Fix undefined/global variable access

Looks like an interesting project. :)
I have some small fixes for you.
I'm using luacheck. ;)

Great.
I probably need to use luacheck too.
Thanks!


Fix tensorflowhub caching issue

Right now, the tfhub test can fail because of a caching issue. When loading from tensorflow hub using tfhub.resolve, the model is saved in a temporary directory. That file can be persisted between test runs, in which case tfhub.resolve will no-op. If the model is deleted and the file isn't, tfhub.resolve will still no-op and tf.keras.models.load_model will throw.To avoid this (and test more robustly) we can delete the temporary directory entirely between runs.
This fixes the currently failing python 3.7 postcommit (along with https://github.com/apache/beam/pull/25654)
See some more discussion here - https://stackoverflow.com/questions/63078695/savedmodel-file-does-not-exist-when-using-tensorflow-hub

Thank you for your contribution! Follow this checklist to help us incorporate your contribution quickly and easily:

[ ] Mention the appropriate issue in your description (for example: addresses #123), if applicable. This will automatically add a link to the pull request in the issue. If you would like the issue to automatically close on merging the pull request, comment fixes #<ISSUE NUMBER> instead.
[ ] Update CHANGES.md with noteworthy changes.
[ ] If this contribution is large, please file an Apache Individual Contributor License Agreement.

See the Contributor Guide for more tips on how to make review process smoother.
To check the build health, please visit https://github.com/apache/beam/blob/master/.test-infra/BUILD_STATUS.md
GitHub Actions Tests Status (on master branch)

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Run Python 3.7 PostCommit

Run Python 3.7 PostCommit

Run Gradle Publish

Python postcommit failure isn't tensorflow - test_tf_imagenet_image_segmentation succeeded (other issue should be fixed by #25654).
Gradle publish issue is unrelated as well, that's part of the release and I just needed a PR on master

R: @riteshghorse @Abacn


Latest updates broke my automation built on top of github-release

Hi,
Thank you for making this amazingly useful tool!
In the future, it'd be great if output formatting changes were avoided, or if a JSON output format were added.  Basically, the change of outputting tags: instead of git tags: broke part of a release pipeline that I maintain, and the subtlety of difference made it kind of painful to track down.
Thanks again for all your hard work on this.
Best,
Jay

Hi Jay,
First of all, thanks for the kinds words. Second: you're absolutely right. Breaking the output, even if it follows no sane convention, was gratuitous. There was no real reason for it apart from the fact that my current easthetic sensibility preferred a single word. I thought for just a moment that somebody may be relying on it, then discarded the idea as I thought the output formart looked sufficiently random to be "for humans only". As it turns out, that was wrong. Your suggestion of adding a JSON output format is a good one. When I get some time or a PR comes, I promise I'll prioritize it over other things (apart from breaking bugs).
Once again, apologies for the gratuitous change.

Nicolas,
I'm glad we've been able to converge to the same wavelength on this, and am pleased the feedback seems to have been received in the spirit I'd intended!
Cheers,
Jay

FYI I've gone ahead and opened PR #65 which addresses the JSON side of this.


Online demo

Can you add online demo link please?

It's in the description of the repo: https://meowni.ca/font-style-matcher


The URI conversion will sometimes fail on file:// handlers.

Sometimes, a Windows pathname will be converted incorrectly.  This is a bandaid fix on the problem.
Previously, we would have a path that started like this: \C:\Users...
When we tossed that path into Sublime, it would not be able to find the view associated to that file.  This bandaid fix would remove the preceding \ in that pathname.
This will mainly fix issues with diagnostics.

Thanks for proposing a fix.
I need a little more information to be convinced to stop using python's built-in url translation logic.
\C:\Users doesn't look like a valid path, what URI did it come from?
Which language server are you using, and do you have a log / repro?

@tomv564 I am using omnisharp-roslyn for my language server.  Here is a log:
LSP:      {'diagnostics': [{'range': {'start': {'line': 3, 'character': 0}, 'end': {'line': 3, 'character': 37}}, 'code': 0, 'source': 'csharp', 'message': 'Unnecessary using directive.', 'severity': 4}, {'range': {'start': {'line': 3, 'character': 0}, 'end': {'line': 3, 'character': 37}}, 'code': 0, 'source': 'csharp', 'message': 'Unnecessary using directive.', 'severity': 4}], 'uri': 'file:///C%3A/Clients/clientname/file.cs'}
LSP: maybe_file_uri: file:///C%3A/Clients/clientname/file.cs
LSP: file_path: \C:\Clients\clientname\file.cs

I updated core\diagnostics.py to print out the above.
debug("maybe_file_uri: " + maybe_file_uri)
file_path = uri_to_filename(maybe_file_uri)
debug("file_path: " + file_path)

Encoding the : as %3A should be unnecessary and is a bit unexpected as they are likely using standard Microsoft APIs to translate paths to URIs?
Any chance we can check on omnisharp's side if they can have a closer look at it? We can refer to https://en.wikipedia.org/wiki/File_URI_scheme#Windows or https://blogs.msdn.microsoft.com/ie/2006/12/06/file-uris-in-windows/

Looking into it further, it does appear that a properly formed URI should use the : instead of %3A.
>>> url2pathname('/C%3A/file.cs')
'\\C:\\file.cs'
>>> url2pathname('/C:/file.cs')
'C:\\file.cs'

So I believe this to be an omnisharp bug.  Whoops!

@tomv564 However, this may be an intentional thing because VSCode uses %3A encoding on uris.  The language server spec doesn't say anything about specially encoding the uris, but the main implementation does this encoding.  omnisharp-roslyn appears to specifically mangle the path to work with VSCode.  I've popped a question at the omnisharp-roslyn team about this, so maybe this will need to be something that will need to be handled by this extension.  If that is the case, I will make another attempt at this (probably by replacing %3A with : before throwing the uri into urllib)


Make sure that App\User exists

Under installation steps. In point 3
Step 3. Check if App\User exists
If I navigate to this link it shows
`<?php
namespace App;
class User extends Models\User {
//leave this empty
}`
I have few questions

What to write inside the class?
If it is supposed to be empty then what is the point of creating it?
How to create a  user?

I am new here and I was helping a user with the same problem on SO.
The idea is that this package still uses the old laravel model's patter (have models in app instead of app\models) but this changed on laravel 8 by default. So for this package to work (because it is doing use App\User; where it needs it) you have to have that class autoloaded/available, hence if you have your model on App\Models\User, you can "alias" it by creating a class that extends the original but is also available as App\User.
That is why it is empty, it is just an alias... This is one file that uses this:
https://github.com/thekordy/ticketit/blob/110d5d78fb997d0ba5d2ac6b9a4f9e31896976bd/src/Models/Agent.php#L5


Storage data sharing

Because we chose to separate the merkle tree from the data storage (and more specifically account storage sub-spaces), we don't have data sharing that is implied by merklelized storage. In some cases it would be preferable to store the data in shared space.
For example, it should be fairly common that a lot of users' validity predicates are the same. Another example is the planned feature for data schema described in data-schema.md.
Open questions:

Do we want to enable data sharing for everything and anything (i.e. storing references via hash of the data to shared storage) or choose when to use it?
Would it be useful to generalize this concept? It would be nice if Anoma users can also benefit from it
How to deal with shared storage space rent fees? Does everyone pay fees as if there was no data sharing? It would be nice if we could reduce the fees, so that shared data that are very common become very cheap to use (this would be especially nice for the data schema).

If we can do automated sharing of e.g. validity predicate code via something like hash-consing, that would be quite nice.

Would it be useful to generalize this concept? It would be nice if Anoma users can also benefit from it

What specifically do you mean - who are users in this context? Users of some particular validity predicate?

What specifically do you mean - who are users in this context? Users of some particular validity predicate?

In this context, it’s the accounts and their sub-spaces. That is transactions would write some custom data that may be common to many accounts and understood by custom VPs


Setup Docusaurus configuration and remove unnecessary files

I setup Docusaurus v2.0 for a side project recently and it's now a fully fledged static site generator. That means by default it renders a website at /, docs at /docs and a blog at /blog.
Quick tip to get just a documentation build setup (which is what I think we want given our docs lie at docs.celo.org).

Delete src/pages/index.js but leave the src/pages folder
Set base URL to /

I setup Docusaurus v2.0 for a side project recently and it's now a fully fledged static site generator. That means by default it renders a website at /, docs at /docs and a blog at /blog.
Quick tip to get just a documentation build setup (which is what I think we want given our docs lie at docs.celo.org).

Delete src/pages/index.js but leave the src/pages folder
Set base URL to /


Update Extensions.swift

the library does not compile without this fix

@kocherovets thank you so much!


[Playstate] AutoHotKey not opening when I launch a game

Autohotkey doesnt open when i launch any game, so the playstate extension never works.

The extension doesn't use AutoHotKey for its functionality. If the extension is not working please open a new issue providing the extension log. Also make sure to update the extension before since I just released a new update with extra logging to help identify issues.

where do i find the extension logs

also what are the default hotkeys. It used to be home but it doesn't work anymore


test_tenants_many[RemoteStorageKind.REAL_S3] is flaky

Example failed runs:
https://github.com/neondatabase/neon/runs/7740424684?check_suite_focus=true
https://github.com/neondatabase/neon/runs/7740121190?check_suite_focus=true
https://github.com/neondatabase/neon/runs/7739496537?check_suite_focus=true
https://github.com/neondatabase/neon/runs/7758820107?check_suite_focus=true

Some of these failures seem to be duplicates of issue #2247.
Assigning to @LizardWizzard since you opened a PR for this already

#2248 is the PR that increases the timeout for waiting until checkpoint is uploaded. This should help because previously we used only local flavours of remote storage (either local fs or mock server running locally) and now we use truly remote s3.
Please reopen if you see this again


Desugar PathParamOrder annotation and fix path param access

Purpose

Inject Resource signature parameter order annotation to HTTP resource which contains path params/ data binding params and WebSocket UpgradePath params
HTTP Resource Path param, Data binding params and WebSocket UpgradePath params compile time validation

Approach

Desugar annotation before annotation rewrite
Use annotation mapping to resolve path param value in the runtime

Check List

[x] Read the Contributing Guide
[ ] Required Balo version update
[ ] Updated Change Log
[ ] Checked Tooling Support (#)
[ ] Added necessary tests

[x] Unit Tests
[ ] Spec Conformance Tests
[ ] Integration Tests
[ ] Ballerina By Example Tests

[ ] Increased Test Coverage
[ ] Added necessary documentation

[ ] API documentation
[ ] Module documentation in Module.md files
[ ] Ballerina By Examples

Codecov Report

:exclamation: No coverage uploaded for pull request base (jballerina@94f9e2a). Click here to learn what that means.
The diff coverage is 44.34%.

@@              Coverage Diff              @@
##             jballerina   #15979   +/-   ##
=============================================
  Coverage              ?   10.62%
  Complexity            ?     2455
=============================================
  Files                 ?     1466
  Lines                 ?    70510
  Branches              ?     8395
=============================================
  Hits                  ?     7493
  Misses                ?    62365
  Partials              ?      652

Impacted Files
Coverage Δ
Complexity Δ

.../ballerinalang/net/http/HttpResourceArguments.java
100% <ø> (ø)
2 <0> (?)

...inalang/net/uri/parser/SimpleStringExpression.java
34% <ø> (ø)
11 <0> (?)

...ballerinalang/compiler/desugar/ServiceDesugar.java
0% <0%> (ø)
0 <0> (?)

...erinalang/compiler/desugar/HttpFiltersDesugar.java
0% <0%> (ø)
0 <0> (?)

...g/wso2/ballerinalang/compiler/desugar/Desugar.java
0% <0%> (ø)
0 <0> (?)

...va/org/ballerinalang/net/http/SignatureParams.java
87.87% <100%> (ø)
20 <1> (?)

.../java/org/ballerinalang/net/http/HttpResource.java
80.7% <100%> (ø)
41 <3> (?)

...g/net/http/compiler/HttpServiceCompilerPlugin.java
97.77% <100%> (ø)
17 <0> (?)

...allerinalang/net/http/HttpResourceDataElement.java
89.31% <50%> (ø)
51 <0> (?)

.../net/http/compiler/ResourceSignatureValidator.java
87.15% <84.14%> (ø)
38 <20> (?)

... and 1 more

Continue to review full report at Codecov.

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Fix responsible confirmed notification text

Coverage increased (+0.005%) to 85.872% when pulling 5f0e8cf35e5d881568ab3b0a52cc378880095b91 on fix-responsible-confirmed-notification-text into 5ab64c39b1b5dc7d61876ce0371df7051315c9a8 on main.


__half2 implementation does not match CUDA one, resulting in a bug in __half2float calls

Hi,
I have a kernel where __half2float behaves differently with HIP vs CUDA.
Reproduce with

RoCm 5.6
hipify-perl 5.6.0
hipcc 5.6.31061-8c743ae5d

Use this CUDA kernel:
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <stdio.h>

#define TPB 32  // threads per block

__global__ void distanceKernel(float* d_out) {
    const int thread_id = blockIdx.x * blockDim.x + threadIdx.x;

    printf("Thread id: %d\n", thread_id);

    float scale_back;
    uint32_t t;
    uint32_t t2;

    float scale = 0.035;

    printf("[THREAD %d] scale %f\n", (int)threadIdx.x, scale);
    half2 scale_half2 = __float2half2_rn(scale);

    memcpy(&t, &scale_half2, sizeof(half2));
    printf("[THREAD %d] scale after memcpy: %lu\n", (int)threadIdx.x, (unsigned long)t);

    scale_back = __half2float(scale_half2.x);
    memcpy(&t2, &scale_back, sizeof(float));

    printf("[THREAD %d] int repr scale_back: %lu\n", (int)threadIdx.x, (unsigned long)t2);
    printf("[THREAD %d] scale_back: %f\n", (int)threadIdx.x, scale_back);

    d_out[thread_id] = scale_back;
}

int main() {
    float* d_out = NULL;
    float d_out_cpu[TPB];
    cudaMalloc(&d_out, TPB * sizeof(float));

    printf("Hey\n");
    distanceKernel<<<1, TPB>>>(d_out);

    cudaMemcpy(d_out_cpu, d_out, TPB * sizeof(float), cudaMemcpyDeviceToHost);

    printf("CPU result:\n");
    for (int i = 0; i < TPB; i++) {
        printf("    %f, \n", d_out_cpu[i]);
    }
    printf("\n");

    cudaFree(d_out);
    return 0;
}

Running this kernel on an Nvidia GPU, we rightfully get:
Hey
Thread id: 0
Thread id: 1
Thread id: 2
Thread id: 3
Thread id: 4
Thread id: 5
Thread id: 6
Thread id: 7
Thread id: 8
Thread id: 9
Thread id: 10
Thread id: 11
Thread id: 12
Thread id: 13
Thread id: 14
Thread id: 15
Thread id: 16
Thread id: 17
Thread id: 18
Thread id: 19
Thread id: 20
Thread id: 21
Thread id: 22
Thread id: 23
Thread id: 24
Thread id: 25
Thread id: 26
Thread id: 27
Thread id: 28
Thread id: 29
Thread id: 30
Thread id: 31
[THREAD 0] scale 0.035000
[THREAD 1] scale 0.035000
[THREAD 2] scale 0.035000
[THREAD 3] scale 0.035000
[THREAD 4] scale 0.035000
[THREAD 5] scale 0.035000
[THREAD 6] scale 0.035000
[THREAD 7] scale 0.035000
[THREAD 8] scale 0.035000
[THREAD 9] scale 0.035000
[THREAD 10] scale 0.035000
[THREAD 11] scale 0.035000
[THREAD 12] scale 0.035000
[THREAD 13] scale 0.035000
[THREAD 14] scale 0.035000
[THREAD 15] scale 0.035000
[THREAD 16] scale 0.035000
[THREAD 17] scale 0.035000
[THREAD 18] scale 0.035000
[THREAD 19] scale 0.035000
[THREAD 20] scale 0.035000
[THREAD 21] scale 0.035000
[THREAD 22] scale 0.035000
[THREAD 23] scale 0.035000
[THREAD 24] scale 0.035000
[THREAD 25] scale 0.035000
[THREAD 26] scale 0.035000
[THREAD 27] scale 0.035000
[THREAD 28] scale 0.035000
[THREAD 29] scale 0.035000
[THREAD 30] scale 0.035000
[THREAD 31] scale 0.035000
[THREAD 0] scale after memcpy: 679159931
[THREAD 1] scale after memcpy: 679159931
[THREAD 2] scale after memcpy: 679159931
[THREAD 3] scale after memcpy: 679159931
[THREAD 4] scale after memcpy: 679159931
[THREAD 5] scale after memcpy: 679159931
[THREAD 6] scale after memcpy: 679159931
[THREAD 7] scale after memcpy: 679159931
[THREAD 8] scale after memcpy: 679159931
[THREAD 9] scale after memcpy: 679159931
[THREAD 10] scale after memcpy: 679159931
[THREAD 11] scale after memcpy: 679159931
[THREAD 12] scale after memcpy: 679159931
[THREAD 13] scale after memcpy: 679159931
[THREAD 14] scale after memcpy: 679159931
[THREAD 15] scale after memcpy: 679159931
[THREAD 16] scale after memcpy: 679159931
[THREAD 17] scale after memcpy: 679159931
[THREAD 18] scale after memcpy: 679159931
[THREAD 19] scale after memcpy: 679159931
[THREAD 20] scale after memcpy: 679159931
[THREAD 21] scale after memcpy: 679159931
[THREAD 22] scale after memcpy: 679159931
[THREAD 23] scale after memcpy: 679159931
[THREAD 24] scale after memcpy: 679159931
[THREAD 25] scale after memcpy: 679159931
[THREAD 26] scale after memcpy: 679159931
[THREAD 27] scale after memcpy: 679159931
[THREAD 28] scale after memcpy: 679159931
[THREAD 29] scale after memcpy: 679159931
[THREAD 30] scale after memcpy: 679159931
[THREAD 31] scale after memcpy: 679159931
[THREAD 0] int repr scale_back:<PHONE_NUMBER>
[THREAD 1] int repr scale_back:<PHONE_NUMBER>
[THREAD 2] int repr scale_back:<PHONE_NUMBER>
[THREAD 3] int repr scale_back:<PHONE_NUMBER>
[THREAD 4] int repr scale_back:<PHONE_NUMBER>
[THREAD 5] int repr scale_back:<PHONE_NUMBER>
[THREAD 6] int repr scale_back:<PHONE_NUMBER>
[THREAD 7] int repr scale_back:<PHONE_NUMBER>
[THREAD 8] int repr scale_back:<PHONE_NUMBER>
[THREAD 9] int repr scale_back:<PHONE_NUMBER>
[THREAD 10] int repr scale_back:<PHONE_NUMBER>
[THREAD 11] int repr scale_back:<PHONE_NUMBER>
[THREAD 12] int repr scale_back:<PHONE_NUMBER>
[THREAD 13] int repr scale_back:<PHONE_NUMBER>
[THREAD 14] int repr scale_back:<PHONE_NUMBER>
[THREAD 15] int repr scale_back:<PHONE_NUMBER>
[THREAD 16] int repr scale_back:<PHONE_NUMBER>
[THREAD 17] int repr scale_back:<PHONE_NUMBER>
[THREAD 18] int repr scale_back:<PHONE_NUMBER>
[THREAD 19] int repr scale_back:<PHONE_NUMBER>
[THREAD 20] int repr scale_back:<PHONE_NUMBER>
[THREAD 21] int repr scale_back:<PHONE_NUMBER>
[THREAD 22] int repr scale_back:<PHONE_NUMBER>
[THREAD 23] int repr scale_back:<PHONE_NUMBER>
[THREAD 24] int repr scale_back:<PHONE_NUMBER>
[THREAD 25] int repr scale_back:<PHONE_NUMBER>
[THREAD 26] int repr scale_back:<PHONE_NUMBER>
[THREAD 27] int repr scale_back:<PHONE_NUMBER>
[THREAD 28] int repr scale_back:<PHONE_NUMBER>
[THREAD 29] int repr scale_back:<PHONE_NUMBER>
[THREAD 30] int repr scale_back:<PHONE_NUMBER>
[THREAD 31] int repr scale_back:<PHONE_NUMBER>
[THREAD 0] scale_back: 0.035004
[THREAD 1] scale_back: 0.035004
[THREAD 2] scale_back: 0.035004
[THREAD 3] scale_back: 0.035004
[THREAD 4] scale_back: 0.035004
[THREAD 5] scale_back: 0.035004
[THREAD 6] scale_back: 0.035004
[THREAD 7] scale_back: 0.035004
[THREAD 8] scale_back: 0.035004
[THREAD 9] scale_back: 0.035004
[THREAD 10] scale_back: 0.035004
[THREAD 11] scale_back: 0.035004
[THREAD 12] scale_back: 0.035004
[THREAD 13] scale_back: 0.035004
[THREAD 14] scale_back: 0.035004
[THREAD 15] scale_back: 0.035004
[THREAD 16] scale_back: 0.035004
[THREAD 17] scale_back: 0.035004
[THREAD 18] scale_back: 0.035004
[THREAD 19] scale_back: 0.035004
[THREAD 20] scale_back: 0.035004
[THREAD 21] scale_back: 0.035004
[THREAD 22] scale_back: 0.035004
[THREAD 23] scale_back: 0.035004
[THREAD 24] scale_back: 0.035004
[THREAD 25] scale_back: 0.035004
[THREAD 26] scale_back: 0.035004
[THREAD 27] scale_back: 0.035004
[THREAD 28] scale_back: 0.035004
[THREAD 29] scale_back: 0.035004
[THREAD 30] scale_back: 0.035004
[THREAD 31] scale_back: 0.035004
CPU result:
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,
    0.035004,

Running then:
hipify-perl kernel_half.cu -o=kernel_half.hip
hipcc kernel_half.hip
./a.out

on an AMD machine (here MI250), we get:
Hey
Thread id: 0
Thread id: 1
Thread id: 2
Thread id: 3
Thread id: 4
Thread id: 5
Thread id: 6
Thread id: 7
Thread id: 8
Thread id: 9
Thread id: 10
Thread id: 11
Thread id: 12
Thread id: 13
Thread id: 14
Thread id: 15
Thread id: 16
Thread id: 17
Thread id: 18
Thread id: 19
Thread id: 20
Thread id: 21
Thread id: 22
Thread id: 23
Thread id: 24
Thread id: 25
Thread id: 26
Thread id: 27
Thread id: 28
Thread id: 29
Thread id: 30
Thread id: 31
[THREAD 0] scale 0.035000
[THREAD 1] scale 0.035000
[THREAD 2] scale 0.035000
[THREAD 3] scale 0.035000
[THREAD 4] scale 0.035000
[THREAD 5] scale 0.035000
[THREAD 6] scale 0.035000
[THREAD 7] scale 0.035000
[THREAD 8] scale 0.035000
[THREAD 9] scale 0.035000
[THREAD 10] scale 0.035000
[THREAD 11] scale 0.035000
[THREAD 12] scale 0.035000
[THREAD 13] scale 0.035000
[THREAD 14] scale 0.035000
[THREAD 15] scale 0.035000
[THREAD 16] scale 0.035000
[THREAD 17] scale 0.035000
[THREAD 18] scale 0.035000
[THREAD 19] scale 0.035000
[THREAD 20] scale 0.035000
[THREAD 21] scale 0.035000
[THREAD 22] scale 0.035000
[THREAD 23] scale 0.035000
[THREAD 24] scale 0.035000
[THREAD 25] scale 0.035000
[THREAD 26] scale 0.035000
[THREAD 27] scale 0.035000
[THREAD 28] scale 0.035000
[THREAD 29] scale 0.035000
[THREAD 30] scale 0.035000
[THREAD 31] scale 0.035000
[THREAD 0] scale after memcpy: 679159931
[THREAD 1] scale after memcpy: 679159931
[THREAD 2] scale after memcpy: 679159931
[THREAD 3] scale after memcpy: 679159931
[THREAD 4] scale after memcpy: 679159931
[THREAD 5] scale after memcpy: 679159931
[THREAD 6] scale after memcpy: 679159931
[THREAD 7] scale after memcpy: 679159931
[THREAD 8] scale after memcpy: 679159931
[THREAD 9] scale after memcpy: 679159931
[THREAD 10] scale after memcpy: 679159931
[THREAD 11] scale after memcpy: 679159931
[THREAD 12] scale after memcpy: 679159931
[THREAD 13] scale after memcpy: 679159931
[THREAD 14] scale after memcpy: 679159931
[THREAD 15] scale after memcpy: 679159931
[THREAD 16] scale after memcpy: 679159931
[THREAD 17] scale after memcpy: 679159931
[THREAD 18] scale after memcpy: 679159931
[THREAD 19] scale after memcpy: 679159931
[THREAD 20] scale after memcpy: 679159931
[THREAD 21] scale after memcpy: 679159931
[THREAD 22] scale after memcpy: 679159931
[THREAD 23] scale after memcpy: 679159931
[THREAD 24] scale after memcpy: 679159931
[THREAD 25] scale after memcpy: 679159931
[THREAD 26] scale after memcpy: 679159931
[THREAD 27] scale after memcpy: 679159931
[THREAD 28] scale after memcpy: 679159931
[THREAD 29] scale after memcpy: 679159931
[THREAD 30] scale after memcpy: 679159931
[THREAD 31] scale after memcpy: 679159931
[THREAD 0] int repr scale_back:<PHONE_NUMBER>
[THREAD 1] int repr scale_back:<PHONE_NUMBER>
[THREAD 2] int repr scale_back:<PHONE_NUMBER>
[THREAD 3] int repr scale_back:<PHONE_NUMBER>
[THREAD 4] int repr scale_back:<PHONE_NUMBER>
[THREAD 5] int repr scale_back:<PHONE_NUMBER>
[THREAD 6] int repr scale_back:<PHONE_NUMBER>
[THREAD 7] int repr scale_back:<PHONE_NUMBER>
[THREAD 8] int repr scale_back:<PHONE_NUMBER>
[THREAD 9] int repr scale_back:<PHONE_NUMBER>
[THREAD 10] int repr scale_back:<PHONE_NUMBER>
[THREAD 11] int repr scale_back:<PHONE_NUMBER>
[THREAD 12] int repr scale_back:<PHONE_NUMBER>
[THREAD 13] int repr scale_back:<PHONE_NUMBER>
[THREAD 14] int repr scale_back:<PHONE_NUMBER>
[THREAD 15] int repr scale_back:<PHONE_NUMBER>
[THREAD 16] int repr scale_back:<PHONE_NUMBER>
[THREAD 17] int repr scale_back:<PHONE_NUMBER>
[THREAD 18] int repr scale_back:<PHONE_NUMBER>
[THREAD 19] int repr scale_back:<PHONE_NUMBER>
[THREAD 20] int repr scale_back:<PHONE_NUMBER>
[THREAD 21] int repr scale_back:<PHONE_NUMBER>
[THREAD 22] int repr scale_back:<PHONE_NUMBER>
[THREAD 23] int repr scale_back:<PHONE_NUMBER>
[THREAD 24] int repr scale_back:<PHONE_NUMBER>
[THREAD 25] int repr scale_back:<PHONE_NUMBER>
[THREAD 26] int repr scale_back:<PHONE_NUMBER>
[THREAD 27] int repr scale_back:<PHONE_NUMBER>
[THREAD 28] int repr scale_back:<PHONE_NUMBER>
[THREAD 29] int repr scale_back:<PHONE_NUMBER>
[THREAD 30] int repr scale_back:<PHONE_NUMBER>
[THREAD 31] int repr scale_back:<PHONE_NUMBER>
[THREAD 0] scale_back: 10360.000000
[THREAD 1] scale_back: 10360.000000
[THREAD 2] scale_back: 10360.000000
[THREAD 3] scale_back: 10360.000000
[THREAD 4] scale_back: 10360.000000
[THREAD 5] scale_back: 10360.000000
[THREAD 6] scale_back: 10360.000000
[THREAD 7] scale_back: 10360.000000
[THREAD 8] scale_back: 10360.000000
[THREAD 9] scale_back: 10360.000000
[THREAD 10] scale_back: 10360.000000
[THREAD 11] scale_back: 10360.000000
[THREAD 12] scale_back: 10360.000000
[THREAD 13] scale_back: 10360.000000
[THREAD 14] scale_back: 10360.000000
[THREAD 15] scale_back: 10360.000000
[THREAD 16] scale_back: 10360.000000
[THREAD 17] scale_back: 10360.000000
[THREAD 18] scale_back: 10360.000000
[THREAD 19] scale_back: 10360.000000
[THREAD 20] scale_back: 10360.000000
[THREAD 21] scale_back: 10360.000000
[THREAD 22] scale_back: 10360.000000
[THREAD 23] scale_back: 10360.000000
[THREAD 24] scale_back: 10360.000000
[THREAD 25] scale_back: 10360.000000
[THREAD 26] scale_back: 10360.000000
[THREAD 27] scale_back: 10360.000000
[THREAD 28] scale_back: 10360.000000
[THREAD 29] scale_back: 10360.000000
[THREAD 30] scale_back: 10360.000000
[THREAD 31] scale_back: 10360.000000
CPU result:
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,
    10360.000000,

which is obviously wrong.
To me, the issue stems from the definition of the __half2 struct in rocm include/hip/amd_detail/amd_hip_fp16.h:
        // BEGIN STRUCT __HALF2
        struct __half2 {
        public:
            union {
                static_assert(
                    sizeof(_Float16_2) == sizeof(unsigned short[2]), "");

                _Float16_2 data;
                struct {
                    unsigned short x;
                    unsigned short y;
                };
            };
// truncated

Compare to the definition in CUDA (though the __CUDA_ALIGN__(4) is obscure):
struct __CUDA_ALIGN__(4) __half2 {
    __half x;
    __half y;
// truncated

Replacing the call
scale_back = __half2float(scale_half2.x);

by scale_back = (float)scale_half2.data.x; or by scale_back = __low2float(scale_half2); solves the issue. But I believe this is a bug, given that the CUDA kernel and HIP kernel behave differently, with no error raised. Maybe the hipifier should handle this case?
Related https://github.com/ROCm-Developer-Tools/HIP/issues/3280
cc @ardfork @cjatin

Same here. Want to know if any solutions.

Thanks for reporting this. Will look into it.

You are right, the issue is due to __half2 using unsigned short x,y , it should be __half x, y.
At the moment HIP is doing a cast of unsigned short to half, which is causing this issue.
Wil raise a PR to fix it, which might take some time to get to github. meanwhile to fix it you can manually cast it to __half before calling __half2float. Something like __half2float(*reinterpret_cast<__half*>(&scale_half2.x));

@fxmarty Can you please test with latest ROCm 6.1.0 (HIP 6.1)? If resolved, please close ticket. Thanks!

@ppanchad-amd Just tested, this is fixed thank you.


Fix TypeError in samplers.py by converting int to str

This PR addresses a TypeError that occurs when running the super-glue-t5-prompt task. The error message is as follows:
2024-07-08:00:27:18,051 INFO     [task.py:411] Building contexts for super_glue-wsc-t5-prompt on rank 0...
  0%|                                                                        | 0/104 [00:00<?, ?it/s]
TypeError: can only concatenate str (not "int") to str

I modified samplers.py on line 55 to ensure that all parts being concatenated are strings.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.yhjo seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.

Do you have a specific case that's not working? This is implementation is for multi-target cases.

my command :
lm_eval --model hf \
    --model_args pretrained=EleutherAI/gpt-j-6B,dtype="float16" \
    --tasks super-glue-t5-prompt,mathqa \
    --num_fewshot=2 \
    --device cuda:0 \
    --batch_size auto \
    --trust_remote_code

error message :
2024-07-08:01:08:18,467 INFO     [task.py:411] Building contexts for super_glue-wsc-t5-prompt on rank 0...
  0%|                                                                                | 0/104 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "/mnt/disk1/anaconda3/envs/llm_eval/bin/lm_eval", line 8, in <module>
    sys.exit(cli_evaluate())
             ^^^^^^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/__main__.py", line 375, in cli_evaluate
    results = evaluator.simple_evaluate(
              ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/utils.py", line 395, in _wrapper
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/evaluator.py", line 277, in simple_evaluate
    results = evaluate(
              ^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/utils.py", line 395, in _wrapper
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/evaluator.py", line 393, in evaluate
    task.build_all_requests(
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/api/task.py", line 434, in build_all_requests
    fewshot_ctx = self.fewshot_context(
                  ^^^^^^^^^^^^^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/utils.py", line 395, in _wrapper
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/api/task.py", line 1076, in fewshot_context
    labeled_examples += self.sampler.get_context(doc, num_fewshot)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/mnt/home/yhjo/LLM_EVAL/lm-evaluation-harness/lm_eval/api/samplers.py", line 55, in get_context
    labeled_examples += (
TypeError: can only concatenate str (not "int") to str


Custom refresh rate override

Custom refresh rate setting in MobFox Control Panel (Publisher->My Sites & Apps->Edit Publication) seems to be unhonored by MobFox ad server.
We noticed that server response refresh rate is always 30 secs in our use case.
We're searching for a quick and dirty solution while waiting for the MobFox team to fix the server issue.
Is there any way to override the server response without having to fork the SDK?
Thanks in advance,
Adriano

Hi,
I've quickly implemented such functionality in iOS SDK, you can find it here:
http://mobia.pl/geckonew/ftp/MobFox/fixes/MobFox.embeddedframework.zip
To use it:
Just call  self.bannerView.customReloadTime = timeInSeconds;
when creating banner.

Thanks for the quick fix ;)
We're going to patch our code this way

test if customReloadTime exists
use it to override refresh rate

Please, implement customReloadTime on the next release of the SDK or at least, do not deprecate it until the bug on your servers get fixed.
Thanks in advance,
Adriano

It will be available with next release :)


SyntaxError: Unexpected end of JSON input

How to reproduced:
I'm trying to execute this example:
https://bl.ocks.org/mbostock/c57be63169694093cca028194068ea3b
but i can not because of this: https://github.com/substack/shp2json/issues/23
So, i modify the code, to not used shp2json, in that way:

# Download.
curl -z build/estados.zip -o build/estados.zip http://mapserver.inegi.org.mx/MGN/mge2010v5_0.zip
# Decompress.
unzip -od build build/estados.zip

#Convert the shape file to GeoJSON:
ogr2ogr -f GeoJSON build/states.json build/Entidades_2010_5.shp

#Now use the ndjson-map in the same way from a cat of the GeoJson file:
cat build/states.json | ndjson-map -r d3=d3-geo 'p = d3.geoIdentity().reflectY(true).fitExtent([[10, 10], [960 - 10, 600 - 10]], d), "d3.geoIdentity().reflectY(true).scale(" + p.scale() + ").translate([" + p.translate() + "])"'

but it resulting in:
stdin:1
{
^
SyntaxError: Unexpected end of JSON input

My data:
lsb_release -a
No LSB modules are available.
Distributor ID:	LinuxMint
Description:	LMDE 2 Betsy
Release:	2
Codename:	betsy
node --version
v6.11.2
ogr2ogr --version
GDAL 1.10.1, released 2013/08/26
ndjson-map --version
0.3.1

So, probably you can embed the shp2json inside your own project, fork it, or add an option to load a geojson from a file directly, because the last update of shp2json was a year ago and not appear to be an active project.

Ok, that was that i installed a wrong package. i install shp2json instead of your shapefile. With your shape file it work... Anyway, please considered to add an option to load a geojson file instead of work from an stream...

I've run into the same error. It'd be nice to just load a geojson file instead of always working form a shapefile-to-json stream via shp2json. In my case, I'm working with a csv of points that I'm convert to geojson for mapping.


Hasura: features and deprecations

Version in DipDup: v2.11.0
Latest stable: v2.12.0
Latest: v2.13.0-beta.1
Deprecations

TODO: current table field customizations
TODO: check 2.12
TODO: check 2.13

Features

https://github.com/dipdup-net/dipdup/issues/420
https://github.com/dipdup-net/dipdup/pull/421
https://github.com/dipdup-net/dipdup/issues/289
https://github.com/dipdup-net/dipdup/issues/313
https://github.com/dipdup-net/dipdup/issues/450

Miscellaneous

https://github.com/dipdup-net/dipdup/issues/281

Closing in favor of https://github.com/dipdup-net/dipdup/discussions/502


Remove locals

https://github.com/akrava/software-engineering-methodology-practices/blob/fe840e69c81350029521012809f3327be4ba95f4/practice1/eurodiffusion/eurodiffusion.go#L24
it seems that offset* are used only once, remove them

Thanks for finding this defect. I agree that we need to make some enhancements in order to remove locals

I've opened PR #7 in order to merge enhancement and fix this issue.

Fixed in https://github.com/akrava/software-engineering-methodology-practices/commit/1aa7ba975aba74f14b7d0453315ede72ea32ddba. Feel free to reopen if needed


add return_fig param such as pyfolio

I use pyfolio and alphalens both. They are awesome!
I notcie that the tears in pyfolio have been added a param named return_fig to return the figure object of the tear, which is convenient to export fig as png/pdf. I hope this feature can also be implemented in alphalens.

https://github.com/xgdgsc/alphalens I added return_fig for create_* functions in tears.py, you can use it from there. If any project member see it appropriate, I will send a PR.

@xgdgsc looking fforward to the pr.


Travis CI broken - ONNX

🐛 Bug
Currently, Travis CI is broken and crashes on  test/test_onnx.py .Fatal Python error: Aborted
https://travis-ci.org/github/pytorch/vision/jobs/743793912#L722
cc @seemethere @neginraoof

@neginraoof could you please take a look this issue ?

FYI I'm removing TravisCI and temporarily removing ONNX tests in https://github.com/pytorch/vision/pull/3137.
They should be re-enabled in CircleCI

@fmassa - just curious, is there a reason why ONNX tests cannot be ported along with other tests to CircleCI as part of your PR. https://github.com/pytorch/vision/pull/3137

@spandantiwari they can be ported to CircleCI, I just didn't do it before because our reference for the ONNX CI up to now (which was TravisCI) has been failing with segfaults, and the failure was probably related to the ORT version being used.

Fixed with https://github.com/pytorch/vision/pull/3144


Add Rating as a search option for replays in vault

How to view and sort replays by player rating in either live, online or local replays?

I think we had that but it meant that if u searched for rating >1000 only one player had to had >1000 plus for the game to appear and we can not change that. And because ppl did not get that we removed it.

Maybe add that option and name it "Any player's rating"  but also rename all other options that act in the same way as "any ...."


use case: train network on remote machine using Exodus, deploy trained network on chip on local machine without GPU

we should make sure that this workflow is supported

currently this throws:

raise RuntimeError(‘Error(s) in loading state_dict for {}:\n\t{}’.format(
RuntimeError: Error(s) in loading state_dict for Sequential:
Unexpected key(s) in state_dict: “1.activations”, “4.activations”, “8.activations”, “12.activations”.

When calling the load_state_dict method, you can just set strict=False , then you should not get this error.
However, the deeper reason for this is that the Exodus layers have activations registered as buffers, whereas the standard sinabs layers don't. I think we should implement the same behavior for both.
Including the activations in the buffers ensures through the is_state_initialized and state_has_shape methods that the activations are initialized with correct shape.

I recently ran into this error myself and I think with strict=False it's actually alright. Sinabs just doesn't need to make use of an additional activation state which costs additional memory. Although we could of course adapt it for the sake of it. My issue is more that it's not documented somewhere.

This could be included in the How-to section of the documentation.
Should be resolved by consistent API/naming convention.

The additional activation state has been removed from exodus and unit tests have been introduced to ensure that state dicts can be transferred between both backends without any issues.

amazing


Adding sample CODE_OF_CONDUCT.md

@redhatrises Hey Gabe - you had some ideas on how to use these templates to cascade into other CRWD projects. Can you describe that again?

Basically, the idea is to point through a link in the README to the CODE_OF_CONDUCT.md in this project rather than maintaining in everyone's own repo... but also have some sort of way for creating your own CODE_OF_CONDUCT if needed for some reason.

Ah, that makes sense. "Look over there!" and link to this.


Update with the react/datagram instead of clue/datagram

@jolicode could you please try merge this if it looks alright? :)


Updated method signature for issue #52

this should resolve the complaints from Xcode regarding an ambiguous reference, and correctly labels the parameters for makeToastActivity
Issue #52

This API is changing in 3.0.0 (coming soon). There will be different parameter names for position and point. See master.


TimeCube or VScube ?

Should we keep use name TimeCube for UI and tooltips description? Or use new name VScube ? Or how exactly it types correctly now?

The name of the library is timecube. vscube is the name of the VapourSynth interface to timecube.


Introduce Glance Extra Volumes support

The Glance operator can now get rid of the CephBackend specific implementation and rely on the general purpose approach provided by lib-common/modules/storage.
ExtraVolumes are now defined as part of the glance top level crd and can be propagated to the GlanceAPI pods according to the specified policy.
Depends-on: https://github.com/openstack-k8s-operators/lib-common/pull/88
Depends-on: openstack-operator#38
Signed-off-by: Francesco Pantano<EMAIL_ADDRESS>

@abays Not sure here I can really add a dependency on lib-common [1] that can be included in the CI pipeline: I suspect we should keep this change as it is until [1] is available.
[1] https://github.com/openstack-k8s-operators/lib-common/pull/88

@abays Not sure here I can really add a dependency on lib-common [1] that can be included in the CI pipeline: I suspect we should keep this change as it is until [1] is available.
[1] openstack-k8s-operators/lib-common#88

This is now solved: lib-common PR merged and we updated it in go.mod

Patch looks fine to me. I tested this in my environment and it works.


Update openpai-js-sdk version for security alert

Related issue: #5268

Coverage remained the same at 34.237% when pulling 02ce17d8ac0985a506114ecf4837f9cda9159081 on yiyi/dependent/update_openpai_js_sdk_version into 2c605389abb5d7fb63fa54fa1e1bc0f47afef612 on master.


Implements calendar algorithm that returns a list of all available time slots given set of attendees

Description: Created an algorithm that takes in a collection of Events and a meeting request. From the meeting request, it generates a list of all unavailable times for the intended attendees. It then parses through this list and merges any overlapping/redundant time ranges. From this list of unavailable times, it filters the available times and adds them to a list if they are greater than or equal to the duration requested for the meeting.
Next Steps: All given test cases currently pass, need to add optional attendee feature to algorithm and create my own test cases.

Description: Completed optional attendee feature. Now, if there are optional and mandatory attendees with open time slots, algorithm will only return slots that everyone can attend. If the optional attendees can't attend any slots, it will only return time slots for the mandatory attendees. Wrote 5 new unit tests to check that the optional attendee behavior is correct. Passes all 26 unit tests.


theme-test-build

build-fixed-for-theme
This commit is made after running the build server locally earlier the build failed.
#45

What type of PR is this

Proposed Changes

@alabulei1 This PR changes all the colors of the docs or the whole theme, and I think we should decide on a color palette that aligns with WasmEdge Project and its colors.  Here are the screenshots of how it looks like wrt this PR
The HomePage background is pink and for this, we can use the color #654FEF

I feel we can use WasmEdgeRuntime Purple #654FEF here

Hover link colors are not visible here as the background is black and link color is dark blue

On dark theme, the text is not clearly visible and might be confusing to some users

@alabulei1 This PR changes all the colors of the docs or the whole theme, and I think we should decide on a color palette that aligns with WasmEdge Project and its colors. Here are the screenshots of how it looks like wrt this PR
The HomePage background is pink and for this, we can use the color #654FEF

I feel we can use WasmEdgeRuntime Purple #654FEF here

Hover link colors are not visible here as the background is black and link color is dark blue

On dark theme, the text is not clearly visible and might be confusing to some users

I think darker shade of blue, such as navy #654FEF / midnight blue #191970 or red orange for grabbing attention, can provide enough contrast with #654FEF to make links stand out without being too distracting.

#654FEF is great! So should I merge #45 first and then merge #51?

Hi  @Aryanryn09
Since you haven't replied to me for a long time, I will close this PR first. Feel free to reopen this PR.


[HUDI-5850] Fix timestamp(6) field  long overflow

Change Logs
Due to the range of the long type, timestamps using the NANOS unit can only represent values between 1677-09-21 00:12:43 and 2262-04-11 23:47:16. Values outside of this range can not be represented with the NANOS unit.
When timestamp(6) field  greater than "2262-04-11 23:47:16" , then throw  long overflow exception.
Impact
Describe any public API or user-facing feature change or any performance impact.
Risk level (write none, low medium or high below)
If medium or high, explain what verification was done to mitigate the risks.
Documentation Update
Describe any necessary documentation update if there is any new feature, config, or user-facing change

The config description must be updated if new configs are added or the default value of the configs are changed
Any new feature or user-facing change requires updating the Hudi website. Please create a Jira ticket, attach the
ticket number here and follow the instruction to make
changes to the website.

Contributor's checklist

[ ] Read through contributor's guide
[ ] Change Logs and Impact were stated clearly
[ ] Adequate tests were added if applicable
[ ] CI passed

@danny0405 PTAL.


LRC commercialization question

Thank you again for your time this week and the very interesting exchange we had. I was trying to figure out a solution ever since and now I’m left with a question for you:
Let’s say we can convince Comscore to ignore their session start and end notification whenever a channel switch is made and they only react on the analytics metadata that are sent with the stream.
Would it hypothetically be possible the exclude the DVR and seeking case for livestreams and generally send such users which are not live the metadata of a webonly stream. At the same time we would only update the analytics metadata realtime for those that are actually watching live.
How much effort would such a change create? And what would be the best authority to place such a change request?

If the only requirement is, for any livestream (with / without DVR), to be able to refresh analytics metadata corresponding to live conditions so that it reflects what is currently on air:
Letterbox

Apple: Done.
Web: Metadata is correctly updated player-side, but Commanders Act does not take such updates into account.
Android: Does not work yet.

Pillarbox


Implement Asciidoctor macros for release notes documents

This is connected with the new release notes procedure. The current qbk-based mechanism for release notes production makes available some "macros" defined here:
https://github.com/boostorg/website/blob/master/feed/ext.qbk
Many of these macros are not in actual use in the release notes (meaning I haven't seen them used recently or ever). The ones that I've seen are (see the latest qbk-based release notes and the generated output):

[phrase library..XX]: produces a header for the section on lib X.
[@/libs/function/ Function] creates a link to the docs for the library (Function in the example). I understand that
[github_pr geometry 1247]: produces this: PR#1247
[github geometry 1231]: produces this: #1231
[@/tools/build/ Build]: I think this is formally equivalent to [@/libs/function/ Function].

We need to have equivalent Asciidoc macros for the benefit of Boost authors contributing their individual notes in the new release notes procedure.

@daveoconnor  you are an admin of https://github.com/cppalliance/asciidoctor-boost


Metrics: Move metrics to opencensus-api.

Move metrics to opencensus-api, for two reasons:

metrics depends on opencensus-api (api-common), and later opencensus-api (api-stats) needs to depend on metrics. If metrics continue to be an independent artifact, this will introduce circular dependency.
Now that we have MetricsComponent and need to reflectively load the implementation, it's reasonable to separate the API and implementation of metrics.

Codecov Report

Merging #1346 into master will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master    #1346   +/-   ##
=========================================
  Coverage     83.15%   83.15%
  Complexity     1369     1369
=========================================
  Files           219      219
  Lines          6594     6594
  Branches        601      601
=========================================
  Hits           5483     5483
  Misses          947      947
  Partials        164      164

Impacted Files
Coverage Δ
Complexity Δ

...va/io/opencensus/metrics/TimeSeriesCumulative.java
100% <ø> (ø)
2 <0> (?)

...rc/main/java/io/opencensus/metrics/TimeSeries.java
100% <ø> (ø)
1 <0> (?)

...n/java/io/opencensus/metrics/MetricsComponent.java
100% <ø> (ø)
2 <0> (?)

.../main/java/io/opencensus/metrics/Distribution.java
94.87% <ø> (ø)
11 <0> (?)

.../src/main/java/io/opencensus/metrics/LabelKey.java
100% <ø> (ø)
2 <0> (?)

...pi/src/main/java/io/opencensus/metrics/Metric.java
91.66% <ø> (ø)
4 <0> (?)

...rc/main/java/io/opencensus/metrics/LabelValue.java
100% <ø> (ø)
2 <0> (?)

...a/io/opencensus/metrics/export/MetricProducer.java
0% <ø> (ø)
0 <0> (?)

...n/java/io/opencensus/metrics/MetricDescriptor.java
100% <ø> (ø)
2 <0> (?)

api/src/main/java/io/opencensus/metrics/Value.java
100% <ø> (ø)
4 <0> (?)

... and 6 more

Continue to review full report at Codecov.

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Holding off this PR for the moment, since we want to finish the data models first.

Please write a big warning in the package-info that this package (classes from io.opencensus.metrics* are very experimental and users should be aware that we may change them in the future).

Please write a big warning in the package-info that this package (classes from io.opencensus.metrics* are very experimental and users should be aware that we may change them in the future).

SG, I updated package-info.java about the potential backwards-incompatible changes in metrics.

Rebased, going to merge this PR once CI is green.


ddot returns value inconsistent with sum(a*b) on newer Intel CPUs

I'm using OpenBLAS 0.3.18 (apparently), from anaconda3, and for this simple fortran program I get an output that is different from 0 by of order 1e-16 on some Intel CPUs (it's not threading, or at least setting OPENBLAS_NUM_THREADS=1 doesn't change it).  With MKL the difference is 0 for all CPUs I've tried.  I have to admit that I'm a bit confused by the anaconda3 versioning, so if there's a canonical version of OpenBLAS (that'd run on CentOS 7), I'd be happy to compare to that.
program test_dot
implicit none
      double precision :: p(3), v(3)
      double precision, external :: ddot
      double precision :: val_sum, val_dot

      p = (/ 16.90513420661038423986610723659396171569824218750000D0, &
             0.50000000000000000000000000000000000000000000000000D0, &
             -1.71583683999999991875995419832179322838783264160156D0 /)
      v = (/ 0.01628648030646704172874628113731887424364686012268D0, &
            -0.17188353256547875269610869963798904791474342346191D0, &
            -0.98498264035059979182307188239064998924732208251953D0 /)

    val_sum = sum(p*v)
    write (*, '(A15,F55.50)') "sum", val_sum
    val_dot = ddot(3, p, 1, v, 1)
    write (*, "(A15,F55.50)") "dot", val_dot
    write (*, '(A15,F55.50)') "dot - sum", (val_dot - val_sum)

end program

The newest CPU that does not show a difference is
Intel(R) Xeon(R) CPU E5-2630 v3 @ 2.40GHz
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm epb invpcid_single intel_ppin ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm xsaveopt cqm_llc cqm_occup_llc dtherm ida arat pln pts md_clear spec_ctrl intel_stibp flush_l1d

and the oldest that does is
Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz
flags           : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc aperfmperf eagerfpu pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch epb cat_l3 cdp_l3 invpcid_single intel_ppin intel_pt ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke md_clear spec_ctrl intel_stibp flush_l1d

Why dont you use v0.3.20 that has important AVX-512 fixes?
If you take newest CPU and set OPENBLAS_CORETYPE=HASWELL - does it start working?

Thanks.  I'll test that version and update this issue.

The numerical error is of order 1e-16, which I agree isn't unreasonable for double precision, but it's inconvenient for unit testing that it's so CPU dependent.  I guess even if this doesn't happen in v0.3.20, I'll need to work around it in my unit testing, because it needs to work with anaconda3/numpy which packages 0.3.18 for now.
Adding OPENBLAS_CORETYPE=HASWELL does make the two expressions equal, yes, so that's a possible workaround for me (as is fundamentally modifying my unit test, I guess).
I've so far been unable to compile 0.3.20 with either gcc 7 or gcc 10. With 10.3.0 I get an internal compiler error (seg fault) compiling sblat1, and with 7 I get an error compiling dasum.c.  If you have any suggestions for setups that are known to work or sources for binary versions for CentOS 7 x86_64, I'd appreciate any suggestions.
../kernel/x86_64/dasum_microk_skylakex-2.c: In function ‘dasum_kernel’:
../kernel/x86_64/dasum_microk_skylakex-2.c:42:38: error: incompatible type for argument 1 of ‘_mm512_abs_pd’
             accum_0 += _mm512_abs_pd(_mm512_load_pd(&x1[i + 0]));
                                      ^~~~~~~~~~~~~~

If you feel that this is just the expected level of accuracy, I'd completely understand if you close the issue as is.  If you want me to pursue it further by testing in the latest version, I'd be happy to continue trying.

The problem is that later calculations build upon earlier ones, and that process is unstable. I do know how to fix it in my tests, and I agree that it's not necessarily indicative of an OpenBLAS bug (although if there are avx512 fixes in later versions, it might be). As I said, I'm happy for this issue to be closed or kept open, if anyone cares, until I determine whether or not it also happens in 0.3.20.

CentOS7

I doubt that 0.3.20 will be any different - no change in the AVX512 ddot microkernel there, the "issue" is probably that it accumulates intermediate results at higher precision. (And I suspect you could run into the same kind and magnitude of problem with compiler optimizations alone...)

The point is that tests need to acknowledge
(1/2^52)*log2(floating point operations per result value) inaccuracy by abs(a-b)< inaccuracy
It cannot be == comparison.

As per faq/softwarecollections web
yum install centos-release-scl-rh
yum install make perl devtoolset-7-gcc-gfortran

$ scl enable devtoolset-7 -- make -s DYNAMIC_ARCH=1 TARGET=CORE2 NUM_THREADS=128

 OpenBLAS build complete. (BLAS CBLAS LAPACK LAPACKE)

  OS               ... Linux
  Architecture     ... x86_64
  BINARY           ... 64bit
  C compiler       ... GCC  (cmd & version : cc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5))
  Fortran compiler ... GFORTRAN  (cmd & version : GNU Fortran (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5))
  Library Name     ... libopenblasp-r0.3.20.a (Multi-threading; Max num-threads is 128)
  Supporting multiple x86_64 cpu models with minimum requirement for the common code being CORE2

To install the library, you can run "make PREFIX=/path/to/your/installation install".

The scal enable ... make ... command gives the same error as I was getting before with gcc 7.3.0 (which was the scl version, just invoked in a different way), specifically
> scl enable devtoolset-7 -- make -s  DYNAMIC_ARCH=1 TARGET=CORE2 NUM_THREADS=128
In file included from ../kernel/x86_64/dasum.c:8:0:
../kernel/x86_64/dasum_microk_skylakex-2.c: In function ‘dasum_kernel’:
../kernel/x86_64/dasum_microk_skylakex-2.c:42:38: error: incompatible type for argument 1 of ‘_mm512_abs_pd’
             accum_0 += _mm512_abs_pd(_mm512_load_pd(&x1[i + 0]));
                                      ^~~~~~~~~~~~~~
In file included from /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h:45:0,
                 from ../kernel/x86_64/dasum_microk_skylakex-2.c:6,
                 from ../kernel/x86_64/dasum.c:8:
/opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/avx512fintrin.h:7301:1: note: expected ‘__m512 {aka __vector(16) float}’ but argument is of type ‘__m512d {aka __vector(8) double}’
 _mm512_abs_pd (__m512 __A)
 ^~~~~~~~~~~~~
In file included from ../kernel/x86_64/dasum.c:8:0:
../kernel/x86_64/dasum_microk_skylakex-2.c:43:38: error: incompatible type for argument 1 of ‘_mm512_abs_pd’
             accum_1 += _mm512_abs_pd(_mm512_load_pd(&x1[i + 8]));
                                      ^~~~~~~~~~~~~~
In file included from /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h:45:0,
                 from ../kernel/x86_64/dasum_microk_skylakex-2.c:6,
                 from ../kernel/x86_64/dasum.c:8:
/opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/avx512fintrin.h:7301:1: note: expected ‘__m512 {aka __vector(16) float}’ but argument is of type ‘__m512d {aka __vector(8) double}’
 _mm512_abs_pd (__m512 __A)
 ^~~~~~~~~~~~~
In file included from ../kernel/x86_64/dasum.c:8:0:
../kernel/x86_64/dasum_microk_skylakex-2.c:44:38: error: incompatible type for argument 1 of ‘_mm512_abs_pd’
             accum_2 += _mm512_abs_pd(_mm512_load_pd(&x1[i +16]));
                                      ^~~~~~~~~~~~~~
In file included from /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h:45:0,
                 from ../kernel/x86_64/dasum_microk_skylakex-2.c:6,
                 from ../kernel/x86_64/dasum.c:8:
/opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/avx512fintrin.h:7301:1: note: expected ‘__m512 {aka __vector(16) float}’ but argument is of type ‘__m512d {aka __vector(8) double}’
 _mm512_abs_pd (__m512 __A)
 ^~~~~~~~~~~~~
In file included from ../kernel/x86_64/dasum.c:8:0:
../kernel/x86_64/dasum_microk_skylakex-2.c:45:38: error: incompatible type for argument 1 of ‘_mm512_abs_pd’
             accum_3 += _mm512_abs_pd(_mm512_load_pd(&x1[i +24]));
                                      ^~~~~~~~~~~~~~
In file included from /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h:45:0,
                 from ../kernel/x86_64/dasum_microk_skylakex-2.c:6,
                 from ../kernel/x86_64/dasum.c:8:
/opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/avx512fintrin.h:7301:1: note: expected ‘__m512 {aka __vector(16) float}’ but argument is of type ‘__m512d {aka __vector(8) double}’
 _mm512_abs_pd (__m512 __A)
 ^~~~~~~~~~~~~
make[1]: *** [Makefile.L1:683: dasum_k_SKYLAKEX.o] Error 1
make[1]: *** Waiting for unfinished jobs....
make: *** [Makefile:174: libs] Error 1

This was #2949, determined to be a header bug in gcc-7.3.0. (A simple patch was proposed as a workaround in #2999, perhaps I should merge it after all, if this keeps biting people). Can't really help with the gfortran-10.3 ICE in sblat1.f, except you could hack the Makefile in test to remove the "level1" BLAS tests from the "all .." line near the top.

scl enable devtoolset-7 -- $SHELL
$ gcc --version
gcc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5)
$ gfortran --version
GNU Fortran (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5)
$ as --version
GNU assembler version 2.28-11.el7
This assembler was configured for a target of `x86_64-redhat-linux'.

Perhaps our scl devtools are not up to date, since I'm getting gcc 7.3.0, so I'll see if that needs to be done (note that we're using CentOS 7, not 6).
By the way, we now have an example (from a piece of software that's too complex to be useful as a test case here, I think), that using the explicit sum is noticeably better behaved than ddot (in this case that's actually python vs. numpy np.dot), which might indicate that whatever OpenBLAS is doing is systematically less accurate than it could be.  I'll try to find a way to test this explicitly for a simple case, and post it later today.

Please follow the rituals from FAQ - install release/repo package, then target package.
(dressing my work-for-bread hat)
do package-cleanup --orphans // --leaves // rpm -Va // yum distribution-synchronization and clean up whatever half-installs are there,
in principle I dont see anthing holding you back from (as) clean (as possible) devtoolset-11 install.

Please follow the rituals from FAQ - install release/repo package, then target package. (dressing my work-for-bread hat) do package-cleanup --orphans // --leaves // rpm -Va // yum distribution-synchronization and clean up whatever half-installs are there, in principle I dont see anthing holding you back from (as) clean (as possible) devtoolset-11 install.

I'm afraid I don't know what FAQ you're referring to exactly.  I went to the FAQ I could find https://github.com/xianyi/OpenBLAS/wiki/faq, and I don't see any procedures that refer to anything in your message.    Regardless, I did as much of the commands you list as I could without breaking this production machine (e.g. distribution-synchronization wanted to downgrade ucx, which would break out MPI), but none indicated they wanted to do anything related to compilers or devtoolset.
I was never able to get OpenBLAS v0.3.20 compiled with devtoolset-7, even after upgrading it to 7.3.1, but with devtoolset-11 it did compile.  I'll try with that, and let you know what happens.

OK - no change between anaconda's v0.3.18 and my devtoolset-11 compiled v0.3.20, consistent with the fact that the ddot kernel hasn't changed.
I've also now compared double precision "manual" multiplication and summation, quad precision manual multiplication and summation, and OpenBLAS ddot. As someone above suggested, the ddot expression does appear to be more accurate - it's certainly closer to the quad precision sum(a*b) result.
Closing this issue, since OpenBLAS is more accurate, not less (although now I'm not sure why using OpenBLAS makes our code converge less well, but that's probably not related to OpenBLAS itself).

CentOS7 or use package from fedora EPEL which is compiled without AVX-512 support.

https://github.com/xianyi/OpenBLAS/wiki/Faq#binutils

Well, OpenBLAS is not that monolithic, could be there is another function you use that actually has lower precision. (One hint could be if convergence varies between cpu generations). Or there is some spot in your production code where it tries to compare floating point values to exact zero (or to each other) without allowing for some suitable epsilon.

@brada4 I don't know why it's not working, but I can assure you that with devtoolset-7 my compilers report the same versions as you posted above, I'm using a fresh git clone + checkout v0.3.20, and it gives the error I reported earlier. I'll post the output.
@martin-frbg I agree that our code may well be doing things in lower precision someplace else.  The thing I find weird is that it's doing a gradient-based minimization (preconditioned LBFGS), and the failure mode is what we expect when the gradients, which are computed analytically, are not sufficiently accurate, i.e. not consistent with the computed quantity which is being minimized. I'm surprised that increasing the precision in one place by using ddot (actually numpy.dot, but I believe it's calling ddot) makes the gradients and value less consistent.  Of course there's a limit to how accurate they can be due to roundoff, but I find it very surprising that doing two things inaccurately is less well behaved than one inaccurately and one accurately.  It's possible, of course, but just surprising (to me).  I'd expect the overall accuracy (i.e. consistency of the gradient and value) would be the same, because it's dominated by the least accurate (or least numerically stable, anyway) operation.  I guess one possibility is that numpy.dot is not calling ddot, but rather some other BLAS or LAPACK function, and that function really does have a bug that makes it less accurate in the presence of the newer CPUs (probably avx512).  I'll try to confirm that np.dot calls ddot, and if not, do a pure OpenBLAS test of whatever it calls.

Here's the output from compiling a fresh v0.3.20 from an scl enable devtoolset-7 -- $SHELL shell with the error.
openblass_err.txt

Your actions look absolutely correct.
Please yum reinstall /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h
I have this
e0fb930cf376411fa9ff58eba8edd4f89976a38c  /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h

devtoolset7 gcc malfunctions in presence of system gcc. use devtoolset 11, i will bisect and up faq version.

Your actions look absolutely correct. Please yum reinstall /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h I have this e0fb930cf376411fa9ff58eba8edd4f89976a38c /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h

Sounds like it isn't the issue, but for what it's worth I have c211cc29678c0f465f0a19b7985188a0  /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h before and after the yum reinstall, so I'm not sure how that could be different from yours.

No /ust/bin/gcc + devtoolset7 - OK
/usr/bin/gcc + devtoolset7  -KO
any + devtoolset8 - OK

i reinstalled and insist on my sha1sym ;-) really makes little sense, i trust you did same thing as me...

You didn't say "sha1sum" -   I was using "md5sum".  SHA1 is the same as yours e0fb930cf376411fa9ff58eba8edd4f89976a38c  /opt/rh/devtoolset-7/root/usr/lib/gcc/x86_64-redhat-linux/7/include/immintrin.h.  I'm not sure if that makes it more or less weird.

We have same file, no ghosts. But devtoolset-8+ is needed as per my testing.

From the time the patch for the gcc problem was posted on the gcc mailing lists (something like two weeks before 7.4 was released), I assume it first appeared in gcc-7.5.0 So if devtoolset-7 is 7.3.1 it is stilll too old.
I have not  looked up if including the cast (from the old PR) would cost anything in terms of precision or performance, but I guess at worst it could be made codintional on `if defined __GNUC_PREREQ and GNUC_PREREQ(7,5) --except there will probably be numerous other reasons to upgrade gcc when using AVX512

I built TARGET=SKYLAKEX with devtoolset-8 gcc (GCC) 8.3.1 20190311 (Red Hat 8.3.1-3) and updated FAQ accordingly.
Seems there is something that downgrades to AVX2 when devtoolset-7 is used without system gcc, and I cannot giuess dependency.
I am sure you find if documented when you click on documentation links provided to you twice.


Use the same empty string literal

What problem is this PR intended to solve?
Avoidable extra memory allocation
While profiling a project to optimize memory usage, the following came to my notice:
Allocated String Report
-----------------------------------
    154375  ""
     88132  nokogiri-1.10.7/lib/nokogiri/xml/node.rb:767

which is:
https://github.com/sparklemotion/nokogiri/blob/e6b3229ec53ddf70f1d198bba0d3fc13fde842a8/lib/nokogiri/xml/node.rb#L767
The explanation is that 'a string of any length' * 0 == "".
String#* generates a new string even if string literals are frozen via the pragma.
Therefore, if the above line was executed (with indent_times == 0) a 100 times, there would be an allocation of 100 empty strings (irrespective of indent_text) .
This PR replaces this deterministic allocation with a single frozen string literal.
(Hope the native method doesn't mutate it).
Have you included adequate test coverage?
No change in behavior.
Does this change affect the C or the Java implementations?
N/A

Strange.. this didn't have an affect at all.. :frowning_face:
Allocated String Report
-----------------------------------
    154390  ""
     88132  nokogiri-1.10.7/lib/nokogiri/xml/node.rb:767

https://github.com/sparklemotion/nokogiri/blob/e6b3229ec53ddf70f1d198bba0d3fc13fde842a8/lib/nokogiri/xml/node.rb#L767

Allocated String Report
-----------------------------------
    154393  ""
     88132  nokogiri-1.11.0.rc1/lib/nokogiri/xml/node.rb:780

https://github.com/sparklemotion/nokogiri/blob/8ce75d120acfe6a04d3e2c158d48050286ad3816/lib/nokogiri/xml/node.rb#L780

@ashmaroli are you saying you didn't test it both ways before submitting the PR? or are you saying the change didn't make it into 1.11.0? i'm a little confused by your response.

OK - Please explain to me how you're profiling so I can either revert or fix.

I've opened a new issue, #1986, to investigate. @ashmaroli I'd love your help there.


Add flag -swift-async-framepointer=auto,never,always to control swift extended frame information emission

On linux we default to disable the extended frame info (since the system
libraries don't support it).
On darwin the default is to automatically choose based on the deployment target.
The Concurrency library explicitly forces extended frame information and the
back deployment library explicitly disables it.

test with https://github.com/apple/llvm-project/pull/3245
@swift-ci test

Build failed
Swift Test OS X Platform
Git Sha - 592704ecffd1f88f1bd02e7bbc80d5ca3cba46d9

test with apple/llvm-project#3245
@swift-ci test

Build failed
Swift Test OS X Platform
Git Sha - 592704ecffd1f88f1bd02e7bbc80d5ca3cba46d9

test with apple/llvm-project#3245
@swift-ci test

Build failed
Swift Test OS X Platform
Git Sha - fad16c86a61b27db80f8e68edf61f67d0369ed73

test with https://github.com/apple/llvm-project/pull/3255
@swift-ci test

@swift-ci test

This pull breaks building the stdlib with a regular clang, ie not the Swift-forked one, on my Android CI. Since that compatibility has been maintained so far, maybe a new CMake flag can be added to only add flags like this for the Swift-forked clang?


100th commit

It has been 25 days since our first commit. Now, this is our 100th commit. Who WILL do the 100th commit?
Qualified:

@UnknownUser1837
@UnknownUser2129
@NSCPyCor
@UnknownUser9561
@UnknownUser2222
Chances are MEDIUM; 1 in 6 odds you will do it.

The 100th commit will be from @NSCPyCor!

Thanks!!!


Documentation for the Docker Compose Application Update Module

Requires mendersoftware/app-update-module#31 (app-gen fix) and mendersoftware/app-update-module#30 (update module fixes) to work.

Any hints on why the internal link checker cannot resolve the header fragments is appreciated :)

Not sure I'll be able to review this until Friday.
My minimal threshold for giving it a green light will be:

The example can be executed on the RPi demo image
It replaces the community container update module in the Getting started - I see no reason the official one shouldn't take priority

The example can be executed on the RPi demo image

The fixes I reported in the initial comment are now merged into master. I was using the RPi 4 demo image to test the snippets.

It replaces the community container update module in the Getting started - I see no reason the official one shouldn't take priority

I would like to get @tranchitella input here. There have already been several twists and turns in this ticket, and I'm not too keen on escalating this ticket beyond the requirements without making a follow-up ticket for restructuring the docs.

@TheMeaningfulEngineer @estape11 @MuchoLucho Are there any plans for another round of reviews? I'm a bit lost about what to do with this one.

@TheMeaningfulEngineer @estape11 @MuchoLucho; I squashed all the commits and fixed the internal links. I also moved the section as a sub-chapter of "Create an artifact"  and renamed the chapter to "Tutorial: Docker Compose update", the rest of the content is the same. Could I get a quick review on the updated docs structure?

@alfrunes we added the final minor corrections. We reviewed, re-reviewed and tested and we agreed it is complete.
Thank you for your openness and patience throughout this review.

I added the changes based on your feedback. I also replaced the paragraph that was moved to the beginning. You can see the diff from the previous version here.

We are all set, thanks @alfrunes

Thanks @estape11 and the CE team :smile_cat:
@TheMeaningfulEngineer I'm still blocked from merging, I need your approval as well.


how to save all history？

it seems can not save history.do you have plan to add this features？

What do you mean "save"?

I like this idea! There could be an "Export" button on the top of the screen, that when clicked, it would save the messages in a .md file, in a format like this:
# ChatALL History

## User
Hi!

## ChatGPT
Hello! How can I assist you today?

## Claude
Hello! Nice to meet you. I'm Claude, an Al assistant created by Anthropic, PBC to be helpful,
harmless, and honest. How can I assist you today?

## Bing
Hello! How can I help you today?

## Bard
Hi there! How can I help you today?

## User
Please, explain quantum computing in simple terms.

## ChatGPT
(...)

I would also love to have a thread view with filterable responses and continuation support.
For example there would be a sidebar with your recent threads, and by default it would start a new chat.
Each thread would have a multiple select at the top allowing you to select the engines to view (previous) responses from. This would simply filter out the responses from the other AIs.

Yes, I need the feature too.

您好，作者，我的意思如何把聊天记录按天导出到本地保存起来，谢谢。

强烈希望能够添加这一功能

Thanks!


Add a data front-end

This PR is in support of #40.
It add the reformat/selectrows  MLJModelInterface.jl data front-end. It also does a bit of cleaning up and adds generic integration tests from MLJTestInterface.jl.
The other test code changes are just adaptions of the existing tests necessary because of the data front-end addition, which changes all the fit/predict signatures.
I have also locally verified that level-4 tests from MLJTestIntegration.jl also pass.

Codecov Report

Merging #41 (39cdbbe) into dev (0f86996) will increase coverage by 10.89%.
The diff coverage is 100.00%.

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@@             Coverage Diff             @@
##              dev      #41       +/-   ##
===========================================
+ Coverage   86.88%   97.77%   +10.89%
===========================================
  Files           1        1
  Lines         122       90       -32
===========================================
- Hits          106       88       -18
+ Misses         16        2       -14

Impacted Files
Coverage Δ

src/MLJDecisionTreeInterface.jl
97.77% <100.00%> (+10.89%)
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@tylerjthomas9 Having just done this for CatBoost.jl, you will be quite familiar with the data front-end API. Any chance you have the bandwidth for a review some time in the next week or so?

This is not in the PR, but 10 seems like a small default value for n_trees with the random forest models. I feel like 100 is a solid default parameter, and should give better results out of the box.
Other than the comment I left, everything looks good to me. You are already working on adding a warm start method for random forest models, and I think that'll also be a great addition.

@tylerjthomas9  Thanks for the review.

Re default, I've posted #43


Cherry pick pr 7678

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Hi @dunjut. 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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/cc @quanjielin

/retest

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

Test name
Commit
Details
Rerun command

prow/e2e-bookInfoTests-v1alpha3.sh
3725ec9eea07f142aabae9dbc056adc42479babb
link
/test e2e-bookInfo-envoyv2-v1alpha3

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/retest

/ok-to-test

New changes are detected. LGTM label has been removed.

Not sure why some of the tests keep failing. Just rebased to latest master.

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

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prow/istio-unit-tests.sh
b579874dea974aacb70d6cbc1e95508b9da84b33
link
/test istio-unit-tests

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/retest

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prow/istio-unit-tests.sh
b579874dea974aacb70d6cbc1e95508b9da84b33
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/test istio-unit-tests

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Looks as though one of the unit tests is failing here:
I0921 03:11:17.578] --- FAIL: TestCreateSelfSignedIstioCAWithSecret (0.00s)
I0921 03:11:17.578] 	ca_test.go:168: Failed to create a self-signed CA Options: failed to create CA KeyCertBundle (cannot verify the cert with the provided root chain and cert pool)

/test istio-unit-tests

/retest

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

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b579874dea974aacb70d6cbc1e95508b9da84b33
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/test istio-unit-tests

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prow/istio-pilot-e2e-envoyv2-v1alpha3.sh
b579874dea974aacb70d6cbc1e95508b9da84b33
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/test istio-pilot-e2e-envoyv2-v1alpha3

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/test istio-pilot-multicluster-e2e

/retest

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I would like to add score card of LGMSOC in read me

I as a LGMSOC participants would like to work on it.

Fine.
Add it just beside the Let's Grow More logo.


Issue #34 - Print the additional platforms in the description table column

WIP !
Prints the optional additional platforms in the description column of the Index table.
Also prints the platforms in the recipe's details page.

This is still work in progress! I'll try to make the Index table more dynamic by using https://datatables.net/

Here is the new version of the Package Index page based on DataTables.net:

I tried to keep it similar to the current UI of that page but if you have ideas how to improve its user experience I'll be glad to implement them!
You could try it at https://dc52-212-50-92-101.ngrok-free.app/conda-package_index.html
Note: it runs on my dev machine, so it might be broken sometimes or offline.

Cool, I like it :)

Why does it show just 63 recipes ?

Because building all recipes takes a lot of time :-)
I use BIOCONDA_FILTER_RECIPES=63 make html to build just 63 of them. A random number.
I just built them all:

Added info about noarch recipes:

Any ideas how to detect whether a recipe is enabled for linux-64 and osx-64 ? Those are implicit, i.e. not explicitly listed in meta.yaml, and they could be disabled via build > skip: True # [...]

I think I figured how to list all available platform builds for a recipe by using the RepoData:

I don't have more ideas for improvements for this PR!

@martin-g this is great, thank you!

I'm glad you all like it! :-)


⚠ Bofrost.com has degraded performance

In f62290f, Bofrost.com (https://www.bofrost.com) experienced degraded performance:

HTTP code: 200
Response time: 4641 ms

Resolved: Bofrost.com performance has improved in 50a5d75 after 7 minutes.


How to make chart without Tasks

Clients may use this chart first with no tasks.
So, I want make Default Ganttchart without Tasks. How Can I do resolve this issue??

This was fixed.