Fixing wrong link to feature coverage for machines

The link was wrongly pointing to Defender for Containers features

@bmansheim
Can you review the proposed changes?
When the changes are ready for publication, add a #sign-off comment to signal that the PR is ready for the review team to merge.
#label:"aq-pr-triaged"
@MicrosoftDocs/public-repo-pr-review-team

#sign-off

The content has been updated since the pull request was created, and the article no longer exists. Thanks for your contribution. We'll close this PR.


Adding some unit tests for string

Description

Added unit tests to cover changes in https://github.com/nanoframework/nf-interpreter/pull/2826

Motivation and Context

There was no unit test coverage

How Has This Been Tested?

Unit tests ;-)

Screenshots
Types of changes

[ ] Improvement (non-breaking change that improves a feature, code or algorithm)
[ ] Bug fix (non-breaking change which fixes an issue with code or algorithm)
[ ] New feature (non-breaking change which adds functionality to code)
[ ] Breaking change (fix or feature that would cause existing functionality to change)
[ ] Config and build (change in the configuration and build system, has no impact on code or features)
[ ] Dependencies (update dependencies and changes associated, has no impact on code or features)
[X] Unit Tests (add new Unit Test(s) or improved existing one(s), has no impact on code or features)
[ ] Documentation (changes or updates in the documentation, has no impact on code or features)

Checklist:

[X] My code follows the code style of this project (only if there are changes in source code).
[ ] My changes require an update to the documentation (there are changes that require the docs website to be updated).
[ ] I have updated the documentation accordingly (the changes require an update on the docs in this repo).
[X] I have read the CONTRIBUTING document.
[X] I have tested everything locally and all new and existing tests passed (only if there are changes in source code).
[X] I have added new tests to cover my changes.

@josesimoes The issue was that none of the tests run in my environment due to the following error:
Could not find test executor with URI 'executor://nanoframeworktestexecutor/'.  Make sure that the test executor is installed and supports .net runtime version  .
I'm assuming this is related to my environment though and I ran these tests in my other repository against a custom firmware build so I'll toss this over.

There are already a bunch of tests for string, no point on scattering them. Better have these new ones along with those, OK? Sorry for the extra work...

No worries, I didn't look hard enough (or at all beyond the fact that there was no project with "String" in the name 😛). I moved them.


Make Drupal VM docs index page more helpful

Currently it's pretty bare:
http://docs.drupalvm.com/en/latest/
It should at least have a few more pointers to direct people where to go/what to do to get started with the project, to contribute, to test things, etc.

Done!


Use the AWS provider from cluster not hosted in AWS

It looks like you can do this with the Azure provider.  Can you do the same thing with the AWS Route-53 provider?

Yes, this works automatically with the AWS SDK, see #391

As this seems to be a "frequently asked question", we should add it to the docs I suppose..

Thanks for the response.  It would be great to see this info in the tutorial docs for AWS.


pad_data function not correct?

Hi tRosenflanz,
Thanks for sharing your work!
it seems to me that the pad_data function is not correct. Please correct me if I am wrong, your code is trying to pad the input sequence with padding value =0
def pad_data(data, length_visits, length_codes, pad_value=0):
but when you do the masking, your code is trying to mask the last weight, shouldn't you mask the first weight instead? Or set pad_value=len(num_codes)?
class FreezePadding(Constraint)
last_weight = K.cast(K.equal(K.reshape(w[-1, :], (1, K.shape(w)[1])), 0.), K.floatx())
Thanks!

I think this is a poor choice of default argument for a function on my part but the code is correct overall:
See lines https://github.com/Optum/retain-keras/blob/46186952c57eb09f79962ee377da85269cbfdaf9/retain_train.py#L70
And https://github.com/Optum/retain-keras/blob/46186952c57eb09f79962ee377da85269cbfdaf9/retain_train.py#L75
Where I explicitly provide different padding values

You right! Thanks for pointing that out.
I've learned a lot form your code:)


Add Starter options to allow running NodeTool

Also add a helper nodetool script.
Expose JMX port in StargateConnectionInfo for tests.

@dougwettlaufer : I've reworked this PR a bit - removed the nodetool script in favour of a custom option parser in Starter. I hope it's more user-friendly and does not require extra shell scripts.

@dougwettlaufer : I've reworked this PR a bit - removed the nodetool script in favour of a custom option parser in Starter. I hope it's more user-friendly and does not require extra shell scripts.


Unable to format unsaved json files

In VSCode if you create a new file, without saving, with JSON content and try to format the document biome is unable to:

Saving the file to disk works and it can format it.

Hey @alex-way,
It appears the document filters we use specify the file scheme, which prevents Biome from formatting untitled files, which unsaved files are.
Did a quick experiment to confirm that Biome can indeed format untitled files by removing the schema constraint, and it appears to work as expected. We'll have to confirm whether this has an impact on linting, but assuming it also works as expected, we could relax the filter to also accept untitled files.
https://github.com/biomejs/biome-vscode/blob/fbc69969577c89aaf54adeaa6fc1795538ccda96/src/main.ts#L121-L128
Would you be willing to contribute ?

Hey @alex-way,
It appears the document filters we use specify the file scheme, which prevents Biome from formatting untitled files, which unsaved files are.
Did a quick experiment to confirm that Biome can indeed format untitled files by removing the scheme constraint, and it appears to work as expected. We'll have to confirm whether this has an impact on linting, but assuming it also works as expected, we could relax the filter to also accept untitled files.
https://github.com/biomejs/biome-vscode/blob/fbc69969577c89aaf54adeaa6fc1795538ccda96/src/main.ts#L121-L128
Would you be willing to contribute ?

Hey Nicolas,
I'd love to contribute - Not sure I'll be able to meet the mark required to get the correct amendments in place but I'll try my best. Expect to see a Pull Request by the end of the day if all goes well 😄
Thanks, Alex

Just done a test by amending the documentSelector to remove the scheme attribute which allows formatting of the various file types. However, linting doesn't work without saving the file. Going to investigate further and see if other extensions follow the same pattern and if not if there's any solution I can implement

I'm not certain, but I think the problem is within the lsp crate: https://github.com/biomejs/biome/tree/main/crates/biome_lsp
My reasoning is that making the previously suggested amendment of removing the scheme attribute (Which is likely a naive solution for now) and running biome in trace mode I see that the untitled file is being sent to the lsp but is being returned with an empty result:
[Trace - 6:05:38 PM] Sending request 'textDocument/codeAction - (93)'.
Params: {
    "textDocument": {
        "uri": "untitled:Untitled-2"
    },
    "range": {
        "start": {
            "line": 2,
            "character": 29
        },
        "end": {
            "line": 2,
            "character": 29
        }
    },
    "context": {
        "diagnostics": [],
        "triggerKind": 2
    }
}

[Trace - 6:05:38 PM] Received response 'textDocument/codeAction - (93)' in 9ms.
Result: []

Conversely when sending the same contents of saved document I see the following result:
[Trace - 6:05:36 PM] Received response 'textDocument/codeAction - (90)' in 3ms.
Result: [
    {
        "edit": {
            "changes": {
                "file:///c%3A/code/svelte.config.js": [
                    {
                        "newText": "path from 'path';\nimport ",
                        "range": {
                            "end": {
                                "character": 7,
                                "line": 0
                            },
                            "start": {
                                "character": 7,
                                "line": 0
                            }
                        }
                    },
                    {
                        "newText": "",
                        "range": {
                            "end": {
                                "character": 22,
                                "line": 2
                            },
                            "start": {
                                "character": 41,
                                "line": 1
                            }
                        }
                    }
                ]
            }
        },
        "isPreferred": true,
        "kind": "source.organizeImports.biome",
        "title": "Organize Imports (Biome)"
    }
]

I'm going to make some kind've assumption that the lsp is receiving/loading the contents of the file based on the textDocument/uri parameter the LSP client is sending. As an unsaved file isn't prefixed with file:// it's likely being ignored.
Some further logs from the server:
├─┐biome_lsp::server::initialized{params=InitializedParams}
│ ├─0ms INFO biome_lsp::server Attempting to load the configuration from 'biome.json' file
│ ├─┐biome_lsp::session::load_extension_settings{}
│ ├─┐biome_lsp::session::load_workspace_settings{}
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\code\\p\\forms\\biome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\code\\p\\biome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\code\\biome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\biome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─0ms ERROR biome_fs::fs Could not read the file from "c:\\biome.json", reason:
│ │ │  The system cannot find the file specified. (os error 2)
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\code\\p\\forms\\rome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\code\\p\\rome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\code\\rome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─┐biome_fs::fs::os::OsFileSystem::open_with_options{path="c:\\rome.json", options=OpenOptions { read: true, write: false, truncate: false, create: false, create_new: false }}
│ │ ├─┘
│ │ ├─1ms ERROR biome_fs::fs Could not read the file from "c:\\rome.json", reason:
│ │ │  The system cannot find the file specified. (os error 2)
│ ├─┘
│ │ ├─12ms INFO biome_lsp::session Loaded client configuration: Object {
│ │ │     "lspBin": String("C:\\Users\\WayA\\AppData\\Local\\pnpm\\global\\5\\.pnpm\\@biomejs+cli-win32-x64@1.4.1\\node_modules\\@biomejs\\cli-win32-x64\\biome.exe"),
│ │ │     "rename": Null,
│ │ │     "requireConfiguration": Bool(false),
│ │ │ }
│ ├─┘
│ ├─29ms INFO biome_lsp::session Unregister capabilities "workspace/didChangeConfiguration, textDocument/rangeFormatting, textDocument/onTypeFormatting, textDocument/rename, textDocument/formatting, workspace/didChangeWatchedFiles"
│ ├─38ms INFO biome_lsp::session Register capabilities "workspace/didChangeConfiguration, textDocument/rangeFormatting, textDocument/onTypeFormatting, textDocument/formatting, workspace/didChangeWatchedFiles"
├─┘
├─┐biome_lsp::handlers::text_document::did_open{params=DidOpenTextDocumentParams { text_document: TextDocumentItem { uri: Url { scheme: "untitled", cannot_be_a_base: true, username: "", password: None, host: None, port: None, path: "Untitled-1", query: None, fragment: None }, language_id: "json", version: 26, text: "{\n    \"test\": \"testing\"\n}" } }}
│ ├─┐biome_lsp::session::update_diagnostics{url=untitled:Untitled-1}
│ │ ├─0ms DEBUG biome_service::workspace The file has the following feature sets:
│ │ │ {Lint: Supported, Format: Supported, OrganizeImports: Supported}
│ │ ├─┐biome_json_parser::parse{}
│ │ ├─┘
│ │ ├─┐biome_service::workspace::server::Pulling diagnostics{categories=RuleCategories(SYNTAX | LINT | ACTION)}
│ │ │ ├─┐biome_service::file_handlers::json::lint{}
│ │ │ ├─┘
│ │ ├─┘
│ ├─┘
├─┘
├─┐biome_lsp::handlers::analysis::code_actions{uri=untitled:Untitled-1, range=Range { start: Position { line: 1, character: 21 }, end: Position { line: 1, character: 21 } }, only=None, diagnostics=[]}
│ ├─0ms DEBUG biome_lsp::handlers::analysis Pull actions result: PullActionsResult { actions: [] }
│ ├─0ms DEBUG biome_lsp::handlers::analysis Suggested actions:
│ │ []
├─┘
├─┐biome_lsp::handlers::analysis::code_actions{uri=untitled:Untitled-1, range=Range { start: Position { line: 1, character: 21 }, end: Position { line: 1, character: 21 } }, only=None, diagnostics=[]}
│ ├─0ms DEBUG biome_lsp::handlers::analysis Pull actions result: PullActionsResult { actions: [] }
│ ├─0ms DEBUG biome_lsp::handlers::analysis Suggested actions:
│ │ []
├─┘
├─┐biome_lsp::handlers::analysis::code_actions{uri=untitled:Untitled-1, range=Range { start: Position { line: 2, character: 1 }, end: Position { line: 2, character: 1 } }, only=None, diagnostics=[]}
│ ├─0ms DEBUG biome_lsp::handlers::analysis Pull actions result: PullActionsResult { actions: [] }
│ ├─0ms DEBUG biome_lsp::handlers::analysis Suggested actions:
│ │ []
├─┘

I could totally be wrong here but that's my current thoughts.
One thing I will say which contradicts myself is that the formatting does work, which is indicative that the lsp is able to handle untitled files but my rust knowledge is extremely basic so I'll likely be unable to dig further into the lsp code to debug 😞


Does not work in safe mode

Self explanatory, you cannot use this is when your PS3 is in safe mode.
I would like to use it in safe mode whenever possible as to enable use of the debug HDD exchange utility with the vita
(I do not currently possess a ps3 controller)

https://github.com/user-attachments/assets/22065ade-9ad3-40b0-bcbf-f298d3028511
Works fine for me. Make sure you aren't using other usb plugins like udcd_uvc


Build failing due to sauce tunnel issue

Sauce is reporting the error as being "Your test errored. No active tunnel found for identifier<PHONE_NUMBER>974". That number looks to be milliseconds since epoch from here, but I think what we need is the Travis job number from here?

That looks correct
https://docs.travis-ci.com/user/sauce-connect/

To allow multiple tunnels to be open simultaneously, Travis CI opens a Sauce Connect Identified Tunnel. Make sure you are sending the TRAVIS_JOB_NUMBER environment variable when you are opening the connection to Sauce Labs’ selenium grid, as the desired capability tunnel-identifier, or it will not be able to connect to the server running on the VM.


Improve initial page load times

Although Atomic-Server feels pretty fast most of the time, the initial load has room for improvement. This is partially due to the amount of round trips:

Fetch the HTML, parse and render loading screen
Fetch the JS assets, parse and execute
Fetch various JSON-AD resources (including the requested page), parse and render

Include in first HTML
We could improve this by sending more data in the first HTML request:

[ ] include essential json ad (properties, classes). This could be either in the JS bundle or on the HTML.
[ ] Include the requested resource's json ad. This should probably be stored in the HTML.
[ ] Include (full) js bundle

Downsides of including things in the HTML:

the first render (of the loading screen) a bit slower. Or is HTML parsed / rendered in a streaming fashion?
the bundle isn't cached
more difficult to set up service worker (has to do with the caching above)

Include script to fetch in first HTML
In the first HTML response, include a script that fetches the JSON-AD for the requested resource + properties + classes. Parse the JSON, put it on window.atomic or something, and then when the JS is parsed, add the parsed files.

Doesn't slow down initial HTML response
Paralellizes JS + JSON-AD fetching
One less roundtrip!

Properly the JSON is important! A lot of bad advice can be found on the web on how to properly add JSON to your HTML. It's very easy to open up a chance for hackers to run some arbitrary code.


YARN-10882. Fix branch-3.1 build: zstd library is missing from the Dockerfile

zstd dependency was not installed in the docker environment and caused
a build issue in hadoop-common
NOTICE
Please create an issue in ASF JIRA before opening a pull request,
and you need to set the title of the pull request which starts with
the corresponding JIRA issue number. (e.g. HADOOP-XXXXX. Fix a typo in YYY.)
For more details, please see https://cwiki.apache.org/confluence/display/HADOOP/How+To+Contribute

(!) A patch to the testing environment has been detected.
Re-executing against the patched versions to perform further tests.
The console is at https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-3297/1/console in case of problems.

:confetti_ball: +1 overall

Vote
Subsystem
Runtime
Logfile
Comment

+0 :ok:
reexec
0m 44s

Docker mode activated.

_ Prechecks _

+1 :green_heart:
dupname
0m  0s

No case conflicting files found.

+0 :ok:
codespell
0m  0s

codespell was not available.

+0 :ok:
shelldocs
0m  0s

Shelldocs was not available.

+1 :green_heart:
@author
0m  1s

The patch does not contain any @author tags.

_ branch-3.1 Compile Tests _

+0 :ok:
mvndep
3m  5s

Maven dependency ordering for branch

+1 :green_heart:
shadedclient
15m 41s

branch has no errors when building and testing our client artifacts.

_ Patch Compile Tests _

+0 :ok:
mvndep
0m 17s

Maven dependency ordering for patch

+1 :green_heart:
blanks
0m  0s

The patch has no blanks issues.

+1 :green_heart:
hadolint
0m  2s

No new issues.

+1 :green_heart:
shellcheck
0m  0s

No new issues.

+1 :green_heart:
shadedclient
13m 23s

patch has no errors when building and testing our client artifacts.

_ Other Tests _

+1 :green_heart:
asflicense
0m 30s

The patch does not generate ASF License warnings.

35m 43s

Subsystem
Report/Notes

Docker
ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-3297/1/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/3297

Optional Tests
dupname asflicense codespell hadolint shellcheck shelldocs

uname
Linux c900e9e214a0 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
branch-3.1 / 5dab985b8575e26d340f8dda43f2302e09592b39

Max. process+thread count
411 (vs. ulimit of 5500)

modules
C:  U:

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-3297/1/console

versions
git=2.17.1 maven=3.6.0 shellcheck=0.4.6 hadolint=1.11.1-0-g0e692dd

Powered by
Apache Yetus 0.14.0-SNAPSHOT https://yetus.apache.org

This message was automatically generated.

Thanks @tomicooler for this fix. Looks good, committing to trunk.

Looks good, committing to trunk.

Actually it is committed to only branch-3.1.


Android Java: 02.14 TabLayout in Android

Description 📜
TabLayout is expalined in detail.
Fixes #6006

Type of change 📝

[ ] Au#dio (Should be in mp3 format Includes speech clarity, Concise ,Low distortion)
[ ] Vi#deo (Animations, screen-recordings, presentations and regular explanatory films are all possibilties etc)
[x] Documentation (Content Creation in the form of codes or tutorials)
[ ] Other (If you choose other, Please mention changes below)

Domain of Contribution 📊

[ ] Android Dev #(Flutter)
[x] Android Dev (Java)
[ ] Android Dev #(Kotlin)
[ ] Backend Dev #(Java)
[ ] Backend Dev #(.NET)
[ ] Backend Dev #(PHP)
[ ] Backend Dev #(Python)
[ ] C/#CPP
[ ] Competitive #Programming
[ ] Cyber #Security
[ ] DS#A
[ ] Data#base
[ ] Datascience with #Python
[ ] Datascience with #R
[ ] Frontend Dev #HTML/CSS/JS
[ ] Frontend Dev #React/Angular/Vue
[ ] Go#lang
[ ] Interview #Prep
[ ] Java_#Domain
[ ] JavaScript_#Domain
[ ] ME#RN
[ ] Machine #Learning
[ ] Open #Source
[ ] Python_#Domain
[ ] Ru#st
[ ] Statis#tics
[ ] UI/#UX

Checklist ✅

[x] I follow Contributing Guidelines & Code of conduct of this project.
[x] I have performed a self-review of my own code or work.
[x] I have commented my code, particularly in hard-to-understand areas.
[x] My changes generates no new warnings.
[x] I'm GWOC'21 contributor

@VikasPandey121
I have created the PR. Please review it.
Issue number - #6006


Extend approval options (#3348)

Backport of #3348

Time to address things?

with my last commit and https://github.com/woodpecker-ci/woodpecker/pull/4456 this is non breaking anymore :)

https://github.com/woodpecker-ci/woodpecker/pull/4429#discussion_r1857164519

For new repos this is actually not required and could stay as is.

Well I still would say this is a soft breaking change if we add it back ... and the new migration at https://github.com/woodpecker-ci/woodpecker/pull/4456 do take it into account already


HDDS-3781. Update the apiVersion to the newer one

What changes were proposed in this pull request?
For some apiVersion has been removed many years ago, so it is not forward-compatible, and i can use it in the newer version kubernetes cluster. For example, v1beta1, v1beta2, v1beta3 are removed in 2015.
What is the link to the Apache JIRA
https://jira.apache.org/jira/browse/HDDS-3781
How was this patch tested?
Run the ozone demo in kubernetes cluster successfully.

Codecov Report

Merging #1056 into master will decrease coverage by 0.00%.
The diff coverage is 100.00%.

@@             Coverage Diff              @@
##             master    #1056      +/-   ##
============================================
- Coverage     69.48%   69.48%   -0.01%
- Complexity     9110     9111       +1
============================================
  Files           961      961
  Lines         48132    48148      +16
  Branches       4672     4679       +7
============================================
+ Hits          33446    33456      +10
- Misses        12468    12472       +4
- Partials       2218     2220       +2

Impacted Files
Coverage Δ
Complexity Δ

.../org/apache/hadoop/hdds/scm/pipeline/Pipeline.java
85.71% <100.00%> (+0.20%)
44.00 <0.00> (+1.00)

.../org/apache/hadoop/ozone/om/helpers/OmKeyInfo.java
86.25% <100.00%> (+0.33%)
42.00 <0.00> (+2.00)

...adoop/ozone/om/helpers/OmKeyLocationInfoGroup.java
75.60% <100.00%> (+1.25%)
12.00 <2.00> (+1.00)

...g/apache/hadoop/ozone/om/helpers/OzoneAclUtil.java
81.91% <100.00%> (+1.23%)
39.00 <4.00> (+2.00)

...adoop/ozone/om/request/key/OMKeyCommitRequest.java
97.00% <100.00%> (ø)
18.00 <0.00> (+1.00)

...otocol/commands/RetriableDatanodeEventWatcher.java
55.55% <0.00%> (-44.45%)
3.00% <0.00%> (-1.00%)

.../apache/hadoop/hdds/scm/node/StaleNodeHandler.java
88.88% <0.00%> (-11.12%)
4.00% <0.00%> (ø%)

...ache/hadoop/ozone/om/codec/S3SecretValueCodec.java
90.90% <0.00%> (-9.10%)
3.00% <0.00%> (-1.00%)

...apache/hadoop/hdds/server/events/EventWatcher.java
77.77% <0.00%> (-4.17%)
14.00% <0.00%> (ø%)

...iner/common/statemachine/SCMConnectionManager.java
77.38% <0.00%> (-3.58%)
13.00% <0.00%> (-1.00%)

... and 12 more

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@elek Aha, so many years, Thank you for your review and merge this PR.


Examples mixed up

Fairly certain the examples for "The following example merges changeset 137 into branch2." and "The following example merges all the changesets up to changeset 137 into branch2." have been switched.  This should be the correct way:
The following example merges changeset 137 into branch2.
c:\projects>tf merge /version:C137 branch1 branch2 /recursive
The following example merges all the changesets up to changeset 137 into branch2.
c:\projects>tf merge /version:C137~C137 branch1 branch2 /recursive

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

ID: 9c2a034e-46b4-0c59-9cc1-b34a199383c9
Version Independent ID: 7022c4b2-7011-5cdc-1b57-f2ee3b594bdc
Content: Merge Command - Azure Repos
Content Source: docs/repos/tfvc/merge-command.md
Product: devops
Technology: devops-code-tfvc
GitHub Login: @apawast
Microsoft Alias: apawast

#reassign @RuslanRasulovAkv

Abu Abed

#reassign @IlyaChistov

@msebolt could you please close it, Ilya fixed it in PR


Supporting cores with private flash partitions

Hi! I'm looking into supporting the nRF5340 in pyocd.
Although it seems easy enough to have multiple flasher algos for different memory partitions, I couldn't find a way to specify on which core the algo needs to run. We would usually have a merged HEX file containing all the partitions that is supplied to the flasher tool. It would be great if someone could help me out here. :)

Unfortunately… pyocd currently can only run the flash algo on the main core. ☹ It's definitely a serious deficiency for certain devices!

It looks like it wouldn't be too hard to implement. The pyocd.flash.flash.Flash class that's responsible for running the flash algo already takes a Target class used to access the core. If the target instance for a core (rather than SoC) is passed in, the algo would be run on that core.
The main changes would be

Tracking the core the algo needs to on. Using a FlashRegion attribute with the core name (or number) would be fine. (Default of None needs to be added to FlashRegion.DEFAULT_ATTRS dict.)
Update CoreSightTarget.create_flash() to look up the core and pass it to the Flash class constructor, or use the primary core if not specified.
Update pyocd.target.pack.cmsis_pack.CmsisPackDevice to set the flash algo core name attribute.

Thanks for the insight! I'm currently tinkering with this on my develop branch.
Do you have an idea why

the second core is not automatically generated
only the first flash region is actually saved as a flash regions, while the others are ROM regions?

Got some more progress, here's a PR: https://github.com/pyocd/pyOCD/pull/1656


Updates planned for 1.2.1

NCO 4.7.5

@zshaheen, @doutriaux1 and @sterlingbaldwin, could you let me know what updates you'd like to see for v1.2.1?  I'll try to get it going tomorrow.

mpas_analysis v1.0

@xylar I'm releasing v1.3.4 of e3sm_diags sometime this week. When do you plan on releasing v1.2.1 of e3sm-unified?

@zshaheen, no rush, I just had the sense that it's about time.  We'll be releasing MPAS-Analysis v1.0 sometime in the next few days.

I guess I'll wait to include any new e3sm_diags in another version of the unified env. Everyone on the team is gone, and I'd like another person to test before we release. So for this release, I don't have anything new.

@zshaheen, I think I might hold off on 1.2.1 for now.  If there are only 2 updated packages, that doesn't seem worth the effort to deploy on all machines.  Keep me posted on the next release of e3sm_diags.

@xylar Im getting closer to the processflow 2.0 release (1-2 weeks). I'll let you know once its ready.

Okay, that also sounds good.  So it definitely sounds like I should wait.

Addressed by #16


Metadata writing/reading for VTK and ITK

This PR adresses two problems (see https://github.com/Inria-Asclepios/medInria-public/issues/46)

The reader/writer for VTK files stores metadata in the header, but this header is limited to 256 characters.
The readers/writers for VTK and ITK files do not store all the metadata.

For VTK I stored the metadata as field data for all cases (except CARTO which is handled by a different writer). In the reader I had to make it "backwards-compatible" since the previously written files will have the metadata in the header. Therefore the reader does the following:

It firsts checks if metadata is present in the field data and loads it.
If the first attempt failed, it tries to take the metadata from the header (provided it is in the format that was written by the previous version of the writer).
if still not found, it checks if the metadata was already loaded and stored in the vtkMetaDataSet metadata dictionary. This dictionary is used by vtkMetaSurfaceMesh when loading CARTO files (so you don't have to manually load the data from the header for CARTO files).

I made a change to this PR. Some of the current bugs in the pipeline are caused by the itk image reader loading metadata that is not from medInria.

Ok for me

Note that this PR needs https://github.com/Inria-Asclepios/medInria-public/pull/51 to work properly

I FINALLY understand it!!!!  :D
Good job, I'll merge it.
2 comments though

As discussed yesterday, maybe we can try to put this code inside vtkMetaSurcfaceMesh
concerning extractMetaDataFromHeader, I am pretty sure it was not used by H&Cie since it's a very new change, so it might just concern us. Maybe we don't need it then.


Add wash tail -f to follow updates

Requires -f as the only allowed semantic. Only displays new updates after tail -f is called. Works for streaming resources and normal files (using inotify).
Resolves #5.

Updated. Also added a little refactoring.


Make it possible to pass objects into Karate context

I have a need to be able to pass an existing object into Karate context so that it would be available inside karate-config.js and feature files by a name which I would give it.
I know that I can instantiate a class in @BeforeClass method but then in order to access it from Karate context I would have use something like this (provided I created KarateContext class which can be used to store references to objects)
var KarateContext = Java.type("KarateContext");
var instance = KarateContext.get("instance")

Do you think it would be reasonable to support something like that out-of-the-box?

@inikolaev can you explain a little more. I actually think having you use a singleton like the above is reasonable, especially considering how rare this use-case is (at least in my experience so far).
Else what is a better way that you can propose that gets a Java object (that has been already instantiated) into Karate ?
Not sure if this helps, but you can use the new keyword in karate-config.js - here is an example from the karate-mock-servlet code - https://github.com/intuit/karate/blob/master/karate-mock-servlet/src/test/java/karate-config.js
There is an experimental userDefined config setting in the mock-servlet doc, take a look at that as well in case that triggers any ideas.
can re-open this if needed.


Warn users about new config args

As we add config args, but users might have old configs, we should tell them that they are missing keys and link to the
https://deepforest.readthedocs.io/en/latest/ConfigurationFile.html
os.getcwd()
'/home/b.weinstein/EvergladesTools'
        m = main.deepforest(num_classes=classes, label_dict=label_dict, config_file="Airplane/deepforest_config.yml")
Reading config file: Airplane/deepforest_config.yml
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/orange/ewhite/b.weinstein/miniconda3/envs/EvergladesTools/lib/python3.11/site-packages/deepforest/main.py", line 64, in __init__
    self.create_model()
  File "/orange/ewhite/b.weinstein/miniconda3/envs/EvergladesTools/lib/python3.11/site-packages/deepforest/main.py", line 162, in create_model
    self.config["architecture"]))
    ~~~~~~~~~~~^^^^^^^^^^^^^^^^
KeyError: 'architecture'

https://github.com/weecology/DeepForest/blob/04a108483160242e2c68a57673864e0344f03f8e/deepforest/main.py#L57C23-L57C32

Can I work on this issue?


When there are multiple Tags in the scene, specify a Tag to run, and the screenshots will not be displayed properly in the report

For Example
Tag P0，P1 exist in senario
run command: flybirds run -T P0

fix on skip case error


commit lib/domains/vn/edu/hust/sis.txt

@hieudo2808 I am sorry, the domain sis.hust.edu.vn is removed from our trusted domains list because it was abused in the past. If you are the student of this school, please enroll to GitHub Student Developer Program. Then apply for JetBrains educational subscription with your GitHub account (GitHub tab at https://www.jetbrains.com/shop/eform/students).


Customize some code

I would like to ask. Is it ok if I'll move oscar code inside my project and will make changes directly in oscar code?
Thanks

Hello @alexkos,
Please read the documentation on customising oscar.
Also this isn't the place to be asking these types of questions, you should direct them to the django-oscar Google group.

Thank you very much


Edit CDIDataImportCronOutdated

Signed-off-by: Avital Pinnick<EMAIL_ADDRESS>

@akalenyu I made quite a few changes to this runbook. Please review.

/lgtm
Thank you!

@sradco Ready to merge.


Add more trinket slots

Given that Botania is in the pack, I think it would be nice if I could equip (say) my ring of mana, or other baubles.
While I'm asking for things, it would be cool if you could wear both a backpack and an elytra. https://modrinth.com/mod/elytra-slot

I'll see what's the best way to implement that. Elytra slot always bothered me bcause I liked the drawback of using only elyra, but in this pack it actually doens't make sense to have that drawback


Move user docs to docs/user-guide and create an up-to-date TOC

We've started to create a user guide in docs/user-guide. We should move related docs and concept-oriented examples to there, and create a TOC.
We probably need to merge, refactor, rename, etc. docs as well.
Files to move:

docs/user-guide.md -> docs/user-guide/README.md, and updated
Generated kubectl docs to docs/user-guide/kubectl/  @jlowdermilk
docs/accessing-the-cluster.md
docs/annotations.md
docs/application-troubleshooting.md
docs/compute_resources.md
docs/container-environment.md
docs/containers.md
docs/downward_api.md
docs/identifiers.md
docs/images.md
docs/k8s-ui-*.png
docs/kibana.png
docs/kubeconfig-file.md
docs/labels.md
docs/logging.md
docs/monitoring-architecture.png
docs/monitoring.md
docs/overview.md
docs/persistent-volumes.md
docs/pod-states.md
docs/pods.md
docs/replication-controller.md
docs/secrets.md
docs/security_context.md
docs/services.md
docs/services*.png
docs/sharing-clusters.md
docs/ui.md
docs/volumes.md
docs/working_with_resources.md
examples/downward-api
examples/environment-guide
examples/explorer
examples/limitrange
examples/liveness
examples/logging-demo
examples/node-selection
examples/persistent-volumes
examples/resourcequota
examples/secrets
examples/update-demo
examples/walkthrough
examples/multi-pod.yaml
examples/pod.yaml
examples/replication.yaml
examples/simple-yaml.md
examples/simple-nginx.md

Related: #9220, #9494
cc @nikhiljindal @lavalamp

Hi @bgrant0607,
Since all user docs are moving over to gh-pages, i dont see this file reorg necessary. Ive also already created the site navigation files for v1 based on the docs/.md and examples/.md file structure so this move will also have impact there. Once we move these files to kubernetes.io (#9494), the site navigation will serve as the TOC. Here is a screen cap from my local build:

cc @mikedanese


Module name case sensitvity on Windows

On Windows, module names are case-insensitive and not always predictable (i.e. kernel32.dll can be loaded as "KERNEL32.DLL"). However, when using e.g. lime::module::get(), the comparison is case-sensitive, leading to failure if the module name was loaded in a different case. The comparison should be made case-insensitive to fix this issue. (Note the same should NOT be done for symbols which are case-sensitive even on Windows).

Is the module lookup case insensitive on windows regardless of the file system used?

Honestly, not sure, can't seem to find a solid answer to that one but I believe users of case-sensitive filesystems would have reported problems if the lookup was ever case-sensitive.

Good Point
To be honest I'm not a huge fan of endorsing windows' way of having things case insensitive because it just leads to bad portability but I can also understand that it might be weird to work with when most windows developers are used to things being case insensitive.
I'll probably implement the suggested change in the next few days - however not by default but behind a compile flag as I want to prevent weird things from happening when using wine or mingw

@RibShark The latest commit adds case insensitive module name comparison, could you confirm that it works?
I don't have a windows machine to test things on me right now


Remove image generation node dependencies on generate.py

Remove node dependencies on generate.py
This is a draft PR in which I am replacing generate.py with a cleaner, more structured interface to the underlying image generation routines. The basic code pattern to generate an image using the new API is this:
from invokeai.backend import ModelManager, InvokeAIGeneratorFactory, Txt2Img, Img2Img

manager = ModelManager('/data/lstein/invokeai-main/configs/models.yaml')
factory = InvokeAIGeneratorFactory(manager)

txt2img = factory.make_generator(Txt2Img)
outputs = txt2img.generate(prompt='banana sushi', steps=12, scheduler='k_euler_a', iterations=5)

# generate() returns an iterator
for next_output in outputs:
    print(next_output.image, next_output.seed)

img2img = factory.make_generator(Img2Img)
outputs = img2img.generate(prompt='strawberry` sushi', init_img='./banana_sushi.png')
output = next(outputs)
output.image.save('strawberries.png')

The ModelManager handles model selection and initialization.
The InvokeAIGeneratorFactory creates InvokeAIGenerator objects of the requested subclass. Defined subclasses are currently Txt2Img, Img2Img and Inpaint. When you create a factory you can optionally provide it with an InvokeAIGeneratorBasicParams object, which contains common values for step, cfg, scheduler, model name, perlin noise, etc. If you don't provide the basic params, a reasonable set of defaults will be chosen. Any of these parameters can be overridden at generate() time.
The InvokeAIGenerator object (e.g. Txt2Img) has one main method named generate() that accepts the prompt and all subclass-specific arguments. The generate() method will return an iterator over a series of InvokeAIGeneratorOutput objects. These objects contain the PIL image, the seed, the model name and hash, and attributes for all the parameters used to generate the object (you can also get these as a dict). The iterations argument controls how many objects will be returned, defaulting to 1. Pass None to get an infinite iterator.
Given the proposed use of compel to generate a templated series of prompts, I thought the API would benefit from a style that lets you loop over the output results indefinitely. I did consider returning a single InvokeAIGeneratorOutput object in the event that iterations=1, but I think it's dangerous for a method to return different types of result under different circumstances.
Changing the model is as easy as this:
factory.model_name = 'inkspot-2.0`
txt2img = factory.make_generator(Txt2Img)

With respect to Nodes, I have updated the generate_initializer service and the generate invocations so that they call into the new InvokeAIGeneratorFactory. I have confirmed that txt2img works in the nodes client. However I'm a bit confused about how to use the node CLI's img2img, as it seems to take an image from memory rather than a path to an image, but then the load_image doesn't work the way I think it should. I need to take a fresh look. But the bottom line is that the image generation nodes no longer need Generate.
The legacy WebUI and CLI are still working off Generate (which has not yet been removed from the source tree) and mostly functional. The exception is that they will crash if the NSFW checker is active, due to the fact that I moved the checker into its own module and haven't fixed up Generate to accommodate this change.
There's still a bit to do before this can be merged:

[ ] Update the pytests, which are failing due to dangling references to generate
[ ] Rewrite the reconstruct.py and upscale.py nodes to call directly into the postprocessing modules rather than going through Generate
[ ] Fix up legacy Generate so that the NSFW checker runs again. Otherwise the CLI and WebUI will be broken.

These objects contain the PIL image, the seed, the model name and hash, and attributes for all the parameters used to generate the object (you can also get these as a dict).

So I'm thinking about attention maps, which need to be bubbled back from the innards of the diffusion step loop all the way up to the UI. They can readily be passed around as a PIL image or a dict of PIL images - i assume that will be easy enough to incorporate?

Yes, at this point we can easily add new fields to InvokeAIGeneratorOutput
to return to the caller. I see that there is already an
attention_maps_callback in the Generator class, and it is generating a
list of PIL images. Is it correct that the last image in the list is the
final generated image and that all the rest are some sort of representation
of the mapping from token to image area? I haven't explored this at all.
How many of these maps are there?

I'll do a full review later, but commenting on the PR summary here. It would be nice to have this sort of pattern instead:
model_manager = ModelManager('/data/lstein/invokeai-main/configs/models.yaml')
model = model_manager.get('stable-diffusion-2.0') # Whatever the standard string identifiers are
txt2img = Txt2Img(model)
outputs = txt2img.generate(prompt='banana sushi', steps=12, scheduler='k_euler_a', iterations=5)

When I had originally suggested "factory", I was looking for something to create and manage the model objects that are used to generate. Factory might not even be the right pattern, but it's what came to mind at the time when I was looking at code.
Anything that would help us utilize Diffusers more directly while still respecting model management (caching, GPU memory, etc.) would be great as well. That would allow us to more rapidly integrate newly-developed functionality in the space.

txt2img = Txt2Img(model)
outputs = txt2img.generate(prompt='banana sushi', steps=12, scheduler='k_euler_a', iterations=5)

Do you do plan to do anything with txt2img besides call that single method on it?
Wondering why that's two steps instead of passing the model along with the rest of the parameters.

I've given this a read-through, now for giving feedback and I'm trying to sort out which parts are inherent to the proposed design and which are temporary considerations that come from doing things one layer at a time -- and this is the Generate layer not the Generator layer (wow names are confusing).
I'm not opposed to ever using the factory pattern, but I am leery of it, so I'd like to make sure it's justified here.
We've got
manager = ModelManager('/data/lstein/invokeai-main/configs/models.yaml')
factory = InvokeAIGeneratorFactory(manager)

txt2img = factory.make_generator(Txt2Img)
generator = txt2img.generate(prompt='banana sushi', steps=12, scheduler='k_euler_a')
output = generate()

So my question would be: What keeps that from being more like this?
manager = ModelManager('/data/lstein/invokeai-main/configs/models.yaml')
model = manager.current_model  # or somesuch
output = txt2img(model, prompt='banana sushi', steps=12, scheduler='k_euler_a')

Yeah, some of the awkwardness of the current code is that I didn't want to break base.py up into separate refactored files at this time because this would create problems for generate.py. I want to keep things working as much as possible during the transition. There will definitely be more refactoring to do.
With respect to the factory pattern, it certainly isn't required but there is an argument to be made for retaining it. What isn't shown in the code example I put up is that there is a shared generation configuration parameter block that can be created and passed to the factory at the time it is initialized. A fuller example would look like this:
manager = ModelManager('/data/lstein/invokeai-main/configs/models.yaml')
generation_parameters =  InvokeAIGeneratorBasicParams(
        model_name = 'stable-diffusion-1.5',
        steps = 30,
        scheduler = 'k_lms',
        cfg_scale = 8.0,
        height = 640,
        width = 640
        )

factory = InvokeAIGeneratorFactory(manager, params=generation_parameters)
txt2img = factory.make_generator(Txt2Img)
img2img = factory.make_generator(Img2Img)

factory.params.update(height=512, width=512)
inpaint = factory.make_generator(inpaint)

This fits the style of having a common set of generation parameters that are usually static and shared among all the generators created by the factory. They can be changed (e.g. by webUI), after which time any new generators created get the changed configuration.
The alternative is simply to keep the generation_parameters data object around and pass it directly to each of the InvokeAIGenerator initializers:
txt2img = Txt2Img(manager, generation_parameters)

Is this preferable?

The alternative is simply to keep the generation_parameters data object around and pass it directly to each of the InvokeAIGenerator initializers:
txt2img = Txt2Img(manager, generation_parameters)
Is this preferable?

From my perspective, yes, definitely: all of the information i need to understand what txt2img is going to contain is right there on that line of code, there's no state or side effects that have been hidden from me as the reader of the code.

I'll do a full review later, but commenting on the PR summary here. It would be nice to have this sort of pattern instead:
model_manager = ModelManager('/data/lstein/invokeai-main/configs/models.yaml')
model = model_manager.get('stable-diffusion-2.0') # Whatever the standard string identifiers are
txt2img = Txt2Img(model)
outputs = txt2img.generate(prompt='banana sushi', steps=12, scheduler='k_euler_a', iterations=5)

When I had originally suggested "factory", I was looking for something to create and manage the model objects that are used to generate. Factory might not even be the right pattern, but it's what came to mind at the time when I was looking at code.
Anything that would help us utilize Diffusers more directly while still respecting model management (caching, GPU memory, etc.) would be great as well. That would allow us to more rapidly integrate newly-developed functionality in the space.

See previous comment. If we're dropping the factory pattern, then I'd like to retain the InvokeAIGeneratorBasicParams so that the basic generation parameters are kept together in a coherent data structure. Could you also advise on whether Txt2Img needs to be an object? generate() could be a class method:
from invokeai.backend.generator import Txt2Img
#... get model
#.. build parameters
outputs = Txt2Img.generate(model, basic_params, prompt="banana sushi")

With respect to making it easier to use Diffusers directly, I need to ask you and @keturn for advice on how this will be used. The objects currently returned by the model manager are StableDiffusionGeneratorPipeline objects, but this could be changed to any other DiffusionPipeline class fairly easily by having an optional parameter that selects the type. My question is whether these alternative pipelines are stanzas in the models.yaml file, or are we configuring them on the fly?

See previous comment. If we're dropping the factory pattern, then I'd like to retain the InvokeAIGeneratorBasicParams so that the basic generation parameters are kept together in a coherent data structure. Could you also advise on whether Txt2Img needs to be an object? generate() could be a class method:

Ah my comment was less about how we call the method and more about getting the model separately from the model manager. (Though the node is already an object that contains all the parameters, has defaults, ranges, validation, etc... so doing things directly in there would make sense).

With respect to making it easier to use Diffusers directly, I need to ask you and @keturn for advice on how this will be used. The objects currently returned by the model manager are StableDiffusionGeneratorPipeline objects, but this could be changed to any other DiffusionPipeline class fairly easily by having an optional parameter that selects the type. My question is whether these alternative pipelines are stanzas in the models.yaml file, or are we configuring them on the fly?

Mostly what I'd like to be able to achieve is the ease with which I was able to write this node:
https://gist.github.com/Kyle0654/57c337f7c005662b98a53f4e1ed7a960
There's a lot in there I'm aware isn't correct for how we do things. In particular, the from_pretrained seems to be what loads the model. If we had a way of creating these from our own model manager models though, then generation code could potentially look like this (though I'm aware a lot of stuff is happening under the hood here that is probably not correct - e.g. it extracts a depth map by getting a depth model itself on-demand, which isn't probably the behavior we want).

The alternative is simply to keep the generation_parameters data object around and pass it directly to each of the InvokeAIGenerator initializers:
txt2img = Txt2Img(manager, generation_parameters)
Is this preferable?

From my perspective, yes, definitely: all of the information i need to understand what txt2img is going to contain is right there on that line of code, there's no state or side effects that have been hidden from me as the reader of the code.

Would it be preferable to reduce everything to one class method call as in:
model = manager.get_model('stable-diffusion-1.5')
params = InvokeAIGeneratorBasicParams(steps=50)
outputs = Txt2Img.generate(model, params=params, prompt="banana sushi")

params could be an optional keyword and default to the default initializer of InvokeAIGeneratorBasicParams, allowing for a one line invocation:
outputs = Txt2Img.generate(manager.get_model('stable-diffusion-1.5'), steps=50, prompt="banana sushi")

Would it be preferable to reduce everything to one class method call as in:
model = manager.get_model('stable-diffusion-1.5')
params = InvokeAIGeneratorBasicParams(steps=50)
outputs = Txt2Img.generate(model, params=params, prompt="banana sushi")

personally i prefer instance methods over class methods, but that's a preference not an "ought".

So I'm hearing a need for the model manager to handle the GPU/CPU caching of arbitrary diffusers pipelines. I think this can actually be done with a method that looks something like this:
pipeline = manager.get_pipeline('stabilityai/stable-diffusion-2-depth')

Internally it would handle the from_pretrained() call, using the configured cache directory, precision and device type, and then use the existing caching system to manage offloading. It would use the repo_id to track the object in lieu of the "model name" in order to avoid having to configure a stanza in models.yaml.
See any problems with this?

So I'm hearing a need for the model manager to handle the GPU/CPU caching of arbitrary diffusers pipelines.

I'm super wary of statements like this because there's a reason why it took three months to do the diffusers integration instead of three days: there are still nearly a thousand lines of code in our diffusers_pipeline module — "bespoke" as hipsterusername would say.
You should not plan on using stock 🧨diffusers pipelines unless you're planning to do so without any InvokeAI features, like using masks with a non-inpainting model, or not using masks with an inpainting model, or cross-attention controls or thresholding or symmetry or attention maps or adjusting slice size based on available capacity.

Internally it would handle the from_pretrained() call, using the configured cache directory, precision and device type, and then use the existing caching system to manage offloading.

These aren't bad ideas, and may well be things we end up doing, but I'd call that beyond the scope of this phase.

Would it be preferable to reduce everything to one class method call as in:
outputs = Txt2Img.generate(model, params=params, prompt="banana sushi")

personally i prefer instance methods over class methods, but that's a preference not an "ought".

If you never need an instance of Txt2Img(), then this can simply be a txt2img function. I doubt we need Txt2Img to be a class at all.

You should not plan on using stock 🧨diffusers pipelines unless you're planning to do so without any InvokeAI features, like using masks with a non-inpainting model, or not using masks with an inpainting model, or cross-attention controls or thresholding or symmetry or attention maps or adjusting slice size based on available capacity.

Some of this might be okay for nodes that don't have exposed UI? And then if we want to expose UI we can always more fully integrate features?
Is there some other way to help contributors more rapidly integrate new features?

Is there some other way to help contributors more rapidly integrate new features?

As long we have a InvokeAIGeneratorBasicParams with parameters for a dozen orthogonal features -- and we do, because we have a Universal Canvas that tells artists they can do all these things to any part of the canvas at any time, instead of each operation being its own independent workflow -- there's no shortcut for doing integration work.
When we add support for some other type of diffusers pipeline, we can do the work to see what we need to do to support whatever additional inputs and parameters it needs. After we do a couple of those, hopefully we're coming up with ways to factor out composible pieces so we're not tying ourselves in knots.
I'm confident we'll figure out how to improve on this over time. But DiffusionPipelines as they're built today are not the answer to all our integration needs. Each is written with a very narrow usage in mind (usually just enough to look cool in a notebook) and they're just not extensible enough.

Hey folks, great discussion and I'm really grateful for the advice and guidance. I'm up against a two week vacation that is starting on Sunday, and I'm not sure how much time I'll have to work on this phase of the refactor. Can I get confirmation that this part of the refactor is not going to block other critical parts of the nodes integration, such as porting the WebUI to nodes?
Realistically before I fly off Sunday morning I think I'll be able to (1) replace the factory paradigm with a simpler direct calls to Txt2Img, Img2Img and Inpaint classes; and (2) wire nodes up to the postprocessing classes so they are not calling in to Generate. After that, further work will drop way off.
However if this is a blocker, then I'm happy to relinquish the task to anyone who would like to volunteer.

Factory pattern is now removed. Typical usage of the InvokeAIGenerator is now:
```
from invokeai.backend.generator import (
    InvokeAIGeneratorBasicParams,
    Txt2Img,
    Img2Img,
    Inpaint,
)
    params = InvokeAIGeneratorBasicParams(
        model_name = 'stable-diffusion-1.5',
        steps = 30,
        scheduler = 'k_lms',
        cfg_scale = 8.0,
        height = 640,
        width = 640
        )
    print ('=== TXT2IMG TEST ===')
    txt2img = Txt2Img(manager, params)
    outputs = txt2img.generate(prompt='banana sushi', iterations=2)

    for i in outputs:
        print(f'image={output.image}, seed={output.seed}, model={output.params.model_name}, hash={output.model_hash}, steps={output.params.steps}')
```

The params argument is optional, so if you wish to accept default parameters and selectively override them, just do this:
```
    outputs = Txt2Img(manager).generate(prompt='banana sushi',
                                        steps=50,
                                        scheduler='k_heun',
                                        model_name='stable-diffusion-2.1'
                                        )

I'm ready to declare victory on this phase of the refactor and turn it back over to @Kyle0654 . I got the safety checker working again, and actually improved it a bit by unloading it from GPU when not in use, thereby recovering about 0.6 GB of VRAM. The face restoration and upscaling routines have been moved into a new restoration service, and a bit of redundant code has been ripped out. I've fully tested the legacy WebUI and CLI to make sure they continue to work during the transition, and am happy to see that there are no longer any calls into the Generate class from within Nodes  (or in fact anywhere else except for the Web and CLI front ends).
Please consider this ready for a review.
After this, I plan to do documentation and a bit more refactoring - in particularly I would like to refactor the two facial reconstruction routines and esrgan upscaling.
I will then rework the legacy CLI so that it no longer uses Generate. I think that cli_app.py with the pipe syntax is great, but making it mimic the "dream" syntax that the legacy CLI uses is not the way to go with it. I think it needs some convenience functions such as autocomplete support, and I'm happy to work on that if it seems reasonable.


Deleting datasource not working

When deleting a datasource, the corresponding database table is not being emptied.

Fixed by this commit.


[k8saudit-eks] cannot parse JSON

Describe the bug
Just set up k8saudit-eks and the audit rules in falco.
I can see the following in the logs, among with valid k8saudit logs:
2023/06/23 15:51:36 [k8saudit-eks] cannot parse JSON: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse array: cannot parse array value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object key: missing closing '"'; unparsed tail: ""
2023/06/23 15:51:36 [k8saudit-eks] unexpected tail: "d\n key value map stored with a resource ...on.gatekeeper.sh\\\",\\\"mutated\\\":false}\"}}"

2023/06/23 15:50:21 [k8saudit-eks] cannot parse JSON: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse array: cannot parse array value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse object: cannot parse object value: cannot parse string: missing closing '"'; unparsed tail: ""
2023/06/23 15:50:21 [k8saudit-eks] cannot parse JSON: cannot parse number: unexpected char: "d"; unparsed tail: "dD"
2023/06/23 15:50:21 [k8saudit-eks] cannot parse JSON: cannot parse number: unexpected char: "u"; unparsed tail: "uringSchedulingIgnoredDuringExecution\":{...he ones selected by namesp[Truncated...]"
2023/06/23 15:50:21 [k8saudit-eks] cannot parse JSON: cannot parse number: unexpected char: "s"; unparsed tail: "st\n and null namespaceSelector means \\\"t...nity) or not co-located (a[Truncated...]"
2023/06/23 15:50:21 [k8saudit-eks] cannot parse JSON: cannot parse number: unexpected char: "b"; unparsed tail: "be"
2023/06/23 15:50:21 [k8saudit-eks] cannot parse JSON: cannot parse number: unexpected char: "l"; unparsed tail: "lSelector in the specified namespaces, w...on.gatekeeper.sh\\\",\\\"mutated\\\":false}\"}}"

How to reproduce it
Configure audit logs in EKS
Configure falco 0.35 with the k8saudit-eks plug-in, default configuration, falco provided audit rules
Expected behaviour
The plug-in should process the logs correctly
Environment

Falco version:
0.35.0
k8saudit-eks:0.2
json:0.7

System info:
Fri Jun 23 16:03:16 2023: Falco version: 0.35.0 (x86_64)
Fri Jun 23 16:03:16 2023: Falco initialized with configuration file: /etc/falco/falco.yaml
Fri Jun 23 16:03:16 2023: Loading plugin 'k8saudit-eks' from file /usr/share/falco/plugins/libk8saudit-eks.so
Fri Jun 23 16:03:16 2023: Loading plugin 'json' from file /usr/share/falco/plugins/libjson.so
Fri Jun 23 16:03:16 2023: Loading rules from file /etc/falco/k8s_audit_rules.yaml
Fri Jun 23 16:03:16 2023: Loading rules from file /etc/falco/falco_rules.yaml
Fri Jun 23 16:03:16 2023: Loading rules from file /etc/falco/rules.d/k8saudit-rules-upm.yaml
Fri Jun 23 16:03:16 2023: Loading rules from file /etc/falco/rules.d/rules-upm.yaml
{
"machine": "x86_64",
"nodename": "falco-9bwd2",
"release": "5.15.0-1037-aws",
"sysname": "Linux",
"version": "41~20.04.1-Ubuntu SMP Mon May 22 18:18:00 UTC 2023"
}

Cloud provider or hardware configuration:
EKS 1.24

OS:
PRETTY_NAME="Debian GNU/Linux 11 (bullseye)"
NAME="Debian GNU/Linux"
VERSION_ID="11"
VERSION="11 (bullseye)"
VERSION_CODENAME=bullseye
ID=debian
HOME_URL="https://www.debian.org/"
SUPPORT_URL="https://www.debian.org/support"
BUG_REPORT_URL="https://bugs.debian.org/"

Kernel:
Linux falco-9bwd2 5.15.0-1037-aws 41~20.04.1-Ubuntu SMP Mon May 22 18:18:00 UTC 2023 x86_64 GNU/Linux

Installation method:
Kubernetes

@Issif

The extraction is made by the functions developed for the classic k8saudit plugin. For now, I don't know if it's an issue with the extraction of the data themselves.
Do you get these errors with all logs or only from time to time?

From time to time

My guess is it's related to the extractor. Do you have an example of of failed events?

Seems to be cause by some cloudwatch logs being truncated and continued in the following line:


put curly braces back on variables

I accidentally removed them when I converted from scss
fun times @incuna/frontend please review

Maybe it would be worth adding some tests here, so we can know it compiles or stuff?

@wytrych if that's easy to do / something you could help me with it would be awesome :)

We need to configure travis, but that's not a big issue, probably 2 hours worth of work.


Tickets Pallet

In fragments branch we renamed pallet_frag into pallet_tickets.
Now this is a big plan to improve the whole tokenomics. We add partner tokens and a different way to lock/stake.
This is in some internal documents. Need to implement all this.

Hey team! Please add your planning poker estimate with ZenHub @guusw @Kryptos-FR @aang114

We need to setup a meeting to discuss it


Unnecessary a.out file created

When running MIOpen code, an a.out file confusingly appears in your current directory. This function appears to be the culprit.
https://github.com/ROCmSoftwarePlatform/MIOpen/blob/08114baa029a519ea12b52c5274c0bd8f4ad0d26/src/ocl/gcn_asm_utils.cpp#L251-L268
Since it looks like it is just testing for a compiler bug and the compiled output isn't necessary, adding -o /dev/null to the arguments should prevent this.

Thats a good point. Lets try to add that to the arguments.


Create CONTRIBUTING.md

Create CONTRIBUTING.md
#3177

How about adding a link to these docs:
documentation/en/community/pull-request_EN.html
documentation/cn/community/pull-request.html

For more details about how to submit a PR.

done


fix: pass-through approval cancelled event

We need to support approvalCancelled events from the iframe. This passes the event through.

:rocket: PR was released in v2.9.1 :rocket:


Update tough-cookie and minimatch due to security risks

Upon running npm install on a brand new checkout, I get the following security-related warnings:
npm WARN deprecated<EMAIL_ADDRESS>ReDoS vulnerability parsing Set-Cookie https://nodesecurity.io/advisories/130
npm WARN deprecated<EMAIL_ADDRESS>Please update to minimatch 3.0.2 or higher to avoid a RegExp DoS issue

Perhaps those version numbers should be incremented, unless there is a specific reason to keep those libraries at the stated versions.

We don't depend on those libraries directly, is a dependency of a dependency. I will check if any of those dependencies got an update.

Closing as your issue is old. Please re-open as a new issue if problem persists.


Bugfix for multiple values of a key in a Config file - apache#9102, apache#12689

Fix #9102 #12689
Overriding the existing values with the last value in the list instead of adding them as a list of values in the Config File.
After Fix: controller.data.dir is taken as the last value.

This will cause problem for real array values. I think the core problem is that there is no way to differentiate key with single value vs array

I didn't recall that there is an explicitly method to merge duplicate keys into one comma separated array.

@Jackie-Jiang Yes, this fix was made assuming there wouldn't be an array of values for a key in a config file. If we are allowing values to be array as well, then I should see a way to find out if the key is already present and eliminate the previous key to bring in new value.


Fixed link to CHANGELOG in Nuget Packaging

:white_check_mark: Build ExtendedXmlSerializer <IP_ADDRESS>7-crfymsob completed (commit https://github.com/ExtendedXmlSerializer/home/commit/079208d2fa by @Mike-EEE)
Install it by running the following command in Package Manager Console:
Install-Package ExtendedXmlSerializer -Version <IP_ADDRESS>7-crfymsob -Source https://ci.appveyor.com/nuget/extendedxmlserializer-preview


Serve Istio CA as SPIFFE trust bundle

Istio supports retrieving SPIFFE trust bundles through spiffeBundleUrl in the mesh config, but does not offer a means to serve its CA as a trust bundle.
Affected product area (please put an X in all that apply)
[ ] Ambient
[ ] Docs
[ ] Installation
[ ] Networking
[ ] Performance and Scalability
[ ] Extensions and Telemetry
[X] Security
[ ] Test and Release
[X] User Experience
[ ] Developer Infrastructure
Affected features (please put an X in all that apply)
[X] Multi Cluster
[ ] Virtual Machine
[ ] Multi Control Plane
Additional context

cc @costinm @shankgan

+1
Also as well known jwk ( we may as well, in some cases we'll sign JWTs)

Not stale


Issue with griddler-sendgrid

I setup on the sendgrid-parse and I wasn't getting the body/body_raw content to populate correctly. I transitioned to using mandrill and everything is working. Its not an issue with Griddler, but I'd like to flag for other users.

This sounds like an issue for https://github.com/thoughtbot/griddler-sendgrid ?

Closing as thoughtbot/griddler-sendgrid#9 tracks this


MatLabel not properly aligned on the new MatFormField outline appearance when using MatPrefix with icons

Bug, feature request, or proposal:
The new outline appearance property introduced on Material 6 is great. After updating the package, I just added appearance="outline" to my templates and got beautifully rendered form fields, just the way I expected. However, on the fields that have a MatPrefix applied with an icon, the label generated by the MatLabel component does not align properly. This is even mentioned in the documentation, where is suggested that prefix should not be used with the new appearance.
What is the expected behavior?
MatLabels on MatFormFields with appearance="outline" should align properly even when they contain MatPrefix with icons.
What is the current behavior?
MatLabels on regular fields align beautifully. When the MatField contains a MatPrefix with an icon on it, they MatLabel align with the actual input field instead of fitting on its proper place, which would be aligned with the icon/MatPrefix. It seems that the gap generated even match the label text size.
What are the steps to reproduce?
The code below renders the field with the label not properly aligned:
<mat-form-field appearance="outline">
     <mat-label>Outline form field</mat-label>
<mat-icon matPrefix>sentiment_very_satisfied</mat-icon>
<input matInput placeholder="Placeholder">
</mat-form-field>
What is the use-case or motivation for changing an existing behavior?
The new appearance property is great. It would be a shame not to be able to use it properly with icons, that help improve the form look and feel. I wonder if there is a fix in mind for the future.
Which versions of Angular, Material, OS, TypeScript, browsers are affected?
Angular 6.0.1
Angular Material 6.0.1
Chrome
Congratulations to the Angular Material team for the great work achieved.
Regards,
Marcio

dup of #11513


Open python files

When hitting the open button, you can also open python files. Fixed some bugs as well

@TomKlimovski can open dags and convert them into wmls now. There's a couple of changes I've left out, because I want to consolidate your navbar changes first. Namely:

Change icon for convert to python DAG to the python icon
Add a navbar button with the current convert to python dag to sort nodes
Add a nanbar button to snap to the top left of the dag
Add a navbar button to delete the currently selected node

Note that upgrading react-flow-chart to 0.0.14 seems to have fixed a bunch of bugs around dragging and dropping and the zoom functionality


Ruler not working on gridless maps

I have the following issue:
On gridless maps, the ruler is no longer working at all. I'm not sure when exactly this happened (we haven't had a fight in a while), but I remember it working before. If I turn on the grid in the scene configuration, the ruler is working again. Is this a known issue?
The system is The Dark Eye 2.5.1, on Foundry 0.8.9, hosted on The Forge.

Please disable all modules except Drag Ruler and socketlib and see if that resolves the issue.

No, even doing as you said and disabling everything but those two did not resolve the issue, which is still present on gridless maps.


Arabic Translation

Context

Language: Standard Arabic
Translator: someone
Project: Documentation Website

Hi @Idrinth ,
Am a native Arabic speaker, I think that I can help but am not familiar with the framework or its website (found this issue while searching GitHub)
Can you please provide more details on what is needed? then I'll be able to tell whether I can do it or not
Is it like one file where I need to translate the labels from the website?
Notice that you may need to address the issue of RTL cause unlike English, Arabic is a right-to-left language
Thanks

Hi @Idrinth ,
Am a native Arabic speaker, I think that I can help but am not familiar with the framework or its website (found this issue while searching GitHub)

hi, thanks for your interest! The translations are done in yaml files in the language folder. It is pretty much the following scheme:
translation_key: "language specific text"

Can you please provide more details on what is needed? then I'll be able to tell whether I can do it or not

copy the en.yml from the language folder and change the quoted strings to arabic text.

Is it like one file where I need to translate the labels from the website?

yes, exactly :)

Notice that you may need to address the issue of RTL cause unlike English, Arabic is a right-to-left language

Will be adding support for that asap, it's been on my todo list for a while.

Thanks for the explanation :)
I'll take it from here

Hi @Idrinth,
Translation ready under PR #154

Hi @Idrinth,
Translation ready under PR 154

Thank you, was sadly sick for a while - sorry about the long wait


Having problems running develop command with v50.0 - must subclass Command

Similar to #2355 but for the develop command. Looks like the develop command is subclassing namespaces.DevelopInstaller --> Installer
This looks like it clashes with the check that each command implements the Command interface in dist.py
Traceback (most recent call last):
  File "setup.py", line 57, in <module>
    setuptools.setup(
  File "/Users/karrie/.local/share/virtualenvs/lib-NEukqkcO/lib/python3.8/site-packages/setuptools/__init__.py", line 153, in setup
    return distutils.core.setup(**attrs)
  File "/Users/karrie/.local/share/virtualenvs/lib-NEukqkcO/lib/python3.8/site-packages/setuptools/_distutils/core.py", line 134, in setup
    ok = dist.parse_command_line()
  File "/Users/karrie/.local/share/virtualenvs/lib-NEukqkcO/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 484, in parse_command_line
    args = self._parse_command_opts(parser, args)
  File "/Users/karrie/.local/share/virtualenvs/lib-NEukqkcO/lib/python3.8/site-packages/setuptools/dist.py", line 903, in _parse_command_opts
    nargs = _Distribution._parse_command_opts(self, parser, args)
  File "/Users/karrie/.local/share/virtualenvs/lib-NEukqkcO/lib/python3.8/site-packages/setuptools/_distutils/dist.py", line 547, in _parse_command_opts
    raise DistutilsClassError(
distutils.errors.DistutilsClassError: command class <class 'setuptools.command.develop.develop'> must subclass Command```

I suspect this is a dupe of #2355.


Column reordering: only move each col once per ALTER

As described in https://github.com/skeema/skeema/issues/36#issuecomment-418090748, there are column-reordering situations in which Table.Diff() may attempt to reposition the same col multiple times, generating illegal SQL. One such case is covered by a new test in 1272a54a311; this hasn't been merged to master yet since the test currently fails.
The root cause is the current algorithm for handling column reorders doesn't guarantee that a column is only moved once. A different algorithm entirely should be used here. I believe this approach would provide the right guarantee:

Among the common columns between the "before" and "after" side of the diff, identify the longest pre-sorted subsequence in the "before" side using an LIS (or, equivalently for this usage, LCS) algorithm. These columns do not need to be moved.
All other columns do need to be moved, so emit exactly one MODIFY COLUMN ... AFTER|FIRST for each.
Any non-moved columns should have a MODIFY COLUMN if (and only if) they had other modifications unrelated to ordering.

In theory, the optimal approach (in terms of minimum number of MODIFY COLUMN clauses) would also break ties in the first step by examining the number of other non-reorder modifications in each tied longest-subsequence candidate, to minimize the number of clauses generated in the third step. But that may wait until a future revision.

Main issue fixed in bca198ed45475, and verified with new test coverage in 1272a54a311a and a41ba075709a8ef4.
Punting on the optimal tie-breaker logic until a future release, since this doesn't actually impact functionality and would greatly complicate the algorithm.


Add reference to private key file, as it's not configured by default

Signed-off-by: John Fletcher<EMAIL_ADDRESS>What this PR does / why we need it:
The getting started with AWS guide doesn't work as it currently stands.
```NONE

@fletchgqc hey and thanks for PR.
We deliberately left out ssh_private_key_file from examples, as it means that SSH private key should be unencrypted. Kubeone can only work with SSH unencrypted private key files. Which is actually sounds quite bad :). Kubeone delegates handling of encrypted SSH key files to ssh-agent. You can find more information here: https://github.com/kubermatic/kubeone/blob/master/docs/ssh.md
I'll close this PR as it's against our original intention.
P.S.
Please don't use ssh_private_key_file — in order to use it you need to store it unencrypted, which is bad for security.

OK, I understand, I would recommend that you nevertheless change your docs to explain this. In the end you want to encourage security, but not scare away beginners by forcing them to change their key management practices when they are just trying to test out your system.


fixed spelling error

🤔 🐛 You appear to be fixing a bug in Go code, yet your PR doesn't include updates to any test files. Did you forget to add a test?
Courtesy of your friendly test nag.

[APPROVALNOTIFIER] This PR is NOT APPROVED
This pull-request has been approved by: starizard
To fully approve this pull request, please assign additional approvers.
We suggest the following additional approver: nmittler
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Hi @starizard. Thanks for your PR.
I'm waiting for a istio member to verify that this patch is reasonable to test. If it is, they should reply with /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.
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/ok-to-test

@starizard: The following test failed, say /retest to rerun them all:

Test name
Commit
Details
Rerun command

prow/integ-mixer-k8s-presubmit-tests.sh
cc364ff264c707a3fbbadd5efe6a58464a1458ac
link
/test integ-mixer-k8s-presubmit-tests-master

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Decoding offset based on alignment offset bit

In the binary format, the offset may or may not be present as specified
by the alignment bitfield.

Hi @naturaltransformation, I'm your friendly neighborhood Microsoft Pull Request Bot (You can call me MSBOT). Thanks for your contribution!

This seems like a small (but important) contribution, so no Contribution License Agreement is required at this point. Real humans will now evaluate your PR.

TTYL, MSBOT;

@naturaltransformation Why did you decide to close this PR?

Replaced with pr#429 submitted under a handle with CLA.
On Mar 2, 2016 12:24 PM, "Doug Ilijev"<EMAIL_ADDRESS>wrote:

@naturaltransformation https://github.com/naturaltransformation Why did
you decide to close this PR?
—
Reply to this email directly or view it on GitHub
https://github.com/Microsoft/ChakraCore/pull/428#issuecomment-191413253.


Feat: Improving Rate us feature

Describe the feature
I would like to improve and enhance the rateus feature of this website.
Add ScreenShots

I would add some emoji based on the rating and improving the section at the same.
Record

[X] I agree to follow this project's Code of Conduct
[X] I'm a GSSOC'24 contributor
[X] I want to work on this issue

@MuraliDharan7 Assigned!
Make sure to attach before & after screenshots in your PR. Also, star the repo before working on it. While creating your PR, ensure you pull all existing changes beforehand to avoid conflicts.
Happy open-source contributing!


Fractional Knapsack in C

🛠 Issue (Number)

Issue no #73
👨💻 Changes proposed

✔ Check List (Check all the applicable boxes)

[x] My code follows the code style of this project.
[x] This PR does not contain plagiarized content.
[x] The title of my pull request is a short description of the requested changes.

📄 Note to reviewers

📷 Screenshots

remove the binary file

I am not able to delte bianry file whenever my previous pr dont get merge otherwise there will be branch conflicts, so I am making new pr


Bumped SDK to 0.47.2 and CometBFT to 0.37.1

One good reason to get this in sooner rather than later is the simtest fix for group that intermittently failed: https://github.com/cosmos/cosmos-sdk/issues/15741

Very nice! Thank you!


Cannot read properties of undefined (reading 'pixelRepresentation')

I used  it in  private project,but it occurs a error

And I run demo on local,it occurs the same error.The scheme name of my local file is dicomweb.

The demo on the website is ok

Could you kindly provide the data if it has been anonymized and you can confirm that there is no patient health information present in any of the headers or embedded within the pixel data?


[FR]: Option or css to be able to align not title not the left.

Contact Details
<EMAIL_ADDRESS>Present your request
My notes in obsidian might have have long names, and because those are always aligned to the center, it makes it hard to read them:

I was trying to do it by myself thru a css snippet but was not able to, so maybe someone with more knowledge of css could help here.
I think this would improve readability a lot,  especially when there are many notes with names that might vary in length.
For which platform do you request this request??
Cross

sure! the logic is already done. We need to test it with another cell types

Added with the next version

Commit 1f677a6e


[Dashboard] Replace JS and TS icons

Problem solved
Short description of the bug fixed or feature added

PR-Codex overview
This PR focuses on updating the icon imports for JavaScript and TypeScript across various components in the dashboard. It replaces the usage of icons from react-icons with newly created custom SVG components.
Detailed summary

Replaced SiJavascript with JavaScript icon in ConnectPlaygroundButton.tsx and CodeOptionButton.tsx.
Replaced SiTypescript with TypeScript icon in SupportedPlatformLink.tsx, ConnectSDKCard.tsx, and CodeSegment.tsx.
Added new JavaScriptIcon.tsx and TypeScriptIcon.tsx components with SVG implementations.

✨ Ask PR-Codex anything about this PR by commenting with /codex {your question}

[!WARNING]
This pull request is not mergeable via GitHub because a downstack PR is open. Once all requirements are satisfied, merge this PR as a stack on Graphite.
Learn more

#4812  👈
#4811
#4810
main

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Join @kien-ngo and the rest of your teammates on  Graphite


Update http4s-server to 0.23.0

Updates org.http4s:http4s-server from 0.17.6 to 0.23.0.
GitHub Release Notes - Version Diff
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Applied Migrations

github:http4s/http4s/v0_22?sha=v0.22.0
dependency:v0_21@org.http4s:http4s-scalafix:0.21.5
github:http4s/http4s/v0_20?sha=v0.20.11

Documentation:

https://github.com/http4s/http4s/releases/tag/v0.21.5
https://github.com/http4s/http4s/blob/v0.20.0/docs/src/main/tut/upgrading.md

Files still referring to the old version number
The following files still refer to the old version number (0.17.6).
You might want to review and update them manually.
build.sc

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "org.http4s", artifactId = "http4s-server" } ]

labels: library-update, semver-minor, scalafix-migrations, old-version-remains

Superseded by #2146.


📝 Use Optional in docs

📝 Use Optional in docs.
This includes all the commits of https://github.com/tiangolo/fastapi/pull/1574 , plus some small extra fixes and updates.
Sadly it seems I can't push these updates to that branch, so I have to create this new one. The good thing is that the commits and authors are preserved :rocket:

closes https://github.com/tiangolo/fastapi/issues/1561


Neoforge 1.21.1 Version not functioning properly

When loading into a world it seems to load the mod in fine, the mod menu says it's loaded, but the camera itself can't be crafted or grabbed by JEI. Idk if it's relevant or not but it seems Sinytra Connector tries to interact with it. At least that's what it shows from a crash report I got (due to another separate issue). Which considering I'm using the neoforge version you uploaded I don't know why it would grab it as it's not Fabric, but that's about all I know.

Same with Fabric. Have button in settings, can't get camera in creative or craft or see any other traces of it.

also experiencing this on fabric 0.16.5 1.21.1

fixed now with mod version 1.8.2, but still no entry in JEI or creative mode, or the recipe book

the only way players could ever learn the recipe is by checking the mod page. could i add the recipe myself somehow? to JEI or recipe book?

pls help still impossible for average players to learn the recipe naturally. creating a datapack to award the recipe upon obtaining quartz not working


Document High Throughput Changefeed settings

if you're designing a system that needs to push through a lot of changefeed messages, whether it be steady traffic or a burst in traffic, you should ideally set up your changefeed in a certain way. We should maybe include this in the "advanced operator" section mentioned: #11001.
Resolved: Don't set resolved messages - or set a high resolved message
Batch messages
high memory budget
avro format (JSON encoding can be a bottle neck)
parallelism in scan requests- for backfills (increase)
heuristic is 3x the number of nodes, but we internally cap at 100 - if you set the setting you can change however you want.
Negative: higher CPU usage - for 100 node cluster, each node will issue requests to the same node, 300 requests
Turn on time based iterator cluster setting

Closed by #12100


Move AMP access demo to subdir amp-access-demo/

In preparation for AMP PWA to live in this repository.

@cramforce @dvoytenko

Could you make a new global README.md that just links to a list of demos?

Why the rename? The folder contains samples for:

amp-access
amp-analytics
amp-user-notification

We'd like to introduce a new PWA example. Suggestion for a better name?

How about:

amp-paywall-demo
amp-pwa-demo

How about extended-components-demo?

amp-paywall-demo sounds good to me.

One more change. Keep LICENSE file in top level dir.

LGTM


Exception connecting to the broker

Hello,
thank you for this great projekt.
i get the following error:

Coud you please help me :)
Best regared
Frank

Hello! this issue happens because you need a broker running in background before executing your session.
You can execute in another terminal the Broker project included in the solution or install any other Broker project like a service, in Mac or Linux Mosquitto works very well.
How was the setup in Windows? I didn't tried yet!

I improved our connection logic adding a default 5 tries (also added a better message output). This will be enough to wait until you want execute the broker in the current solution.
https://github.com/netonjm/HapSharp/commit/ec972aa4b14a8376407f037d4d3e984da9e5ec77
The change is available in master.

Thank you!

You could close the request...


discover lambda tags

Summary
If the log group name is in the format "/aws/lambda/<lambda_name>", we can get the lambda tags using aws services.
This is the default format for lambda cloudwatch logs.
Also modifed
faas.name: <lambda_name>
cloud.resource_id :
Added ED_FORWARD_LAMDA_TAGS environment variable.
Testing
Tested on staging us-west-2. Ran "flog-log-generator" lambda, for whose logs our "latif-forwarder-test" lambda is subscribed to.
Then I observed that tags sent successfully to hosted agent with tag "hosted-agent-lambda-forwarder-test".

We can also support getting tags of this lambda function itself.

I will add it in a followup PR.


CNIOSHA1: make the code more portable

Replace the non-portable u_*_t types with the C standard u*_t types
instead.  Remove the Unix headers as the only headers really needed are
the C standard headers.  Provide shims for deprecated strings.h
functions in terms of "modern" (C89+) functions from string.h.  Move
an android only include into the implementation from the interface.
This enables building this library on Windows.
[One line description of your change]
Motivation:
[Explain here the context, and why you're making that change. What is the problem you're trying to solve.]
Modifications:
[Describe the modifications you've done.]
Result:
[After your change, what will change.]

@compnerd agree with Cory here. Your changes however seem scriptable maybe? Couldn’t we apply these changes in the updater script using sed? I’d like to continue being able to update from upstream with the script if at all possible

Would make NIO rely on Crypto and use the SHA1 function from there be pulling in too much?

That's #1377. As noted in that issue, it's a semver major.

That would also require bringing Crypto to Windows first.  I should be able to script it, it just may not be pretty :)

@compnerd this looks really good, unfortunately there are now some warnings:
03:26:40 In file included from /code/Sources/CNIOSHA1/c_nio_sha1.c:45:
03:26:40 /code/Sources/CNIOSHA1/include/CNIOSHA1.h:74:66: warning: type specifier missing, defaults to 'int' [-Wimplicit-int]
03:26:40 extern void c_nio_sha1_loop(struct sha1_ctxt *, const uint8_t *, size_t);
03:26:40                                                                  ^
03:26:40 /code/Sources/CNIOSHA1/c_nio_sha1.c:232:1: error: conflicting types for 'c_nio_sha1_loop'
03:26:40 c_nio_sha1_loop(ctxt, input, len)
03:26:40 ^
03:26:40 /code/Sources/CNIOSHA1/include/CNIOSHA1.h:74:13: note: previous declaration is here
03:26:40 extern void c_nio_sha1_loop(struct sha1_ctxt *, const uint8_t *, size_t);
03:26:40             ^
03:26:40 1 warning and 1 error generated.

It's unclear if the failures are related to this change, but they are appearing on all the versions.

Yeah, this looks like the SHA1 hashing isn't right anymore. We simply get the wrong value out of the hasher. This is pretty wild: the hasher is entirely stable, always generating the same wrong answer, but the answer is definitely wrong.
ASAN and UBSAN don't reveal anything.

Yeah, ok, this seems to be an endianness issue. For some reason Linux is incorrectly determining the endianness of the system as big-endian. Let me dig into why.

@Lukasa - I think that we can just include <sys/types.h> on __linux__ instead of __ANDROID__ and that should fix the endianness.

WFM.

I generalized it even further to __unix__ so that BSDs are correct as well

Bleh, seems that s-p-m is too old to support the language version.  I guess time to make the script uglier.

@Lukasa - okay, addressed the warning, its not pretty, but works

@swift-nio-bot test this please

I'm not sure I understand how this is impacting the syscall wrapping :-(


feat(thanks): add a thank you section

Description
Add a section to highlight who has helped us get here
Motivation
Give back to the orgs and brands that help us
Testing Guidelines
Release Checklist

[ ] This code has unit tests
[ ] I have a plan to verify that these changes are working as expected after deploy
[ ] I have a plan for how to revert, rollback, or disable these changes if things are not working as expected

Security Checklist
This PR creates, modifies, or deletes:

[ ] API routes: API routes, parameters, or user authorization
[ ] Authentication: Authentication mechanism
[ ] Credentials: Server side credentials, or secrets in configuration / source code
[ ] Cryptography: Encryption, hashing, certificates, signatures, random numbers, etc.
[ ] User data: personal information handling, logs, error messages, etc.

Additional Notes

Related to #246


Add Checkstyle formatter

Hi, Rubocop can use a checkstyle output format so that CI systems like Jenkins can pick it up, and I was wondering if there's something similar for this since it's integrated with Rubocop? Checkstyle is similar to JSON, just in XML.
The module that does it is at https://github.com/eitoball/rubocop-checkstyle_formatter but I'm not clear how the integration works.
Thanks,
Sean

Since haml-lint handles its own output, it can't use any custom formatters from RuboCop.
Happy to accept a pull request adding a Checkstyle formatter.

Thanks Shane. I'll see what I can do.

Implemented in #111. Thanks!


Running under runtime-native silently exits when request is made

#![feature(async_await)]

#[runtime::main]
async fn main() -> std::io::Result<()> {
    let mut app = tide::App::new();
    app.at("/").get(async move |_| "Hello, world!");
    app.serve("<IP_ADDRESS>:8000").await?;
    Ok(())
}

using current master of both Tide and Runtime.
Running with cargo run starts the server and then sits waiting for a request, once the first request is made it fails to connect and the server silently exits.
Switching to use runtime_tokio::Tokio it successfully runs and serves requests.
I would expect if Tide using http-server-hyper can't run on runtime_native then it would return an error from serve when it failed.

I have tried running http-service-hyper directly on runtime-native and confirmed it exits with a valid error
Error: Custom { kind: Other, error: Error(User(Execute), "tokio::spawn failed (is a tokio runtime running this future?)") }

checking the code there is a todo about this https://github.com/rustasync/tide/blob/8b667fed05b2cb306d00835188f5a4427431b713/tide-core/src/app.rs#L260-L263

What do you suppose would be a good error message for this? std::io::ErrorKind doesn't quite have anything that fits this particular case... Should serve return a different type of result with the hyper::Error type?


feat(wind-waker): change whole API to functions

Codecov Report

Merging #10 (66ed8af) into main (2c70e16) will decrease coverage by 5.29%.
The diff coverage is 70.75%.

@@            Coverage Diff             @@
##             main      #10      +/-   ##
==========================================
- Coverage   67.98%   62.68%   -5.30%
==========================================
  Files          23       18       -5
  Lines         278      201      -77
  Branches       62       37      -25
==========================================
- Hits          189      126      -63
+ Misses         89       74      -15
- Partials        0        1       +1

Impacted Files
Coverage Δ

src/pipes/logger.ts
0.00% <0.00%> (ø)

src/pipes/code.ts
50.00% <50.00%> (ø)

src/utils/parseUrl.ts
55.55% <55.55%> (ø)

src/pipes/pipe.ts
66.66% <66.66%> (+16.66%)
:arrow_up:

src/pipes/input.ts
68.75% <68.75%> (ø)

src/server/server.ts
78.57% <71.87%> (-2.39%)
:arrow_down:

src/server/request-handler.ts
90.32% <88.88%> (+9.24%)
:arrow_up:

src/actions/actions.ts
100.00% <100.00%> (+66.66%)
:arrow_up:

src/actions/index.ts
100.00% <100.00%> (ø)

src/exception/exception-handler.ts
20.00% <100.00%> (ø)

... and 10 more

Continue to review full report at Codecov.

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client.Conn.Execute(cmd) blocks sometimes

When I run conn.Execute(fmt.Sprintf("show BINLOG events in '%s' from %d limit 1", filename, pos)) with a wrong pos that it is not the start of an event, this method call blocks.
Why it blocks and does not return me an error? And how I can work around it? Thanks.

You can check the goroutine profile to know where it blocks.
follow https://pkg.go.dev/net/http/pprof
then access http://localhost:6060/debug/pprof/goroutine?debug=2

Actually I printed some logs and I think it blocks in ReadPacket(), but is it normal to block there just because an incorrect statement?

Of course not, please help fix it :smile:

Thanks, I'll try in the future. But currently do we have any way to work around it? I mean maybe set a timeout context and cancel the execution when the deadline approaches? How can we cancel it?

currently I have no time to reproduce it so I don't know the walkaround

Ok so I find out that one walkaround is to SetReadDeadline before execute the command.


I created variable c, this should be good to go.