Step1 missing parameters

Powershell for step 1 is wrong
It should be
New-RdsAppGroup  -TenantName <YourTenantName>   -HostPoolName <YourHostPoolName> -Name <NewAppGroupname>  -ResourceType <Desktop or RemoteApp>

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

ID: c05d017a-8ce4-d3c2-333c-9f1decbc8e6c
Version Independent ID: 7f2287e0-71d2-05ef-335b-45bb4cd6cfe3
Content: Manage app groups for Windows Virtual Desktop - Azure
Content Source: articles/virtual-desktop/manage-app-groups.md
Service: virtual-desktop
GitHub Login: @Heidilohr
Microsoft Alias: helohr

Actually it should be for allmost all the steps in this tutorial.

@kantipenko Thanks for pointing this out. I have updated the document and  changes will go live once PR is approved.


[Thread] Support Thread network provisioning using Thread operational dataset TLV

Problem
We does not use TLV for network provisioning in thread, we should support it.

Summary of Changes
Add TLV support in SetThreadProvisioning

Fixes #5039

Will the corresponding change using operational dataset in DeviceController come in another PR?

https://github.com/project-chip/connectedhomeip/pull/5041 Will use operational dataset.

Where is this TLV coming from?  Is this intended to work with the CHIP network provisioning commands, or is this something else?

Where is this TLV coming from?  Is this intended to work with the CHIP network provisioning commands, or is this something else?

Yes, it is intended to work with the CHIP network commission commands.


Integration no longer loads

Please check Services, Known Bug / Issues and Troubleshooting over here first: https://github.com/fuatakgun/kia_uvo/blob/master/README.md
Region and Brand of car
Version of the integration
2.31.0
Describe the bug
The integration no longer loads.
Debug logs if an error occurred
Failed setup, will retry: Config Not Ready: Error communicating with API: Traceback (most recent call last): File "/config/custom_components/kia_uvo/coordinator.p
Outlined here: https://github.com/fuatakgun/kia_uvo/blob/master/README.md
To Reproduce
Expected behavior
Screenshots
If applicable, add screenshots to help explain your problem.
Additional context

Please complete the rest of the details.
In particular region and the rest of the logs.


[NNVM][KERAS] Fix keras model converter and improve tutorial

In the current converter a single conv2d with padding in keras will be expanded into two nnvm symbols (sym.pad + sym.conv2d). This can harm the performance and result in some mismatches when using TopHub.
This pr fixes this.

cc @Huyuwei


enable separate data output

Description
This shrinks the linux installer for daedalus.

Linked issue
https://iohk.myjetbrains.com/youtrack/issue/CBR-532

Type of change

[ ] 🐞 Bug fix (non-breaking change which fixes an issue)
[ ] 🛠 New feature (non-breaking change which adds functionality)
[ ] ⚠ Breaking change (fix or feature that would cause existing functionality to change)
[ ] 🏭 Refactoring that does not change existing functionality but does improve things like code readability, structure etc
[ ] 🔨 New or improved tests for existing code
[ ] ⛑ git-flow chore (backport, hotfix, etc)

Developer checklist

[ ] I have read the style guide document, and my code follows the code style of this project.
[ ] If my code deals with exceptions, it follows the guidelines.
[ ] I have updated any documentation accordingly, if needed. Documentation changes can be reflected in opening a PR on cardanodocs.com, amending the inline Haddock comments, any relevant README file or one of the document listed in the docs directory.
[ ] CHANGELOG entry has been added and is linked to the correct PR on GitHub.

Testing checklist

[ ] I have added tests to cover my changes.
[ ] All new and existing tests passed.

QA Steps

Screenshots (if available)

How to merge
Send the message bors r+ to merge this PR. For more information, see
docs/how-to/bors.md.

bors r+


Pass UNIX socket parameters to runserver, and hence to gunicorn

I'd prefer to have Gunicorn serve requests from a UNIX socket instead of via HTTP. Is this something that can be added to a near future version of Superset?

You can add your own thin wrapper for gunicorn, runserver is not much more than that https://github.com/airbnb/superset/blob/master/superset/cli.py#L61

Right. You can issue your own gunicorn command or hook up whatever else wsgi server and configure is however you prefer

Thanks for your replies. While it's not very challenging to create a Gunicorn startup script to allow Superset to be served from a socket, I think it's a common enough set up to warrant having runserver (or the Superset config file) accept a path to a UNIX socket for the sake of consistency and simplicity. So I've added a pull request: https://github.com/airbnb/superset/pull/2627


[GH-6] Use cardano-prelude

https://github.com/input-output-hk/cardano-shell/issues/6
Switching to cardano-prelude.
Working with Stack, ~not working with Nix~ working with Nix as well, Cabal working as well.
Continuation from https://github.com/input-output-hk/cardano-shell/pull/5, which needs to be merged first.

Merged edits from #3 and from rcohen/GH-6 branch. Changed CI to nix. Appears to be working.

Wait, @robcohen.
How does this work then https://github.com/input-output-hk/cardano-shell/blob/develop/stack-shell.nix#L3 ?
Did you build with stack and cabal before adding these commits?


Allow skipping name verification

This implements an option to skip name verification which will allow rewriting names. See #1057 for more details.

@stevvooe, can you review this?
(The failures look irrelevant; I see failed builds for master too.)

@tt The code looks okay. However, I am not sure if we can support any registry that returns an image from a repository with a different name. The data model just doesn't work like that. Relaxing this requirement may be okay, but due diligence must be done to ensure that guarantee isn't relied upon.
We are changing the manifest format to not have the name, which is arguably the correct design. Repository rename will be less of an issue.
@RichardScothern @dmcgowan Are there places in the client and notary that we need to update for this to work correctly?

I'm actually less concerned with the client supporting this and more with not persisting names on disk making it harder to support it later without renaming all files.
I'll take a look at the manifest format proposal but I'd appreciate if you can still consider merging this in the interim.

@tt It absolutely matters if the clients validate this, as a registry that has enabled this option would be completely useless. Manifests served with the incorrect name would be rejected. I don't think we can do this without the due diligence.

@stevvooe, the point is that my mapping is internal; it's still served from the original name.

@tt That is the problem. The puller says fetch foo/bar and the a manifest comes back with the name bar/baz, since the backend repository bar/baz was renamed to foo/bar. If the client expects that the name field of the manifest matches the thing they ask for, which is a reasonable expectation, it will reject it.

It has less to do with allowing user-facing renames (for now) and more about choosing a storage strategy that will support it when the manifest changes.
That said, I think it would be possible to allow renames by also patching the manifest when a rename happens.

I can confirm that the Docker client version 1.6 - 1.9 do not check the manifest name and there are no plans to. We did not check the manifest name since we were intent on deprecating the name field in the manifest pre-1.6.

@tt Due to content addressability, the name cannot be rewritten at request time, unless the manifest is requested by tag.
@dmcgowan In your opinion, could we just remove the name check altogether?

@stevvooe I don't think the name check is in use. My only concern would be by removing it we are opening up possible use cases we have no interest in supporting for the current manifest schema version.  Aside from this concern, removing altogether is favorable than making it configurable. So yes, we should just remove altogether.

Okay, let's get some quorum going here.
@RichardScothern @aaronlehmann @jlhawn @dmp42
Are we okay with allowing manifests to have different names than their repositories?

Will this have an impact on notification hooks? I may be misremembering, but I thought the names in notifications came from the manifest. If so, some notification consumers may assume this is actually the repository's name.

@aaronlehmann Interesting. Repository name is all set by the repository hooked into the notifications. No issue there.

Any news?

@tt We need consensus from @RichardScothern @aaronlehmann @jlhawn @dmp42 @endophage

oh, sorry. LGTM
The name really should have never been in the manifest anyway.

LGTM

Circle and Janky don't seem to agree :-)
@RichardScothern are you comfortable with this change?

@dmp42, the CircleCI failure looks like misconfiguration of the S3 driver. I don't think that's related to this pull request.
@stevvooe, based on the feedback, should this really be an option or should I open another pull request that removes the check entirely?

I've restarted the build

@tt We are leaning towards removing the check entirely.

I support removing the check.

+1

@tt Go ahead and update that PR. Sounds like we have solid consensus here.
Sorry for all the flip flopping on this one. This is a very sensitive piece of code. We are glad to have your contributions!

I'm closing this; #1211 is where the magic happens.


Improve proxy-config log command with envoy all loggers format

Please provide a description of this PR:

Currently there's no mention of how to set all loggers to a level in proxy-config log. Upon looking through the code I found it could be set directly with istioctl pc log pod-name --level debug, added an explaination to the flag description.

Also, this can not be configured intuitively like the Envoy style - other separate loggers are conforming this format:

curl localhost:15000/logging?level=debug

So the defaultLogger check to set all active loggers has been excluded.

The output flag is a persistent flag of proxy-config, and it's not funcioning in this command, added an info log.

@hanxiaop: The following test failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

Test name
Commit
Details
Required
Rerun command

release-notes_istio
a91a0be4a76767c87460e2b4e342454120996d91
link
true
/test release-notes

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

@hanxiaop: The following test failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

Test name
Commit
Details
Required
Rerun command

lint_istio
1b434b3f62fa733ec7a664fa54d16c8d213c3025
link
true
/test lint

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

@hanxiaop: The following test failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

Test name
Commit
Details
Required
Rerun command

integ-ambient_istio
7a584783150e664eccfa751b21896b1850fe1bbd
link
unknown
/test integ-ambient

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.


Update minSdkVersion and "compile" to "implementation"

This sample has been deprecated/archived (check README for more information on newer samples related to this technology).
As recommended by GitHub, we are closing all issues and pull requests.


Documentation Issues

There is an error in the documentation.  When configuring the "certificates:" section of the config.yaml, it should be "trusted_ca_cert:" not "trusted_ca_certs".
Please confirm that the inbound 8000, 5671, 8883 and 443 ports need to be opened on the bottom child device.
When configuring the "lower devices", do we need to enter the "hostname:" property? The documentation wasn't clear on that.
Should the "hostname:" property in the config.yaml match the name used when generating the certificates.  If so the documentation should say that.

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

ID: b9ceabb9-bbb4-c27b-3072-76f03fdba9a0
Version Independent ID: eb2ccbe0-ea6f-ef67-9efb-649302f7d8d7
Content: Tutorial - Create a hierarchy of IoT Edge devices - Azure IoT Edge
Content Source: articles/iot-edge/tutorial-nested-iot-edge.md
Service: iot-edge
GitHub Login: @v-tcassi
Microsoft Alias: v-tcassi

@terrymandin Thank you for your feedback . We will investigate and update the thread further.

@terrymandin I have assigned the issue to the content author to evaluate and update as appropriate.

I've also created a StackOverflow issue as I haven't been able to get nested edge working.
Nested Edge: unable to get local issuer certificate

Hi! We're currently working on updating the flow of this tutorial for simplicity and clarity, as there are a lot of moving parts. Some of these changes have addressed your first item of feedback.
@ebertrams should be able to provide more detailed information about the remaining items.
I'll return to this issue and inform you when the tutorial has been updated with the new flow!

Hi @terrymandin , sorry for the very long delay. We have been working on redesigning the entire tutorial experience. We included your feedback in the new version. The new version went live alongside the general audience release of IoT Edge version 1.2.

The new flow greatly simplifies the certificate setup, so customers will not need to touch the config.
The tutorial now clarifies that the ports only needs to be opened on all but the lowest layer devices.
The new flow uses a tool which prompts the user for all necessary config items, so there will not be any mistakes on which properties need to be filled out or not.
The hostname is clarified to be either the IP address or FQDN of the device IoT Edge is being installed on.

Thanks for your feedback, and sorry again for the radio silence. I expected the PM would quickly address your questions, but that didn't happen.

The documentation updates appear to have resolved the issues brought up here. If you have any follow up questions, you can reopen it!
Thanks!
#please-close


Garage: Fix listing of owned NFTs when piloting a Rig

Removes the alchemy AIRDROPS filter from useOwnedNFTs, something muyt have changed in alchemy's api because this filter used to work well but now it filters out a lot of non-spam NFTs

nice! thanks for jumping in @datadanne


Cross origin for javascript CDN stack traces

Hi @benaadams, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

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

TTYL, AZPRBOT;


Upgrade Az.Tools.Migration to support Az 6.0

Component
[X] PowerShell module
[] VSCode extension
[] Other
Description of the new feature
We need to upgrade the migration module to support Az version 6.0

Sounds good, will take care of this soon.


Refactor tests

Changes done:

Moved tests to their own package
Exposed type replicator, re-wrote replicator tests without internals (using mocks)
Re-wrote serf tests without broker
Minor code changes in commitlog and server: stop accepting connections after server shutdown

Next steps (TODO):

Raft: move leader.go from broker to raft package to finish their separation, write tests for raft
Broker: write tests for broker (mocking out serf/raft) to cover more cases
Server: modify server tests by mocking out broker, add tests to cover remaining request/response cases

Added a commit to this branch to fix a minor issue in a test file. CI build had passed for this PR earlier, but after the commit, CI build was triggered again and it failed for a different (non-related) test.
@travisjeffery Could you re-trigger the build to see if the issue persists?

-1 on having all the tests in the same package. all the tests should be alongside the code they test. and if possible those can be in their own packages. e.g. the server package and server_test package how it was before.
the only top-level test dirs there should be are "testutil" and "mock" to include the mock types. So there'd be a file called mock/mock.go and it'd include a type called Proxy that's the Proxy mock.

Cool. I'll move the tests back to their packages. Would you be okay with each package having its own test sub-directory e.g. server package would have a sub-directory tests (package "server/tests") containing the server_test file, broker package would have a sub-directory tests (package "broker/tests") containing broker_test and replicator_test files, and so on?

no keep them in the same directory /server/{server.go,server_test.go} I don't see many projects that have nested test directories. even in packages with lots of files it's easy to see the groups of files when they're sorted alphabetically.

OK, moved tests back to code packages.

merged thanks!


[BEAM-22] Execute ModelEnforcements in TransformExecutor

This allows a configurable application of Model Enforcement based on the
class of transform being executed, both before and after an element is
processed and after the transform completes.

R: @kennknowles

Just a couple nits & questions, then LGTM.


Peer DiD priviledge model

From https://youtu.be/d-5MmLLd3xY
Register
Route
Authcrypt
Plaintext
Oblige
Key_admin
Se_admin
Rule_admin

and the jvm version:
https://github.com/sicpa-dlab/peer-did-jvm

@rodolfomiranda will generate specific tickets as our DIDComm implementation did:peer usage continues progress.


feat: add methods to make setting invalid overridable

Description
Backports the following PRs as part of an EoD task:

https://github.com/vaadin/web-components/pull/4097

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.1 out of 2 committers have signed the CLA.:white_check_mark: mukherjeesudebi:x: vursenYou have signed the CLA already but the status is still pending? Let us recheck it.


handling many requests per second

Hi, I use the api and my bot is polling like this :
bot.onText(/blah/, function (msg) {
	sessionManager(msg)
…..
}
bot.onText(/foo/, function (msg) {
	sessionManager(msg)
…..
}
It works fine until request per second goes upper than 4 or 5. Then it seems that my session manager function –which I call in every function that matches regex-  is mixing values of different requests!!!
I don’t know where the problem is. Is this happening because of polling and I should use webhooks? Could it be the problem of the api? Could it be my node ttl map that I am using as a session?
Please help me go through this. Requests per second will go up to 50 or 60 per second! And the bot is completely useless then.

Hi, Did you solve this problem ?

hey vio17,
The problem was in my session management actually. I used a global array as session but it seems nodejs does not support modifying same global variable on different threads and it gets all messed up. So i started using Redis-session module as my session.


Consider uploading to PyPI

Are there any barriers beyond learning the usual process of pushing this tool to PyPI? This process has been performed by multiple WS-DLers, so it should be straightforward for this tool unless there is a reason not to do so.
/cc @anwala

Hello @machawk1,
No barriers, it's on the to do list. Hoping to get to it very soon.

Hey @anwala, by being a GitHub issue, it is now officially on the to-do list. 😄
If there are other to-dos, you may want to create GitHub issues for them. This might facilitate collaboration for those that want to get involved will be able to see outstanding tasks.

Great idea! Thanks!

Hello again @machawk1,
You can now install sgsuite via: pip install sgsuite


In-code documentation with PEP 727

[!NOTE]
PEP 727 is currently in "draft" status.
If accepted, it'll probably be a Python 3.14 feature.
If rejected, but this feature has already been implemented, then it'll be removed.

Requires upgrading the minimum typing_extensions version to 4.8, and its python restriction to python<3.14, so that the typing_extensions.Doc backport can be used.

After experimenting with it, I found out that it's basically useless, because none of Python's introspection tools (like help() or inspect.getcomments()) support it.
I at least expected it to update the __doc__ of the annotation itself, but it doesn't.
I also found out that a Python 3.12 type alias (TypeAliasType) defines __slots__ without __doc__. This makes it effectively impossible to properly document type aliases (i.e. so that help(MyAlias) shows it), without resorting to very sketchy hacks.


[Report Fields] [External] implement the policy report field delete flow

[Main tracking issue].(https://github.com/Expensify/Expensify/issues/365155)
Design doc link.
Implement the following section of the design doc: https://docs.google.com/document/d/10b7pTVvgpB6_O8sRTKaCzZEVM3Ba6hxnIwyyQSSXCLY/edit#bookmark=kix.53mwf06dzdi0
This might technically be on hold for https://github.com/Expensify/App/issues/43677 but I think Callstack can start on these in parallel using feature branch.
Include unit tests for the optimistic actions
Issue OwnerCurrent Issue Owner: @allroundexperts

Hello, Im Artem from Callstack and would like to help with this issue

I believe we are all done here


Add fast-forward version value to operations

This should enable future fast-forward updates.
Currently version must be enforced at the type level, i.e. like
struct Transition<const VERSION: u8 = 0> {
   version: Ffv,
}

impl<const VERSION: u8> StrictDecode for Transition {
  fn strict_check(&self) -> Result<(), DecodeError> {
    if self.version != Ffv::V0 {
      return ....
    }
  }
}

Closed with #151


Trim whitespace

Dear @sarusso,
first things first: Thanks for conceiving this excellent module!
Before adding further commits, I would like to bring this minor nit to the codebase. Without further ado, my editor trimmed all whitespace so I believe it would be most appropriate to upstream this change in order not to clutter subsequent edits too much.
With kind regards,
Andreas.

Thank you @amotl!! I tried to do my best :) Anyway, I should really change IDE.. merging the PR!


[turbopack] Local PostCSS configuration is not applied to CSS files imported from node_modules when using workspaces

What version of Next.js are you using Turbopack in?
13.4.3
What package manager are you using / does the bug impact?
npm
What operating system are you using?
Linux
Describe the Bug
When a workspace with a Next.js application is configured with a local PostCSS config file, CSS files imported from node_modules do not have locally-configured transformations applied.
For example, given the following:
<EMAIL_ADDRESS>.root {
  background-color: tomato;
  padding: mod(50px, 51px);
  @media (--medium-up) {
    background-color: aqua;
  }
}

<EMAIL_ADDRESS>@custom-media --small (max-width: 767px);
@custom-media --small-up (min-width: 0px);
@custom-media --medium (min-width: 768px) and (max-width: 1119px);
@custom-media --medium-up (min-width: 768px);
@custom-media --large (min-width: 1120px);

apps/repro/postcss.config.js
module.exports = {
  plugins: [
    [
      "@csstools/postcss-global-data",
      {
        files<EMAIL_ADDRESS>      },
    ],
    [
      "postcss-preset-env",
      {
        stage: 2,
        browsers: ["defaults"],
        autoprefixer: { flexbox: "no-2009" },
        features: {
          "nesting-rules": true,
          "custom-media-queries": true,
          "custom-properties": false,
        },
      },
    ],
  ],
};

The line padding: mod(50px, 51px); should be transformed to padding: 50px; and the custom media query @media (--medium-up) should be transformed to @media (min-width: 768px). However, Turbopack emits the following CSS:
/* chunk [root of the<EMAIL_ADDRESS>*/
/*<EMAIL_ADDRESS>(css, css module) */
.root__style__7a7d5953 {
  background-color: tomato;
  padding: mod(50px, 51px);
}
@media (--medium-up) {
  .root__style__7a7d5953 {
    background-color: aqua;
  }
}

This does not match the CSS emitted by Next.js when running without Turbopack, or when the application is run outside of a monorepo using Turbopack.
.localButton {
  background-color: tomato;
  padding: 50px;
}
@media (min-width: 768px) {
  .localButton {
    background-color: aqua;
}
  }

Expected Behavior
CSS files imported from node_modules in applications stored in a workspace are transformed according to the locally supplied PostCSS configuration.
To Reproduce

Clone https://github.com/dstaley/turborepo-turbopack-postcss
npm install
npm run make-package
npx turbo run dev, open localhost:3000, and confirm that the two buttons are equal in size, that in viewports narrower than 768px the buttons are orange, and that in viewports wider than 768px the buttons are aqua.
npx turbo run dev-turbopack, open localhost:3000, and confirm that the "node_modules button" button has no padding, and that in viewports wider than 768px the "node_modules button" button remains orange.

Reproduction Repo
https://github.com/dstaley/turborepo-turbopack-postcss

This is basically the same bug as #4861 (which 13.4.3 fixes) except the issue only occurs when the Next.js application is within an npm workspace. This isn't Turborepo specific, and reproduces when calling npm run dev-turbopack -w repro.

Same problem. need help


fade out and fade in to specific volume.

After some testings i think i got the function i need to smoothly change volume for specific duration.
Here is my function
const lowerSoundSmoothCommand = (start, end, decibel = 0, fadeDuration = 0) => {
  return [
    `volume=enable='between(t,${start - fadeDuration},${start})':volume='max(1-(t-${start - fadeDuration})/${fadeDuration},${decibel})':eval=frame`,
    `volume=enable='between(t,${start},${end})':volume='${decibel}':eval=frame`,
    `volume=enable='between(t,${end},${end + fadeDuration})':volume='min(${decibel}+(t-${end})/${fadeDuration},1)':eval=frame`
  ]
}

Is there any idea to implement something like this in fluent-ffmpeg, so everyone can use this?

You can submit a PR if you want, but this is a very specific feature, and I'm not sure it has its place in fluent-ffmpeg


input_fn not being applied for incoming requests in non-local mode

Hi,
I have setup a small regression example to test Sagemaker Tensorflow pipeline from beginning to end following the examples here.
Everything worked OK, except when I want to overwrite input_fn method in my module so I can parse/transform incoming data at prediction time. If I use instance_type='local' the code works and the customized input_fn method is called during the estimator.predict call.  However, when I deploy the model to an endpoint, and I try to query it with the following call
aws sagemaker-runtime invoke-endpoint --region 'us-east-2' --endpoint-name house-price-estimator-test-synthetic-keras --body "{\"int_living_sqft\": 0.5, \"int_beds\": 0.2}" --content-type "application/json" --accept "application/json" outputJson.json
the custom method input_fn seems to not be called.  If I call the endpoint like this
aws sagemaker-runtime invoke-endpoint --region 'us-east-2' --endpoint-name house-price-estimator-test-synthetic-keras --body "{\"inputs\":  [ [0.5, 0.2]]}" --content-type "application/json" outputJson.json
the request succeeds, which is a clear indication it is using the default Json parser from here.
I include a Zip file to reproduce everything: it has the notebook used to train and deploy a simple toy regression model in a Sagemaker notebook. It also has the python file with the model_fn, input_fn and other methods required by the python notebook.
Any help would be appreciated as I am out of ideas on what can be going wrong and why input_fn is not being called by the endpoint when it receives a prediction request. Again the instance_type='local'  seems to work fine.
Thanks,
Fernando
sagemaker_input_fn_issue.zip
This is the traceback from the CloudWatch Console:
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/container_support/serving.py", line 182, in _invoke
self.transformer.transform(content, input_content_type, requested_output_content_type)
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 281, in transform
return self.transform_fn(data, content_type, accepts), accepts
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 208, in f
prediction = self.predict_fn(input)
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 223, in predict_fn
return self.proxy_client.request(data)
File "/usr/local/lib/python2.7/dist-packages/tf_container/proxy_client.py", line 71, in request
return request_fn(data)
File "/usr/local/lib/python2.7/dist-packages/tf_container/proxy_client.py", line 99, in predict
result = self.prediction_service_stub.Predict(request, self.request_timeout)
File "/usr/local/lib/python2.7/dist-packages/grpc/beta/_client_adaptations.py", line 309, in __call__
self._request_serializer, self._response_deserializer)
File "/usr/local/lib/python2.7/dist-packages/grpc/beta/_client_adaptations.py", line 195, in _blocking_unary_unary
raise _abortion_error(rpc_error_call)

AbortionError: AbortionError(code=StatusCode.INVALID_ARGUMENT, details="input size does not match signature")

Hi,
LocalMode is implemented outside of the containers. For the code running inside of the containers it should work exactly the same with localmode and cloudmode. Could you show me the entire log from endpoint? Including when the endpoint was starting. Thanks!

Hi @icywang86rui ,
Here I copy the entire log from cloudwatch for the endpoint: it basically shows from the moment I call estimator.deploy to create the endpoint to the moment I try to invoke the endpoint and it returns an error. Let me know if you need anything else.
Thanks,
@fernandoamat
2018-10-16 12:34:55,034 INFO - root - running container entrypoint
2018-10-16 12:34:55,034 INFO - root - starting serve task
2018-10-16 12:34:55,034 INFO - container_support.serving - reading config
2018-10-16 12:34:55,548 INFO - container_support.serving - importing user module
2018-10-16 12:34:55,548 INFO - container_support.serving - loading framework-specific dependencies
2018-10-16 12:34:57,024 INFO - container_support.serving - starting nginx
2018-10-16 12:34:57,043 INFO - container_support.serving - starting gunicorn
2018-10-16 12:34:57,051 INFO - container_support.serving - inference server started. waiting on processes: set([21, 22])
2018-10-16 12:34:57.117647: I tensorflow_serving/model_servers/main.cc:154] Building single TensorFlow model file config: model_name: generic_model model_base_path: /opt/ml/model/export/Servo
2018-10-16 12:34:57.118730: I tensorflow_serving/model_servers/server_core.cc:444] Adding/updating models.
2018-10-16 12:34:57.118753: I tensorflow_serving/model_servers/server_core.cc:499] (Re-)adding model: generic_model
2018-10-16 12:34:57.123848: I tensorflow_serving/core/basic_manager.cc:716] Successfully reserved resources to load servable {name: generic_model version:<PHONE_NUMBER>}
2018-10-16 12:34:57.123868: I tensorflow_serving/core/loader_harness.cc:66] Approving load for servable version {name: generic_model version:<PHONE_NUMBER>}
2018-10-16 12:34:57.123983: I tensorflow_serving/core/loader_harness.cc:74] Loading servable version {name: generic_model version:<PHONE_NUMBER>}
2018-10-16 12:34:57.124102: I external/org_tensorflow/tensorflow/contrib/session_bundle/bundle_shim.cc:360] Attempting to load native SavedModelBundle in bundle-shim from: /opt/ml/model/export/Servo/1538917129
2018-10-16 12:34:57.124180: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:242] Loading SavedModel with tags: { serve }; from: /opt/ml/model/export/Servo/1538917129
2018-10-16 12:34:57.125830: I external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
2018-10-16 12:34:57.145138: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:161] Restoring SavedModel bundle.
2018-10-16 12:34:57.156822: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:196] Running LegacyInitOp on SavedModel bundle.
2018-10-16 12:34:57.164458: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:291] SavedModel load for tags { serve }; Status: success. Took 40328 microseconds.
2018-10-16 12:34:57.164739: I tensorflow_serving/core/loader_harness.cc:86] Successfully loaded servable version {name: generic_model version:<PHONE_NUMBER>}
2018-10-16 12:34:57.168421: I tensorflow_serving/model_servers/main.cc:316] Running ModelServer at <IP_ADDRESS>:9000 ...
[2018-10-16 12:34:57 +0000] [22] [INFO] Starting gunicorn 19.9.0
[2018-10-16 12:34:57 +0000] [22] [INFO] Listening at: unix:/tmp/gunicorn.sock (22)
[2018-10-16 12:34:57 +0000] [22] [INFO] Using worker: gevent
[2018-10-16 12:34:57 +0000] [47] [INFO] Booting worker with pid: 47
[2018-10-16 12:34:57 +0000] [48] [INFO] Booting worker with pid: 48
2018-10-16 12:34:57,487 INFO - container_support.serving - creating Server instance
2018-10-16 12:34:57,509 INFO - container_support.serving - creating Server instance
2018-10-16 12:34:58,805 INFO - tf_container - ---------------------------Model Spec---------------------------
2018-10-16 12:34:58,806 INFO - tf_container - {
"modelSpec": {
"version": "1538917129",
"name": "generic_model"
},
"metadata": {
"signature_def": {
"@type": "type.googleapis.com/tensorflow.serving.SignatureDefMap",
"signatureDef": {
"serving_default": {
"inputs": {
"inputs": {
"dtype": "DT_FLOAT",
"name": "Placeholder_1:0",
"tensorShape": {
"dim": [
{
"size": "-1"
},
{
"size": "2"
}
]
}
}
},
"methodName": "tensorflow/serving/predict",
"outputs": {
"price": {
"dtype": "DT_FLOAT",
"name": "Reshape:0",
"tensorShape": {
"dim": [
{
"size": "-1"
}
]
}
}
}
}
}
}
}
}
2018-10-16 12:34:58,807 INFO - tf_container - ----------------------------------------------------------------
2018-10-16 12:34:58,807 INFO - tf_container - TF Serving model successfully loaded
2018-10-16 12:34:58,810 INFO - container_support.serving - returning initialized server
2018-10-16 12:34:58,824 INFO - tf_container - ---------------------------Model Spec---------------------------
2018-10-16 12:34:58,824 INFO - tf_container - {
"modelSpec": {
"version": "1538917129",
"name": "generic_model"
},
"metadata": {
"signature_def": {
"@type": "type.googleapis.com/tensorflow.serving.SignatureDefMap",
"signatureDef": {
"serving_default": {
"inputs": {
"inputs": {
"dtype": "DT_FLOAT",
"name": "Placeholder_1:0",
"tensorShape": {
"dim": [
{
"size": "-1"
},
{
"size": "2"
}
]
}
}
},
"methodName": "tensorflow/serving/predict",
"outputs": {
"price": {
"dtype": "DT_FLOAT",
"name": "Reshape:0",
"tensorShape": {
"dim": [
{
"size": "-1"
}
]
}
}
}
}
}
}
}
}
2018-10-16 12:34:58,824 INFO - tf_container - ----------------------------------------------------------------
2018-10-16 12:34:58,825 INFO - tf_container - TF Serving model successfully loaded
2018-10-16 12:34:58,826 INFO - container_support.serving - returning initialized server
[2018-10-16 12:36:46,649] ERROR in serving: invalid literal for float(): 0.5,0.2
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/container_support/serving.py", line 182, in _invoke
self.transformer.transform(content, input_content_type, requested_output_content_type)
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 281, in transform
return self.transform_fn(data, content_type, accepts), accepts
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 207, in f
input = input_fn(serialized_data, content_type)
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 238, in _default_input_fn
return self._parse_csv_request(serialized_data)
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 195, in _parse_csv_request
full_array = [float(i) for i in row]
ValueError: invalid literal for float(): 0.5,0.2
[2018-10-16 12:36:46,650] ERROR in serving: invalid literal for float(): 0.5,0.2

Could you show me the environment variables set in your sagemaker model's primary container? You can find this from the aws console on the model's page. Let's confirm that the model is setup correctly.

Hi @icywang86rui,
Here are the environment variables listed in the models page.
SAGEMAKER_CONTAINER_LOG_LEVEL	20
SAGEMAKER_ENABLE_CLOUDWATCH_METRICS	false
SAGEMAKER_PROGRAM	keras_linear_regression_synthetic_house_price.py
SAGEMAKER_REGION	us-east-2
SAGEMAKER_SUBMIT_DIRECTORY	s3://test-estimator/customcode/tensorflow_synthetic_test_house_price/house-price-estimator-tensorflow-test-ts1539692900/source/sourcedir.tar.gz

Thanks,
Fernando

Hi @fernandoamat ,
The input_fn is working in SageMaker as well. Let me explain what I think is happening:

Your input_fn receives "{\"inputs\": [ [0.5, 0.2]]}" and returns {"inputs": [ [0.5, 0.2]]}
The server sends the data to the proxy client https://github.com/aws/sagemaker-tensorflow-container/blob/master/src/tf_container/serve.py#L223
The proxy client needs to transform your dictionary to a valid GRPC request https://github.com/aws/sagemaker-tensorflow-container/blob/master/src/tf_container/proxy_client.py#L98
Your request is translated to a valid GRPC https://github.com/aws/sagemaker-tensorflow-container/blob/master/src/tf_container/proxy_client.py#L145

To achieve your goal, which is to receive "{\"int_living_sqft\": 0.5, \"int_beds\": 0.2}" as a valid request , I would do:
def input_fn(data, content_type):
    """
    if content_type == "application/json":
        # Expected a Json string like {"int_living_sqft": 0.5, "int_beds": 0.2}
        obj = json.loads(clean_input)
        return {"inputs": [[obj['int_living_sqft'], obj['int_beds']]}

Please, let me know if it works.
Thanks for using SageMaker.
Márcio

Hi @mvsusp
Thanks for taking a look at this and for the clear explanation. I included the modification you suggested and rerun the notebook to retrain and redeploy the endpoint and unfortunately it does not work. When I call the endpoint like this:
aws sagemaker-runtime invoke-endpoint --region 'us-east-2' --endpoint-name house-price-estimator-test-synthetic-keras --body "{\"int_living_sqft\": 0.5, \"int_beds\": 0.2}" --content-type "application/json" --accept "application/json" outputJson.json

I get the following stacktrace in cloudwatch:
[2018-10-30 12:48:02,868] ERROR in serving: AbortionError(code=StatusCode.INVALID_ARGUMENT, details="input size does not match signature")
12:48:03
Traceback (most recent call last): File "/usr/local/lib/python2.7/dist-packages/container_support/serving.py", line 182, in _invoke self.transformer.transform(content, input_content_type, requested_output_content_type) File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 281, in transform return self.transform_fn(data, content_type, accepts)
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/container_support/serving.py", line 182, in _invoke
self.transformer.transform(content, input_content_type, requested_output_content_type)
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 281, in transform
return self.transform_fn(data, content_type, accepts), accepts
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 208, in f
prediction = self.predict_fn(input)
File "/usr/local/lib/python2.7/dist-packages/tf_container/serve.py", line 223, in predict_fn
return self.proxy_client.request(data)
File "/usr/local/lib/python2.7/dist-packages/tf_container/proxy_client.py", line 71, in request
return request_fn(data)
File "/usr/local/lib/python2.7/dist-packages/tf_container/proxy_client.py", line 99, in predict
result = self.prediction_service_stub.Predict(request, self.request_timeout)
File "/usr/local/lib/python2.7/dist-packages/grpc/beta/_client_adaptations.py", line 309, in __call__
self._request_serializer, self._response_deserializer)
File "/usr/local/lib/python2.7/dist-packages/grpc/beta/_client_adaptations.py", line 195, in _blocking_unary_unary
raise _abortion_error(rpc_error_call)
AbortionError: AbortionError(code=StatusCode.INVALID_ARGUMENT, details="input size does not match signature")
AbortionError: AbortionError(code=StatusCode.INVALID_ARGUMENT, details="input size does not match signature")

However, when I call the same endpoint like this
aws sagemaker-runtime invoke-endpoint --region 'us-east-2' --endpoint-name house-price-estimator-test-synthetic-keras --body "{\"inputs\": [ [0.5, 0.2]]}" --content-type "application/json" outputJson.json

the requests success and returns the expected result. This is why I am puzzled: if the input_fn was being called, the second request should not succeed.
The error stack trace and error are pretty cryptic so I am not sure where to look at.
My input_fn looks like this:
def clean_serialized_input(serialized_input):
    """
    Saemaker request adds all sorts of odd balls in the serialized string from the request
    This method tries to clean it up to be robust to that.
    :param serialized_input:
    :return:
    """
    clean_input = serialized_input.replace("\\", "")  # request adds \" to the string
    if clean_input[0] == "\"":
        offset_start = 1
    else:
        offset_start = 0
    if clean_input[-1] == "\"":
        return clean_input[offset_start:-1]
    else:
        return clean_input[offset_start:]

def input_fn(data, content_type):
    if content_type == "application/json":
        # Expected a Json string like {"int_living_sqft": 0.5, "int_beds": 0.2}
        clean_input = clean_serialized_input(data)
        # Request adds " in the string
        obj = json.loads(clean_input)
        # change suggested by @mvsusp
        #return [[obj['int_living_sqft'], obj['int_beds']]]
        return {INPUT_TENSOR_NAME: [[obj['int_living_sqft'], obj['int_beds']]]}
    elif content_type == "text/csv":
        clean_input = clean_serialized_input(data)
        # Request adds " in the string
        return [[float(i) for i in clean_input.split(',')]]
    else:
        raise ValueError(
            'Endpoint is not prepared for contenty type {}. It only accepts application/json or text/csv'.format(
                content_type))

Any help is appreciated.
Thanks,
@fernandoamat

Hi,
As mentioned above by my teammates the input_fn/default_input_fn logic is part of the container and does not depend on local/non-local mode.
Would it be possible to see how you deployed the endpoint in local and non-local mode cases? Did you use python SDK estimator both times?
What happens if you query the endpoint using python sdk?
Also would it be possible to see the tar file from s3://test-estimator/customcode/tensorflow_synthetic_test_house_price/house-price-estimator-tensorflow-test-ts1539692900/source/sourcedir.tar.gz with source code container was running.

closing due to inactivity. feel free to reopen if necessary.


Remove 2+ line breaks in REC-xml-c14n-20010315 canonicalization

Hello, I was playing around with the canonicalization algo of REC-xml-c14n-20010315, and I notice that it's not removing any excessive line breaks( more than 2+ ), is this intentional or it's missing in the code? I could do a PR if you guys want.
Thanks 🎉

Sorry, that was probably my fault while coding, I'll close this for now.


Logrus logging

I've added a small package that provides a hook to enable logging with logrus, Is it implemented correctly? I've based it on how the logging is done internally: https://github.com/oiime/logrusbun

Looks pretty good :+1: What do you think about adding a link with brief description to https://github.com/go-bun/bun-docs/blob/master/docs/guide/tracing.md ?

Ok, https://github.com/go-bun/bun-docs/pull/2

:+1:


Non-canonical infinity point & bad flags in BLS12-381 serialization should fail

Description
Follow-up to https://github.com/arkworks-rs/curves/pull/157, the original is stale.
Thanks @ArnaudBrousseau for providing a test for bad flags (lmk if you'd like me to add you as co-author on the commit here)
closes: #157

Before we can merge this PR, please make sure that all the following items have been
checked off. If any of the checklist items are not applicable, please leave them but
write a little note why.

[x] Targeted PR against correct branch (master)
[x] Linked to Github issue with discussion and accepted design OR have an explanation in the PR that describes this work.
[x] Wrote unit tests
[x] Updated relevant documentation in the code
[ ] Added a relevant changelog entry to the Pending section in CHANGELOG.md
[x] Re-reviewed Files changed in the Github PR explorer

Thanks for the great PR @mmagician! Could you add a CHANGELOG entry as this is an important fix? Thanks!

@Pratyush It's actually a breaking change no?

In Rust breaking changes are only when the API changes, not necessarily behaviour

@Pratyush Thanks, I moved it to Bugfixes.


fix: confirmation view

:tada: This PR is included in version 1.1.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Fix #83: Support for boolean sortObjectKeys prop

Documentation suggests that passing a boolean to the sortObjectKeys prop should provide a default sorting method. This commit adds a type check to support both boolean and comparator functions.
Otherwise, invoking array.sort(true) yields:

TypeError: invalid Array.prototype.sort argument[

Fixes https://github.com/alexkuz/react-json-tree/issues/83

Thanks for the contribution! I changed it to be a bit shorter. I think throwing when the argument is not boolean and not function is ok, helping debugging.


Minio Client re-connected

Hello!
I see in Minio logs this:
Client 'http://servername:9000/minio/storage/mnt/hdd/15/v50' re-connected in 7m39.151020782s
How solve this?

Have a stable network. (repo is https://github.com/minio/minio - but you'd get the same answer there)


Feature/add undo functionality

Pull Request Type

[ ] ✨ feat
[x] 🐛 fix
[ ] ♻ refactor
[ ] 💄 style
[ ] 🔨 chore
[ ] 📝 docs

Relevant Issues

resolves #2590
What is in this change?
This pull request addresses the issue of the lack of undo functionality for paste actions in the main prompt text box of Anything LLM. Specifically, it ensures that when users press Ctrl+Z on Windows or Command+Z on Mac after pasting text, the paste operation is undone, and the pasted text is removed from the text box. This change improves the user experience by allowing users to easily revert paste actions without manually deleting the text.
Additional Information

The implementation includes modifications to the event handling for the main prompt text box to correctly process Ctrl+Z and Command+Z as undo operations for paste actions.
Manual tests have been performed to verify that the undo functionality works as expected across pasting, and text input.
This update enhances the usability of the text box, aligning with common text editing behaviors found in other applications, thereby making the interaction more intuitive for users.
No additional dependencies were added in this PR. Existing functionality was extended to include proper handling of undo operations for pasted text.
Code conforms to the pattern found in the same file and prettier rules have been followed/adjusted for.

Developer Validations

[ ] I ran yarn lint from the root of the repo & committed changes
[ ] Relevant documentation has been updated
[x] I have tested my code functionality
[ ] Docker build succeeds locally

LGTM

LGTM


Appstudio update rhtap-demo-component-usnw

Pipelines as Code configuration proposal
To start the PipelineRun, add a new comment with content /ok-to-test
For more detailed information about running a PipelineRun, please refer to Pipelines as Code documentation Running the PipelineRun
To customize the proposed PipelineRuns after merge, please refer to Build Pipeline customization

Pipelines as Code CI has failed.There was an error creating the PipelineRun: rhtap-demo-component-usnw-on-pull-request-
creating pipelinerun rhtap-demo-component-usnw-on-pull-request- in namespace rhtap-demo-dev-aqma-tenant has failed.
Tekton Controller has reported this error: the namespace of the provided object does not match the namespace sent on the request


Error: Failed to load plugin 'prettier' declared in '.eslintrc.js » @react-native-community/eslint-config': Cannot find module 'eslint-plugin-prettier' Require stack:

After installing react-native with npx it throws an error on me with eslint settings in webstorm.
Description
I have tried installing prettier on it's own but it didn't worked
React Native version: 0.65.1
Run react-native info in your terminal and copy the results here.
info Fetching system and libraries information...
System:
OS: macOS 11.5.2
CPU: (8) arm64 Apple M1
Memory: 179.45 MB / 16.00 GB
Shell: 5.8 - /bin/zsh
Binaries:
Node: 16.8.0 - /opt/homebrew/bin/node
Yarn: Not Found
npm: 7.21.0 - /opt/homebrew/bin/npm
Watchman: 2<IP_ADDRESS> - /opt/homebrew/bin/watchman
Managers:
CocoaPods: 1.11.0 - /opt/homebrew/bin/pod
SDKs:
iOS SDK:
Platforms: iOS 14.5, DriverKit 20.4, macOS 11.3, tvOS 14.5, watchOS 7.4
Android SDK: Not Found
IDEs:
Android Studio: Arctic Fox 2020.3.1 Patch 2 Arctic Fox 2020.3.1 Patch 2
Xcode: 12.5.1/12E507 - /usr/bin/xcodebuild
Languages:
Java: Not Found
npmPackages:
@react-native-community/cli: Not Found
react: 17.0.2 => 17.0.2
react-native: 0.65.1 => 0.65.1
react-native-macos: Not Found
npmGlobalPackages:
react-native: Not Found
Steps To Reproduce
Provide a detailed list of steps that reproduce the issue.

npx react-native some
open app in webstorm

Expected Results
Describe what you expected to happen.
no errors is shown
Snack, code example, screenshot, or link to a repository:

I haven't changed anything from the app created with npx

for me, with rn 0.64.2 and<EMAIL_ADDRESS>, when yarn install, i got the error:

error An unexpected error occurred: "could not find a copy of prettier to link in C:\code\tt\fatboy\node_modules\@react-native-community\eslint-config\node_modules".
when changing<EMAIL_ADDRESS>i got no errors.
It's not a solution, but can bypass this problem temp.

Can confirm that this is happening with both 3.0.0 and 3.0.1 of @react-native-community/eslint-config. A check reveals that node_modules/eslint-plugin-prettier does not exist, nor eslint-config-prettier. However, some of the packages specified in this package.json do exist, and it strikes me as odd that only some are being included. Any ideas?

I should mention that running the linter by itself also throws this error (not just VSCode).
ESLint: 7.32.0

ESLint couldn't find the plugin "eslint-plugin-prettier".

(The package "eslint-plugin-prettier" was not found when loaded as a Node module from the directory "/Users/kendallroth/Development/payme".)

It's likely that the plugin isn't installed correctly. Try reinstalling by running the following:

    npm install eslint-plugin-prettier@latest --save-dev

The plugin "eslint-plugin-prettier" was referenced from the config file in ".eslintrc.js » @react-native-community/eslint-config"

Installing as instructed/recommended that moves the error to prettier, which is definitely installed properly (works in VSCode and terminal).
Oops! Something went wrong! :(

ESLint: 7.32.0

ESLint couldn't find the config "prettier" to extend from. Please check that the name of the config is correct.

The config "prettier" was referenced from the config file in "/Users/kendallroth/Development/payme/node_modules/eslint-plugin-prettier/eslint-plugin-prettier.js".

I was unable to "fix" this by downgrading to version 2.0.0 unfortunately. Also of interest, I verified that version 3.0.0 is currently working on my Windows machine; however, the same dependencies does not work on Mac (clean NPM install on both).

I can verify that version 3.0.0 works but 3.0.1 does not.
Using also<EMAIL_ADDRESS>and<EMAIL_ADDRESS>in my project.
eslint has version 7.32.0.

Further digging revealed that this happened to me after as a side-effect of upgrading to Expo 43 (from 42). I'm trying to figure out which of the included package changes may have impacted the project. The only change made in that commit was a change to package.json (below) and lock file.
       "dependencies": {
-        "@react-native-masked-view/masked-view": "0.2.4",
+        "@react-native-masked-view/masked-view": "0.2.5",
         "@react-navigation/native": "^6.0.2",
         "@react-navigation/stack": "^6.0.7",
-        "expo": "~42.0.1",
-        "expo-linking": "~2.3.1",
-        "expo-splash-screen": "~0.11.2",
-        "expo-status-bar": "~1.0.4",
-        "react": "16.13.1",
-        "react-dom": "16.13.1",
-        "react-native": "https://github.com/expo/react-native/archive/sdk-42.0.0.tar.gz",
+        "expo": "^43.0.0",
+        "expo-linking": "~2.4.2",
+        "expo-splash-screen": "~0.13.4",
+        "expo-status-bar": "~1.1.0",
+        "react": "17.0.1",
+        "react-dom": "17.0.1",
+        "react-native": "0.64.2",
         "react-native-gesture-handler": "~1.10.2",
-        "react-native-screens": "~3.4.0",
+        "react-native-safe-area-context": "3.3.2",
+        "react-native-screens": "~3.8.0",
         "react-native-vector-icons": "^8.1.0",
-        "react-native-web": "~0.13.12"
+        "react-native-web": "0.17.1"
       },
       "devDependencies": {
-        "@babel/core": "^7.9.0",
+        "@babel/core": "^7.12.9",
         "@react-native-community/eslint-config": "^3.0.0",
-        "@types/react": "~16.9.35",
-        "@types/react-native": "~0.63.2",
+        "@types/react": "~17.0.21",
+        "@types/react-native": "~0.64.12",
         "eslint": "^7.32.0",
         "prettier": "^2.3.2",
-        "typescript": "~4.0.0"
+        "typescript": "~4.3.5"
       }
     },

This is proving to be quite frustrating, as my linting has stopped working entirely in VSCode (and CLI/tests). I will try to create a replica on a new project (from Expo) but would be very curious if anyone would have any ideas about this (can share original project if needed).

Created a minimum test case that illustrates the issue, but for the life of me cannot figure out what is going wrong.
package.json
{
  "name": "react-native-eslint-plugin-test",
  "version": "0.1.0",
  "scripts": {
    "lint": "eslint ."
  },
  "dependencies": {
    "expo": "~43.0.0",
    "expo-status-bar": "~1.1.0",
    "react": "17.0.1",
    "react-dom": "17.0.1",
    "react-native": "0.64.2",
    "react-native-web": "0.17.1"
  },
  "devDependencies": {
    "@babel/core": "^7.12.9",
    "@react-native-community/eslint-config": "^3.0.0",
    "@types/react": "~17.0.21",
    "@types/react-native": "~0.64.12",
    "eslint": "^7.32.0",
    "prettier": "^2.4.1",
    "typescript": "~4.3.5"
  },
  "private": true
}

.eslintrc.js
module.exports = {
  parser: "@typescript-eslint/parser",
  parserOptions: {
    ecmaVersion: 2020,
    sourceType: "module",
    ecmaFeatures: {
      jsx: true,
    },
  },
  extends: [
    "@react-native-community",
    "plugin:react/recommended",
    "plugin:@typescript-eslint/recommended",
    // Disable ESLint rules that would conflict with Prettier
    "prettier",
    "plugin:prettier/recommended",
  ],
  rules: {
    "@typescript-eslint/ban-ts-comment": "off",
    "@typescript-eslint/no-explicit-any": "off",
    "no-console": "warn",
    "prettier/prettier": "warn",
    "prefer-const": "warn",
    "react/display-name": "off",
  },
};

Error:
> eslint .

Oops! Something went wrong! :(

ESLint: 7.32.0

ESLint couldn't find the plugin "eslint-plugin-prettier".

(The package "eslint-plugin-prettier" was not found when loaded as a Node module from the directory "/Users/kendallroth/Development/eslint-copy-test".)

It's likely that the plugin isn't installed correctly. Try reinstalling by running the following:

    npm install eslint-plugin-prettier@latest --save-dev

The plugin "eslint-plugin-prettier" was referenced from the config file in ".eslintrc.js » @react-native-community/eslint-config".

Reminder that installing as it mentions then complains about eslint-config-prettier, then global jest types, and so on (does not fix problem)! It's almost as if the dependencies of the community package are not being installed at all!

Ooookay, so to add to the confusion, I tried running the exact setup from @react-native-commnity/eslint-config on both Windows WSL2/Ubuntu (Node 16.6.0, NPM 7.20.6) and Mac (Node 16.7.0, NPM 7.20.3).
# Install dependencies
> npm install --save-dev eslint prettier @react-native-community/eslint-config

# Create ESLint file and copy in from NPM page
> touch .eslintrc

# Create simple TypeScript file with some to be caught by linter
> touch index.ts

# Add ESLint script and run
> npm run lint

For some unknown reason, this succeeded on Windows WSL2/Ubuntu, but failed on Mac! Exact same commands...everything 😱! At this point I am probably going to have to replace this package with the underlying packages (less rules), unless anyone has some ideas on why this is different between Linux and Mac. Also curious if anyone else can replicate this issue with the above workflow?

i had the same probleme. i think there is a trouble with the path of dependency of this package. i fixed it by installing those and his dependencies manually :
"eslint-config-prettier"
"eslint-plugin-eslint-comments"
"eslint-plugin-flowtype"
"eslint-plugin-jest"
"eslint-plugin-prettier"
"prettier"
try to install the same version of packages, you can use npm ls <package_name> to get the version. and npm install -D <package_name>@ to install specific version.
don't forget to delete package.lock and node_modules if you have some troubles. and don't forget to restart vscode after package installation to allow eslint server to restart.

I got the same error after upgrading a project from Node.js 14.18.1 to version 16.13.0. No other changes were made. Installing the aforementioned packages manually fixed the problem.

For those using yarn, try npx yarn-deduplicate.

I got the same error after upgrading a project from Node.js 14.18.1 to version 16.13.0. No other changes were made. Installing the aforementioned packages manually fixed the problem.

I have downgraded from 16.13.0 to 14.18.1 to fix the issue. Do you think it's better to manually install all the missing packages instead? (both are just a workaround for the broken default react-native project init on Mac)

Looks like this is related to #32528. Try downgrading ESLint to v7, it fixed the issue for me.
npm i eslint@7

Hi, this might be unrelated, but I noticed something after moving from React Native 0.63 to 0.66 all the red lines and auto-formatting I get from Prettier suddenly disappeared, how can I get them back? I use VS Code and they really helped me keep my code organised.

The package isn't found because it is placed underneath @react-native-community/eslint-config instead of the root node_modules. don't know why

Using yarn install instead of npm fixed the issue for me....

Using yarn install instead of npm fixed the issue for me....

I'm using yarn but it didn't work, what I don't understand is that when using the default project created by react native cli it works

as @SimonChaumet stated: "the package isn't found because it is placed underneath @react-native-community/eslint-config instead of the root node_modules"
this happens when there are multiple versions of prettier installed on your project (you can find them all in your yarn.lock by searching for "prettier@")
For instance, a faulty yarn.lock:
<EMAIL_ADDRESS>  version "2.1.2"
  resolved "https://registry.yarnpkg.com/prettier/-/prettier-2.1.2.tgz#3050700dae2e4c8b67c4c3f666cdb8af405e1ce5"
  integrity sha512-16c7K+x4qVlJg9rEbXl7HEGmQyZlG4R9AgP+oHKRMsMsuk8s+ATStlf1NpDqyBI1HpVyfjLOeMhH2LvuNvV5Vg==

<EMAIL_ADDRESS>  version "2.5.1"
  resolved "https://registry.yarnpkg.com/prettier/-/prettier-2.5.1.tgz#fff75fa9d519c54cf0fce328c1017d94546bc56a"
  integrity sha512-vBZcPRUR5MZJwoyi3ZoyQlc1rXeEck8KgeC9AwwOn+exuxLxq5toTRDTSaVrXHxelDMHy9zlicw8u66yxoSUFg==

The first line (v2.1.2) comes from @react-native-community/eslint-config, the second (v2.5.1) from my package.json
To make sure that only 1 version is installed:

ensure that all prettier requirements (the version in your package.json and the version of all libs using prettier) are compatible.
remove all the resolution line from your yarn.lock (these are the lines above)
run yarn again
check that it finished successfully, and that your yarn.lock file is updated:

<EMAIL_ADDRESS><EMAIL_ADDRESS>  version "2.5.1"
  resolved "https://registry.yarnpkg.com/prettier/-/prettier-2.5.1.tgz#fff75fa9d519c54cf0fce328c1017d94546bc56a"
  integrity sha512-vBZcPRUR5MZJwoyi3ZoyQlc1rXeEck8KgeC9AwwOn+exuxLxq5toTRDTSaVrXHxelDMHy9zlicw8u66yxoSUFg==

I think it's all caused by peer dependency in npm >=7.
In my case, installing dependencies in the old npm 4-6 mode helped, i.e.:

Remove node_modules, package-lock.json
npm install --legacy-peer-deps

Article about dependencies:

Create a File .prettierignore in your root Directory of Project, add following lines,
./*
/
/.


Error Validation

This is the command I get when I try to use the .jar
[scallop] Error: Validation failure for 'fiction-link' option parameters: https://royalroadl.com/fiction/XXX

@learn2learn1 how does the command that your try to run looks like?
If you just tried to run the jar without any parameters, then it's not how it suppose to work. Check the How to Use section in readme.

Just tried it myself:
royaldl_test2016-12-08_17.11.59 $ wget https://github.com/Aivean/royalroadl-downloader/releases/download/1.2.0/royalroadl-downloader-assembly-1.2.0.jar
....
2016-12-08 17:12:19 (3.11 MB/s) - 'royalroadl-downloader-assembly-1.2.0.jar' saved [39678256/39678256]
royaldl_test2016-12-08_17.11.59 $
royaldl_test2016-12-08_17.11.59 $ java -jar royalroadl-downloader-assembly-1.2.0.jar http://royalroadl.com/fiction/1234
Title: The Mansion | RoyalRoadL
parsing: http://royalroadl.com/fiction/chapter/9007
parsing: http://royalroadl.com/fiction/chapter/9151
Saving as: The_Mansion_RoyalRoadL.html
done
royaldl_test2016-12-08_17.11.59 $ ls -l
total 77560
-rw-r--r--  1 Aivean  staff     28079 Dec  8 17:12 The_Mansion_RoyalRoadL.html
-rw-r--r--  1 Aivean  staff  39678256 Oct 14 20:56 royalroadl-downloader-assembly-1.2.0.jar
royaldl_test2016-12-08_17.11.59 $
royaldl_test2016-12-08_17.11.59 $ less The_Mansion_RoyalRoadL.html

Closing issue for now. Feel free to reopen if you still can't make it work.

This is what happens when I run it. I am not exactly sure what "parameters" mean, is that the command line argument thing? "java -jar my.jar [argument] ?

I renamed the .jar to Royalroadl.jar.

@learn2learn1 ah, I see the problem. Program expects url with http protocol (not https). I'll update it to accept https, meanwhile you can work around the issue by replacing https in your link with http.

Alright thank you.


Remove seek and volume actions from throttling to improve smoothness …

…of progressbar. So both bars seem completely smooth on my laptop and it doesn't seem to have any side effect.
I just call the setState directly in the callback. I kept the throttling method for everything else.
I think we shouldn't worry too much about the number of renders generated as React is suppose to deal with that anyway.
Maybe a quick test on a slow/mobile device would let us know if it's fine this way or not.
Thanks!

Related to #43.

Thank you. I believe this was indeed a good solution. I made some tweaks and landed it to master https://github.com/mderrick/react-html5video/commit/08658353826d70536dd68e8d6a86ed8946ba3516.

Good job! 👍


v5.0.0-rc

missing features for v5.0.0-rc

[x] datasource env vars
[ ] website with documentation https://github.com/grafana-operator/grafana-operator-experimental/issues/64
[ ] manifest overlays to produce both namespaced and cluster scoped resources
[x] e2e tests, at least some unit tests
[ ] jsonnet and grafonnet support https://github.com/grafana-operator/grafana-operator-experimental/issues/67

I close this issue since we use milstones instead.


Fix README file. Use MD instead of RST.

let's review before, after that squash commits and merge it


Complete all DB operations before returning responses to client.

This commit ensures all DB operations are successfully completed before sending success response to client. If DB operations are unsuccessful, an error message is sent. Closes #304

Closing per conversation in #304


Allow split component definitions in packages

Description:
Two different configuration styles are described in
https://www.home-assistant.io/docs/configuration/devices/#style-2-list-each-device-separately
But only one is allowed in packages according to
https://www.home-assistant.io/docs/configuration/packages/
This change allows "Style 2" configuration in packages.
Related issue:  N/A
Pull request in home-assistant.github.io with documentation (if applicable): home-assistant/home-assistant.github.io#6075
Example entry for configuration.yaml (if applicable):
homeassistant:
  packages: !include dir_named packages

packages/my_package.yaml
sensor first:
  - platform: template
    sensors:
      my_sensor_1:
        value_template: 1

sensor second:
  - platform: template
    sensors:
      my_sensor_2:
        value_template: 2

Checklist:

[X] The code change is tested and works locally.

[X] Local tests pass with tox. Your PR cannot be merged unless tests pass
If user exposed functionality or configuration variables are added/changed:

[X] Documentation added/updated in home-assistant.github.io

If the code communicates with devices, web services, or third-party tools:

[X] New dependencies have been added to the REQUIREMENTS variable (example).
[X] New dependencies are only imported inside functions that use them (example).
[X] New or updated dependencies have been added to requirements_all.txt by running script/gen_requirements_all.py.
[X] New files were added to .coveragerc.

If the code does not interact with devices:

[ ] Tests have been added to verify that the new code works.

Hi @thomasloven,
It seems you haven't yet signed a CLA. Please do so here.
Once you do that we will be able to review and accept this pull request.
Thanks!

Hi @thomasloven,
It seems you haven't yet signed a CLA. Please do so here.
Once you do that we will be able to review and accept this pull request.
Thanks!

I've added a test that checks that components like light 1: and light 2: are added to the configuration. Making sure they are read correctly, and that the actual configurations are merged is the responsibility of async_process_component_config and not related to my changes.

Congrats on your first PR merged 🎉


CAMEL-11781: Support for BoxUser.moveFolderToUser in camel-box.

Add support for BoxUser.moveFolderToUser in order to be able to move data from a user account into another before deleting an enterprise user as in the Box user interface.

Thanks for the PR it has been merged. Do you mind closing this?

Thanks.


Add widget to apply transform and produce new layer

Work in progress to apply affine transformation to another layer.
Still need to add tests but it seems to be working.

We're currently processing your upload.  This comment will be updated when the results are available.

@andreasmarnold I've made a few changes, you can have a look at the commits above for context. 😊 (btw: by default, when you use a branch in your own fork to make a PR to an upstream repo, the owners of that repo (🙋♂) can push to that specific branch, which is what I did here.
But anyway, now locally you can grab these changes with git switch main; git pull upstream main, and we can move on to the next thing! 😊


Outdated extension indicator outputs wrong number

description
As you can see below there's no outdated extension showed inbox but indicator shouts out that I need to update one.
Personally I don't met this issue before 1.25.0.

enviroment

VSCode Version: 1.25.0
OS Version: Mac OSX 10.13.6

Does this issue occur when all extensions are disabled?: No

Sorry I just notice that vscode separates disabled extension in 1.25. The extension which needs to be updated is in the disabled category.


Remove warning on downcasting from size_t to btf_type_id

In the function btf_type_data::append(const btf_kind &kind), id_to_kind.size() is downcast from size_t to btf_type_id, which generates a C4267: 'initializing': conversion from 'size_t' to 'libbtf::btf_type_id' warning.
To fix this, check for size_t range and static cast it.

coverage: 93.565% (-0.07%) from 93.632% when pulling 36ed6041d479c6d6d937a9b481ee7d4ba00790c1 on warning_narrowing into<PHONE_NUMBER>ddf1e89cc75e416a36611267d38cff on main.


ThreadPool() is not supported on AWS Lambda using Python 3.7 and above

We use docspring for filling out documents in our event-driven python system that runs within AWS Lambdas.
Recently, when upgrading from Python 3.6, your component started failing with the following callstack:
File "/var/task/api/external/docspring_api.py", line 10, in __init__     self._client = docspring.Client()
File "/var/task/docspring/api/pdf_api.py", line 32, in __init__     api_client = ApiClient()
File "/var/task/docspring/api_client.py", line 68, in __init__     self.pool = ThreadPool()
File "/var/lang/lib/python3.8/multiprocessing/pool.py", line 925, in __init__    Pool.__init__(self, processes, initializer, initargs)
File "/var/lang/lib/python3.8/multiprocessing/pool.py", line 196, in __init__     self._change_notifier = self._ctx.SimpleQueue()
File "/var/lang/lib/python3.8/multiprocessing/context.py", line 113, in SimpleQueue     return SimpleQueue(ctx=self.get_context())
File "/var/lang/lib/python3.8/multiprocessing/queues.py", line 336, in __init__     self._rlock = ctx.Lock()
File "/var/lang/lib/python3.8/multiprocessing/context.py", line 68, in Lock     return Lock(ctx=self.get_context())   File "/var/lang/lib/python3.8/multiprocessing/synchronize.py", line 162, in __init__     SemLock.__init__(self, SEMAPHORE, 1, 1, ctx=ctx)
File "/var/lang/lib/python3.8/multiprocessing/synchronize.py", line 57, in __init__     sl = self._semlock = _multiprocessing.SemLock( OSError: [Errno 38] Function not implemented

This occurs because the lambda execution environment does not support shared memory.
More: https://aws.amazon.com/blogs/compute/parallel-processing-in-python-with-aws-lambda/

Hello, sorry to hear about that! I’m not too familiar with the internals of how our python API library works, or why it needs to use shared memory. We generate this client library using OpenAPI generator. It might be possible that this issue is fixed in a later version, but I’m not sure, and it can take a lot of effort to update since we have a few customizations that need to be merged in carefully. The other difficulty is that this might just be a limitation with AWS functions, so not too sure if we promise anything unfortunately. But I will definitely put this on our todo list and see if there’s something we can do. In the meantime, it might be easier if you could please make the HTTP requests to call the API directly.

Just wanted to add to this seeing third-party move to a log in system that use multiprocessing in the backend and cause failures.
as example https://community.wandb.ai/t/integration-of-wandb-with-aws-lambda/2280/3

I found that someone else ran into a similar issue, and solved it by using their own thread-safe (not multiprocessing-safe) lock.
Since the one built in to Python is meant to be multiprocessing-safe, and requires /dev/shm (which doesn't exist in Lambda).
https://github.com/ecederstrand/exchangelib/pull/1001/commits/ea45d19ff8dac343e24aadb031df464808313abb


Error occur when executing 'install_dependencies'

Line 47 in android/build.sh
curl -o install-build-deps-android.sh https://src.chromium.org/svn/trunk/src/build/install-build-deps-android.sh
the above command does not work anymore, producing HTTP404 error

Can you try with the latest version? it was updated yesterday

now it works, thanks.


[FEATURE] Default theme refactor for small components

Description

Refactor default theme to be able to have the smallest reasonable components to override while implementing the project
Acceptance criteria

[ ] chop big default-theme components to smaller parts

May I help with this or is this strictly for the core team?

@Rigo-m sorry for missing this question. Sure you can help and it would be great:) Keep in mind to have as small changes as possible per PR so to not interfere with other works as there is a lot going on now:) with any questions just ask me on Slack

Done as for 0.1.0. We'll be going this way without breaking changes with priority for parts which will be suggested in issues from the community.


Support string to IValue dict in stringMapFrom for pytorch

Description
I’m planning to use djl mainly for serving pytorch models given it seems to be the most performant option available apart from implementing a service in c++.
The input type of my model is quite complex so it’s not possible for me to use the Predictor api which feeds NDList to model. As a result I decided to work directly with the pytorch engine.
When I was researching how to construct an IValue that matches my model’s input type, I realized the current JNI layer only supports Map<String, NDArray>, but not Map<String, IValue>.
I think supporting Map<String, IValue> will make it much more flexible for anyone working with pytorch engine. In my case, for example, I need to create Map<String, Tuple<Tensor, Tensor>>, which is impossible right now.
If I’m understanding correctly it should not be a lot of effort to add this support given Tensor (NDArray) is itself an IValue base type

We do support IValue in PyTorch. But IValue is PyTorch specific, so didn't make it available at DJL API level. So if you want to use IValue, you have to write engine specific code.
See test code: https://github.com/deepjavalibrary/djl/blob/master/engines/pytorch/pytorch-engine/src/test/java/ai/djl/pytorch/integration/IValueTest.java#L37
When you using IValue, you must be care to close all IValue you created, otherwise will cause memory.

@frankfliu thanks for your reply! Just to clarify, I’m already using IValue, and I’m asking if we can enhance the IValue creation api.
In the existing IValue api, there’s a method IValue.stringMapFrom which takes a Map<String, PtNDArray>, but in my case I need to create an IValue from Map<String, IValue>

@jiyuanq
No, we currently don't support it. I think PyTorch java api doesn't support it either. Feel free add add a PR to add Map<String, IValue> support if you need such feature.

@frankfliu By “pytorch Java API” do you mean this? https://pytorch.org/javadoc/1.9.0/
it looks like it’s supported there, see “dictStringKeyFrom”
I think the c++ api supports generic dict of Dict<IValue, IValue>, so I’m guessing even when we pass in a Map<String, PtNDArray>, underlying the keys and values will be wrapped as IValues

@jiyuanq I see, now I remember, we dropped Dict(str, IValue) in favor of Dict(str, Tensor), C++ API support generic dict, but it's a bit hard to map in java, for simplicity, we only exposed Dict(str,  Tensor)
We cannot have both:
    public static IValue stringMapFrom(Map<String, PtNDArray> map);
    public static IValue stringMapFrom(Map<String, IValue> map);

The following works, but a bit ugly:
    public static IValue stringTensorMapFrom(Map<String, PtNDArray> map);
    public static IValue stringIValueMapFrom(Map<String, IValue> map);

@frankfliu I see. Thanks for the additional context! Is it possible to add stringIValueMapFrom as a new method?
I took a look at the code and it looks like it doesn't involve too much change. Just some changes to Java_ai_djl_pytorch_jni_PyTorchLibrary_iValueFromStringMap in ai_djl_pytorch_jni_PyTorchLibrary_ivalue.cc plus corresponding java changes in IValue.java.
I was thinking about taking a stab myself but the build and release process seems quite complex, and the documentation about testing the JNI layer end to end seems rather sparse.
It would be great if someone familiar with the dev process can help add the support. What do you think?

@jiyuanq
We will consider to priorities this feature.

This functionality is now included in DJL https://github.com/deepjavalibrary/djl/blob/master/engines/pytorch/pytorch-engine/src/main/java/ai/djl/pytorch/jni/IValue.java#L313.


[Bug] Non-Admin / Participant Roles not usable

Currently, JUDGE and VIEWER are not able to use the system, as the frontend receives 404 for run/info requests

See #76


Set AWS_DEFAULT_REGION environment variable

Set AWS_DEFAULT_REGION environment variable to one set as default region in security monkey.
This fix addresses following issue in aws govcloud:
botocore.exceptions.ClientError: An error occurred (InvalidClientTokenId) when calling the AssumeRole operation exception in absence of .aws/config file for all find_changes calls.

@mikegrima I am not sure why SyncNetworksTestCase.test_add_whitelist_entries_with_s3 would fail with HTTPClientError: An HTTP Client raised and unhandled exception: I/O operation on closed file