Milvus embedding store + Dev services

Unfortunately I had to go with the official Milvus Java client in the end, and that contains some crazy dependencies that probably prevent us from compiling in native for now.
I tried a REST client, but Milvus's REST api seems quite unfinished and doesn't seem to allow specifying the schema of a newly being created collection.
But hey, with this approach, it should be relatively low amount of maintenance work for us, because we basically just take what langchain4j has, without changes.
The bad part is that since we're using their gRPC client it's not integrated with the gRPC extension (so no metrics, tracing etc)

The bad part is that since we're using their gRPC client it's not integrated with the gRPC extension (so no metrics, tracing etc)

Hopefully at some point in the future we can use our own which would allow us to reap the many benefits as you mentioned


Create CONTRIBUTING.md

Created CONTRIBUTING.md explaining how to contribute to the projects of the DCI

@vijayg10 @chris-me-law could you please merge this pull request into the master branch (and/or give either me or @rajdeepaccessh more rights to do so) ? (if you have any questions or want to follow up, please reach out to either me or @rajdeepaccessh)


Indent guide

Great theme - my favorite one on VSCode.  I was wondering if you could add the ability to enable indent guides?  Maybe the same color as comments?

Indent guides are an editor setting and if you enable them you should be seeing subtle guides:

I see them in the solarized light scheme, but not the solarized dark one.

Oh, you're right! They're no use like this. Thanks for catching that.


ChatGPT failed to refresh auth token. Error: Unauthorized

ChatGPT failed to refresh auth token. Error: Unauthorized

@classfang what was the issue you had? Was the session token expired?

I've had the same issue, although I have two session tokens. Have tried both but each have the same error message as above.

@theorigden I'd try clearing your application's local cache in devtools which will forcefully log you out. Then log back in and use the single session token. Let me know how that works.

Okay, seems to work when using a regular account, but not through Google Sign In, which I had been using. Thanks


Fix randomization in AQC plugin unit tests

Summary
On rare occasions the TestAQCSynthesisPlugin.test_with_pass_manager may fail due to unlucky randomization of the initial parameters and the algorithm does not converge with the default number of iterations. This PR aims to fix randomization in the AQC plugin unit tests and make them fully reproducible.
Details and comments
In the CI an error like this may be seen:
      File "D:\a\1\s\test\python\transpiler\aqc\test_aqc_plugin.py", line 100, in test_with_pass_manager
    np.testing.assert_array_almost_equal(np.eye(8), approx_unitary, 3)

      File "D:\a\1\s\test-job\lib\site-packages\numpy\testing\_private\utils.py", line 1046, in assert_array_almost_equal
    assert_array_compare(compare, x, y, err_msg=err_msg, verbose=verbose,

      File "D:\a\1\s\test-job\lib\site-packages\numpy\testing\_private\utils.py", line 844, in assert_array_compare
    raise AssertionError(msg)

    AssertionError:
Arrays are not almost equal to 3 decimals

Mismatched elements: 8 / 64 (12.5%)
Max absolute difference: 0.76537652
Max relative difference: 1.
 x: array([[1., 0., 0., 0., 0., 0., 0., 0.],
       [0., 1., 0., 0., 0., 0., 0., 0.],
       [0., 0., 1., 0., 0., 0., 0., 0.],...
 y: array([[ 7.071e-01-7.071e-01j, -2.841e-06-1.166e-05j,
        -5.438e-06-7.126e-06j, -3.161e-06-4.705e-07j,
         2.074e-06+4.451e-06j, -8.117e-06+1.068e-05j,...

@kdk I was unlucky enough to break the CI in the main branch due to randomization in the AQC plugin unit tests. I hope, I have fixed this randomization issue in this PR. Terribly sorry for the inconvenience caused.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.003%) to 82.756%

Totals

Change from base Build<PHONE_NUMBER>:
0.003%

Covered Lines:
50170

Relevant Lines:
60624

💛  - Coveralls


Use jump table and better code generation without local_const_stream

The commit message "Remove local streams from parse null, true, and false" adds no information beyond what is already obvious from the diff. Consider "Better code generation without local_stream" as an alternative.

Already in #116


README: add badges

I'm going to close this for the following reasons:

There's no need for the license badge, as GitHub inspects the repo and lists the license in the top header.  Clicking on it even opens up the LICENSE file as well as a summary of what the license says.

We don't need a build status.  Build status badges are for projects that are consistently broken.  Every tool on master is expected to compile.

Badges are ugly.


Map pages

created three map control buttons

Also see the explanation in the gc for why the linter tests are failing.


Multiple github repos in same TRAC

You mention in the readme this setting:
[github]
repository = <user>/<project>

I have multiple github repos in the same TRAC env. How should I set them in this config?
As list?

See https://github.com/trac-hacks/trac-github#multiple-repositories.


Simplifying API

This issue was opened to keep track of this PR. Please review it and we can change it according to the comments and decisions that will be made.

@NoelWirzius I don't have permissions to add you as a reviewer.

Is the proposal that we have separate APIs (i.e. separate basePaths) per use case? So if connectivity status was re-introduced, that would be a new API with its own YAML definition?

Is the proposal that we have separate APIs (i.e. separate basePaths) per use case? So if connectivity status was re-introduced, that would be a new API with its own YAML definition?

Hello @eric-murray. Yes, the proposal is to have a portfolio of Device Status APIs. So we can call this API " Device Roaming Status" (which is the only use case that we currently have) and whenever we receive new requirements related to Device Connectivity Status we discuss them again and categorize them (if they’re not related to roaming) as new APIs with their own YAML files with dedicated endpoints.
The users might not be interested in all use cases that can be grouped in a big API and if we gather different kind of status/connectivity in a single API they might be forced to implement the API partially.
Does it work for you?

@monamok
Thanks. There are advantages and disadvantages of both approaches. I just wanted to be sure I understood what was being proposed. I think I would prefer a common basePath for anything that was considered to be a "device status", even if each path (i.e. use case) was published in a separate YAML file. I'll discuss internally.
Another question is that PR #21 is also proposing changes to the API definition. Either could be merged at the moment, but after the first is merged, the other will need to be re-based. Is it agreed which should be merged first?

I'll discuss internally.
@eric-murray, of course. Please let us know.

@NoelWirzius can we please have also your feedback about this?

Another question is that PR https://github.com/camaraproject/DeviceStatus/pull/21 is also proposing changes to the API definition. Either could be merged at the moment, but after the first is merged, the other will need to be re-based. Is it agreed which should be merged first?

I already mentioned this point in the issue [#22] (https://github.com/camaraproject/DeviceStatus/issues/22) that I opened for this PR. If PR #21 get merged before this one, I'll update my branch with the approved changes so there's no conflict. The only thing we should decide is if we keep the version or should we update it too?

@monamok
I discussed with our developers, and they much prefer to have separate basepaths for different API definitions (i.e. different YAML files). So I'm happy to tie the basepath to the use case (i.e. /device-roaming-status). though do wonder if we should keep the path itself as status rather than also changing that to roaming.
I'm also awaiting feedback from @NoelWirzius on the order in which PRs should be treated before approving this one.

@eric-murray @monamok
we checked the different pro and cons and the cons are really big in our views. So the maintenance of the APIs will get really complex when we build for everything an own API - then we need to do changes to each API for example changing the naming or adding a new function like "list of devices"
but there are also pros of course
Our suggestion is:

stay at one YAML and adding different Endpoints for each API

Example for Roaming, Connectivity and subscription:
server/devicestatus/v1/roaming
server/devicestatus/v1/connectivity
server/devicestatus/v1/subscriptions
is this sth we can go as a compromise?

@eric-murray  fully agree with you! the same feedback I also got. If we split -> then different YAMLs - but we would prefer a single common YAML with a common basepath and just different endpoints for each "Feature"

I'm also in favor of a common YAML in order to be consistent with other API with several 'sub' function as we have this pattern in number verification API and SIM Swap API. The YAML covers the 'family' and we have several endpoints.
We have distinct YAML for Carrier billing/SIM SWAP/Number Verification when we have distinct flavor of the requirement  (MC vs specific, oma vs specific) but same functions are covered in each YAML.

Thank you @eric-murray @NoelWirzius @bigludo7 for your feedback. Sorry I was trying to resolve the conflicts and I accidentally closed the PR. I'm not sure if someone from the code owners can reopen it or should I open a new PR?
I aligned the YAML file with your comments and I already pushed it to my repo in order to have a dedicated endpoint for roaming as @NoelWirzius suggested with a common base path for future usecases.

I'm not sure if someone from the code owners can reopen it or should I open a new PR?
I was able myself to reopen it :)

Hi Team , if we will go with single YAML file for all related cases (device status) then how the basepath will be defined to create proxy. It would be challenging to have different proxy for individual endpoint (Roaming, Connectivity etc)  and with single porxy, it will make our job more tough to manage Spike, authentication/Authorisation and other security policies for specific requirement.

I'm approving this because it keeps open the question of whether additional statuses (such as connectivity) should be in the same or a separate YAML. When an addition status is proposed, that issue can be addressed then.

@MarkusKuemmerle could you please add again @NoelWirzius as a reviewer. I think he was removed automatically when the PR was reopened. Thanks.


xh: 0.7.0 -> 0.9.1

Motivation for this change
Update to upstream package
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[x] Tested compilation of all pkgs that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[ ] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 117097 at 1a020c7b run on aarch64-linux 1

1 package built successfully:

xh

1 suggestion:

error: no-flags-array
checkFlagsArray is only intended to be used in Bash, not as a Nix attribute.
Near pkgs/tools/networking/xh/default.nix:23:3:
   |
23 |   checkFlagsArray = [ "--skip=basic_options" ];
   |   ^

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/486


Setup cluster with xpack enabled.

Hello all,
I would like to run elasticsearch cluster in kubernetes with isito installed and mtls forced over envoy proxy.
Cluster is running, but if I did not set any security, the cluster members never go to ready  state.
If I enable security, then cluster restarting all time
my values.yaml

elasticsearch:
  clusterName: elasticsearch
  replicas: 2
  volumeClaimTemplate:
    resources:
      requests:
        storage: 8Gi
  securityContext:
    runAsNonRoot: true
    runAsUser: 1000
    capabilities:
      drop: [ALL]
  protocol: https
  roles:
    master: "true"
    ingest: "true"
    data: "true"
  #extraEnvs:
  #  - name: ELASTIC_PASSWORD
  #    valueFrom:
  #      secretKeyRef:
  #        name: elasticsearch-secret
  #        key: password
  #  - name: ELASTIC_USERNAME
  #    valueFrom:
  #      secretKeyRef:
  #        name: elasticsearch-secret
  #        key: username

#  keystore:
#    - secretName: elasticsearch-secret
  #esConfig:
  #  elasticsearch.yml: |
  #    xpack.security.enabled: true
  #    xpack.security.transport.ssl.enabled: true
  #    xpack.security.transport.ssl.verification_mode: certificate
  #    xpack.security.transport.ssl.keystore.path: /usr/share/elasticsearch/config/certs/elastic-certificates.p12
  #    xpack.security.transport.ssl.truststore.path: /usr/share/elasticsearch/config/certs/elastic-certificates.p12
  #    xpack.security.http.ssl.enabled: true
  #    xpack.security.http.ssl.truststore.path: /usr/share/elasticsearch/config/certs/elastic-certificates.p12
  #    xpack.security.http.ssl.keystore.path: /usr/share/elasticsearch/config/certs/elastic-certificates.p12
  secretMounts:
    - name: elastic-certificates
      secretName: elastic-certificates
      path: /usr/share/elasticsearch/config/certs

curl -XGET localhost:9200/_cluster/health?pretty
{
"cluster_name" : "elasticsearch",
"status" : "green",
"timed_out" : false,
"number_of_nodes" : 2,
"number_of_data_nodes" : 2,
"active_primary_shards" : 0,
"active_shards" : 0,
"relocating_shards" : 0,
"initializing_shards" : 0,
"unassigned_shards" : 0,
"delayed_unassigned_shards" : 0,
"number_of_pending_tasks" : 0,
"number_of_in_flight_fetch" : 0,
"task_max_waiting_in_queue_millis" : 0,
"active_shards_percent_as_number" : 100.0

Hi @SCLogo,
We don't have enough informations to help you.
Can you provide the informations requested in the bug report issue template: https://github.com/elastic/helm-charts/issues/new?template=bug_report.md

Closing it as there is not enough details and no answer from author


[ADnD_2E_Revised] Bugfix/ Updated PSP progression to use ned psionic only fields for Con, Int, Wis

Submission Checklist
Required

[X] The pull request title clearly contains the name of the sheet I am editing.
[X] The pull request title clearly states the type of change I am submitting (New Sheet/New Feature/Bugfix/etc.).
[X] The pull request makes changes to files in only one sub-folder.
[X] The pull request does not contain changes to any json files in the translations folder (translation.json is permitted)

Changes / Description
Described in the title of the PR

Character Sheet Info Roll20 Internal Use only.


BLOCK_N in _layer_norm_fwd()

Hello,
First, I wanted to thank the authors of Mamba for your amazing work, and your masterful codebase. I have been tweaking it in many directions for a while now, and it's been a great playground.
I have a question regarding the implementation of layer norm (and I notice it is likely derived from code at triton.org, here):
_layer_norm_fwd() uses the following two lines to compute a BLOCK_N for the given N=x.shape[0]
MAX_FUSED_SIZE = 65536 // x.element_size()
BLOCK_N = min(MAX_FUSED_SIZE, triton.next_power_of_2(N))

It makes sense for BLOCK_N to be the next multiple of memory cache line size (e.g., next multiple of 128), or more precisely, some function of N, x.element_size(), warp_size and cache_line_size, but instead this code uses next_power_of_2(). This sounds excessive, and I wonder if it's a mistake that has been replicated in code bases that copy/use the triton implementation of layer norm. Of course it is common/standard for models to have a power-of-two d_model, and thus this may not cause any overhead. But I wanted to bring it up to your attention and see what your thoughts are.
https://github.com/state-spaces/mamba/blob/a07faffa36a7b89e754b5de972418475bcdd77b6/mamba_ssm/ops/triton/layernorm.py#L150C35-L150C57

Have you tried non-power-of-2? Triton doesn't support non-power-of-2 afaik.

No, I had not tried it. My GPU was busy when I noticed that line of code (and still is), and I thought of asking anyway. You must be right, according to what is said here. Thanks for your time responding.


Add codecov

Codecov Report

:exclamation: No coverage uploaded for pull request base (main@3c4fc99). Click here to learn what that means.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main       #4   +/-   ##
=======================================
  Coverage        ?   95.40%
=======================================
  Files           ?        8
  Lines           ?      283
  Branches        ?        0
=======================================
  Hits            ?      270
  Misses          ?       13
  Partials        ?        0

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


feedback form text box size

Describe the feature
I would like to change the feedback input to a text box because it would be inconvenient  for the user to read his/her feedback.
if increase the height of the text box then the user can read his entire feedback
Add ScreenShots

Record

[X] I agree to follow this project's Code of Conduct
[X] I'm a GSSOC'23 contributor
[X] I want to work on this issue

So can I work on this issue?


chore: fix clippy errors

Needed for #374.

Oh these issues are with generated files!

@hawkw should I have clippy ignore the generated files?

@hawkw should I have clippy ignore the generated files?

yeah, probably...that's annoying. :|

Done.

Alright, it looks to be passing CI. Is squashing enabled for this repo?

squashed

@hawkw I don't have merge permissions for this repo, so you'll have to do it.

Thanks!


chore: use metabase enterprise docker container

@matthieu-foucault @marcellmueller , can we close this?
It's been under "Sprint Done" for about 4 months.


chore: remove packages

Removes pfe-health-index, pfe-icon-panel, pfe-markdown, and pfe-number.
Closes #2122, #2123, #2124, and #2126
Note to reviewers, this PR selects the packages which shouldn't affect the docs site build. Please check that nothing broke there

Built the project, ran the tests and the docs server and it looks good from my end.  Do we also want to remove the references in package-lock.json?  Didn't see anything necessarily change from leaving those in there but wanted to make sure that was on purpose.

@brianferry just run npm i and commit the changes to package-lock.json


Display code failed in Docusaurus 3.4.0

Hi @christian-bromann 👋
Docusaurus 3.4.0 seems to have issue in showing the code

That's not good 🙈 any contribution would be appreciated!

Workaround appears to be using CodeBlock
import CodeBlock from "@theme/CodeBlock";

<CodeBlock language="js" reference>
{`
    https://github.com/christian-bromann/docusaurus-theme-github-codeblock/blob/main/src/theme/ReferenceCodeBlock/index.tsx
`}
</CodeBlock>


fix: quick search tooltip & resize settings icons

This PR...
Changes

added a tooltip for quick search
set setting icons size 18px

Fixes

How to test it

Screenshots

Checklist

[x] tested locally
[ ] added new dependencies
[ ] updated the docs
[ ] added a test

Tooltip message would be Filter results – Hint: quick-filter using CTRL + P


Missing xmlns:image even \Image sub-element was used in sitemap

Hi there!
Maybe I'm wrong... here is an example which generates 2 <url> tags with additional Image and Link parts. The resulting XML does not contains an expected namespaces xmlns:xhtml and xmlns:image.
But if you change the order of adding (addUrl) urls to Urlset:
$urlSet->addUrl($urlB);
$urlSet->addUrl($urlA);

All will be fine, the missing namespaces appears in the output file.

Thanks for the report, going to take a look at this further.

+1

+1


[CRO] Fix validation in Partners Signup Form [FE]

Changes:
Right now we have few unhandled errors while users trying to sign up as partners
This fix updating regex rules in form side to make them the same as third-party service
Type of change

[ ] Bug fix
[ ] New feature
[ ] Update feature
[x] Refactor code
[ ] Translation to code
[ ] Translation to crowdin
[ ] Script configuration
[ ] Improve performance
[ ] Style only
[ ] Dependency update
[ ] Documentation update
[ ] Release

@NikitK-deriv PR title convention please :)


Disable tapping feed items while pending

Description
This PR disables the tapping on feed items while they are in a pending state.
Other changes
Updates to snapshots and mobile tests.
Tested
Tested locally on iOS and Android.
How others should test
Test case - Send From Home Screen

From the home screen send cUSD or cEUR to another account.
While Items displays 'Confirming...' attempt to tap it - It should not load info.
When transaction is no longer pending tap it and view info - It should load info.

Test case - Exchanging

From CELO exchange sell CELO.
While Items displays 'Confirming...' attempt to tap it - It should not load info.
When transaction is no longer pending tap it and view info - It should load info.

Test case - Withdraw CELO

From exchanges withdraw CELO.
While feed item displays 'Confirming...' attempt to tap it - It should not load info.
When transaction is no longer pending tap it and view info - It should load info.

Related issues

Fixes #178

Backwards compatibility
This is a small UI change and is backwards compatible.

Hey @MuckT , We have verified this issue using the Latest Test flight Build V1.21.0(1635160132) & updated the status in the Test Quality Tool.
iOS (13.0):

https://valora.testquality.com/project/12128/plan/22175/run/151573/result/2540329

Verified On Device: iPhone SE (13.6.1)


Invalid type in built-in function 'dict2inst' warning

Hi, I develop a vertical-scrolling game. The obstacles such as enemies, rocks, etc., are generated programatically by instantiating scenes:
var obs = load(obstacle_list[randrange(0,10)] + ".scn").instance()
add_child(obs)
When I tested on my PC (Ubuntu 14.04) everything was OK. Obstacles are generated smoothly. But I got this error message when I run on android (from adb logcat):
"Invalid type in built-in function 'dict2inst'. Cannot convert argument 1 from String to Dictionary."
The game was running, but the obstacles are not generated. No instantiated scene.

Can you still reproduce this issue in the current master branch / nightly builds? If so, do you still have the problem if you prefix "res://" to the string in the load() function?

Could you provide a sample project that reproduces the bug?


Delay gnocchi client creation

During the config phase, the python threading system is not yet
initialized. Making some lib not behaving correctly.
This moves the gnocchiclient setup to the init phase.

Pull-request updated, HEAD is now e8713ba158b8b117d120e5ffc02bf30a05b3883e

This monotonic error seems to be new, but I'd prefer we fix first before merging anything else. I don't know why it does not work here. I imagine the same is going to happen on gnocchiclient gate.

Pull-request updated, HEAD is now a077c15ffa57ca38bfcdd3903bbe9c4275262a49

Pull-request updated, HEAD is now a077c15ffa57ca38bfcdd3903bbe9c4275262a49

Pull-request updated, HEAD is now b7e81461c6467b150648b34ca14e1b8310d2055c

Pull-request updated, HEAD is now c2c8d9837d2340dd7d70c12f1c22a4cfb524afad


Allow pressure coeff to be read from ak & bk data

Description
In order to facilitate integration with existing model, we allow the pressure coefficients AK/BK to be read from data. We keep the same checks and give precedence to the data to keep backward compatibility.
How Has This Been Tested?
Tested on GEOS integration. No unit test present but default behavior did not change.
Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[ ] Any dependent changes have been merged and published in downstream modules
[ ] New check tests, if applicable, are included

PR died because of mpi4py build failing on the setup side of things, will investigate.


material-components-web 0.31.0

Another update to material-components-web
Breaking changes mostly on chips. Hover, focus, and pressed states on card CHANGELOG.

The mdc team is moving at lightspeed. They're now on 0.33.0

What's the plan for the library going forward? The MDC is and has been making a ton of disruptive changes.


[New feature] satisfy the https private key decrypt requirement

1. feature background
As a https server, for better security consideration, user may not keep the  private key(for example: named as tls.key) in a clear text. it may use some encryption algo to encrypt the tls.key for protecting from server inbreak.
so when before use tls.key to create a https connection,  user first decrypt the tls.key.
2. current implementation
now, in the evhtp_ssl_init(),  cfg->privfile is used directly. this means that user should use a unencrypted privfile. user can not use a encrypted privfile.
    SSL_CTX_use_PrivateKey_file(htp->ssl_ctx,
                                cfg->privfile ? cfg->privfile : cfg->pemfile, SSL_FILETYPE_PEM);

3. solution
i'd like add a member callback (for example: decrypt_privfile_cb) in the evhtp_ssl_cfg_t struct. if this callback is set, it will be called to decrypt the privfile and used by SSL_CTX_use_PrivateKey().
@NathanFrench  if this feature is welcome, i can make a commit.  Thanks in Advance.

This is actually a really good idea. Take the security out of the libraries hands.
I welcome this type of ingenuity.

@NathanFrench  Please review the commit.  any suggestions are welcome.
thank you  in advance.
BTW:  i have tested the customize_decrpyt_privfile_cb in my machine and it works ok.

Merged, thank you very much.


Design Product List Page

Good evening boss.
Task received with thanks😐

For desktop,
I have designed the following categories:

popular products
mobile devices
Cameras
Laptops and desktops

For mobile,
I have designed the following categories:

popular products
mobile devices
Cameras
Laptops and desktops(pending)

Product page- DESKTOP

Product page-MOBILE

I recently completed;

Documentation Page
Research Slides on figma
I also conducted the User Research via Word Doc and updated the details on Figjam

Design of Product page-Desktop(completed)

Design of Product page-Desktop Dark Mode(completed)

Design of Product page-Mobile(completed)

Design of Product page-Mobile Dark Mode(completed)


docker image install errors

The Docker image installation instructions have fallen out of date. The following need to be addressed:

As of Docker 19.03 the docker-nvidia2 package is not needed.
rosdep is no longer included by default
The Dockerfile is out of sync with host-based installation instructions, which is causing runtime errors.
The ./run.bash script should support mounting a host-based repositories so the image can be used for development and will stay in sync with the repository.

Fixed with PR #38 Docker install.


AssetLib pagination modifications

Indirectly fixes https://github.com/godotengine/godot/issues/15705
Clicking on single character links are difficult, so changed them into buttons.
Removed cryptic totals line.
Made navigation buttons always visible, so whole pagination doesn't shift when navigating pages.
Old and new comparison.

I think it would be better to write "Previous" in full rather than just "prev". Also, button labels should be capitalized.

It's OK to change the strings for 3.1, translators will have some time to check the new strings.

Capitalized navigation buttons. Should be good now.

LGTM

Changed prev into Previous.
Although prev made symmetry in English locale, I don't think it's important enough to confuse translators or potentially users. And that symmetry only occurs in English anyway.

Thanks!


TextEditor rewrite data-grammar attribute updating regression

Description
It seems like there's a regression with the TextEditor rewrite. The specs for my package css-declaration-sorter-atom suddenly started failing. @Arcanemagus found out that if you place a breakpoint at main-spec.js#L39 then editor.getGrammar() shows what you expect, but the data-grammar property of main-spec.js#L9  hasn't been updated, so the command "doesn't match".
Although editor.GetGrammar() is showing the expected CSS, the data-grammar property of the actual workspaceElement is still only text plain null-grammar. A workaround for now is decreasing the editor specificity.
Steps to Reproduce

Change editor grammar
See editor's data-grammar not being changed

Expected behavior: data-grammar to reflect the currently used grammar.
Actual behavior: data-grammar stays the same.
Reproduces how often: 100%
Versions
Atom    : 1.19.3
Electron: 1.6.9
Chrome  : 56.0.2924.87
Node    : 7.4.0

Hello @Siilwyn and thanks for the bug report! ✨

Although editor.GetGrammar() is showing the expected CSS, the data-grammar property of the actual workspaceElement is still only text plain null-grammar.

The data-grammar attribute is added and updated only on atom-text-editor elements, and never on atom-workspace element. Did you mean "the actual editorElement"?
If so, I am unable to reproduce this locally; when changing the grammar of the editor, the data-grammar attribute seems to update correctly for me. Can you post some reproduction steps that I can follow by opening Atom in safe mode? Thanks!

@Arcanemagus could you shed some light on this? If I log atom.workspace.getActiveTextEditor().getGrammar().scopeName after setting the grammar it does return the proper grammar.

@as-cii @Siilwyn
Assuming you have reverted https://github.com/Siilwyn/css-declaration-sorter-atom/commit/36049ffdd2e02bdb453c91559fb024aec8aff69e locally, here are the steps to reproduce:

Open Atom on the project
For simplicities sake while testing, focus this spec
Run the specs (the focused spec will fail)
Open Developer Tools in the spec window and place breakpoints on these lines:

here
here

Run the specs again
When you hit the first breakpoint on L38, check editor.getGrammar() and note that it has correctly been changed to CSS. For some reason Developer tools doesn't allow access to workspaceElement here, even though it is in the closure, so let the code continue.
You should now hit the breakpoint on L9. Checking workspaceElement.dataset.grammar shows that it is still set to text plain null-grammar.

Note that if you save a reference to editor in the console (var ed = editor) you can access it on the breakpoint on L9 and see that editor still has the correct grammar.

Thanks a ton @Arcanemagus, I can reproduce these steps!

@Ben3eeE hi, could you re-label this issue since a way to reproduce has been given?

/cc: @nathansobo

Bumping the priority on this since it's affecting a package author.

@Siilwyn if I understand the situation correctly, I think your problem may be due to the fact that the dataset.grammar property is now assigned asynchronously along with the rest of the editor updates. In general, it's not a good idea to rely on the state of the DOM for this kind of information. If you have a workaround that interacts directly with the model, I'd recommend sticking with that. I want to keep all of our editor DOM interaction asynchronous where possible going forward, so I'm going to close this. If you think I'm misunderstanding something, please let me know.

Hi @nathansobo I understand however does that mean having grammar specific commands is not possible anymore? The temporary fix just removes the specificity. I would actually expect the grammar to be set when the package is activated. Maybe I'm misunderstanding something too, thoughts?

@Siilwyn I'm seeing the grammar being reassigned when I inspect via the dev tools after switching the grammar.

Your mention of breakpoints leads me to suspect that your issue could be timing related, meaning there is a very narrow gap before the next frame render where the property isn't updated. For user-executed commands, using the grammar in the selector seems like it should work.

@nathansobo thank you for for continuous help!
So if I understand it right, using the grammar selector still works but the issue is in the way my tests are written. Should I listen & wait for a particular event in the tests?

Yeah, it can be tricky and the API can be improved in this area. You should be able to wait on the scheduler update via atom.views.getNextUpdatePromise().

@nathansobo sorry to bother you again but that doesn't seem to work for me. Waiting for it (using waitsForPromise as await does not work at all) on any of the lines in this function causes the test to timeout after waiting five seconds:
https://github.com/Siilwyn/css-declaration-sorter-atom/blob/c438a873e78454c04cb8e2ea6d5b2c006d076524/spec/main-spec.js#L35-L43

You might try switching to atom-mocha-test-runner to get better support for returning promises from tests. That will help you leverage async/await but will take some work to restructure.
It was hard to see in your link exactly where you were having the problem.

Yes, switching from test runner sounds good but more something I would do in the future.
Created a branch so the difference is visible and highlighted the view promise: https://github.com/Siilwyn/css-declaration-sorter-atom/compare/wait-for-view#diff-eb8118eda5229cd4256dde54e28ad36fR39
This results in the test timing out, I think because the promise never resolves.

Okay, sorry, after cloning that branch and messing with it I see I have led you astray.
You are using the legacy spec environment which forces all editor DOM updates to be synchronous, so it wasn't a timing issue. The problem is that the editor now only updates when it is visible. Since in that test your editor element isn't on the DOM, it isn't visible and therefore isn't getting updated.
If you need the editor element to update, try attaching it to the document like this:
jasmine.attachToDOM(editor.element)

Good luck!

Thanks that solved it! Did not know there is a new spec environment, the atom flight manual examples look similar. Any post on moving from to the new environment?

We have some basic documentation here in the "Customizing your test runner" section, but I think we need to do a better job advertising to people that they can transition off of Jasmine 1.3. Unfortunately many of our bundled packages are still on it, so we're still in transition ourselves.

I think we should open an issue for improving this documentation on the flight-manual repo. I can open one later unless someone gets to it first.

All right! Opened an issue: https://github.com/atom/flight-manual.atom.io/issues/394
Appreciate all helpful replies, thanks a bunch!

Thank you for opening the issue @Siilwyn :bowing_man:


Interest in more react-testing-library style queries?

Is the feature request related to a problem? Please elaborate.
I'm a big fan of React Testing Library style queries where you can do things like getByLabelText("First Name") to ensure that an input is wired up to a label for a11y reasons. Right now I don't see easy equivalents with bUnit without getting into CSS selectors which can get a little gnarly (and might not take into account both labels and aria-labels for instance).
The suggested solution
I was curious if there was an appetite for adding some of these helper queries to bUnit and if so, if you'd be willing to take some PRs after some discussion.

Hey @scottsauberv - we are already tracking this request here: https://github.com/bUnit-dev/bUnit/issues/938
If you wish, you can contribute to the discussion and of course a PR is always welcome.


I can use the client to deploy decision table dmn and get decisionsMetadata

Is your feature request related to a problem? Please describe.
When i used the client to deploy dmn response not contains decisionsMetadata.
Describe the solution you'd like
Use the client to deploy dmn and get decisionsMetadata from response.
Describe alternatives you've considered
Example of using a client to retrieve decisionsMetadata for the deploy action.

@KevMyst please take a look at the last releases we have now support for this


Error message is confusing and misleading

Environment

Version:

cli version: 0.6.0
core version: 0.6.0
build version: 0.6.0
serve version: 0.6.0

OS: macOS

What's wrong?
There is an error message shown by VulcanSQL as following:
ERROR: {"code":"ERR_BAD_REQUEST","requestUrl":"http://host.docker.internal:3000/auth/available-types","method":"get","status":404,"data":"Not Found"}
actualUrl:  http://host.docker.internal:3000/api/agg_revenue_per_platform

However, it turns out I only need to add csv in the response-format field in vulcan.yaml
What's the correct behavior?
The error message should be clear enough to tell me what's wrong.
Notes: This issue is raised by our user armaan in Discord.
Reproducing steps

To reproduce this issue:

update the vulcan.yaml to

response-format:
  enabled: true
  options:
    default: json
    formats:
      - json

run the catalog server
Try to connect to an api endpoint via the UI


fix isue #2976, to be compatible with bad response type definition for strict route function

Codecov Report
Patch coverage: 100.00% and project coverage change: +0.01% :tada:

Comparison is base (5219c5c) 79.08% compared to head (7619287) 79.09%.
Report is 5 commits behind head on master.

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@            Coverage Diff             @@
##           master    #2977      +/-   ##
==========================================
+ Coverage   79.08%   79.09%   +0.01%
==========================================
  Files         643      636       -7
  Lines       52744    52441     -303
==========================================
- Hits        41710    41479     -231
+ Misses       8952     8899      -53
+ Partials     2082     2063      -19

Flag
Coverage Δ

go-1.18-amd64
?

go-1.19-386
?

go-1.19-amd64
?

go-1.20-amd64
?

go-1.21-386
?

go-1.21-amd64
79.09% <100.00%> (-0.01%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Files Changed
Coverage Δ

net/ghttp/ghttp_server_service_handler.go
64.23% <100.00%> (+0.97%)
:arrow_up:

... and 15 files with indirect coverage changes

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.


Can only see a few blocks out when looking through the portal

According to your testing, does the issue occur with ONLY Immersive Portals mod installed?
Yes
Forge Version
43.2.3
ImmersivePortals Version
2.3.1 - mc1.19.2
Latest Log
https://gist.github.com/Scifantech/b92330eb6d2067ad57d0ddac45c53535
Crash Report (if applicable)
No response
Steps to Reproduce
All I did was create the portal ignited it and it is solid grey until you get right up on the portal then you can see a few blocks in. As soon as you enter it then you can see the whole dimension.
What You Expected
When I use to use Immersive Portals back in mc1.12.2 when you looked through the portal you could see way off in the distance.
What Happened Instead
With this version i can only see abut 4 to 6 blocks into the dimension then nothing but grey after that.
Additional Details
No response
Please Read and Confirm The Following

[X] I have confirmed this bug can be replicated without the use of Optifine.
[X] I have confirmed the details provided in this report are concise as possible and does not contained vague information (ie. Versions are properly recorded, answers to questions are clear).
[X] I have confirmed this does not happen on the fabric version (If it does please report to here instead).
[X] I have confirmed I'm not using a hybrid server (Magma, Cauldron) or a different (non official) Forge Server release.
[X] I have confirmed this issue is unique and has not been reported already.

Log contains Optifine.


Add destruction functionality for snowflake_account resource

Terraform CLI and Provider Versions
TF version 1.6.6
Provider version 0.82.0
Use Cases or Problem Statement
We would like to fully manage, that is both create and destroy, Snowflake accounts through Terraform and this Provider. Today, the creation operation work, but the destruction of the snowflake_account resources does nothing except remove the resource from the Terraform state. This behaviour is documented and expected, as one previously had to contact Snowflake support to drop an account, but that is no longer the case.
Proposal
The ORGADMIN role can schedule an account to be dropped though both the Snowsight UI and SQL. The account will then be dropped after the grace period expires.
I propose that on destruction of the snowflake_account resource, the account is scheduled for deletion upon the expiry of the grace period.
How much impact is this issue causing?
Medium
Additional Information
Workaround today is to manually drop the account after Terraform has deleted the snowflake_account resource from its state.

Hey @sivertflu. Thanks for creating the issue.
We will be refining the existing resources soon. You can check our roadmap here: https://github.com/Snowflake-Labs/terraform-provider-snowflake/blob/main/ROADMAP.md#our-roadmap. I will make sure we discuss this topic then.

Hey @sivertflu 👋
We recently released v0.100.0 and v1.0.0 version where this functionality is supported and tested. Please migrate to the latest possible version with the help of migration guide and let us know if the issue can be closed.


Load custom font with webpack

Tried it out with random text and it looks like this:

If you want to have a different font (especially @emdevs you haven't told your preference ety) we can replace it.

this or cartoonish are good fonts for header text imo. What about the font for "normal" text though? I like the Basic Comica and Super kid fonts you sent on discord.

this or cartoonish are good fonts for header text imo. What about the font for "normal" text though? I like the Basic Comica and Super kid fonts you sent on discord.

So now also font implemented for normal text:


Fixed sklearn.svm import statement.

Submodules are not implicitly imported by the interpreter.

Thanks for the correction!


pulp_push: omit redirect-url when creating repositories on demand

When creating a Pulp repository on demand, do not set a redirect URL. By leaving as the default value, redirects will work correctly for both V1 and V2 with the default Pulp configuration (i.e. not CDN).
Note that dockpulp.conf will need an additional section to allow this, something like:
[redirect]
myenv = no

(see https://github.com/release-engineering/dockpulp/commit/da3260229c738355f9e32790de331f939b92ae1c)

During testing of this I saw a dockpulp traceback, will update when I have more info.

Re-tested, this time using the correct version of dockpulp. :-)
Works fine for me.

Does what it promised, merging.


[#342] Add new race type

This introduces a new race item type to the system. This type is very simple, just having the normal description fields, an identifier, and a set of advancements. Additional race data for things like creature type, movement, and senses will be handled by a new RaceAdvancement.
I have converted the races in the SRD over to the new type, removing the base race types in the process (so we have "Lightfoot Halfling", but no longer the generic "Halfling"). I have also split up the dragonborn's breath weapon so each type has its own item for the player to select.

Is scale value a possible Advancement of the item type?

Is scale value a possible Advancement of the item type?

It will be, but there need to be some changes to its logic because currently it assumes it is using the class level, rather than the character level. That will probably be better handled in a follow-up PR.

Big feature changes like this would be much easier to review if we separated them into a structured sequence of individual PRs, for example like:

I plan on splitting this up.

Ability Score Increase

I designed the existing ASIAdvancement to also handle being used for race.

Age

I figured this would just be part of the description because there isn't a particular mechanical implementation here.

Size

I think this should be handled by an advancement because some races give players the option of choosing between small and medium, so it would be good to prompt them for that choice. I figure using the existing advancement system for presenting this choice would be better than designing a whole new system that also prompts the player when they select their race.

Speed
Senses

No races offer choices here, so we could handle this using a separate system without issue.

I don't love having race handled as "just another item" where the actor could be assigned multiple races. For race and background I think a better design would be to add these to the Actor data model as a singleton data structure like system.details.race and system.details.background (names are negotiable). We would then prevent creating race and background items on the actor and instead populate these singleton data fields.

I suppose my question is do we want to copy the data over when the race/background are added, or do we want to keep them as items and create links to them inside the data structure. So system.details.background would be a field similar to ForeignDocumentField that contains a link to a single background item in the items DB. That would allow us to avoid duplicating the data structure and still keep those item types unique (intercepting item creation would allow us to first remove the old background if a new one is added).
I feel like copying over the data to the actor would lead to issues with the advancement data and implementation which is entirely based on advancements being on items.


Can't hear the audio

import sys
sys.path.append('./')
from videollama2 import model_init, mm_infer
from videollama2.utils import disable_torch_init
def inference():
disable_torch_init()
# Video Inference
modal = 'video'
modal_path = '/data/video-llama2-av/VideoLLaMA2-audio_visual/assets/00001.mp4'
instruct = 'What exactly did the person in the video say?'

model_path = '/data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-AV'
model, processor, tokenizer = model_init(model_path)
output = mm_infer(processor[modal](modal_path), instruct, model=model, tokenizer=tokenizer, do_sample=False, modal=modal)

print(output)

if name == "main":
inference()
The output is: The person in the video spoke a few words, but they were not audible.
I input a video with sound, but it seems the model didn't pick it up. Is it because the audio branch isn't functioning properly? Also, I changed "mm_audio_tower" in VideoLLaMA2.1-7B-AV/config.json to the provided BEATs_iter3_plus_AS2M_finetuned_on_AS2M_cpt2.pt. Is this the correct place to make the change? Thanks for your reply!

Thanks for your attention! Currently, our audio branch mainly focuses on understanding audio events, and has not yet included speech recognition functions, so the model cannot identify the specific content of the speaker.

Thank you for your response. I have a few more questions.
First question: I have some video data that I want to fine-tune, and in va_joint.sh, I use --data_path ${DATA_DIR}/stage3_video_audio.json,${DATA_DIR}/stage2_audio_subset_new.json,${DATA_DIR}/stage2_video_subset.json . How should I design this? My understanding is that stage3_video_audio.json and stage2_audio_subset_new.json use the same set of videos, while ${DATA_DIR}/stage2_video_subset.json uses the audio from the videos.
Second question: I want to further train using VideoLLaMA2.1-7B-AV. How should I modify va_joint.sh? Additionally, what should I pay attention to during this process? Is it possible to see the prompts you used in your paper?
Looking forward to your response, and thank you again!

For the first question, stage3_video_audio.json represents the newly added audio-video data in the joint training stage, stage2_video_subset.json represents the video subset used in the two-stage training of video, and stage2_audio_subset_new.json represents the audio subset used in the two-stage training of audio.
For the second question, for the stage3_video_audio.json and stage2_video_subset.json files storing video data, the data formats are mainly the following two categories:
{
"id": 1,
"video": "images/xxx.jpg",
"conversations": [
{
"from": "human",
"value": "\nWhat are the colors of the bus in the image?"
},
{
"from": "gpt",
"value": "The bus in the image is white and red."
},
...
],
}
{
"id": 2,
"video": "videos/xxx.mp4",
"conversations": [
{
"from": "human",
"value": "\nWhat are the main activities that take place in the video?"
},
{
"from": "gpt",
"value": "The main activities that take place in the video are the preparation of camera equipment by a man, a group of men riding a helicopter, and a man sailing a boat through the water."
},
...
],
},
For the stage2_audio_subset_new.json file that stores audio data, the data format is as follows:
{
"id": 0,
"audio": "audio/xxx.wav",
"conversations": [
{
"from": "human",
"value": "\nPlease describe the sound event within the audio."
},
{
"from": "gpt",
"value": "Loud television static dips in and out of focus."
},
...
],
}

Thank you again for your response. Can I use only stage3_video_audio.json for the fine-tuning of the model? If so, should I simply provide the .json file for joint training in line 45 of va_joint.sh like this: --data_path ${DATA_DIR}/stage3_video_audio.json? Additionally, I would like to train on VideoLLaMA2.1-7B-AV. Should I change line 43 from --model_path DAMO-NLP-SG/VideoLLaMA2.1-7B-16F to VideoLLaMA2.1-7B-AV?
Thank you for taking the time to answer my question amidst your busy schedule！

You can fine-tune the model using only stage3_video_audio.json like this --data_path ${DATA_DIR}/stage3_video_audio.json; you can also use --model_path DAMO-NLP-SG/VideoLLaMA2.1-7B-AV to continue training VideoLLaMA2.1-7B-AV.

Thank you very much for your response. When executing bash scripts/custom/va_joint.sh, I encountered the following error:
Traceback (most recent call last):
File "/data/VideoLLaMA2-audio_visual/videollama2/train.py", line 683, in
train()
File "/data/VideoLLaMA2-audio_visual/videollama2/train.py", line 590, in train
model.get_model().initialize_audio_modules(
File "/data/VideoLLaMA2-audio_visual/./videollama2/model/videollama2_arch.py", line 126, in initialize_audio_modules
self.config.mm_hidden_size_a = audio_tower_cfg.encoder_embed_dim
UnboundLocalError: local variable 'audio_tower_cfg' referenced before assignment
Is this error caused because my audio_tower didn't load correctly? I have already implemented the inference for Video-Llama2. The va_joint.sh I used is as follows:
#!/bin/bash
Environment Variables
ARG_WORLD_SIZE=${1:-1}
ARG_NPROC_PER_NODE=${2:-8}
ARG_MASTER_ADDR="<IP_ADDRESS>"
ARG_MASTER_PORT=16666
ARG_RANK=0
Multiple conditions
if [ ! -n "$WORLD_SIZE" ] || [ ! -n "$NPROC_PER_NODE" ]; then
WORLD_SIZE=$ARG_WORLD_SIZE
NPROC_PER_NODE=$ARG_NPROC_PER_NODE
fi
if [ ! -n "$MASTER_ADDR" ] || [ ! -n "$MASTER_PORT" ] || [ ! -n "$RANK" ]; then
MASTER_ADDR=$ARG_MASTER_ADDR
MASTER_PORT=$ARG_MASTER_PORT
RANK=$ARG_RANK
fi
echo "WORLD_SIZE: $WORLD_SIZE"
echo "NPROC_PER_NODE: $NPROC_PER_NODE"
Training Arguments
GLOBAL_BATCH_SIZE=128
LOCAL_BATCH_SIZE=4
GRADIENT_ACCUMULATION_STEPS=$[$GLOBAL_BATCH_SIZE/($WORLD_SIZE*$NPROC_PER_NODE*$LOCAL_BATCH_SIZE)]
Log Arguments
export TRANSFORMERS_OFFLINE=1
export WANDB_PROJECT=audio_visual_stage3_qwen2
RUN_NAME=audio_visual_stage3_qwen2
DATA_DIR=/data/VideoLLaMA2-audio_visual/datasets
OUTP_DIR=work_dirs
torchrun --nnodes $WORLD_SIZE
--nproc_per_node $NPROC_PER_NODE
--master_addr=$MASTER_ADDR
--master_port=$MASTER_PORT
--node_rank $RANK
videollama2/train.py
--deepspeed scripts/zero2.json
--model_type videollama2_qwen2
--model_path /data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-AV
--data_folder ${DATA_DIR}
--data_path ${DATA_DIR}/custom.json
--vision_tower /data/video-llama2-av/av-weight/siglip-so400m-patch14-384
--audio_tower /data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-AV/audio_tower.bin
--pretrain_mm_mlp_adapter_a /data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-AV/mm_projector_a.bin
--mm_projector_type stc_connector_v35
--mm_projector_a_type mlp2x_gelu
--va True
--tune_audio_tower True
--tune_adapter_llm True
--tune_mm_mlp_adapter_a True
--mm_vision_select_layer -2
--image_aspect_ratio pad
--num_frames 16
--bf16 True
--tf32 True
--fp16 False
--output_dir $OUTP_DIR/${WANDB_PROJECT}/VideoLLaMA2.1-7B-AV
--num_train_epochs 2
--per_device_train_batch_size $LOCAL_BATCH_SIZE
--per_device_eval_batch_size 4
--gradient_accumulation_steps $GRADIENT_ACCUMULATION_STEPS
--evaluation_strategy "no"
--save_strategy "steps"
--save_steps 2000
--save_total_limit 2
--learning_rate 2e-5
--weight_decay 0.
--warmup_ratio 0.03
--lr_scheduler_type "cosine"
--logging_steps 1
--model_max_length 2048
--gradient_checkpointing True
--dataloader_num_workers 4
--lazy_preprocess True
--report_to tensorboard
--run_name $RUN_NAME \
I have made the following changes to VideoLLaMA2.1-7B-AV/config.json:
"mm_audio_tower": "/data/video-llama2-av/av-weight/BEATs_iter3_plus_AS2M_finetuned_on_AS2M_cpt2.pt",
"mm_vision_tower": "/data/video-llama2-av/av-weight/siglip-so400m-patch14-384",
"_name_or_path": "/data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-16F".
Thank you again for your help!

Thank you very much for your response. When executing bash scripts/custom/va_joint.sh, I encountered the following error: Traceback (most recent call last): File "/data/VideoLLaMA2-audio_visual/videollama2/train.py", line 683, in train() File "/data/VideoLLaMA2-audio_visual/videollama2/train.py", line 590, in train model.get_model().initialize_audio_modules( File "/data/VideoLLaMA2-audio_visual/./videollama2/model/videollama2_arch.py", line 126, in initialize_audio_modules self.config.mm_hidden_size_a = audio_tower_cfg.encoder_embed_dim UnboundLocalError: local variable 'audio_tower_cfg' referenced before assignment Is this error caused because my audio_tower didn't load correctly? I have already implemented the inference for Video-Llama2. The va_joint.sh I used is as follows: #!/bin/bash
Environment Variables
ARG_WORLD_SIZE=${1:-1} ARG_NPROC_PER_NODE=${2:-8} ARG_MASTER_ADDR="<IP_ADDRESS>" ARG_MASTER_PORT=16666 ARG_RANK=0
Multiple conditions
if [ ! -n "$WORLD_SIZE" ] || [ ! -n "$NPROC_PER_NODE" ]; then WORLD_SIZE=$ARG_WORLD_SIZE NPROC_PER_NODE=$ARG_NPROC_PER_NODE fi if [ ! -n "$MASTER_ADDR" ] || [ ! -n "$MASTER_PORT" ] || [ ! -n "$RANK" ]; then MASTER_ADDR=$ARG_MASTER_ADDR MASTER_PORT=$ARG_MASTER_PORT RANK=$ARG_RANK fi
echo "WORLD_SIZE: $WORLD_SIZE" echo "NPROC_PER_NODE: $NPROC_PER_NODE"
Training Arguments
GLOBAL_BATCH_SIZE=128 LOCAL_BATCH_SIZE=4 GRADIENT_ACCUMULATION_STEPS=$[$GLOBAL_BATCH_SIZE/($WORLD_SIZE*$NPROC_PER_NODE*$LOCAL_BATCH_SIZE)]
Log Arguments
export TRANSFORMERS_OFFLINE=1 export WANDB_PROJECT=audio_visual_stage3_qwen2 RUN_NAME=audio_visual_stage3_qwen2 DATA_DIR=/data/VideoLLaMA2-audio_visual/datasets OUTP_DIR=work_dirs torchrun --nnodes $WORLD_SIZE --nproc_per_node $NPROC_PER_NODE --master_addr=$MASTER_ADDR --master_port=$MASTER_PORT --node_rank $RANK videollama2/train.py --deepspeed scripts/zero2.json --model_type videollama2_qwen2 --model_path /data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-AV --data_folder ${DATA_DIR} --data_path ${DATA_DIR}/custom.json --vision_tower /data/video-llama2-av/av-weight/siglip-so400m-patch14-384 --audio_tower /data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-AV/audio_tower.bin --pretrain_mm_mlp_adapter_a /data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-AV/mm_projector_a.bin --mm_projector_type stc_connector_v35 --mm_projector_a_type mlp2x_gelu --va True --tune_audio_tower True --tune_adapter_llm True --tune_mm_mlp_adapter_a True --mm_vision_select_layer -2 --image_aspect_ratio pad --num_frames 16 --bf16 True --tf32 True --fp16 False --output_dir O U T P D I R / {WANDB_PROJECT}/VideoLLaMA2.1-7B-AV --num_train_epochs 2 --per_device_train_batch_size $LOCAL_BATCH_SIZE --per_device_eval_batch_size 4 --gradient_accumulation_steps $GRADIENT_ACCUMULATION_STEPS --evaluation_strategy "no" --save_strategy "steps" --save_steps 2000 --save_total_limit 2 --learning_rate 2e-5 --weight_decay 0. --warmup_ratio 0.03 --lr_scheduler_type "cosine" --logging_steps 1 --model_max_length 2048 --gradient_checkpointing True --dataloader_num_workers 4 --lazy_preprocess True --report_to tensorboard --run_name $RUN_NAME \ I have made the following changes to VideoLLaMA2.1-7B-AV/config.json: "mm_audio_tower": "/data/video-llama2-av/av-weight/BEATs_iter3_plus_AS2M_finetuned_on_AS2M_cpt2.pt", "mm_vision_tower": "/data/video-llama2-av/av-weight/siglip-so400m-patch14-384", "_name_or_path": "/data/video-llama2-av/av-weight/VideoLLaMA2.1-7B-16F". Thank you again for your help!

I solved this by adding self. before all audio_tower_cfg in videollama2/model/videollama2_arch.py

Thank you for your response. I would like to ask what size GPU you used to get it running. I used 8 A100-40G GPUs, but I keep getting the following error:
[2024-10-27 17:04:36,988] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: -9) local_rank: 6 (pid: 2829472) of binary: /opt/conda/envs/Videollama2/bin/python
Traceback (most recent call last):
File "/opt/conda/envs/Videollama2/bin/torchrun", line 8, in
sys.exit(main())
File "/opt/conda/envs/Videollama2/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 347, in wrapper
return f(*args, **kwargs)
File "/opt/conda/envs/Videollama2/lib/python3.9/site-packages/torch/distributed/run.py", line 812, in main
run(args)
File "/opt/conda/envs/Videollama2/lib/python3.9/site-packages/torch/distributed/run.py", line 803, in run
elastic_launch(
File "/opt/conda/envs/Videollama2/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 135, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "/opt/conda/envs/Videollama2/lib/python3.9/site-packages/torch/distributed/launcher/api.py", line 268, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:"                                                                                n addition, I made the following adjustments:
GLOBAL_BATCH_SIZE=32
LOCAL_BATCH_SIZE=1
--num_frames 8
--bf16 False
--tf32 True
--fp16 True \
But it still cannot train properly.

I encountered the same issue. Does further fine-tuning of the VideoLLaMA2.1-7B-AV model require a larger GPU? I modified the va_joint.sh script to fine-tune the AV model, but kept getting OOM errors. However, I was able to fine-tune the VideoLLaMA2-7B model on the same GPU before.
Could you kindly provide an official script for further fine-tuning the VideoLLaMA2.1-7B-AV model?
Thank you very much. Looking forward to your response.

I encountered the same issue. Does further fine-tuning of the VideoLLaMA2.1-7B-AV model require a larger GPU? I modified the va_joint.sh script to fine-tune the AV model, but kept getting OOM errors. However, I was able to fine-tune the VideoLLaMA2-7B model on the same GPU before. Could you kindly provide an official script for further fine-tuning the VideoLLaMA2.1-7B-AV model? Thank you very much. Looking forward to your response.

Has your problem been solved? I'm also having issues with OOM

Has your problem been solved? I'm also having issues with OOM

No... Without an official response and unsure how to solve it, I have temporarily put it aside.

Thank you very much for your response. When executing bash scripts/custom/va_joint.sh, I encountered the following error:
Traceback (most recent call last):
File "/data/VideoLLaMA2-audio_visual/videollama2/train.py", line 683, in
train()
File "/data/VideoLLaMA2-audio_visual/videollama2/train.py", line 590, in train
model.get_model().initialize_audio_modules(
File "/data/VideoLLaMA2-audio_visual/./videollama2/model/videollama2_arch.py", line 126, in initialize_audio_modules
self.config.mm_hidden_size_a = audio_tower_cfg.encoder_embed_dim
UnboundLocalError: local variable 'audio_tower_cfg' referenced before assignment
Is this error caused because my audio_tower didn't load correctly? I have already implemented the inference for Video-Llama2. The va_joint.sh I used is as follows:
#!/bin/bash

I used 6 A100-80G and set the local batch size to 2 it worked...


cmake -S /root/ByConity -B build_dev报错

describe your build problem
carry： cmake -S /root/ByConity -B build_dev
Operating system
win10， docker desktop
get docker through：
cd byconity/docker/debian/dev-env
make pull
make run
Cmake version
get docker through：
cd byconity/docker/debian/dev-env
make pull
make run
Ninja version
get docker through：
cd byconity/docker/debian/dev-env
make pull
make run
Compiler name and version
get docker through：
cd byconity/docker/debian/dev-env
make pull
make run
Full cmake and/or ninja output
-- Using sentry=ON: sentry
-- Using stats=1 : /root/ByConity/contrib/stats/include
-- Using gcem=1: /root/ByConity/contrib/gcem/include
Source dir of datasketches_proj = /root/ByConity/build_dev/datasketches-prefix
-- Using gflags: /root/ByConity/build_dev/contrib/gflags/include : gflags::gflag
s
-- Using brpc=1
-- Using Hive=1: /root/ByConity/contrib/hivemetastore : hivemetastore
-- Using cppjieba=1 : /root/ByConity/contrib/cppjieba/include : cppjieba
-- Using TSQuery = 0 :
CMake Warning at cmake/find/nlp.cmake:10 (message):
submodule contrib/libstemmer_c is missing.  to fix try run:
git submodule update --init --recursive
Call Stack (most recent call first):
CMakeLists.txt:583 (include)
CMake Error at cmake/find/nlp.cmake:11 (message):
Can't find internal libstemmer_c library, NLP functions will be disabled
Call Stack (most recent call first):
CMakeLists.txt:583 (include)
-- Configuring incomplete, errors occurred!
See also "/root/ByConity/build_dev/CMakeFiles/CMakeOutput.log".
See also "/root/ByConity/build_dev/CMakeFiles/CMakeError.log".

dont know why， I solve it by this:
rm -rf  /root/ByConity/contrib/libstemmer_c
git submodule update --init --recursive

finish


how to do 'hard negative mining'?

how to do 'hard negative mining'? can you share the process detail？thank you very much

@swy0915 This is the tricky part. Usually it includes two steps. The first random sampling step is easier, it starts with obtaining the tissue mask of each tumor slide. Then I randomly sample coordinates based on the tumor tissue mask and determine it's label based on the annotation. The code for the second hard negative mining part is messy, and it involves training a first model, obtain false tumor regions with high probability, and save them as coordinates.

What do I need to do after i save  false tumor regions coordinates?

@yil8 combined those coordinates with the randomly sampled ones,and retrain model again .and repeating this process?

@swy0915 I only do it once, but in theory repeatedly online hard negative mining is a better solution, which I'm actually thinking about working on it next. I combined the randomly sampled coordinates from the first step with the hard negative coordinates.

@yil8 thank you very much, I will try ...


Multisearch

@flauc is this the desired functionality?
If yes, should I instead of this separate component make optional loadMore and search on multiselect (it's essentially this component)?


installation problem on Opensuse tumbleweed: atom-1.51.0-0.1.x86_64 requires lsb-core-noarch, but this requirement cannot be provided

Dear all,
I run openSUSE Tumbleweed x86_64 in VERSION="20201009".
I have added the Atom repo at "https://packagecloud.io/AtomEditor/atom/el/7/x86_64".
When I do "zypper in atom" to install atom, I get the following message:
Loading repository data...
Reading installed packages...
Resolving package dependencies...

Problem: atom-1.51.0-0.1.x86_64 requires lsb-core-noarch, but this requirement cannot be provided
  not installable providers: lsb-4.0.fake-1.5.i586[repo-oss]
                   lsb-4.0.fake-1.5.x86_64[repo-oss]
 Solution 1: Following actions will be done:
  deinstallation of sysvinit-tools-2.97-1.1.x86_64
  deinstallation of openvpn-2.4.9-1.1.x86_64
  deinstallation of xorg-x11-essentials-7.6_1-16.10.noarch
  deinstallation of lightdm-1.30.0-3.1.x86_64
  deinstallation of sddm-0.18.1-3.2.x86_64
  deinstallation of NetworkManager-openvpn-1.8.12-2.3.x86_64
  deinstallation of patterns-base-x11_enhanced-20200505-7.1.x86_64
  deinstallation of lightdm-lang-1.30.0-3.1.noarch
  deinstallation of lightdm-gtk-greeter-2.0.6-1.8.x86_64
  deinstallation of sddm-branding-openSUSE-0.18.1-3.2.x86_64
  deinstallation of NetworkManager-openvpn-lang-1.8.12-2.3.noarch
  deinstallation of lightdm-gtk-greeter-branding-openSUSE-2.0-3.2.noarch
 Solution 2: do not install atom-1.51.0-0.1.x86_64
 Solution 3: break atom-1.51.0-0.1.x86_64 by ignoring some of its dependencies

Choose from above solutions by number or cancel [1/2/3/c/d/?] (c):

Before I updated both Linux and atom, I had no issues with atom installation.
I went for solution 3 as a work around.

Do you experience this issue when you download atom from https://atom.io?

I did again a test with zypper in atom, which pulls atom-1.54.0-0.1.x86_64. I could not reproduce the problem any longer.
I run:
NAME="openSUSE Tumbleweed"
VERSION="20210131"


Blank White Screen on Launch

Blank white screen on launching the app & goes away after a while
on WIndows 10
have tried full uninstall and then reinstalled but still the same issue.
Edit: started launching properly now

If you still have a problem, please let me know


matrix display in R

sth. wrong with matrix dimnames in R.
e.g.
l <- list(c("-1","1"), c("-1","1"))
matrix(c(200,34,41,225), nrow=2, dimnames=l)

I suppose to get
    -1   1
-1 200  41
1   34 225

but beaker gave me
     -1    1
0 200.0000	41.0000
1 34.0000	225.0000

https://pub.beakernotebook.com/#/publications/5647ddcd-a9ae-4367-baa2-a427f22f85e5

thanks for the report.  we got row names but i did not know about dim names.
will look into fixing it.


[Feature Request]: OAuth Support for ATProtoKit

Summary
OAuth support will need to be implemented for authenticating through the AT Protocol services.
Pain points
App Passwords will be eventually deprecated. ATProtoKit needs to get ahead of this by implementing OAuth, which will be the new way for users to log into Bluesky and other services that are built on the AT Protocol.
Considered Alternatives
No response
Is this a breaking change?
No
Library Examples
The Rust API library has implemented OAuth from what I can gather. We can possibly convert the Rust code into Swift code.
Additional Context
This is a fairly difficult part of the AT Protocol to understand. Even if I look at the Rust API library linked above and convert it into Swift code, it's still going to be challenging to understand.
This will most likely require multiple pull requests and iterations before it works as well as the official TypeScript API library.
That said, for future reference, these are some links that may help:

Bluesky Doc's webpage for OAuth.
AT Protocol Doc's webpage for OAuth.
The original design specification proposal.

The last one is not authoritative, but it may help.

You should consider using a third party library like https://github.com/ChimeHQ/OAuthenticator to get the initial implementation in place, then decide if you need to build this out yourself.

I'll look into that library and see if it works well for my needs. But I fear that I will have to write it by scratch after all (or at least grab a few projects and put them together).

With social cards now available, this is my next-most-wanted feature. :-)

+1 this is my biggest feature request

I understand this and I'm working on trying to figure out a solution. I'll soon release a branch of my progress with this and I hope that others will be able to help contribute code and other ideas into this, since this is a top priority for me as well.
I just want to do this right: OAuth is a fairly complicated thing to understand.

Of course! Completely fine to take your time, thank you so much for all the work you're doing on this.


Output to DRM framebuffers

Is it possible to specify the output buffers in this library? I'd like the decoder to write directly to DRM Prime output buffers.

No, this isn't possible right now and, to be honest, I don't know how I'd do it in the plain ffmpeg. If you have some experience with this topic, feel free to share a code snippet or open a pull request.

I've seen some documentation on it but it seems a little tricky to setup. I decided to just use ffmpeg for the parsing and V4L2 for the actual decode which is fairly simple to output straight into DRM.


[bazel] Some unittest are not runnable on host by mistake

Description
While working #24443, I realize that the unittest //sw/device/silicon_creator/lib/cert:cert_unittest had become unrunnable on host by mistake due to the following dependency:
Dependency chain:
    //sw/device/silicon_creator/lib/cert:cert_unittest (a54725)
    //sw/device/silicon_creator/lib/cert:cert (97da4a)
    //sw/device/silicon_creator/lib:otbn_boot_services (97da4a)   <-- target platform (@local_config_platform//:host) didn't satisfy constraint @platforms//cpu:riscv32

This is now fixed by #24440 but it illustrates that it is very easy to make a unittest unrunnable on host by mistake. Unfortunately, since we run host tests using //..., those incompatible tests will simply be skipped in CI so they are disable without anyone realizing.
Out of curiosity, I looked at the list of test that are currently incompatible with host:
# incompatible.cquery
def format(target):
  if "IncompatiblePlatformProvider" in providers(target):
    return target.label
  return ""

run with
$ bazel cquery 'tests(//sw/device/...)' --output=starlark --starlark:file=incompatible_targets.cquery
@//sw/device/silicon_creator/lib/cert:cert_unittest
@//sw/device/silicon_creator/lib/ownership:ownership_unlock_unittest
@//sw/device/silicon_creator/lib/sigverify:sigverify_unittest
@//sw/device/silicon_creator/rom_ext/keys/fake:fake_unittest
@//sw/device/silicon_creator/rom_ext/prodc/keys:keys_unittest
@//sw/device/silicon_creator/rom_ext/sival/keys:keys_unittest

This means that those tests have been disabled by mistake, I think all of them due to the extra dependency on //sw/device/silicon_creator/lib:otbn_boot_services.
Short-term solution
Fix the dependency and make those tests runnable again.
Long-term solution
We need to ensure that we don't disable such tests silently in CI. This could either be a lint in the CI, or maybe a way to mark some tests in bazel as "must run on host".

@moidx @cfrantz @timothytrippel

I think a lint check is probably easiest since its a simple query?

Done in #24484, could you look at the other unrunnable tests? I think they are all due to otbn boot services


tree refactor

Codecov Report

Merging #63 (b417f36) into master (b09195c) will decrease coverage by 1.21%.
The diff coverage is 39.78%.

:exclamation: Current head b417f36 differs from pull request most recent head a9ff288. Consider uploading reports for the commit a9ff288 to get more accurate results

@@            Coverage Diff             @@
##           master      #63      +/-   ##
==========================================
- Coverage   79.62%   78.40%   -1.22%
==========================================
  Files         106      106
  Lines        9707     9577     -130
  Branches      984      945      -39
==========================================
- Hits         7729     7509     -220
- Misses       1978     2068      +90

Flag
Coverage Δ

unittests
78.40% <39.78%> (-1.22%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

packages/lib/components/tree/tree.tsx
23.80% <17.58%> (-76.20%)
:arrow_down:

packages/lib/components/tree/tree-utils.ts
29.78% <29.78%> (ø)

packages/lib/components/accordion/accordion.tsx
96.62% <90.90%> (-1.40%)
:arrow_down:

...ages/lib/components/accordion/accordion-header.tsx
95.00% <100.00%> (+0.10%)
:arrow_up:

packages/lib/components/index.ts
2.27% <100.00%> (+2.27%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update b09195c...a9ff288. Read the comment docs.


add --cookie option

A simple pull request that adds a --cookie flag that allows setting a cookie header in the format key1=value;key2=value
Solves #67

Replaced by #229


Who those who have issues on 4K devices

Those who have problems on 4K devices. Please  Use Unc0ver dark 1.1.5 its much stable on 4K devices
Latest Versions of Unc0ver Dark Have problems and bugs.

GitHub Issues is a place for bugs and feature requests, not general advice/common sense such as updating software to the latest version. Please only submit issues when you encounter an error or need help.
If you would like to submit feedback, please do so in the Unc0ver Dark Discord.
Please close this issue. Thank you.


cant save the theme change

everytime I closed the acode app the theme i setup was been initialized
the plugin version is 3.1.3

Do you mean that your custom theme is not saved?

Do you mean that your custom theme is not saved?

i mark it on the screenshoot

This is weird because this saving etc are managed by Acode not by Plugins , please tell me other app settings are saved and remains same after restarting? Same as AcodeX plugin settings.

no, just AcodeX plugin.it doesnt happen on Acode itself.I have tried for many times.I'd like to know does this only happen on my device.

no, just AcodeX plugin.it doesnt happen on Acode itself.I have tried for many times.I'd like to know does this only happen on my device.

Maybe yes because no one had reported it.
Btw what's your Acode version?
And try to check settings.json(from Settings > Edit settings.json) file at bajrangcoder.acodex after modifying AcodeX plugin settings , is it updated with your latest changes or not?

no, just AcodeX plugin.it doesnt happen on Acode itself.I have tried for many times.I'd like to know does this only happen on my device.

Maybe yes because no one had reported it. Btw what's your Acode version? And try to check settings.json(from Settings > Edit settings.json) file at bajrangcoder.acodex after modifying AcodeX plugin settings , is it updated with your latest changes or not?

ACODE:v1.8.7 device:oppo opd2201
and the setting.json remains same problem.It updated after i modified the setting but return to default after restarting acode.
Anyway,l'll close the issue several days later if no one meet the same problem,maybe it's really my device's problem

Please update your Acode to latest version because there was a bug in v1.8.7 related to settings, I guess that's the reason behind this

Please update your Acode to latest version because there was a bug in v1.8.7 related to settings, I guess that's the reason behind this

OK,l'll try

however,it doesn't work.I update acode to v1.9.0 from f-droid,the problem still exists

however,it doesn't work.I update acode to v1.9.0 from f-droid,the problem still exists

Then I guess any plugin is causing this issue.
Btw settings of other plugin works?
If you can then share a screen recording

Acode: 1.10.0 & AcodeX: 3.1.3
After changing settings in AcodeX, upon reopening the application, the settings are reverted back. I've checked settings.json and noticed changes, but upon reopening the app, settings.json is restored to its previous state.
I have also installed other plugins like Prettier, and the modified settings are saved correctly.

can't save setting app after restart again default setting again,please fix that problem

@Misakamoe and @tharindu899, I am unable to reproduce the issue on my device. Could you please guide me on how to reproduce it? Alternatively, if you can identify the root cause, contributions are welcomed. Additionally, feel free to share your findings. If possible, could you also share the setting.json file of the acodex section? Furthermore, checking the logs would be beneficial in pinpointing the cause of the issue.

change setting and after restart like this

after restart settings .json
settings.json

after restart settings .json settings.json

once check settings.json after changing acodex settings from its before restarting

btw let me test it on some other devices because on my main device , I am not able to get this issue

acodex 3.0.1 is working bro.


OutOfMemory Error when Loading a 4GB TinyLlama Model with wasi-nn Interface

Rust code for loading models
use std::convert::TryInto;
use std::fs;
use wasi_nn;
use rand::Rng;
use bytemuck::cast_slice;

pub fn main() {
    let xml = fs::read_to_string("fixture/model.xml").unwrap();
    println!("Read graph XML, first 50 characters: {}", &xml[..50]);

    let weights = fs::read("fixture/model.bin").unwrap();
    println!("Read graph weights, size in bytes: {}", weights.len());

    let graph = unsafe {
        wasi_nn::load(
            &[&xml.into_bytes(), &weights],
            wasi_nn::GRAPH_ENCODING_OPENVINO,
            wasi_nn::EXECUTION_TARGET_CPU,
        )
        .unwrap()
    };
    println!("Loaded graph into wasi-nn with ID: {}", graph);

    let context = unsafe { wasi_nn::init_execution_context(graph).unwrap() };
    println!("Created wasi-nn execution context with ID: {}", context);

    let input_text = "你好，今天的天气怎么样？";

    let tokenized_input = tokenize(input_text);
    let indexed_tokens: Vec<i32> = tokenized_input.iter().map(|&token| token as i32).collect();

    let tensor_a = wasi_nn::Tensor {
        dimensions: &[1, indexed_tokens.len() as u32],
        r#type: wasi_nn::TENSOR_TYPE_I32,
        data: bytemuck::cast_slice(&indexed_tokens),
    };

    unsafe {
        wasi_nn::set_input(context, 0, tensor_a).unwrap();
    }

    unsafe {
        wasi_nn::compute(context).unwrap();
    }
    println!("Executed graph inference");

    let mut output_buffer = vec![0i32; 1];
    unsafe {
        wasi_nn::get_output(
            context,
            0,
            &mut output_buffer[..] as *mut [i32] as *mut u8,
            (output_buffer.len() * 4).try_into().unwrap(),
        )
        .unwrap();
    }
    println!("output: {:?}", output_buffer);
}

fn tokenize(input: &str) -> Vec<i32> {
    input.chars().map(|c| c as i32).collect()
}

Steps to Reproduce
I encountered an OutOfMemory error when trying to load a TinyLlama model (with approximately 4GB of parameters) using the wasi-nn interface in Wasmtime. The model is in OpenVINO format. This is the url of TinyLlama:https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T.
Here is the command I used:
 /home/maochenxi/wasm/runtime/wasmtime-v24.0.0-x86_64-linux/wasmtime  run -S nn --dir=fixture::fixture target/wasm32-wasip1/release/wasi-nn-example.wasm
Actual Results
However, it throws the following error:

The error message suggests that the model might be exceeding Wasmtime's memory allocation limits, even though I set max-memory-size to larger momery. Such as:
/home/maochenxi/wasm/runtime/wasmtime-v24.0.0-x86_64-linux/wasmtime  run -W max-m emory-size=10240000000 -S nn --dir=fixture::fixture target/wasm32-wasip1/release/wasi-nn-example.wasm
Versions and Environment
Wasmtime version or commit: 24.0.0
Operating system: Archlinux
Questions

Is there a specific parameter in Wasmtime that can further increase memory allocation or better manage memory for large models?
Are there any other workarounds or configurations within Wasmtime or wasi-nn that could help with loading models of this size?

Wasm32 is limited to 4GB of linear memory. Subtract from that static data and the emulated stack and you have less than 4GB of memory you have to fit the weights and all other memory allocations in. Wasm64 allows significantly more memory to be used, but I'm not sure if wasi-nn works with wasm64. You can try compiling for the wasm64-wasip1 rustc target. Make sure to also pass the right flags to wasmtime to enable the memory64 proposal.

Thank you for your response! I tried wasm64, and it does seem that wasi-nn does not support wasm64. Therefore, I’ll have to try switching to a smaller model.

Yes unfortunately currently no 64-bit WASI targets exist. I'm not personally aware of any implementation of 64-bit WASI implementation myself.
Otherwise though it's expected to see an OOM as 32-bit linear memories are limited to 4GiB. In that sense this is expected behavior and I'm not sure there's much we can do in Wasmtime about it, so I'm going to close this issue. If you're interested in a 64-bit WASI target it might make sense to open a dedicated tracking issue for that on the WASI repo (or one probably already exists)


TFLu Apollo3 Maintenance

Resolves benchmark performance for Apollo3 EVB
Updates Apollo3 support to the 2.5.1 AmbiqSuite SDK
Supports additional SFE Apollo3 boards for micro_speech, magic_wand and person_detection examples

@oclyke Can you please sign CLA. Thanks!

@gbaned I seem to be having some issues with the CLA. I've previously signed the CLA with both my work and personal emails. I reviewed the commits and the only emails associated were:

<EMAIL_ADDRESS><EMAIL_ADDRESS>
AFAIK both those emails have signed CLAs at this point. Is there any additional information you could provide for me about this issue?
Thank you much!

@oclyke Can you please resolve conflicts? Thanks!

@oclyke, we will not be able to accept this PR in its current for per our updated contribution guidelines.
The underlying issue in the case of this particular PR is that we want to control the amount of duplicated code involved in supporting examples across a range of very similar but slightly different target hardware and keep the scope of the pull requests to doing one thing.
If you are up for a rethink and refactoring of the exisitng apollo3/sparkfun_edge support towards this end then I'd be happy to give you pointers on the direction that I would like this to go in.
If you have the time and interest in pursuing this, a next step would be to make a github issue describing the problem (and tag me) and I can guide the refactoring as a series of smaller PRs.
I'm going to close the current PR but would be happy to continue the conversation via a github issue to figure out a path forward.


feat(streaming): introduce dedup cache and append-only dedup executor

I hereby agree to the terms of the RisingWave Labs, Inc. Contributor License Agreement.
What's changed and what's your intention?
Introduce dedup cache and append-only dedup executor. They are used for DISTINCT ON (without ORDER BY) to reserve the append-only attribute of the stream.
The DedupCache behaves very similar to MaterializeCache with an ignore-conflict behavior. We however decided to introduce a new cache, and there's a possibility to merge these caches in the future. Besides, DedupCache may also be useful in DistinctDeduplicater.
Related issue: #8118

Checklist For Contributors

[x] I have written necessary rustdoc comments
[x] I have added necessary unit tests and integration tests
[x] All checks passed in ./risedev check (or alias, ./risedev c)

Checklist For Reviewers

[ ] I have requested macro/micro-benchmarks as this PR can affect performance substantially, and the results are shown.

Documentation

[x] My PR DOES NOT contain user-facing changes.

Click here for Documentation
Types of user-facing changes
Please keep the types that apply to your changes, and remove the others.

Installation and deployment
Connector (sources & sinks)
SQL commands, functions, and operators
RisingWave cluster configuration changes
Other (please specify in the release note below)

Release note

Good work! Can we use this DedupCache to refactor distinct agg?  @richardchien
fyi https://github.com/risingwavelabs/risingwave/blob/99a1ca29230b6fb36069d6ed8e10e3a6e7116618/src/stream/src/executor/aggregation/distinct.rs#L33-L34

Good work! Can we use this DedupCache to refactor distinct agg? @richardchien fyi
https://github.com/risingwavelabs/risingwave/blob/99a1ca29230b6fb36069d6ed8e10e3a6e7116618/src/stream/src/executor/aggregation/distinct.rs#L33-L34

For append-only case maybe we can use this


Add simple trace view mode

Without the need for other infra solution.
Allows simple trace viewing by itself.
Support for clustering in the future.

released!

released!


[Question]: Output Integrations?

Does k8sgpt have the concept of output plugins like an HTTPS endpoint?
For example, can I run k8sgpt analyze -b noopai --explain -o json then output that via HTTPS POST to an endpoint?
I'm happy to write code and / or docs for this if it's technically feasible right now.

It's completely possible and could be the door to outputs to services like slack.

I also think this would make sense.
@agardnerIT: Do you want to take this over?

I'd love to see this shortly

This has been picked up in the operator for now https://github.com/k8sgpt-ai/k8sgpt-operator/issues/133


⚠ Bofrost.de has degraded performance

In 0642172, Bofrost.de (https://www.bofrost.de) experienced degraded performance:

HTTP code: 200
Response time: 1016 ms

Resolved: Bofrost.de performance has improved in adb3295 after 28 minutes.


Costly behavior when early exit + sync in progress + mark-and-sweep record + fast merge.

Early exit + sync in progress -> not all records are unmarked correctly
start program -> marked records are deleted
fast merge -> parent record says nothing's changed but some local record is corrupted

The diff df1c417df4ec755e7884103eab98876b21d59230 will let each MergeDirTask clean up its untouched records.


⭐FEAT: Add a list of issues

TODO

Add a list of issues as a json object, which will be used to add issues manually in the website.
Render the issue cards on the issue page.

Feat completed


Preserve extended attributes when migrating disk data

The following commit tried to fix the preservation of extended attributes when migrating disk data, however is not complete, as also the --xattrs-include=*.* parameter is required to achieve for example the preservation of capabilities: https://github.com/cloudfoundry/bosh-agent/commit/c3f558b4d705c0d78b624bfc2b378901d338600b
With this we try to finally fix the preservation of all extended attributes, such as capabilities for example.
Preservation of capabilities are for importance in PKS (Tanzu Kubernetes Grid Integrated Edition / TKGI), as Docker images are stored on persistent disks.
Whenever a Docker image includes a binary with some capabilities (for example nginx-ingress-controller), these capabilities, without this change, get lost after disk migrations, which prevents the successful starting of containers after the disk migration.
So far in TKGI all docker images need to be manually wiped from disk, after disk migration and re-pulled, so that the capabilities get instanciated.
Behaviour comparison of both commands (current vs. proposed):
$ getcap original/nginx-ingress-controller
original/nginx-ingress-controller = cap_net_bind_service+ep

$ (tar -C original --xattrs -cf - .) | (tar -C copy --xattrs -xpf -)
$ getcap copy/nginx-ingress-controller
$

$ (tar -C original --xattrs --xattrs-include=*.* -cf - .) | (tar -C copy --xattrs --xattrs-include=*.* -xpf -)
$ getcap copy/nginx-ingress-controller
copy/nginx-ingress-controller = cap_net_bind_service+ep

For further reference:

https://www.gnu.org/software/tar/manual/html_node/Extended-File-Attributes.html
VMware Bug: BOSH-180

@speer could you add a test to demonstrate the case this code is fixing?

@speer could you add a test to demonstrate the case this code is fixing?

What do you mean exactly by test? We have PKS/TKGI and whenever disk migrations happen (ex. increase persistent disk size via Opsman), binaries within Docker images (ex. nginx-ingress-controller) loose the capabilities they had before.
As stated in the commit message --xattrs-include=*.* preserves capabilities and should solve this problem.

Thanks! @speer

Internal VMWare FYI: We failed to get this merged into the branch of the Agent that's used in our Xenial stemcells, disappointing some of our Corporate customers. So, we cherry-picked this commit and pushed it to the 2.268.x. Here's the commit, just in case one of us at VMware comes looking one day 1f3763259a340d2bc09abddfea3bc19bb8ad8730


Update and apply scalafmt

Description
This PR updates the scalafmt config to the newest version as well as replacing a pre commit git hook with a github workflow action. This may be subjective but I have a personal hate with putting formatters within githooks because it really messes with IDE's especially in large codebases. Instead the github workflow action

Runs concurrently to the main build and uses the scala-native version of  scalafmt. This means its ultra fast, taking only around 2-3 seconds on small projects
You can add the check to the list of branch checks that must pass before merging a PR to enforce not being able to merge unformatted code, i.e.

Type of change
Updating of scalafmt
Checklist:

[X] I have performed a self-review of my own code
[X] I have commented my code, particularly in hard-to-understand areas
[X] I have made corresponding changes to the documentation
[X] My changes generate no new warnings
[X] Any dependent changes have been merged and published in downstream modules
[X] I have checked my code and corrected any misspellings

This may be subjective but I have a personal hate with putting formatters within githooks because it really messes with IDE's especially in large codebases.

Which IDE do you use? I use IntelliJ and you can tell it to not run git hooks. Also, you don't have to install pre-commit hooks locally.

No longer at Rally myself, but from my time there, I found pre-commit-hooks absolutely invaluable.  In combination with scalafmt and a properly-configured IntelliJ, it meant that I almost never needed to think about formatting, which was a non-trivial time-saver.

Regarding me personally when I did have them available it slowed down my workflow especially in large projects. I typically only ran a scalafmt just before I was going to push something where as locally I may commit many times quickly. In tandem with the github actions scalafmt which takes a few seconds to complete on CI, if I did happen to forget to format I pretty got immediate feedback just when creating the PR.

I wonder how we can bridge the gap between the github action and pre-commit-conifg... I want to be able to run hooks that will autoformat the code (quickly) so that it passes CI. I think the "quickly" part rules out the old pre-commit-hooks that requires running a new JVM and sbt (not to mention it didn't even run scalafmtSbt). I wonder if we can run scalafmt-native from pre-commit the same way as github actions.

@mdedetrich it was easier than I thought. pre-commit supports docker images directly, so I could just use this: https://hub.docker.com/r/scalameta/scalafmt/tags

Still something wonky going on: https://github.com/rallyhealth/scalacheck-ops/actions/runs/3235997094/jobs/5301188323

Still something wonky going on: https://github.com/rallyhealth/scalacheck-ops/actions/runs/3235997094/jobs/5301188323

Well, I re-ran it and it was fine... hopefully not a source of flakiness.

Still something wonky going on: https://github.com/rallyhealth/scalacheck-ops/actions/runs/3235997094/jobs/5301188323

Well, I re-ran it and it was fine... hopefully not a source of flakiness.

Weird... looks like it had trouble downloading sbt... hopefully a rare issue.


ask: is it possible to change the Admin LTE template into other?

hi @volkanceylan ,
i'm still learning how to use and be productive with serene. enjoying the learning and having fun also.
i would like to ask, is it possible to change the Admin LTE template into other bootstrap template that i can found on wrapbootstrap.com maybe? if its possible, would you like please to share the big picture of how of doing it?
thank you for create and share this great product
merci,
ismail.

AdminLTE is also a bootstrap template so it shouldn't be very hard. Make sure you change LeftNavigation.cshtml, site.less with adminlte include and script includes to something compatible with your new template.

hi @volkanceylan ,
thank you for your feedback.
merci,
ismail

@go2ismail Does it work for you ? can u give me a short description how you do it please
Thanks


Change Channel.props values type from String to Object (fix #99)

For example, channel_mentions property value is string array. So we need to change Map's value type to Object.

We need test case to verify the problem has been fixed correctly...


Decouple plugin GUI from server code, if possible

@jhg023 could this be done with Java 9+ modules? Or would it be better to just completely decouple it into its own project. The plan once Luna is stable, is to incorporate a plugin repository where users can install their own plugins

Will just ship it with Luna for 1.0

In order for the GUI to work as a stand-alone application, it would need to import the server as a library. Which means, at least in my mind, we'd need to publish the server's build artifacts to a maven repository like JCenter or Maven Central. This opens up the possibility for developers to create their own tools on top of the server.
That being said, this feature indirectly broadens the scope of the project. @lare96 Is this the direction that you want to go in?

I was thinking that the GUI would be imported into Luna as a maven artifact or local JAR, then the implementation could be added
if(Luna.settings().pluginGui()) {
    var impl = new PluginWindowListener(pluginMap, ..., ...);
    var window = new PluginWindow(impl);
    window.open();
}

I'm not a fan of having GUI components tightly coupled to the server logic. If a developer doesn't want the GUI, he/she shouldn't be forced to download it unnecessarily. Like I said earlier, if instead we were to export Luna modules as maven artifacts, then we could achieve the same result. An unintended benefit of this approach is that it would open up the possibility for other application-wide extensions.
Now the implementation of such a design would be a bit more complex than the sample code you provided but I'm positive we're able to come up with an intuitive solution.


Issue to mount storage in usb. symlink hostname /bin/dnsdomainname: operation not permitted

Hello,
I'm trying do change the docker storage to point to usb(fat32). I created this file:
/etc/docker/daemon.json
{
"graph": "/mnt/usb"
}
When I pull some image this issue happens:
failed to register layer: Error processing tar file(exit status 1): symlink hostname /bin/dnsdomainname: operation not permitted
Can someone help me with it?

Please keep in mind that the GitHub issue tracker is not intended as a general support forum,
but for reporting bugs and feature requests. For other type of questions, consider using one of;

https://forums.docker.com
the Docker community Slack channel (register here: http://dockr.ly/community)
StackOverflow

I'm going to close this issue because this is not a bug, but feel free to comment after I closed 👍