) & (intNorthwestY >= 0) & (intNorthwestY < SIZE_2(zee))) {
				atomicMin(&zee[OFFSET_4(zee, intSample, 0, intNorthwestY, intNorthwestX)], dblError);
			}

		} else if ((dblNortheast >= dblNorthwest) & (dblNortheast >= dblSouthwest) & (dblNortheast >= dblSoutheast)) {
			if ((intNortheastX >= 0) & (intNortheastX < SIZE_3(zee)) & (intNortheastY >= 0) & (intNortheastY < SIZE_2(zee))) {
				atomicMin(&zee[OFFSET_4(zee, intSample, 0, intNortheastY, intNortheastX)], dblError);
			}

		} else if ((dblSouthwest >= dblNorthwest) & (dblSouthwest >= dblNortheast) & (dblSouthwest >= dblSoutheast)) {
			if ((intSouthwestX >= 0) & (intSouthwestX < SIZE_3(zee)) & (intSouthwestY >= 0) & (intSouthwestY < SIZE_2(zee))) {
				atomicMin(&zee[OFFSET_4(zee, intSample, 0, intSouthwestY, intSouthwestX)], dblError);
			}

		} else if ((dblSoutheast >= dblNorthwest) & (dblSoutheast >= dblNortheast) & (dblSoutheast >= dblSouthwest)) {
			if ((intSoutheastX >= 0) & (intSoutheastX < SIZE_3(zee)) & (intSoutheastY >= 0) & (intSoutheastY < SIZE_2(zee))) {
				atomicMin(&zee[OFFSET_4(zee, intSample, 0, intSoutheastY, intSoutheastX)], dblError);
			}

		}
	} }

run python kbe.py in https://github.com/pierlj/ken-burns-effect
found error：
!CUDA_AVAILABLE_DEVICES=0 python kbe.py --in ./images/doublestrike.jpg --out ./videos/test_1.mp4 --estim-path ./models/trained/disparity-estimation-no-mask.tar --refine-path ./models/trained/disparity-refinement.tar --inpaint-path ./models/trained/inpainting-color.tar --write-frames --startU 512 --startV 512 --endU 600 --endV 600 --startW 400 --startH 200 --endW 300 --endH 150

@VolkerH
I am not familiar with this cupy programming for the first time. Could you please give me some advice？

Sorry, I am not a cupy expert either, I just wanted to point out the fact that this version is no longer current.

cupy.cuda.compiler.CompileException: /tmp/tmpl94lnfh3/6335edf91d36e122532b0e6f44001e82f777db6a.cubin.cu(2): catastrophic error: cannot open source file "/home/s182169/Master_thesis/GAN-Burns-effect/utils/helper_math.h"

One of your project dependencies (/DATA/jupyter/share/haodawei/improved-kbe/utils/common.py) hard-coded this header path. I don't think this is a problem in either CuPy or cupyimg.

Thank you very much for your answer. I have carefully checked my C++ file path, and the path I referenced was wrong。
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On 03/11/2022 15:34，Leo @.***> wrote：
cupy.cuda.compiler.CompileException: /tmp/tmpl94lnfh3/6335edf91d36e122532b0e6f44001e82f777db6a.cubin.cu(2): catastrophic error: cannot open source file "/home/s182169/Master_thesis/GAN-Burns-effect/utils/helper_math.h"
One of your project dependencies (/DATA/jupyter/share/haodawei/improved-kbe/utils/common.py) hard-coded this header path. I don't think this is a problem in either CuPy or cupyimg.
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