Siblings

Is it possible, given an empty , to render into it the following:

...some sidebar content
...the main application
These are 3 siblings not a single hierarchy. Have not seen how this can be achieved in inferno, which only seems to render a single hierarchy. Wrapping the siblings inside the div is not an option as they must be parented to

Hi @minimok can you give some example code? It sounds like you want to render multiple adjacent children?

yep...sorry...the editor swallowed it..markup problem...
"" should contain..
""
""
""

Yes that's the idea. Cannot get the markdown into this editor.
but basically a body elem containing 3 divs

The sidebar and the main view of course have their own elements inside. The overlay just gets its class set to visible/hidden.
So yep...just 3 siblings all parented to body

Well in terms of context, you need to make sure an array of child nodes has a single parent node. So for example:
InfernoDOM.render((

), document.body);```

Aha, yes. This is my problem. That 'wrapper' div breaks the css for the app, which is 200k minified!

Ok, will close. But thanks for confirming. Excellent job by the way. We have it working, driven off a 'mobx' instance and performance is excellent.

@minimok could you simply change how your CSS works to get around this? Mounting multiple "root" nodes is difficult to manage in a performant way, I mean it's definitely possible to change Inferno to support this (0.8 will have better support) but it means a more complex/slower handling of large lists of nodes. Ah, MobX is great, I'm glad you've had great results with Inferno :)

Yep...will do. Changing the CSS was 'Plan B'. Thought I'd see first  if I'd missed any obvious way of rendering 3 elems without declaratively 'parenting' them...Enjoy the weekend!

Thanks, you too :)


la-go-live

Docs Build status updates of commit 35770fd:
:white_check_mark: Validation status: passed

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For more details, please refer to the build report.
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For any questions, please:Try searching in the Docs contributor and Admin GuideSee the frequently asked questionsPost your question in the Docs support channel


Fix logging to use new format

Tested in triple trouble with trace level logging on, no FormatExceptions in the debugger.
┆Issue is synchronized with this Asana task

Added the changes 👍


Add .vscode folder for recommended extensions and settings

What kind of changes does this PR include?

Changes to the docs site code

Description

Removes .vscode from .gitignore
Adds Astro and ESLint as recommended extensions
Adds Astro to eslint.validate

You probably want to commit the files and then re-add .vscode to .gitignore, or you'll get PRs with random settings at times (some extensions add stuff there, some users add settings sometimes etc)

@Princesseuh thanks!


add skip provider registration

Fix to resolve issue #622

This looks great to me Richard. This will help me run individual validations against my employer's subscriptions where I don't have the owner rights to any of the subscriptions I would use and have ran into this many times trying to use Terraform to provision against Azure.

@tsalright and @yorinasub17, I made a change to have this as an input with a default value of false.  This should elminate need to create a commit on user fork but still achieve desired behavior.  This is needed to support a user/service principal that has contributor access to subscription but not owner.  Terraform by default wants to register resource providers in Azure before it starts provisioning resources.  Contributors do not have permissions to register resource providers but do have permissions to provision resources which is common scenario.

@tsalright, can you run test with this input fix and confirm it is working for you as expected?

@rguthriemsft, I will run it and get back to you shortly. I like the use of the variable to pass in on execution. Removes the need for me to do an extra commits to test the pipeline in my fork.

@rguthriemsft that change worked for me. https://github.com/tsalright/terratest/runs/1113774135

@yorinasub17, there is still the scenario where someone wanting to contribute to terratest, forks main repo, makes their change and then runs the full CI to ensure they didn't break any other code in terratest.  They may only be a contributor to the subscription they have access to do the validation in.  We had envisioned that with this CI job, a terratest contributor could run it against their subscription for their PR and expose the results as part of their PR.  as long as the CI shows it ran against same commit at head of their PR that should be valid assuming all the test passed.  Hope that makes sense?

Thanks for the explanation, but I think I am just struggling with the why. In any case, that point doesn't really matter for merging this in so will go ahead to merge this in.
If you want to know my thought process...
I am struggling to see what is the advantage of doing that from their fork in Github Actions in their subscription, as opposed to running it locally or waiting for the integration with the Microsoft fork. E.g., if we are going to run the full test anyway on the Microsoft fork, why would contributors want to setup their fork to run the github action?
If they want to test before they commit and push I am more inclined to recommend and support running it locally, outside of CI. This workflow actually gives a lot of benefits including:

Being able to use TestStages.
Being able to rerun destroy if the test fails with a panic or some other catastrophic way and you need to clean up the resources.
Being able to run a subset of tests using -run.

I guess this comes from our experience with AWS and GCP contributions, where in almost all cases contributors would run a subset of the tests from their local machine against their sandbox account for verification testing, and rely on our build process in our account for the full test build.


sandiegodata.org.crime-201303.yaml import error: NotObjectNumberError: Unknown type character 'a' for '2pN5m'

run:
python load_pre10.py ../../pre-10-bundles/converted/sandiegodata.org.crime-201303/sandiegodata.org.crime-201303.yaml

error:
Starting import ../../pre-10-bundles/converted/sandiegodata.org.crime-201303/sandiegodata.org.crime-201303.yaml...
Traceback (most recent call last):
  File "load_pre10.py", line 251, in <module>
    main()
  File "load_pre10.py", line 219, in main
    b = _import(args[0])
  File "load_pre10.py", line 129, in _import
    b = library.new_from_bundle_config(config)
  File "/home/nmb10/projects/ambry_project/ambry/library/__init__.py", line 202, in new_from_bundle_config
    identity = Identity.from_dict(config['identity'])
  File "/home/nmb10/projects/ambry_project/ambry/identity.py", line 1282, in from_dict
    ono = ObjectNumber.parse(d['id'])
  File "/home/nmb10/projects/ambry_project/ambry/identity.py", line 757, in parse
    raise NotObjectNumberError("Unknown type character '{}' for '{}'".format(type_, on_str))
ambry.identity.NotObjectNumberError: Unknown type character 'a' for '2pN5m'

Moved to CivicKnowledge/pre-10-bundles#8


Make terraform scripts work on MacOS (i.e. darwin_arm64)

The /hashicorp/template provider is not compatible with the darwin_arm64 platform.
╷
│ Error: Incompatible provider version
│
│ Provider registry.terraform.io/hashicorp/template v2.2.0 does not have a package available for your current platform, darwin_arm64.
│
│ Provider releases are separate from Terraform CLI releases, so not all providers are available for all platforms. Other versions of this provider may have different platforms supported.
╵

The template_file data source could be swapped with a templatefile function call to resolve this.

This might also help: https://sharepointdevelopmentblog.wordpress.com/2023/02/07/terraform-template-v2-2-0-does-not-have-a-package-available-mac-m1/


fix fix get String index out of range exception

Proposed changes
Issue Number: close #xxx
Problem summary
will get String index out of range exception when use error datetime values like '2020-02-01'
before:
MySQL [test]> select test121.k1 from test121 where k1 != ('9102-12-');
ERROR 1105 (HY000): errCode = 2, detailMessage = Unexpected exception: String index out of range: 8
after:
MySQL [test]> select test121.k1 from test121 where k1 = '9102-12-';
ERROR 1105 (HY000): errCode = 2, detailMessage = Incorrect datetime value: '9102-12-' in expression: k1 = '9102-12-'
Checklist(Required)

[ ] Does it affect the original behavior
[ ] Has unit tests been added
[ ] Has document been added or modified
[ ] Does it need to update dependencies
[ ] Is this PR support rollback (If NO, please explain WHY)

Further comments
If this is a relatively large or complex change, kick off the discussion at<EMAIL_ADDRESS>by explaining why you chose the solution you did and what alternatives you considered, etc...

run buildall

run clickbench

run p0

run p0

run p0


[APPEXT-563] Add the untyped model api docs

@pavel-constantinov - is this for release now, or is it a new feature in 10.15?

As far as I know it is planned to be released as soon as possible because it got delayed by quite a while.

@MarkvanMents This is a new feature that will be released in 10.15 (provided we make the freeze in two weeks 😉).

@pavel-constantinov I edited the files. Could you please review the changes when you have time?

@pavel-constantinov I edited the files. Could you please review the changes when you have time?

I also posted some changes just now, please take a look, I hope you'd agree that I improved the wording. If you have any other ideas, I'd be happy to see them!

Rebased to get rid of the conflict blocking the merge.


Correct highlighting of ng-repeat-start and ng-repeat-end attributes

First, thanks for keeping up this package!
I spotted a minor bug when using ng-repeat-start and ng-repeat-end attributes. They are higlighted as ng-repeat.

Fix with corresponding test attached.

@vlki Good point!! Thank you.


Add very brief examples for disambiguation

Type of issue
Missing information
Description
This page is the F1 target for the ref keyword. The ref keyword can be used in many contexts. This page provides links to each of those contexts.
It would help readers to have a very brief example of each in order to know which link is correct for their current usage.
Page URL
https://learn.microsoft.com/en-us/dotnet/csharp/language-reference/keywords/ref
Content source URL
https://github.com/dotnet/docs/blob/main/docs/csharp/language-reference/keywords/ref.md
Document Version Independent Id
4f413bcc-90e7-d971-fe75-b4876124e75d
Article author
@BillWagner
Metadata

ID: 3d67349b-72bc-b7cf-f754-fa62d1fb592d
Service: dotnet-csharp
Sub-service: lang-reference

Hi @BillWagner
Wouldn't it be possible to just reference the examples in the links? Since those are the accepted examples?
Or new examples should be created?

@bigboybamo
It's fine to use the same examples as the linked articles. However, I want to see them displayed in this page. A reader should be able to pick the right page without guessing and clicking to all of the linked pages.
Thanks for asking.

Hi @BillWagner
I opened a PR #42178


YARN-11148. In federation and security mode, nm recover may fail.

Description of PR
https://issues.apache.org/jira/browse/YARN-11148
How was this patch tested?
manual test in our cluster.
For code changes:
support security

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@zhengchenyu Thanks for your contribution. It makes sense at first glance. How about to add unit test to cover this case?

I think we should apply https://issues.apache.org/jira/browse/YARN-6539 firstly, then I will add UT. Because If yarn router does not support security mode, this PR is meaningless. (Notes: in our cluster, YARN-6539 is apply).
I don't know why YARN-6539 are not merge int trunk?

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@zhengchenyu Thanks for your contribution. It makes sense at first glance. How about to add unit test to cover this case?

@Hexiaoqiao Can you please review this PR? I have add the unit test. In the unit test, I setup a rpcserver to simulate the security mode. This bug is easy to reproduce in this unit test.

@goiri Can you please review this PR?

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/buildtool-patch-checkstyle-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-nodemanager.txt
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-1 :x:
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/patch-spotbugs-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-nodemanager.txt
hadoop-yarn-server-nodemanager in the patch failed.

-1 :x:
shadedclient
4m  8s

patch has errors when building and testing our client artifacts.

_ Other Tests _

-1 :x:
unit
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/patch-unit-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-nodemanager.txt
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76m 36s

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ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-4308/3/artifact/out/Dockerfile

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Build tool
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Personality
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git revision
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Default Java
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Multi-JDK versions
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the patch passed

+1 :green_heart:
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checkstyle
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/results-checkstyle-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-nodemanager.txt
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager: The patch generated 1 new + 0 unchanged - 0 fixed = 1 total (was 0)

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+1 :green_heart:
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ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-4308/5/artifact/out/Dockerfile

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git revision
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+1 :green_heart:
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the patch passed with JDK Private Build-11.0.15+10-Ubuntu-0ubuntu<IP_ADDRESS>

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0m 30s
/results-checkstyle-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-nodemanager.txt
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager: The patch generated 1 new + 0 unchanged - 0 fixed = 1 total (was 0)

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the patch passed with JDK Private Build-11.0.15+10-Ubuntu-0ubuntu<IP_ADDRESS>

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+1 :green_heart:
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+1 :green_heart:
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ClientAPI=1.41 ServerAPI=1.41 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-4308/4/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/4308

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient codespell detsecrets xmllint spotbugs checkstyle

uname
Linux 8fbae87c6ad8 4.15.0-175-generic #184-Ubuntu SMP Thu Mar 24 17:48:36 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux

Build tool
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Personality
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git revision
trunk / 64be3968af021fe350bdd3d6b3cadc89fd36b550

Default Java
Private Build-1.8.0_312-8u312-b07-0ubuntu1~20.04-b07

Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Private Build-11.0.15+10-Ubuntu-0ubuntu<IP_ADDRESS> /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_312-8u312-b07-0ubuntu1~20.04-b07

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@goiri Can you help me review this PR? this is an obvious error! And this patch have been applied on our cluster for long time.

@goiri How about merge to trunk?

@Hexiaoqiao  can you take a final look?


chore: update curl

Pull Request Test Coverage Report for Build 415944706

0 of 0   changed or added relevant lines in 0 files are covered.
5 unchanged lines in 2 files lost coverage.
Overall coverage remained the same at 58.192%

Files with Coverage Reduction
New Missed Lines
%

internal/agent/event_sender.go
1
72.56%

pkg/integrations/v4/logs/cfg_watcher.go
4
67.5%

Totals

Change from base Build 415929449:
0.0%

Covered Lines:
11401

Relevant Lines:
19592

💛  - Coveralls


Add files via upload

Add Cape Cod Tech High School

@MarcCodes456 techstudents.txt I am sorry, I have to close the request without merging, because you made a mistake in a request and did not specify any filepath. Please ensure that you are familiar with this repository rules located at the bottom of this page and make a new correct request. Thank you for your understanding!


FormArray sortable example incorrect

I'm submitting a ...
[x] bug report
[ ] feature request
[ ] question about the decisions made in the repository

Do you want to request a feature or report a bug?
Documentation error

What is the current behavior?
https://github.com/akserg/ng2-dnd#14-simple-formarray-sortable-with-drag-and-drop
The existing example shows [sortableData]="listOne"

What is the expected behavior?
It should be [sortableData]="listOne.controls"

This is not a bug, example is correct. Controls manipulations should be performed on FormArray object, not on array of AbstractControl in .controls, as stated in documentation.

I made a plunker to verify and it looks like I was mistaken. Not sure what was happening in my other project but actually both seem to work.

Yes, both seem to work, as .controls is an array. It's just it's not working correctly, as FormArray internals do not get updated when reordering .controls directly.


Nothing happens

Hi there
I finale understand the issue with code errors so there should not be an interruptions in video/frames where there is no fase on the screen, so the face should always be on the screen to make it works.
So it works but did nothing.
I choose the video, cut out the audio and then insers that video and the same cut audio as an audio.
program perform the task for several hours and as a result now I have the same video with audio. No any animations no effects there were nothing. looks like and output of video converter where I just merge video and audio.
May me I did somethig wrong. I choose revanimated checkpoint and the rest as it was shown in 'code' page.

Hi,
Contact me on discord NumZ#7184, i'll try to help you

@Zakabaka Try setting the "resize factor" to 4. If it works, it indicates that your graphics card is working hard to get the task done. If 4 works, then try 3, followed by 2...
let me know

Hi,
I'm closing this issue, certainly come from video resolution too high or video too long for gpu rtx2060


RocksDB: Fix bloom filter incompatible issue

What is changed and how it works?

Issue Number: Close #17272

What's Changed:
TiKV no longer names bloom filter blocks with suffix like "FullBloom" or "Ribbon".

Related changes

[ ] PR to update pingcap/docs/pingcap/docs-cn:
[x] Need to cherry-pick to the release branch

Check List
Tests

[ ] Unit test
[ ] Integration test
[ ] Manual test (add detailed scripts or steps below)
[x] No code

Side effects

[ ] Performance regression: Consumes more CPU
[ ] Performance regression: Consumes more Memory
[ ] Breaking backward compatibility

Release note

1. TiKV no longer names bloom filter blocks with suffix like "FullBloom" or "Ribbon".
2. Use prefix match instead of exact match to determine whether a bloom filter created before can be used (compatible with the new version) to solve the "bloom filters were incorrectly invalidated after upgrade" issue, after all, TiKV only uses RocksDB native bloom filters, i.e. FullBloom, Ribbon, and according to RocksDB's doc, they can be used interchangeably.

@overvenus Can you please take a look at the pull-unit-test failure, seems related to vendored openssl. I upgrade openssl, because cargo build failed complaining about a vulnerability found in the previous version.


Don't block the event loop

some operations like processing 10 thousands of items in objectlist (in a loop) and sending all these items over grpc protocol can take considerable amount of time. To avoid blocking vertex event loop run these costly operations on the worker pool (using the executeBlocking() method)

By fixing the memory leak this is not an issue any more, can be closed.


Add Desktop Type wrappers

Summary: This diff implements a centralized location for desktop components properties and a wrapper over 4 React Core Components for flow typing.
Differential Revision: D55710355

Closed internally


paperless-ngx 1.7.0

Checklist

[x] Checked the nixpkgs master branch

[x] Checked the nixpkgs pull requests

Project name
nix search name: paperless-ngx

current version: 1.6.0
desired version: 1.7.0
Notify maintainers

maintainers: @lukegb @erikarvstedt
Note for maintainers
Please tag this issue in your PR.

Release here : https://github.com/paperless-ngx/paperless-ngx/releases/tag/ngx-1.7.0

Fixed in https://github.com/NixOS/nixpkgs/pull/170781  (currently a draft).

The PR was merged so this can be closed.


Logging Enhancement for Preemption

Logging Enhancement for Preemption Logs
Newly Added fields in the Preemption Logs

applicationID of ask => "askApplicationID"
allocationKey of ask => "askAllocationKey"
queue of ask => "askQueue"
queue of victim => "victimQueue"

Also, rename a few of the existing output items:

"applicationID" => "victimApplicationID"
"allocationKey" => "victimAllocationKey"
"nodeID" -> victimNodeID
"resources" -> victimAllocatedResource

What type of PR is it?

[ ] - Bug Fix
[x] - Improvement
[ ] - Feature
[ ] - Documentation
[ ] - Hot Fix
[ ] - Refactoring

What is the Jira issue?
https://issues.apache.org/jira/browse/YUNIKORN-2052

@wilfred-s Do you have anymore comments?


MessageSource config

Summary
MessageSource config
Description
#18
Checklist

[x] 1. Build successfully on local
[x] 2. Format all code files included in the PR
[x] 3. No more unconfirmed specs in the PR
[x] 4. Tested the normal case and error cases following specs
[ ] 5. Is there a refactor to the old code? If yes, have you tested the old function and noted the impact yet?
[ ] 6. Loops have a set length and correct termination conditions
[ ] 7. There aren't any redundant or duplicate codes in PR (clean code)
[ ] 8. There aren't any hard-coded in the code in PR
[ ] 9. Optimization logic handling and optimizations SQL (for example, don't get redundant data or add an index to optimize performance, query only necessary fields...)
[ ] 10. Set pull-request title by format: Feature new #{id}: {short des}, Bug fix #{id}: {short des}
[x] 11. Update issue

Evidence
(Screenshot or Video)
Discussion
Note the part that you are not sure. Comment on your code is OK.

Merge trước ae xem lại sau nhé!


Unit tests for enableFeaturesFromFlags function

note: we don't test for persistence of the feature flags (since from discussions that maybe subject to change in future).

@zees-dev I've added a test that shows how I think the current implementation would be used in go code (and it highlights something we should improve when we can).
I've also added a test for persistence - imo its better to use the tests to explore the current implementation, so that if and when we change that, its highlighted in the tests too


[WIP][SPARK-15208][Core][Streaming][Docs] Update Spark examples with AccumulatorV2

What changes were proposed in this pull request?
The patch updates the codes & docs in the example module as well as the related doc module:

[ ] [docs] streaming-programming-guide.md

[x] scala code part
[ ] java code part
[ ] python code part

[x] [examples] RecoverableNetworkWordCount.scala
[ ] [examples] JavaRecoverableNetworkWordCount.java
[ ] [examples] recoverable_network_wordcount.py

How was this patch tested?
Ran the examples and verified results manually.

Once the AccumulatorV2 Java API is finalized, I would update the Java & Python part. Thanks

Test build #58087 has started for PR 12981 at commit 2d51982.

Test build #58087 has finished for PR 12981 at commit 2d51982.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/58087/
Test PASSed.

Do you want to bring this up to date?

@rxin sure, I'll resolve the conflicts very soon; and once the Java APIs are updated in the next couple of days, I'll update the Java examples accordingly.
Thank you for bringing this up!

Test build #59735 has started for PR 12981 at commit 1d4d897.

Test build #59735 has finished for PR 12981 at commit 1d4d897.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
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Test PASSed.

This looks good. Are there other accumulator examples that need an update?

@srowen, there are no other examples that need an update :-)

Merged to master/2.0


Azure Instances configuration details need updating

The instance configuration details of Azure instances is out of date.  There are some definitions in Cloudbreak that have less CPU and Memory than the instance type now has.

I close this one, please feel free to reopen if you have any issue with the fix.


Authentication docs could do with a note around .NET 8 changes

Docs Update Suggestion
The section in the authentication docs that deals with overriding the mapping of the scp claim no longer applies in .net 8.

Ocelot Authentication | Auth0 by Okta

The JwtSecurityTokenHandler is no longer the default, and has been replaced by JsonWebTokenHandler
The example in the docs will work in .net 8 by simply replacing the reference to the JwtSecurityTokenHandler.
i.e.
JsonWebTokenHandler.DefaultInboundClaimTypeMap.Remove("scp");
JsonWebTokenHandler.DefaultInboundClaimTypeMap.Add("scp", "scope");

It is perhaps also worth mentioning in the docs that this does not solely apply to using Okta (in my case it also applies to Azure AD)
References:

https://github.com/dotnet/AspNetCore.Docs/issues/30935
https://learn.microsoft.com/en-us/aspnet/core/security/authentication/claims?view=aspnetcore-8.0#claims-namespaces-default-namespaces
https://github.com/aspnet/Announcements/issues/508

Motivation for New Feature

Avoid confusion for anyone attempting to configure Ocelot authentication on .NET 8.
Without this change, scopes do not work.

Steps to Reproduce the Problem
n/a
Specifications
n/a

Hi Bryan!
Welcome to Ocelot world! 🐯
Thanks for reporting this issue and letting us know about these changes in claims mapping!
Will you contribute to update the docs?
Ideally, this issue ticket can be closed by a PR with acceptance tests or develop a sample to merge.
Writing acceptance tests is not easy.
Create a sample is a bit easier.
But I believe simple updating of our docs will be fine too.
Do you have an intention to work on this issue being created by you?

@devsbryan  Could you help us to upgrade docs plz?

@ramam-m Can I do it?
I would first update the docs, then develop a sample as you suggested earlier

@jvanderlei  Welcome! You are assigned!

Please be aware that we have a strict deadline to complete the .NET 9 milestone tasks. How soon can you open a pull request?

I'll send the PR for the documentation today, I'm now just reading the details on the breaking changes.

Motivation for New Feature

Avoid confusion for anyone attempting to configure Ocelot authentication on .NET 8.
Without this change, scopes do not work.

@jvanderlei Please note that the issue has been marked with a  label. Therefore it would be advisable to write actual unit & acceptance tests to demonstrate the issue. Please include them in the current open PR.
However I have a concern: does Okta Auth provide a sandbox environment for testing and development purposes? How do you utilize Okta?

@raman-m All right. I'm not the most versed dev on acceptance testing, but I'll try my best to deliver it until tomorrow.
And yes, Okta Auth0 provides a development enviroment when you register a new app on them. I'm developing a personal project as a angular SPA and .Net backend

@jvanderlei wrote:

Please don't rush! Please relax this weekend. You may return to writing tests on Monday.
FYI, we have a dedicated project for tests: Ocelot.AcceptanceTests. Specifically, the tests should be placed in: AuthenticationTests. However, you may create a OktaAuthenticationTests class.

And yes, Okta Auth0 provides a development environment when you register a new app on them. I'm developing a personal project as a angular SPA and .Net backend

Very well. Could you help us register an Ocelot native account for testing from both local and CircleCI environments? We need your instructions on that...

Perfect. And yes, I can. I'll look some more about the registering for CI pipeline, and return to you about this process.

@jvanderlei Any news?


Allow decoration of NewService registration

We've found a few scenarios where we've wanted to easily add tags and programmatically set some of the values (extremely useful in a Kubernetes environment) and found ourselves having to override ConsulLifecycle to get it done.
It'd be nice if we could decorate / instrument the service definition before it's registered with Consul. Would that be something welcome in the actual library? Perhaps something like the following:
public class DecoratingConsulLifecycle extends ConsulLifecycle {

    private final Collection<Decorator> decorators;

    public DecoratingConsulLifecycle(ConsulClient client, ConsulDiscoveryProperties properties,
                                     HeartbeatProperties ttlConfig, Collection<Decorator> decorators) {
        super(client, properties, ttlConfig);
        this.decorators = decorators;
    }

    @Override
    protected void register(NewService newService) {
        for(Decorator d : decorators ){
            d.decorate(newService);
        }
        super.register(newService);
    }

    @FunctionalInterface
    public interface Decorator {
        void decorate(NewService service);
    }
}

If so, happy to submit a PR.

Won't be able to use @FunctionalInterface since we're still java 7. We'll discuss it.

Old school... ;) I can live with that. Thanks

@dwelch2344 next year when we have a release based on spring 5 & boot 2 the baseline moves to java 8. It will be our E release after Camden and Dalston.

@spencergibb , this ConsulRegistration class will allow us to add tags to the service that are not coming from the yml?

@ezraroi you can create your own ConsulRegistration instance with whatever tags you wish.

thanks

Agreed @spencergibb. Like the new changes to the API. Great work!


Add a function that allows you to get the "source" or "destination" operand

Is your feature request related to a problem? Please describe.
I am trying to write a Ghidra script where this function would be very useful to have, and as far as I have seen there isn't a function that will do this. Currently I am just using getOpObjects() assuming for 2-operand instructions that the first operand is the source and the second is the destination (this is for M68000), but it would be nice to have a more robust function that could handle possible edge cases that I am not aware of. Additionally, there is a separate issue for M68000 where some 2-operand instructions are being interpreted as having 4 operands, which means my current workaround breaks in that case.
Describe the solution you'd like
Two functions that would allow you to get the "source" and "destination" operand objects. I'm not sure how this would work with instructions that use 1 (maybe both return the same thing) or >2 operands.
Describe alternatives you've considered
As mentioned above, I'm just assuming that for 2-operand instructions in M68000, that left is source and right is destination, but I'm sure there are cases where this won't work and I will run into issues.
Additional context
N/A

I believe you are looking for getInputObjects and getResultObjects

lol, completely missed those functions. Thank you!


Oops: Ticket value wasn't found in response

Hi, I having this problem when I write a invalid passoword gives

Oops: Ticket value wasn't found in response - looks like the authentication failed.please refresh page!

Then when I write a valid password still gives the same error!
-Best

With this particular issue, you will need to remove the cookie storage from disk, and re-authenticate.


Compile Time and 5x Latency Regression on CUDA

What happened?
Compilation of some T5 models is taking >5 hours for batches 64 and 512. This is a recent regression as earlier this week we were able to compile all T5 models in under 15 mins (see this CI run: https://github.com/openxla/iree/actions/runs/4738436860/jobs/8412407639).
Steps to reproduce your issue

Download SavedModel: https://storage.googleapis.com/iree-model-artifacts/tensorflow/tf_models_2.12.0_1681193933/T5_LARGE/batch_512/tf-model.tar.gz

Import:

iree-import-tf --output-format=mlir-bytecode --tf-import-type=savedmodel_v2 --tf-savedmodel-exported-names=forward <saved_model> -o </path/to/model.mlirbc>

Compile:

iree-compile --iree-hal-target-backends=cuda --iree-input-type=mhlo --iree-hal-cuda-llvm-target-arch=sm_80 </path/to/model.mlirbc> -o </path/to/model.vmfb>
What component(s) does this issue relate to?
Compiler
Version information
Rebased from 8a1182c
Additional context
This is blocking our ability to track performance progress on large models.

Please include profile before and after. And it would be useful to summarize differences too.

Here's some IR for one of the slow-to-compile executables: https://gist.github.com/ScottTodd/fc30c728a1d1774b799830600d21e3f1 (~9000 ops of vector.transfer_read -> elementwise -> vector.transfer_write, 1000s to gpu.subgroup_mma_load_matrix, gpu.subgroup_mma_compute, gpu.subgroup_mma_elementwise, gpu.subgroup_mma_store_matrix)
My gist isn't even uploading for the really slow-to-compile executable...
Input IR:
// -----// IR Dump Before mlir::iree_compiler::IREE::HAL::TranslateExecutablesPass (iree-hal-translate-executables) //----- //
hal.executable private @forward_dispatch_18 {
  hal.executable.variant public @cuda_nvptx_fb, target = <"cuda", "cuda-nvptx-fb", {target_arch = "sm_80"}> {
    hal.executable.export public @forward_dispatch_18_generic_512x16x512x512x64_f32 ordinal(0) layout(#hal.pipeline.layout<push_constants = 1, sets = [<0, bindings = [<0, storage_buffer, ReadOnly>, <1, storage_buffer>]>]>) {
    ^bb0(%arg0: !hal.device, %arg1: index, %arg2: index, %arg3: index, %arg4: index):
      %x, %y, %z = flow.dispatch.workgroup_count_from_dag_root %arg1, %arg2, %arg3, %arg4
      hal.return %x, %y, %z : index, index, index
    }
    builtin.module {
      func.func @forward_dispatch_18_generic_512x16x512x512x64_f32() {
        %cst = arith.constant 9.99999971E-10 : f32
        %cst_0 = arith.constant 0.000000e+00 : f32
        %c2147483648 = arith.constant<PHONE_NUMBER> : index
        %c2164260864 = arith.constant<PHONE_NUMBER> : index
        %c3238002688 = arith.constant<PHONE_NUMBER> : index
        %0 = hal.interface.constant.load[0] : i32
        %1 = arith.index_castui %0 {stream.alignment = 16777216 : index, stream.values = [4311744512 : index,<PHONE_NUMBER> : index]} : i32 to index
        %2 = hal.interface.binding.subspan set(0) binding(0) type(storage_buffer) alignment(64) offset(%c3238002688) flags(ReadOnly) : !flow.dispatch.tensor<readonly:tensor<512x512x16x64xf32>>
        %3 = hal.interface.binding.subspan set(0) binding(0) type(storage_buffer) alignment(64) offset(%c2164260864) flags(ReadOnly) : !flow.dispatch.tensor<readonly:tensor<512x512x16x64xf32>>
        %4 = hal.interface.binding.subspan set(0) binding(0) type(storage_buffer) alignment(64) offset(%c2147483648) flags(ReadOnly) : !flow.dispatch.tensor<readonly:tensor<512x512x16xf32>>
        %5 = hal.interface.binding.subspan set(0) binding(1) type(storage_buffer) alignment(64) offset(%1) : !flow.dispatch.tensor<writeonly:tensor<512x16x512x512xf32>>
        %6 = flow.dispatch.tensor.load %2, offsets = [0, 0, 0, 0], sizes = [512, 512, 16, 64], strides = [1, 1, 1, 1] : !flow.dispatch.tensor<readonly:tensor<512x512x16x64xf32>> -> tensor<512x512x16x64xf32>
        %7 = flow.dispatch.tensor.load %3, offsets = [0, 0, 0, 0], sizes = [512, 512, 16, 64], strides = [1, 1, 1, 1] : !flow.dispatch.tensor<readonly:tensor<512x512x16x64xf32>> -> tensor<512x512x16x64xf32>
        %8 = flow.dispatch.tensor.load %4, offsets = [0, 0, 0], sizes = [512, 512, 16], strides = [1, 1, 1] : !flow.dispatch.tensor<readonly:tensor<512x512x16xf32>> -> tensor<512x512x16xf32>
        %9 = tensor.empty() : tensor<512x16x512x512xf32>
        %10 = linalg.fill ins(%cst_0 : f32) outs(%9 : tensor<512x16x512x512xf32>) -> tensor<512x16x512x512xf32>
        %11 = linalg.generic {indexing_maps = [affine_map<(d0, d1, d2, d3, d4) -> (d0, d2, d1, d4)>, affine_map<(d0, d1, d2, d3, d4) -> (d0, d3, d1, d4)>, affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3)>], iterator_types = ["parallel", "parallel", "parallel", "parallel", "reduction"]} ins(%6, %7 : tensor<512x512x16x64xf32>, tensor<512x512x16x64xf32>) outs(%10 : tensor<512x16x512x512xf32>) {
        ^bb0(%in: f32, %in_1: f32, %out: f32):
          %13 = arith.mulf %in, %in_1 : f32
          %14 = arith.addf %out, %13 : f32
          linalg.yield %14 : f32
        } -> tensor<512x16x512x512xf32>
        %12 = linalg.generic {indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>, affine_map<(d0, d1, d2, d3) -> (d2, d3, d1)>, affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%11, %8 : tensor<512x16x512x512xf32>, tensor<512x512x16xf32>) outs(%9 : tensor<512x16x512x512xf32>) {
        ^bb0(%in: f32, %in_1: f32, %out: f32):
          %13 = arith.addf %in, %in_1 : f32
          %14 = arith.addf %13, %cst : f32
          linalg.yield %14 : f32
        } -> tensor<512x16x512x512xf32>
        flow.dispatch.tensor.store %12, %5, offsets = [0, 0, 0, 0], sizes = [512, 16, 512, 512], strides = [1, 1, 1, 1] : tensor<512x16x512x512xf32> -> !flow.dispatch.tensor<writeonly:tensor<512x16x512x512xf32>>
        return
      }
    }
  }
}

Similar pattern of vector ops -> gpu ops, but with 98000 ops (yes, ninety-eight thousand ops) between LLVMGPUVectorToGPU and SCFToControlFlow
Pretty slow executable / input -> hal phase:

Slowest executable, zoomed out:

Only 15 unique hal.executables, so deduping is working well enough. Seems like vectorization / tiling is just generating a lot of code for a few of the executables.

Still collecting a trace (50GB of memory used so far...), sampling is pointing to one thread, deep in LLVM instruction code, right after CombineInitializers (so in SerializeExecutables -> LLVMIR/ModuleTranslation):

My machine has spent 30 minutes on that one thread, likely serializing that one huge executable

What's the leaf there? isBlockIn...?
If we're emitting 20 million instructions in a single function it'd likely lead to things like that during LLVM codegen

thought: serialize executables pass could append an int64 trace zone value of the number of ops within the executable - would at least give us a signal as to how much work we're sending down to llvm

isBlockInLCSSAForm
llvm::ScalarEvolution::visitAndClearUsers

yeah that's probably too much IR in a loop body hitting a pathologically slow path in there - may need a "0 days since last lack of vectorization making things sad" sign :P

Here's are some snippets from the middle of the slowest executable to compile:
    %452729 = vector.fma %452728, %452630, %452681 : vector<16xf32>
    %452730 = vector.extract %108464[1] : vector<8xf32>
    %452731 = vector.splat %452730 : vector<16xf32>
    %452732 = vector.fma %452731, %452630, %452684 : vector<16xf32>
    %452733 = vector.extract %108465[1] : vector<8xf32>
    %452734 = vector.splat %452733 : vector<16xf32>
    %452735 = vector.fma %452734, %452630, %452687 : vector<16xf32>
    %452736 = vector.extract %108466[1] : vector<8xf32>
    %452737 = vector.splat %452736 : vector<16xf32>
    %452738 = vector.fma %452737, %452630, %452690 : vector<16xf32>
    %452739 = vector.extract %108451[2] : vector<8xf32>
    %452740 = vector.splat %452739 : vector<16xf32>
    %452741 = vector.fma %452740, %452632, %452693 : vector<16xf32>

  %62058 = vector.insert %62057, %62051 [6] : vector<16xf32> into vector<16x16xf32>
  %c57344_32872 = arith.constant 57344 : index
  %62059 = arith.addi %c57344_32872, %22 : index
  %c8192_32873 = arith.constant 8192 : index
  %62060 = arith.muli %24, %c8192_32873 : index
  %62061 = arith.addi %62059, %62060 : index
  %c16_32874 = arith.constant 16 : index
  %62062 = arith.muli %35, %c16_32874 : index
  %62063 = arith.addi %62061, %62062 : index
  %62064 = scf.for %arg0 = %c0 to %c16 step %c1 iter_args(%arg1 = %cst_0) -> (vector<16xf32>) {
    %c16_44555 = arith.constant 16 : index
    %98866 = arith.muli %arg0, %c16_44555 : index
    %98867 = arith.addi %62063, %98866 : index
    %reinterpret_cast = memref.reinterpret_cast %base_buffer_20502 to offset: [%98867], sizes: [1, 1, 1], strides: [8192, 16, 1] : memref<f32> to memref<1x1x1xf32, strided<[8192, 16, 1], offset: ?>>
    %98868 = memref.load %reinterpret_cast[%c0, %c0, %c0] : memref<1x1x1xf32, strided<[8192, 16, 1], offset: ?>>
    %98869 = vector.insertelement %98868, %arg1[%arg0 : index] : vector<16xf32>
    scf.yield %98869 : vector<16xf32>
  }

so not only are there ~100k ops, but many of those are used within 16xf32 loops

Scott's going to find the commit, and figure out what to do next (set status to Inbox) to find someone to fix.

Looking for patterns in the IR to see what changed. The IR before (from ~1 week ago) has linalg.batch_matmul ops, while the IR after does not.
Scanning for commits that might be relevant (could also run a bisect):

https://github.com/openxla/iree/commit/ed174dc866c38b3cc0802f9a950b354ad373b255
https://github.com/openxla/iree/commit/20e014b8d63264d6f4cc0ae78de27bcefc25af0e
LLVM integrates

@manishucsd anything here ring any bells?

Started a git bisect, should have a culprit identified in ~4 steps x 10-15 minutes per step to build + check compile time / IR dumps

bisect points to https://github.com/openxla/iree/commit/479900afe1467cd10f349894f758135e54d487e2
(https://github.com/openxla/iree/pull/13153 , @jpienaar , @hanhanW )

That pattern is incorrect and blocks other models. Which pass is producing that huge amount of IR?

Here's IR before and after iree-mhlo-to-mhlo-preprocessing with that commit reverted: https://gist.github.com/ScottTodd/62c453547b4bb53cb1fb3709ba10b5d8

Most of the op explosion occurs in iree-llvmgpu-tensorcore-vectorization.
Here's forward_dispatch_6_generic_512x16x512x512x64_f32 before/after that pass: https://gist.github.com/ScottTodd/4435728d6b66550282b6ae64c23634c2

I've done what I can to triage this. Who can follow-up next?
It sounds like removing the incorrect pattern in iree-mhlo-to-mhlo-preprocessing exposed a latent issue in iree-llvmgpu-tensorcore-vectorization.

This change has also increased latency in all TF models on CUDA:

Can we revert that PR while it gets resolved?

I'd prefer not to revert as both Phoenix's model and a proprietary model runs into a failure with that faulty pattern and regression is due to triggering an underlying issue that needs to be addressed (it could be triggered by regular linalg-on-tensor input or other HLOs, so revert only helps avoid issues on a specific path). It depends on timelines and different workarounds could be considered, the "final" fix is already in progress and folks have been working towards that, but I don't think it is at "flip switch" ready yet.
For this specific case I don't know what alternatives there are with this vectorization behavior - @dcaballe is our expert there and could list some options. E.g., I heard that one option was to limit tile size. That would help consider shorter term options.
We definitely need to address this before our next stable release.

It looks like the outermost dimension (512) is fully unrolled. There should be a pass where we are tiling for vectorization and generating subview_3 below. That subview should have [1, 1, 16, 16] sizes and not [512, 1, 16, 16] sizes if we don't have the 512 unrolling to happen. Then another scf.for should be generated in addition to the existing one, to iterate over the 512 size one by one:
    %subview_3 = memref.subview %subview[0, 0, %11, %12] [512, 1, 16, 16] [1, 1, 1, 1] : memref<512x1x32x32xf32, strided<[4194304, 262144, 512, 1], offset: ?>> to memref<512x1x16x16xf32, strided<[4194304, 262144, 512, 1], offset: ?>>
    linalg.fill {__internal_linalg_transform__ = "vectorize", lowering_config = #iree_codegen.lowering_config<tile_sizes = [[0, 1, 32, 32, 16]]>} ins(%cst_0 : f32) outs(%subview_3 : memref<512x1x16x16xf32, strided<[4194304, 262144, 512, 1], offset: ?>>)
    scf.for %arg0 = %c0 to %c64 step %c16 {
      %subview_6 = memref.subview %subview_1[0, 0, 0, %arg0] [512, 32, 1, 16] [1, 1, 1, 1] : memref<512x32x1x64xf32, strided<[524288, 1024, 64, 1], offset: ?>> to memref<512x32x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>>
      %subview_7 = memref.subview %subview_2[0, 0, 0, %arg0] [512, 32, 1, 16] [1, 1, 1, 1] : memref<512x32x1x64xf32, strided<[524288, 1024, 64, 1], offset: ?>> to memref<512x32x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>>
      %subview_8 = memref.subview %subview_6[0, %11, 0, 0] [512, 16, 1, 16] [1, 1, 1, 1] : memref<512x32x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>> to memref<512x16x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>>
      %subview_9 = memref.subview %subview_7[0, %12, 0, 0] [512, 16, 1, 16] [1, 1, 1, 1] : memref<512x32x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>> to memref<512x16x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>>
      linalg.generic {indexing_maps = [affine_map<(d0, d1, d2, d3, d4) -> (d0, d2, d1, d4)>, affine_map<(d0, d1, d2, d3, d4) -> (d0, d3, d1, d4)>, affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3)>], iterator_types = ["parallel", "parallel", "parallel", "parallel", "reduction"]} ins(%subview_8, %subview_9 : memref<512x16x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>>, memref<512x16x1x16xf32, strided<[524288, 1024, 64, 1], offset: ?>>) outs(%subview_3 : memref<512x1x16x16xf32, strided<[4194304, 262144, 512, 1], offset: ?>>) attrs =  {__internal_linalg_transform__ = "vectorize", lowering_config = #iree_codegen.lowering_config<tile_sizes = [[0, 1, 32, 32, 16]]>} {
      ^bb0(%in: f32, %in_10: f32, %out: f32):
        %13 = arith.mulf %in, %in_10 : f32
        %14 = arith.addf %out, %13 : f32
        linalg.yield %14 : f32
      }
    }

I'm not very familiar with this pipeline but there should be a Tile or TileAndFuse pass doing that.

It should be related to https://github.com/openxla/iree/issues/13205 . We only distribute three dimensions today on CPU backend... just havent changed it to distribute all dimensions (even though TileAndDistribute can do that)
Then we just need to set the tile sizes of the dimensions greater than three to 1.

@MaheshRavishankar @hanhanW @dcaballe Trying to follow here, who is working on this next? I think we need to update the assignee and status.

I am confused too actually... Is this a CUDA bug or CPU bug?

It's a CUDA bug and in addition to causing a compile-time regression, it has also caused a 5x latency regression.

It's a CUDA bug and in addition to causing a compile-time regression, it has also caused a 5x latency regression.

Is the compile time regression with CUDA backend, or all backends

Looking at perf.iree.dev, only CUDA is affected.

Moved it to Thomas. Thomas is OOO, so assigning to Kojo for now.

@KoolJBlack Let us know when you've had a chance to review this!

@manishucsd anything here ring any bells?

This didn't hit me in my flow of improving codegen, where I compile linalg.matmul down to nvptx. I also discussed with  @jpienaar on this and this is expected. The issue only affects the lowering pass leading up to linalg.

@KoolJBlack have you had a chance to review this?

@allieculp I will get to it later today

So I've done a dump and believe this issue is related to https://github.com/openxla/iree/issues/13202
Looking at the dump below LLVMGPUTensorCoreVectorization we're endlessly unrolling the patch dimensions which are tiled to 0. The fix in https://github.com/openxla/iree/pull/13294 should hopefully address this bug.

Some of the latency regressions in MiniLM (and most likely in more of the models) come from the fact that we now fuse elementwise producer into matmul op. In general it is not a good idea but here it is worse because it makes us not use the tensorcore pipeline.
For instance those ops:
   %8 = linalg.fill {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 32, 32, 16]]>} ins(%cst : f32) outs(%7 : tensor<12x128x128xf32>) -> tensor<12x128x128xf32>
      %9 = linalg.batch_matmul {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 32, 32, 16]]>} ins(%4, %5 : tensor<12x128x32xf32>, tensor<12x32x128xf32>) outs(%8 : tensor<12x128x128xf32>) -> tensor<12x128x128xf32>

Became:
 %20 = linalg.fill {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 1, 1], [0, 0, 0, 32]]>} ins(%cst_1 : f32) outs(%19 : tensor<12x128x128xf32>) -> tensor<12x128x128xf32>
 %21 = linalg.generic {indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d1, d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d2, d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d2, d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)>], iterator_types = ["parallel", "parallel", "parallel", "reduction"]} ins(%14, %15, %16, %17 : tensor<128x12x32xf32>, tensor<12x32xf32>, tensor<128x12x32xf32>, tensor<128x12x32xf32>) outs(%20 : tensor<12x128x128xf32>) attrs =  {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 1, 1], [0, 0, 0, 32]]>} {
      ^bb0(%in: f32, %in_2: f32, %in_3: f32, %in_4: f32, %out: f32):
        %23 = arith.addf %in_3, %in_4 : f32
        %24 = arith.addf %in, %in_2 : f32
        %25 = arith.mulf %24, %23 : f32
        %26 = arith.addf %out, %25 : f32
        linalg.yield %26 : f32
      } -> tensor<12x128x128xf32>

This is due to the https://github.com/openxla/iree/commit/479900afe1467cd10f349894f758135e54d487e2 as pointed out by Scott.
to solve this we would need to change the fusion heuristic to prevent this assuming we want to keep this representation. We had discussed using the generic representation for matmul in the past however this is most likely not going to be a trivial change and will have performance impact on potentially many cases.
My suggestion would be to first try to revert back to a state like we had before and if we want to support the generic version of matmul work on it separately and enable it when it is ready doing it as a fix forward is most likely going to be hard.
@jpienaar @MaheshRavishankar @hanhanW do you have any suggestions?

Yup, this was discussed earlier. https://github.com/openxla/iree/pull/13308 prevents those fusions when it's not a named op. That was blocked on some time out during compilation on CUDS backend. I have to try on ToT after some recent fixes went in

Yup, this was discussed earlier. #13308 prevents those fusions when it's not a named op. That was blocked on some time out during compilation on CUDA backend. I have to try on ToT after some recent fixes went in

yes with ToT the problems should be gone

https://github.com/openxla/iree/issues/13202#issuecomment-1535433910

Some of the latency regressions in MiniLM (and most likely in more of the models) come from the fact that we now fuse elementwise producer into matmul op. In general it is not a good idea but here it is worse because it makes us not use the tensorcore pipeline.
For instance those ops:
   %8 = linalg.fill {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 32, 32, 16]]>} ins(%cst : f32) outs(%7 : tensor<12x128x128xf32>) -> tensor<12x128x128xf32>
      %9 = linalg.batch_matmul {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 32, 32, 16]]>} ins(%4, %5 : tensor<12x128x32xf32>, tensor<12x32x128xf32>) outs(%8 : tensor<12x128x128xf32>) -> tensor<12x128x128xf32>

Became:
 %20 = linalg.fill {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 1, 1], [0, 0, 0, 32]]>} ins(%cst_1 : f32) outs(%19 : tensor<12x128x128xf32>) -> tensor<12x128x128xf32>
 %21 = linalg.generic {indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d1, d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d2, d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d2, d0, d3)>, affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)>], iterator_types = ["parallel", "parallel", "parallel", "reduction"]} ins(%14, %15, %16, %17 : tensor<128x12x32xf32>, tensor<12x32xf32>, tensor<128x12x32xf32>, tensor<128x12x32xf32>) outs(%20 : tensor<12x128x128xf32>) attrs =  {lowering_config = #iree_codegen.lowering_config<tile_sizes = [[1, 1, 1], [0, 0, 0, 32]]>} {
      ^bb0(%in: f32, %in_2: f32, %in_3: f32, %in_4: f32, %out: f32):
        %23 = arith.addf %in_3, %in_4 : f32
        %24 = arith.addf %in, %in_2 : f32
        %25 = arith.mulf %24, %23 : f32
        %26 = arith.addf %out, %25 : f32
        linalg.yield %26 : f32
      } -> tensor<12x128x128xf32>

This is due to the 479900a as pointed out by Scott.
to solve this we would need to change the fusion heuristic to prevent this assuming we want to keep this representation. We had discussed using the generic representation for matmul in the past however this is most likely not going to be a trivial change and will have performance impact on potentially many cases. My suggestion would be to first try to revert back to a state like we had before and if we want to support the generic version of matmul work on it separately and enable it when it is ready doing it as a fix forward is most likely going to be hard.
@jpienaar @MaheshRavishankar @hanhanW do you have any suggestions?

Just a heads up, this bad IR transform you're seeing here is related to the loss of the dot_general lowering from the frontend. See comment here: https://github.com/openxla/iree/issues/13202#issuecomment-1535433910
This will likely be addressed by reverting https://github.com/openxla/iree/issues/13458

@mariecwhite this should be fixed  at ToT (by https://github.com/openxla/iree/pull/13468 ) . Please verify and close.

This is fixed and the benchmarks have been re-enabled in https://github.com/openxla/iree/pull/13515


Support of several grids

Currently I need to keep the list of grids to be able to access them. Also some methods should contain grid as a parameter to be able to identify where they belong, for example: getFormatter() or filter(items[i], args)
example:

for my filter i need dataView to know which filter is it and take proper data
function TreeFilter(item, args, dataView) {
var parent = dataView.getItemById(item.parent);
}
for my formatter i need grid to be passed as an argument because it's important for behavior
function TreeFormatter (row, cell, value, columnDef, dataContext, grid) {
//set behavior by grid data
};

I agree, this is something that needs to be tweaked. The current code often relies on closures or grid-specific functions, which can be clunky in a multi-grid scenario.
Over at my ['alternate master' repo] (https://github.com/6pac/SlickGrid), I've put together some multi-grid sample pages, but I haven't got around to making this change. Perhaps in the next week.

OK, in the alternate master I have just committed the following:

add grid parameter to the end of the parameter list for every grid event
add grid parameter to the end of the parameter list for grid column formatter function
add dataview parameter to the end of the parameter list for every dataview event

for the DataView filter function I'd argue that the DataView object should just be added as a member of the args object.

in slick.grid.js i currently use
stringArray.push(getFormatter(row, m)(row, cell, value, m, item, self));
instead of stringArray.push(getFormatter(row, m)(row, cell, value, m, item));
because I have no other way to get other grid parameters - for example I don't have data to compare the rows hierarchy in tree (as in example http://mleibman.github.io/SlickGrid/examples/example5-collapsing.html )

I believe that's what I've just done. bullet point number 2. I haven't tagged and release it yet, it's just the latest commit to the repo


Subset Manager: Multi Selection

Is your feature request related to a problem? Please describe.
Be able to multi select in the subset manager.
Describe the solution you'd like
Would like to see multi selection in the subset manager so larger sets of instances can be cleared all at once.
[cuID:861m6jr5a]

Be able to multi select in the subset manager.

Note. I suspect this tool will be dropped rather soon in favor of the new Publisher - since that internally allows to manage the scene's instances/subsets. Or is the Subset Manager about something else?

That is a very good point! @iLLiCiTiT ?


Unable to use addressindex RPC calls

Hi all,
I'm running on the testnet trying to using the following very useful commands:
== Addressindex ==
getaddressbalance                          Returns the balance for an address(es) (requires addressindex to be enabled).
getaddressdeltas                           Returns all changes for an address (requires addressindex to be enabled).
getaddressmempool                          Returns all mempool deltas for an address (requires addressindex to be enabled).
getaddresstxids                            Returns the txids for an address(es) (requires addressindex to be enabled).
getaddressutxos                            Returns all unspent outputs for an address (requires addressindex to be enabled).
I am making a block explorer of sorts and these would be a god-send! In my dash.conf I have the following information:
rpcuser=good_username
rpcpassword=good_password
rpcport=9998
rpcallowip=interesting_ip
rpcallowip=interesting_ip
rpcclienttimeout=30
testnet=1
listen=1
server=1
daemon=1
maxconnections=64
txindex=1
addressindex=1
timestampindex=1
spentindex=1
Unfortunately, when I call it, I get this error for the testnet address yaEjcAUVJUoVnPC5DMU5Au2EFDXETHPmsm
{"result":null,"error":{"code":-5,"message":"No information available for address"},"id":"curltest"}
But I know there are transactions for that address:
https://testnet-insight.dashevo.org/insight/address/yaEjcAUVJUoVnPC5DMU5Au2EFDXETHPmsm
Any ideas?
Thanks

Hi @mrwillis , were you able to fix this per @UdjinM6 's instructions above?

I get same exact error, however after i reindexed, i get a new error code -28 Loading wallet...

Error -28 - is an error that is human readable. One of the few :)
"Loading wallet" just meant you need to wait a little before making those calls. The wallet is re-indexing and setting everything up for you.


Testera 2.0 by Aapm

Publicación original de @MRFROG2106 en https://github.com/MRFROG2106/AANGELAA/issues/1

Maybe spam and not a mistake, see #176483 and #174745


Internal: src/sentencepiece_processor.cc(1101) [model_proto->ParseFromArray(serialized.data(), serialized.size())]

Merged Weights
https://huggingface.co/truehealth/LLaVar

Startup Script
pip install --upgrade huggingface_hub
huggingface-cli login --token $HF_TOKEN
git clone https://github.com/SALT-NLP/LLaVAR
cd LLaVAR/LLaVA
pip install -e .
python -m llava.eval.run_llava \
    --model-name /workspace/llavar_v1 \
    --image-file "https://cdn.shopify.com/s/files/1/0057/3728/3618/products/a-man-called-otto_ezrjr0pm_480x.progressive.jpg" \
    --query "Who starred in the movie?"

Error
root@d38c96939557:/workspace/LLaVAR/LLaVA# python -m llava.eval.run_llava     --model-name /workspace/llavar_v1     --image-file "https://cdn.shopify.com/s/files/1/0057/3728/3618/products/a-man-called-otto_ezrjr0pm_480x.progressive.jpg"     --query "Who starred in the movie?"
Traceback (most recent call last):
  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/workspace/LLaVAR/LLaVA/llava/eval/run_llava.py", line 148, in <module>
    eval_model(args)
  File "/workspace/LLaVAR/LLaVA/llava/eval/run_llava.py", line 58, in eval_model
    tokenizer = AutoTokenizer.from_pretrained(model_name)
  File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/tokenization_auto.py", line 682, in from_pretrained
    return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py", line 1805, in from_pretrained
    return cls._from_pretrained(
  File "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py", line 1959, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "/usr/local/lib/python3.10/dist-packages/transformers/models/llama/tokenization_llama.py", line 71, in __init__
    self.sp_model.Load(vocab_file)
  File "/usr/local/lib/python3.10/dist-packages/sentencepiece/__init__.py", line 905, in Load
    return self.LoadFromFile(model_file)
  File "/usr/local/lib/python3.10/dist-packages/sentencepiece/__init__.py", line 310, in LoadFromFile
    return _sentencepiece.SentencePieceProcessor_LoadFromFile(self, arg)
RuntimeError: Internal: src/sentencepiece_processor.cc(1101) [model_proto->ParseFromArray(serialized.data(), serialized.size())]

Hi!
I downloaded the model checkpoint you are using and cannot reproduce the error. The checkpoint seems fine.
It seems this error is related to the checkpoint downloading according to Issue 1 (in Chinese) and Issue 2 (in Chinese).
I recommend using this script to download the huggingface checkpoint.


Ignore HCC runtime library in case hip-clang toolchain is used

Introduce changes needed for hip-clang toolchain to address SWDEV-184933.

hip-clang may also be turned on by default in HIP. In that case it can be detected by
grep 'HIP_COMPILER=clang' /opt/rocm/hip/lib/.hipInfo

@yxsamliu in this case would HIP_CLANG_PATH HIP_VDI_HOME still be set by hipcc?

hip-clang may also be turned on by default in HIP. In that case it can be detected by
grep 'HIP_COMPILER=clang' /opt/rocm/hip/lib/.hipInfo

@yxsamliu in this case would HIP_CLANG_PATH HIP_VDI_HOME still be set by hipcc?

hipcc does not set these variables. Users set them and hipcc is affected by them. If HIP is built with -DHIP_COMPILER=clang, hipcc will by default use hip-clang to compile HIP programs. Also HIP/VDI runtime always use hip-clang. If HIP_CLANG_PATH or HIP_VDI_HOME is set by users, hipcc also use hip-clang even if it is built without -DHIP_COMPILER=clang.

jenkins: retest this please


CMake - Boost flag

This is a great project and very solid. Thank you. Also, I have a query...
I build the VS solution and have a problem with the makefile examples project. The lib builds fine.
Also when I try and build with CMAKE I am struggling to disable BOOST using a flag. Seems strange.
Best wishes

Thanks for using redis3m!
Unfortunately I don't have personally experience with Windows, but probably if you write in more detail the error, you'll be able to get more help either from me or someone else.

Thanks for your kind offer of help. What I'll do is just stay with the MSVC project as this builds the library fine (but not the nmake project). Its a great project and I will be having a play with upgrading to Redis 4.


Create marun.edu.tr

@EceAkgull lib/domains/tr/edu/marun.edu.tr: this request has an incorrect file path format, please ensure that you are familiar with     this repository rules located at the bottom of this page and change     your request accordingly. If you don't know how to change request, close it and open a new one.     If you are not able to make the pull request according the instructions, please send us an email to<EMAIL_ADDRESS>Please mention this request URL in the message.


nyc returns Unknown for all fields after test run successfully

Description
nyc returns Unknown for all fields after test run successfully.
  18 passed
  1 known failure

----------|----------|----------|----------|----------|----------------|
File      |  % Stmts | % Branch |  % Funcs |  % Lines |Uncovered Lines |
----------|----------|----------|----------|----------|----------------|
All files |  Unknown |  Unknown |  Unknown |  Unknown |                |
----------|----------|----------|----------|----------|----------------|

Command-Line Arguments
Copy your npm build scripts or the ava command used:
    "test": "cd test/resources && npm install && nyc ava ../app-test.js",

Relevant Links

Project link: https://github.com/GoogleChrome/rendertron
Reproduction steps (this app requires Node 8 because it contains ES7 codes):

git clone https://github.com/GoogleChrome/rendertron.git
cd rendertron
npm install
npm install nyc --save-dev

modify "test" in package.json to "test": "cd test/resources && npm install && nyc ava ../app-test.js",

npm run test

Environment
node -v => 8.9.4
ava --version => 0.20.0
npm --version => 5.6.0
nyc => 11.4.1

Additional Info
I have tried solutions from #374 and readme. But coverage is still unknown.
The source code is using ES7 syntax, async await. I have transpiled ES7 codes down to ES6 compatible.
But coverage is unknown for both ES7 source code and ES6 compatible code.
I have tried the same solution for another node module. It worked and generated .nyc_output file after npm run test.
But this time, after running npm run test, it did NOT generate .nyc_output file.

The same issue, please help me!
Run test as below:
nyc --reporter=html --reporter=text mocha --require ts-node/register src/**/*.spec.ts

339 passing (12s)

----------|----------|----------|----------|----------|----------------|
File      |  % Stmts | % Branch |  % Funcs |  % Lines |Uncovered Lines |
----------|----------|----------|----------|----------|----------------|
All files |  Unknown |  Unknown |  Unknown |  Unknown |                |
----------|----------|----------|----------|----------|----------------|

@hekod777 in my case, because src/**/*.spec.ts didn't include *.spec.js, nyc made the report based on javascript files. So, I think you should check the folder "../app-test.js" is existing or not.

The rendertron project specifically is an interesting case, I've looked at it a few times... its structure doesn't necessarily play nicest with nyc. For the adventurous, I would recommend something else from  https://istanbul.js.org/integrations/ (primarily jest or node-tap).
For now however, I'm going to close this issue as stale since I know the project has moved on to TypeScript and I think there are other issues in here relating to it.

I'm facing this same problem.  Here's what coverage output looks like:
=============================== Coverage summary ===============================
Statements   : Unknown% ( 0/0 )
Branches     : Unknown% ( 0/0 )
Functions    : Unknown% ( 0/0 )
Lines        : Unknown% ( 0/0 )
================================================================================

This only recently starting happening for me on a project I maintain.

@jsdevel please open a new issue, using the latest version of NYC and providing a reproduction in a repo that follows the documented instructions

The solution for me was to delete the node_modules and reinstall all the packages:
rm -rf node_modules/
npm install


Added iOS specific option for specifying the modal presentation style of the media picker

Changes Proposed in this pull request:
According to View Controller Programming Guide on iOS

When presenting a view controller using the UIModalPresentationFullScreen style, UIKit normally removes the views of the underlying view controller after the transition animations finish. You can prevent the removal of those views by specifying the UIModalPresentationOverFullScreen style instead. You might use that style when the presented view controller has transparent areas that let underlying content show through.

Removing the views of the underlying view controller can also have side effects on Xamarin Forms, specially when using a framework such as MVVMCross with a MvxMasterDetailPage, as its viewmodel's lifecycle gets triggered when returning from the Media Picker.

This PR allows the user to choose the modal presentation style used when presenting the media picker on iOS.
It defaults the modal presentation style to FullScreen so that the current behaviour will not be changed.

Would love to get this in


Should address issue #163.

Updated the useragent being used to identfy Helium to be the same as most recent OSX and Safari versions.

:clap:


In Safari, seems like the 1fr is calculated based on the actual image size and not the stretched one

Detailed description of the issue and example code
https://stackoverflow.com/questions/49103403/grid-template-rows-auto-bug-in-safari/49117333#49117333
PS: The solution for now is adding: grid-template-columns: 100%; to the grid element

Thanks for the workaround 👍
This is still a bug in Safari 14 (iOS + OS X)


Explore splitting CI into multiple workflow files

Problem

In the API and Frontend repositories we stuff all our CI into a single workflow. This helps with some things, like being able to share Docker builds, but hurts other things, like not being able to use the paths option to selectively run steps only when necessary.
For example: it's a waste of time and resources to run unit and e2e tests on the frontend with nothing in the src directory or the CI configuration for those tests has changed. Same with the API unit tests, it doesn't make sense to run the ingestion tests if the API was updated nor the API tests if only the ingestion server is updated. It doesn't make sense to run either if only documentation has been updated.
Description

Explore the possibility of splitting CI into multiple workflow files so that we can use the paths option to selectively run certain CI steps only when relevant.
We could also try something like this: https://github.com/orgs/community/discussions/25669
Because we have required checks that need to pass on PRs, we might have to use that strategy to cause the checks to automatically pass instead of running. Splitting into multiple files may not even be possible with required checks, I'm not sure.
Implementation

[ ] 🙋 I would be interested in implementing this feature.

The CI + CD workflow is very selective now and only runs the necessary steps based on the changed files.


Preserve PostCSS declaration sources

Fixes #89
See changes w/o whitespace
If anybody is seeing errors like the following:
<css input>: Cannot read property 'input' of undefined

This is because the source is not being preserved when new PostCSS declarations are created. You have to clone existing declarations to preserve the source.

@vvasilev- the build failure doesn't look related to the changes in this PR. Can you have a look?

https://github.com/npm/normalize-package-data/issues/85

@vvasilev- should be ready to merge now. Please do a patch release once it's in. Thanks!

Hey @jedmao, thanks for the PR. 😄


[Packaging] Use Python 3.9 in RHEL 8's RPM

Description
Red Hat Enterprise Linux (RHEL) 8 now has Python 3.6, 3.8, and 3.9: https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux/8/html/configuring_basic_system_settings/assembly_installing-and-using-python_configuring-basic-system-settings
Since Python 3.6 has been deprecated (#19858), we use Python 3.9 on RHEL 8.

Off-topic: Personally, I don't really like the inconsistency of python3 package. This consistency causes all the fuss in this PR:

RHEL 8's python3 should point to a more modern version, instead of the deprecated Python 3.6.
Mariner should have specific versions of Python packages like python39, so that users can choose which one to install.

There are many sed: command not found error in  Rpm Package Mariner 2.0 log. Is this a bug of Mariner 2?


Contextuality demo

Demo: Contextuality and inductive bias in quantum machine learning
This is a demo for my recent paper https://arxiv.org/abs/2302.01365
In the demo we study the toy learning problem described in the paper, and build and train a quantum model that encodes the relevant inductive bias. The model is shown to outperform a 'generic' quantum model that does not encode this bias.
The demo is not focused much on contextuality (because it would require a lot of explanation), but rather focuses on the type of learning problem (inspired from contextuality) that is presented in the paper.
JAX is used for vectorization and JIT compilation.

Here are some minor copy editing changes and suggestions. Everything else looks good to me. :)

Thanks @ikurecic :D

A problem has been detected with the jax version (it is not a problem of this demo). Next week it will be fixed :)


Addded AV (Camera and Microphone) Permissions check

Added the changes that @tromg suggested, modifying them to support both Camera and Microphone.  I also added all the method headers to the private interface.  There is both a generic showAVPermissionsWithType: method as well as showCameraPermissionsWithTitle: and showMicrophonePermissionsWithTitle: methods.

Can somebody please merge this feature?

Sorry I've been late on this! Nice work!


Fix race conditions in test_purge_on_delete.py

Description
The race condition that was fixed in #4912 seems to be present in a lot more test cases defined in the same file. This PR fixes the remaining test cases.
Self Check:

[ ] Attached issue to pull request
[x] Changelog entry
[x] Type annotations are present
[x] Code is clear and sufficiently documented
[x] No (preventable) type errors (check using make mypy or make mypy-diff)
[x] Sufficient test cases (reproduces the bug/tests the requested feature)
[x] Correct, in line with design
[ ] End user documentation is included or an issue is created for end-user documentation

Reviewer Checklist:

[ ] Sufficient test cases (reproduces the bug/tests the requested feature)
[ ] Code is clear and sufficiently documented
[ ] Correct, in line with design

Processing this pull request

Merged into branches master in 78658bb4e163aef8c761a22bdb4ac6babedb51b3

Processing #4918.

Processing #4917.


add map-elites, with a brax ant example

Add a simple implementation of the MAP-Elites algorithm (ref1, ref2), with an example on the Brax Ant task.
Users can implement their own behavior descriptor extractor, see an example in task/brax_task.py.
Example commands
python train_ant_map_elites.py --max-iter=3000
python train_ant_map_elites.py --max-iter=3000 --save-gif  # This can be slow

Example output

Note We plan to add more Quality Diversity methods, the implementations and related interfaces are subject to change.

LGTM!
Before merging, please have a look at the one minor issue (see the comment).


[QUESTION] Equivalent of GET DIAGNOSTICS :NbrOfRows = DB2_NUMBER_ROWS

Hey!
A common use case when writing web services is to offer filtered and paginated lists of records.
Pagination requires a couple of things:

A limit (Using LIMIT in the SQL)
An offset (Using OFFSET in the SQL)
A count of retrieved records (Available in the .length property of the result array)
A count of total number of records available - how can I retrieve this? is it possible without writing a separate SQL query with COUNT(*)?
In embedded sql/rpgle we have DB2_NUMBER_ROWS. Can this be achieved using ODBC?

I don't believe so. I think you best bet is using COUNT(*)
I remember reading a while ago about this, since it is a very helpful case, but I don't believe that there is an ODBC way to get the total number of records available from a statement before actually fetching them. This package currently just calls SQLFetch until there are no more rows to return, so you have to limit it using SQL like LIMIT and OFFSET. There is a SQLRowCount function, but this only returns the number of rows affected on UPDATE/INSERT/DELETE (and passed to you in the Result object as count).
There are some DBMS that do allow you to get this information, but that is because they buffer all of the rows.
I think this is related to the effort to get cursors and SQLFetchScroll working in the package. Using that (future functionality), you could indicate that you want to fetch rows X at a time (similar to limit), and can just keep calling next or whatever function name to get the next X rows. You can also position the cursor where you want it, similar to OFFSET. But again, this won't tell you the total number of records available. That is something I will be working heavily on in the next few weeks!

I don't believe so. I think you best bet is using COUNT(*)
I remember reading a while ago about this, since it is a very helpful case, but I don't believe that there is an ODBC way to get the total number of records available from a statement before actually fetching them. This package currently just calls SQLFetch until there are no more rows to return, so you have to limit it using SQL like LIMIT and OFFSET. There is a SQLRowCount function, but this only returns the number of rows affected on UPDATE/INSERT/DELETE (and passed to you in the Result object as count).
There are some DBMS that do allow you to get this information, but that is because they buffer all of the rows.
I think this is related to the effort to get cursors and SQLFetchScroll working in the package. Using that (future functionality), you could indicate that you want to fetch rows X at a time (similar to limit), and can just keep calling next or whatever function name to get the next X rows. You can also position the cursor where you want it, similar to OFFSET. But again, this won't tell you the total number of records available. That is something I will be working heavily on in the next few weeks!


iradon: threading, interpolations, and tests

Updates to iradon:

Added threading for iradon
Use LinearInterpolation from Interpolations.jl for inverse radon transform
Add a test

ohhhh Sorry I meant to say extra section. Not compat section.
Really sorry
Johnny Chen
陈久宁
School of Mathematical Sciences, East China Normal University, Shanghai
华东师范大学数学科学学院
2020年3月3日 +0800 12:07 kczimm<EMAIL_ADDRESS>
@kczimm commented on this pull request.
In Project.toml:

@@ -4,6 +4,9 @@ version = "0.1.0"

[deps]
FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
+Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
I'm not too familiar with the compat section but I did just read Pkg compatibility. What version of Statistics should I put? and should I also add FFTW and Images, too? Why not?
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No problem. Thanks for the advice. I’ll add that.

On Mar 2, 2020, at 10:00 PM, Johnny Chen<EMAIL_ADDRESS>wrote:
@johnnychen94 commented on this pull request.
In Project.toml https://github.com/JuliaImages/ImageReconstruction.jl/pull/3#discussion_r386787700:

@@ -4,6 +4,9 @@ version = "0.1.0"

[deps]
FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
+Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
Images and Statistics should be put in compat section
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No labels ?

Labels do not seem to appear.
For clarification, I am not using any vim related plugin in VS code; and I have tried using this plugin w/ all other plugins deactivated.

Repeated & Solved: https://github.com/MurlocCra4ler/vscode-leap/issues/14