Allow sanitising of batch variable names.

I only fixed the merge conflict between develop and #139. I'm not convinced that the name cleaning approach in batch.py is the right way to go though -- it allows sanitization to be turned off, silently replaces invalid chars rather than throwing exceptions, and might itself be vulnerable to SQL injection. It's certainly better than not having any sanitization whatsoever (the current state), but I think it needs more work before I'd consider it production-ready.

Not sure why the CI build failed, the test file didn't get changed and looks fine to me. I restarted the build, and we'll see what happens now.

@mogui this is really weird, and I can't figure out what's going on. The test claims that on the line:
class OGMAnimalsTestCase(OGMAnimalsTestCaseBase):

we have that OGMAnimalsTestCaseBase is undefined, even though its definition is ~10 lines above that. Furthermore, the test claims that the problematic line is line 65 in its file, whereas my editor shows it as line 52. The file in question wasn't modified in this commit.
Thoughts on what's going on? Can you pull the branch manually and test it locally? The tests run fine on my machine.

wait @obi1kenobi it was my fault messing with the merge I've now restored it correctly :)
Something is wrong with Travis it seems that randomly it doesn't launch orient correctly and tests fails failing the connection :O

Restarting the build again, hopefully it'll work this time :)

Great. The last thing would be to update PyPI with a new version that has all these extra checks, if you have a moment.


Create .gitignore  file

Added .gitignore  file  for HF Platform push and deploy in HuggingFace spaces

Approved for merge


Readme example fails; could use a little more detail on usage

Hi, new to mermaid and to this plugin.  Thank you for making it available!
Issue
The example given in the readme fails, at the moment.  Looks like inline comments are broken for "graph TB" diagrams.  I naively used this as my initial test and it wasn't working at all.  (I know, this isn't your fault.)

Couple that with errors displayed on both the Package Control page:

and the Github one:

... and everything seemed a little shakey, for a while.  I was able to test in parallel in VSCode and managed to figure stuff out.
Suggestions

Use a trivial Hello, world example. (Can have a fancy one as an additional example to show off the coolness ;-) )
Add usage.  How to run it in the most foolproof manner -- is it better to start with a .mermaid file or a .md one?  Use the Build feature or is there some other way?
What is expected to happen.  Turns out it creates .png files in the same location as the input file.

I'm spoiled by Markdown Preview, because somehow I was expecting a browser window to pop up with the markdown and mermaid output seamlessly integrated.   Guess I need to go talk to those people to suggest they add support for your plugin...
Thanks

I'm in the same boat as @tomhundt . I've got Mermaid installed, and I've got the Mermaid package for Sublime Text installed. But now what? I can create a Mermaid file, set it as Mermaid syntax, and then do the command Build With: Mermaid. That leaves me with a .png file. OK, cool. But how do I embed Mermaid code in my Markdown and make them play together?


[Bug][Manager] Manager client occurred NPE when parsing the ext info

What happened
Manager client occurred NPE when parsing the ext info.
What you expected to happen
The error trance is:
java.lang.NullPointerException: null
    at org.apache.inlong.manager.client.api.util.InlongParser.parseGroupFrom(InlongParser.java:134)

How to reproduce
Just call the method InlongParser.parseGroupFrom(), you'll see the above error.
Environment
No response
InLong version
master
InLong Component
InLong Manager
Are you willing to submit PR?

[X] Yes, I am willing to submit a PR!

Code of Conduct

[X] I agree to follow this project's Code of Conduct

I'll fix this bug.


All the query params in "Additional Query Parameters" of federated oauth/openid connect IDP config is not visible in management console

Add space separated multiple scopes in additional query parameters of fed authenticator configs.
scope=openid profile vo fed rrn
Save and view again. few values are missing as below.
scope=openid
Same issue reported in : https://wso2.org/jira/browse/IDENTITY-6736
IS - 5.1.0

Fixed in https://github.com/wso2-support/carbon-identity/pull/323

Additional fixes in https://github.com/wso2-support/carbon-identity/pull/324

Fixed in master with https://github.com/wso2/carbon-identity-framework/pull/2181


2.9 not published on nuget?

Is it github-only release or something went wrong with publishing?

Also curious. NuGet releases always seem to be forgotten or delayed.


Is there any plan to add demonstration of the Java technology stack?

Question
Hi,
I've given a rough preview of the technology stack used in the webstore demo, and I noticed the grpc framework is involved.
But, from my point of view, the content of the Java technology stack involves less, especially the more popular springboot/springcloud.
Do we have a plan on this?
BTW, I can participate in this part of the enhancement. :-P
Use Github Discussions.

The thought with gRPC & http as our communication protocols is that they’d be broadly generic to cover any service communication.
I’d recommend commenting or adding this suggestion to our open architectural doc. There’s a link in GitHub discussions to it.
I’m not sure of any Java specific additions outside of ensuring all the OpenTelemetry signals / features are demonstrated. But we’d certainly love some energy in this space

Okay, I will add it.


From Discord: Effect.mergeAll failing in case of Z being an array

What version of Effect is running?
No response
What steps can reproduce the bug?
The user described scenarios with Effect.mergeAll that yielded failures during runtime:
import { Effect, pipe,ReadonlyArray } from "effect";

const program = Effect.gen(function*($) {
    const result = yield* $(
        pipe([["a"],["aa"],["aaa"],["aaaa"]].map((a) => Effect.succeed(a)), Effect.mergeAll("", (b, a) => [...b,...a])))
      })

    Effect.runFork(program);

import { Effect, pipe,ReadonlyArray } from "effect";

const program = Effect.gen(function*($) {
    const result = yield* $(
        pipe([["a"],["aa"],["aaa"],["aaaa"]].map((a) => Effect.succeed(a)), Effect.mergeAll("", (b, a) => ReadonlyArray.appendAll(b,a))))
      })

    Effect.runFork(program);

Returns: [ 'a', 'aa', 'aaa', 'aaaa' ]
Yet Typewise, b should be a string.
import { Effect, pipe,ReadonlyArray } from "effect";

const program = Effect.gen(function*($) {
    const result = yield* $(
        pipe([["a"],["aa"],["aaa"],["aaaa"]].map((a) => Effect.succeed(a)), Effect.mergeAll([], (b, a) => [...b,...a])))
      })

    Effect.runFork(program);

import { Effect, pipe,ReadonlyArray } from "effect";

const program = Effect.gen(function*($) {
    const result = yield* $(
        pipe([["a"],["aa"],["aaa"],["aaaa"]].map((a) => Effect.succeed(a)), Effect.mergeAll(ReadonlyArray.empty<string>(), (b, a) => ReadonlyArray.appendAll(b,a))))
      })

    Effect.runFork(program);

Was described as being fine typewise, yet failing with TypeError: ab is not a function on runtime.
What is the expected behavior?
The user would expect the possibility of the return type being an array.
What do you see instead?
No response
Additional information
No response

Repro:
it.effect("mergeAll - should work when Z is an interable", () =>
  Effect.gen(function*($) {
    const result = yield* $([3, 5, 7].map(Effect.succeed), Effect.mergeAll([] as Array<number>, (b, a) => [...b, a]))
    assert.deepStrictEqual(result, [3, 5, 7])
  }))

The likely source of the issue is this check https://github.com/Effect-TS/effect/blob/2c64bf0f003c9542b0b6efd571c516337b32b6af/src/internal/fiberRuntime.ts#L2228
In the repro, Z is an Iterable, and the condition results in the utilization of the data-first version.

Will need to add a check to see if args[2] is a function.

@tim-smart (args) => args.length >= 3 && Predicate.isFunction(args[2]) perhaps?


Can't disable copy of scripts and include

Hi Mr. Hedgefog, thanks a lot for the new features and for having adressed some the issues I have posted, I didn't have the time to test them because I wasn't into AMXX development anymore by that time.
Removing or leaving empty the variables scripts or include on the output section will not disable the copying of these files on the dist default folder.
My proposed solution will be the same as in #3, when the string is empty '' or not provided in the file, then disable the copying.
The feature is useful if you're just planning on only distributing compiled binaries, or you're just using the hot-reload feature (my case).

Make sure you are using the latest version.
Scripts output is optional: https://github.com/Hedgefog/node-amxxpack/blob/964547c4258c1abaec90318c19d0a57dfcb64e8d/src/builder/builder.ts#L157
What about include output, I'll make it optional in a future update.

According to amxxpack --version, I'm using version 1.3.3 which I downloaded from npm.
And my .amxxpack.json looks like this:
{
  "input": {
    "scripts": "./valve/addons/amxmodx/scripting",
    "include": "./valve/addons/amxmodx/scripting/include",
    "assets": [
      {
        "dir": "./valve",
        "filter": "*.!(so)"
      }
    ]
  },
  "output": {
    "plugins": "C:/Users/rtxa/Documents/Servidores HL/AG Mod X/valve/addons/amxmodx/plugins",
    "assets": "C:/Users/rtxa/Documents/Servidores HL/AG Mod X/valve",
    "scripts": "",
    "include": ""
  },
  "compiler": {
    "dir": "./.compiler",
    "version": "1.10",
    "executable": "amxxpc"
  },
  "thirdparty": {
    "dir": "./.thirdparty",
    "dependencies": []
  },
  "include": [],
  "rules": {
    "flatCompilation": true
  }
}

And the log:
[INFO] Plugin updated: C:/Users/rtxa/Documents/Servidores HL/AG Mod X/valve/addons/amxmodx/plugins/agmodx.amxx
[INFO] Script updated: C:/Users/rtxa/Documents/GitHub/agmodx/dist/addons/amxmodx/scripting/agmodx.sma

I'm also using this with amxxpack build --watch

PD: When it's set to an empty string, it's copied in the project folder, which will be C:/Users/rtxa/Documents/GitHub/agmodx/, and not in the dist folder.
When the variable is just removed, then it gets copied to the default directory which is the dist folder: C:/Users/rtxa/Documents/GitHub/agmodx/dist.

Ok, that makes sense, I'll investigate and fix it.

Thanks for your report! Fixed in version 1.4.0.

Thanks for your report! Fixed in version 1.4.0.

It's been a while since you released the new version but I just stopped coding for HL in that time. I'm testing with version 1.4.4 and unfortunately the issue is still not fixed, not sure what are the changes you made but using an empty string on scripts and include isn't disabling the copy but instead copying the files in the base folder "C:/Users/rtxa/Documents/GitHub/agmodx/".

It's been a while since you released the new version but I just stopped coding for HL in that time. I'm testing with version 1.4.4 and unfortunately the issue is still not fixed, not sure what are the changes you made but using an empty string on scripts and include isn't disabling the copy but instead copying the files in the base folder "C:/Users/rtxa/Documents/GitHub/agmodx/".

Use null value instead of an empty string 😉
https://github.com/Hedgefog/node-amxxpack/blob/93206d5615ae8bfd1547ff5b4ffd862862516a3b/tests/project-config/resolver.test.ts#L33

Thanks, but because the change doesn't mention how the option is disabled I though that was the way without taking a look into the code. Anyway, it should be documented in the README.md to avoid any confusions.

Yep, that makes sense. Updated!


Update sbt-typelevel-ci-release, ... to 0.6.5

About this PR
📦 Updates

org.typelevel:sbt-typelevel-ci-release
org.typelevel:sbt-typelevel-mergify

from 0.4.22 to 0.6.5
📜 GitHub Release Notes - Version Diff
Usage
✅ Please merge!
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

⚙ Adjust future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "org.typelevel" } ]

Or, add this to slow down future updates of this dependency:
dependencyOverrides = [{
  pullRequests = { frequency = "30 days" },
  dependency = { groupId = "org.typelevel" }
}]

labels: sbt-plugin-update, early-semver-major, semver-spec-minor, version-scheme:early-semver, commit-count:n:2

Superseded by #122.


The format of the connection string is incorrect that created by clicking 'Get Shared Access Signature...' against a name & key attached storage account

Storage Explorer Version: 1.29.0-dev
Build Number: 20230215.1
Branch: main
Platform/OS: Windows 10/Linux Ubuntu 22.04/MacOS Ventura 13.2.1 (Apple M1 Pro)
Architecture: ia32/x64
How Found: Exploratory testing
Regression From: Not a regression
Steps to Reproduce

Select one storage account -> Use name & key to attach it.
Right click the name & key attached storage account.
Click 'Get Shared Access Signature...' -> Click 'Create'.
Copy the connection string -> Paste it to a clipboard or a text file.
Check whether the format of the connection string is correct.

Expected Experience
The format of the connection string is correct.
Actual Experience
The format of the connection string is incorrect.

Well, the connection string is clearly missing information. You can't connect to anything with just a SAS. You need endpoints, or at least an account name. So the problem is probably where the SAS is generated.

Hi @craxal Verified this issue on the main build 20230330.3.
The connection string is not correct but the error message has been removed. Could you please take a look?

@craxal the comments issue has been fixed with the bug 6737.
This bug still reproduces on the new build 20230413.5. So we are going to re-open it.

I'm using the same build (20230413.5), but it doesn't reproduce on my end. Please verify again, and if it still reproduces, please share the connection string in text (not a screenshot) you use (be sure it's secure).

Hi @craxal
To make sure we are on the same page.

The behavior I expected is 'the connection string is correct when creating by clicking 'Get Shared Access Signature...' against a name & key attached storage account.

The current behavior is 'the connection string created by clicking 'Get Shared Access Signature...' against a name & key attached storage account is incorrect. and prompts a clear error message when pasting on 'Connection string' field.

For secure, I will share the connection string on teams.

@v-xianya Using build 20230416.3, the SAS dialog from my end appears to be generating a valid SAS. Are you still able to reproduce? Am I missing something?

@craxal I am able to reproduce on the new build 20230418.4. The SAS is created against a name & key attached storage account node.

@MRayermannMSFT
It's not a regression. For name & key attached storage account, the action 'Get Shared Access Signature...' is added from the version 1.25.0. The related issue 5818

@v-xianya Oh, I see. The SAS was generated from an attached storage account. That's what I wasn't understanding. Yeah, key-attached connection strings don't explicitly define the endpoints, so we will need to infer them when generating the SAS. I've got a fix.

Verified this issue on the build main 20230419.4. Fixed.


Support web workers

I scoured the docs but couldn't find where Worker is exposed.

Perhaps a more general multi-threading API would be more fitting for RN? Though I can see the appeal, as web workers are very straightforward to both understand and use.

I think for now this is a "wontfix". Maybe if you have a specific proposal in mind it would be interesting to flesh it out in more detail and open a RFC-type issue? For now I am going to close this though.

Shouldn't Workers be a JSCore feature, not specific to React Native?

Workers are a Safari feature, not a JS feature. Some mechanisms like shared memory are JS features though.

Workers are a Safari feature, not a JS feature. Some mechanisms like shared memory are JS features though.

Not sure what you mean by this @ide.  Web Workers are in the standards.  MDS shows all of the browsers supporting at least some of the standard: https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers#Browser_compatibility

@jsdevel I think what he means, is that workers are actually built into safari, not JSCore, the Js engine that React Native uses since it not loading up a browser.
So yes, they do exist in all browsers, but when it comes to the split of what the feature is apart of, it means that React Native actually doesn't have access to them.

I think the fact that safari has them built in is irrelevant.   All browsers support the WW spec to some extent.
RN has ported WebSocket, fetch, and GeoLocation.

Well there are 2 discussions going on here. I was just asking about it being in JSCore which means it should be available. But it's probably not that trivial to add


CollectedClientData extensibility

It's unclear how the CollectedClientData struct would accommodate new keys in the future given its current state. Are there any plans to add an additional field to accommodate for unexpected keys? Something like kandim's CollectedClientData:
/// The data collected and hashed in the operation.
/// <https://www.w3.org/TR/webauthn-2/#dictdef-collectedclientdata>
#[derive(Debug, Serialize, Clone, Deserialize)]
pub struct CollectedClientData {
    /// The credential type
    #[serde(rename = "type")]
    pub type_: String,
    /// The challenge.
    pub challenge: Base64UrlSafeData,
    /// The rp origin as the browser understood it.
    pub origin: url::Url,
    /// The inverse of the sameOriginWithAncestors argument value that was
    /// passed into the internal method.
    #[serde(rename = "crossOrigin", skip_serializing_if = "Option::is_none")]
    pub cross_origin: Option<bool>,
    /// tokenBinding.
    #[serde(rename = "tokenBinding")]
    pub token_binding: Option<TokenBinding>,
    /// This struct be extended, so it's important to be tolerant of unknown
    /// keys.
    #[serde(flatten)]
    pub unknown_keys: BTreeMap<String, serde_json::value::Value>,
}

Closed by #6


Fix inconsistency recon config keys starting with recon and not ozone

What changes were proposed in this pull request?
Fix recon configs inconsistent
What is the link to the Apache JIRA
https://issues.apache.org/jira/browse/HDDS-4309?jql=project in (HDDS) AND labels in (newbie) AND assignee is EMPTY AND status in (open%2C Reopened)
How was this patch tested?
Build up project, launch dockers, and new default parameters were present but not old ones anymore.
On recon container:
> ozone getconf confKey recon.om.socket.timeout
Configuration recon.om.socket.timeout is missing.
> ozone getconf confKey ozone.recon.om.socket.timeout
5s

@frischHWC Thanks for working on this! The patch looks good to me except the failing checkstyles. Please fix those longer lines and I can merge it.
hadoop-ozone/recon/src/main/java/org/apache/hadoop/ozone/recon/ReconServerConfigKeys.java
 74: Line is longer than 80 characters (found 86).
hadoop-ozone/recon/src/main/java/org/apache/hadoop/ozone/recon/spi/impl/OzoneManagerServiceProviderImpl.java
 128: Line is longer than 80 characters (found 82).
hadoop-ozone/recon/src/main/java/org/apache/hadoop/ozone/recon/spi/impl/PrometheusServiceProviderImpl.java
 68: Line is longer than 80 characters (found 84).
hadoop-ozone/integration-test/src/test/java/org/apache/hadoop/ozone/recon/TestReconWithOzoneManager.java
 99: Line is longer than 80 characters (found 82).
hadoop-ozone/integration-test/src/test/java/org/apache/hadoop/ozone/TestOzoneConfigurationFields.java
 72: Line is longer than 80 characters (found 82).

Thanks @frischHWC for updating the patch.  Sorry, I forgot TestOzoneConfigurationFields, a unit test that checks whether properties in ozone-default.xml and the *ConfigKeys classes are in sync.  We need to enumerate the deprecated constants in addPropertiesNotInXml, since these are no longer present in the XML.
https://github.com/apache/hadoop-ozone/blob/f9b1ca45fdeaaa63b9355c5c54fafc96ddf4597e/hadoop-ozone/integration-test/src/test/java/org/apache/hadoop/ozone/TestOzoneConfigurationFields.java#L60-L76

Codecov Report

Merging #1478 into master will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master    #1478   +/-   ##
=========================================
  Coverage     75.49%   75.49%
  Complexity    10798    10798
=========================================
  Files          1021     1021
  Lines         52095    52095
  Branches       5103     5103
=========================================
  Hits          39328    39328
  Misses        10321    10321
  Partials       2446     2446

Continue to review full report at Codecov.

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@adoroszlai Thanks for the review and @frischHWC thanks for the contribution.


Solved issue #166

Updated badges in README.md with cooler badges.

Great! Thanks for the PR @GamerWhoDoesntGame.
However, I just noticed that white font over the yellow badge isn't readable. Can you change the 'issues' and 'pull requests' badge colour to something (try green?) which makes the text on it easily readable?

Ok, I'm on it.

I added it. You can have a look.

Great work @GamerWhoDoesntGame!


RNN: InvalidArgumentError when adding InitialState

Please go to Stack Overflow for help and support:
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes.  The current stock examples are pre-TF1.0 and do not run.  I have already posted an issue regarding them. (https://github.com/tensorflow/tensorflow/issues/9294#issuecomment-294944970)
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 14.04
TensorFlow installed from (source or binary): Binary
TensorFlow version (use command below): TF1.1.0
Bazel version (if compiling from source): n/a
CUDA/cuDNN version: 5.1
GPU model and memory: p2-xlarge with 12GiB
Exact command to reproduce:

When training a simple two layer RNN, if I do not include the initialstate, the graph trains properly, if I add the initialstate, then I get the following error.
Brief code (full code below):
    initial_state = lstm_cells.zero_state(batch_size, tf.float32)
    RNN_outputs, state = tf.contrib.rnn.static_rnn(lstm_cells, inputs=Xnew, dtype=tf.float32, initial_state=initial_state)

Error message (full message below):
InvalidArgumentError (see above for traceback): ConcatOp : Dimensions of inputs should match: shape[0] = [20,75] vs. shape[1] = [2500,75]
	 [[Node: RNN/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/basic_lstm_cell_1/concat = ConcatV2[N=2, T=DT_FLOAT, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/gpu:0"](RNN/split, RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros_1, RNN/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/basic_lstm_cell_1/concat/axis)]]
	 [[Node: Mean_1/_9 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_16414_Mean_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

If I print the initial_state variable, I get this:
(LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros_1:0' shape=(2500, 75) dtype=float32>), LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros_1:0' shape=(2500, 75) dtype=float32>))

If I print the state producted by static_rnn call:
(LSTMStateTuple(c=<tf.Tensor 'RNN/rnn/multi_rnn_cell_299/cell_0/basic_lstm_cell/add_1:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/rnn/multi_rnn_cell_299/cell_0/basic_lstm_cell/mul_2:0' shape=(2500, 75) dtype=float32>), LSTMStateTuple(c=<tf.Tensor 'RNN/rnn/multi_rnn_cell_299/cell_1/basic_lstm_cell/add_1:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/rnn/multi_rnn_cell_299/cell_1/basic_lstm_cell/mul_2:0' shape=(2500, 75) dtype=float32>))

Here is the full message:
---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-15-5e6d1756b352> in <module>()
     90         Xin   : X_test,
     91         Ytrue : one_hot(y_test, LabelMax),
---> 92         keep_prob: 1.0
     93     }
     94 )

/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
    776     try:
    777       result = self._run(None, fetches, feed_dict, options_ptr,
--> 778                          run_metadata_ptr)
    779       if run_metadata:
    780         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
    980     if final_fetches or final_targets:
    981       results = self._do_run(handle, final_targets, final_fetches,
--> 982                              feed_dict_string, options, run_metadata)
    983     else:
    984       results = []

/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1030     if handle is None:
   1031       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1032                            target_list, options, run_metadata)
   1033     else:
   1034       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args)
   1050         except KeyError:
   1051           pass
-> 1052       raise type(e)(node_def, op, message)
   1053
   1054   def _extend_graph(self):

InvalidArgumentError: ConcatOp : Dimensions of inputs should match: shape[0] = [20,75] vs. shape[1] = [2500,75]
	 [[Node: RNN/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/basic_lstm_cell_1/concat = ConcatV2[N=2, T=DT_FLOAT, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/gpu:0"](RNN/split, RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros_1, RNN/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/basic_lstm_cell_1/concat/axis)]]
	 [[Node: Mean_1/_9 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_16414_Mean_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op u'RNN/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/basic_lstm_cell_1/concat', defined at:
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/traitlets/config/application.py", line 658, in launch_instance
    app.start()
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/zmq/eventloop/ioloop.py", line 177, in start
    super(ZMQIOLoop, self).start()
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-14-eaca1bbf91d8>", line 48, in <module>
    RNN_outputs, state = tf.contrib.rnn.static_rnn(lstm_cells, inputs=Xnew, dtype=tf.float32, initial_state=initial_state)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn.py", line 197, in static_rnn
    (output, state) = call_cell()
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn.py", line 184, in <lambda>
    call_cell = lambda: cell(input_, state)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 953, in __call__
    cur_inp, new_state = cell(cur_inp, cur_state)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 241, in __call__
    concat = _linear([inputs, h], 4 * self._num_units, True)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 1048, in _linear
    res = math_ops.matmul(array_ops.concat(args, 1), weights)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1034, in concat
    name=name)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 519, in _concat_v2
    name=name)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/ubuntu/anaconda2/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): ConcatOp : Dimensions of inputs should match: shape[0] = [20,75] vs. shape[1] = [2500,75]
	 [[Node: RNN/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/basic_lstm_cell_1/concat = ConcatV2[N=2, T=DT_FLOAT, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/gpu:0"](RNN/split, RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros_1, RNN/rnn/multi_rnn_cell/cell_0/basic_lstm_cell/basic_lstm_cell_1/concat/axis)]]
	 [[Node: Mean_1/_9 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_16414_Mean_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Here is the network creation code:
# Clear the graph memory
tf.reset_default_graph()

# Graph input/output
Xin   = tf.placeholder(tf.float32, [None, n_steps, n_input] , name= "Xin")
Ytrue = tf.placeholder(tf.float32, [None, n_classes]        , name= "Ytrue")

# Graph weights
weights={}
weights['Pre' ] = tf.Variable(tf.random_normal([n_input     , n_hiddenPre ]), name="Wght_Pre") # Hidden layer weights
weights['LSTM'] = tf.Variable(tf.random_normal([n_hiddenPre , n_hidden    ]), name="Wght_LSTM") # Hidden layer weights
weights['Post'] = tf.Variable(tf.random_normal([n_hidden    , n_hiddenPost]), name="Wght_Post")
weights['out' ] = tf.Variable(tf.random_normal([n_hiddenPost, n_classes   ]), name="Wght_Out")

biases={}
biases['Pre' ] = tf.Variable(tf.random_normal([n_hiddenPre ]), name="Bias_Pre")
biases['LSTM'] = tf.Variable(tf.random_normal([n_hidden    ]), name="Bias_LSTM")
biases['Post'] = tf.Variable(tf.random_normal([n_hiddenPost]), name="Bias_Post")
biases['out' ] = tf.Variable(tf.random_normal([n_classes   ]), name="Bias_Out")

Xnew = prepareX(Xin)

with tf.name_scope('DensePre'):
    Xpre = tf.matmul(Xnew, weights['Pre']) + biases['Pre']
    keep_prob  = tf.placeholder(tf.float32)
    Xpre_drop = tf.nn.dropout(Xpre, keep_prob)

    # Linear activation
    Xnew = tf.matmul(Xpre_drop, weights['LSTM']) + biases['LSTM']

with tf.name_scope('RNN'):
    # Split data because rnn cell needs a list of inputs for the RNN inner loop
    Xnew = tf.split(Xnew, n_steps, axis=0)
    # new shape: n_steps * (batch_size, n_hidden)

    # Can use one or more LSTM layers
    lstm_cell1  = tf.contrib.rnn.BasicLSTMCell(n_hidden, state_is_tuple=True)
    lstm_cell2  = tf.contrib.rnn.BasicLSTMCell(n_hidden, state_is_tuple=True)
    lstm_cells  = tf.contrib.rnn.MultiRNNCell([lstm_cell1,lstm_cell2], state_is_tuple=True)
    #RNN_outputs, state = lstm_cells(Xnew, state=state)  # this code fails, so used line above without state

    # The following lines are for the bidirectional RNN, but effort was blocked due to an opaque error message
    #  lstm_cell_back   = tf.contrib.rnn.BasicLSTMCell(n_hidden, state_is_tuple=True)
    #  lstm_cells_back  = tf.contrib.rnn.MultiRNNCell([lstm_cell_back] * 2, state_is_tuple=True)

    # Get LSTM cell output
    initial_state = lstm_cells.zero_state(batch_size, tf.float32) # Not used, but should be!
    RNN_outputs, state = tf.contrib.rnn.static_rnn(lstm_cells, inputs=Xnew, dtype=tf.float32, initial_state=initial_state)
    #RNN_outputs, state = tf.contrib.rnn.static_rnn(lstm_cells, inputs=Xnew, dtype=tf.float32)
    print(initial_state)
    print(state)

with tf.name_scope('DensePost'):
    Xnew = tf.matmul(RNN_outputs[-1], weights['Post']) + biases['Post']
    Xnew = tf.nn.dropout(Xnew, keep_prob)

with tf.name_scope('DenseOut'):
    # Linear activation
    Ypred        = tf.add(tf.matmul(Xnew, weights['out']),biases['out'], name="Ypred_raw")
    # Compute softmax result
    YpredSoftMax = tf.nn.softmax(Ypred   , dim =1, name="prediction")
    YpredIndex   = tf.argmax(YpredSoftMax, axis=1, name="predIndex" )
# Loss, optimizer and evaluation; Regularization term
l2 = lambda_loss_amount * sum(tf.nn.l2_loss(tf_var) for tf_var in tf.trainable_variables())
# L2 loss prevents this overkill neural network to overfit the data
cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=Ypred, labels=Ytrue)) + l2 # Softmax loss
optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(cost) # Adam Optimizer

correct_pred = tf.equal(tf.argmax(Ypred,1), tf.argmax(Ytrue,1))
accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))

To summarize, it looks like the state is [2500, 75], but the initial state expected by the code is [20, 75].
@ebrevdo any idea?

Yeah, so if the lstm_cells object is generating its own initial state vector, then why is it generating the wrong dimensions?

If I'm not incorrect, the proper initial_state tensor should be [2500,75].  Given that the mini-batch size is 2500 and the lstm cell count is 75.

I'm seeing that you have:
Xnew = tf.split(Xnew, n_steps, axis=0)
How many elements are there in Xnew after this step, and what are their shapes?
Furthermore, can you print(initial_state) for me?

@ebrevdo : Thanks for replying.  initial_state is shown at the top of the original post here.
Reprinting:
(LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros_1:0' shape=(2500, 75) dtype=float32>), LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros_1:0' shape=(2500, 75) dtype=float32>))

Got it.  Did you expect to have a batch_size of 2000?  It seems like the
batch_size variable you passed to cell.zero_state was 2000.
On Sat, May 6, 2017 at 2:41 PM, Kevin Shaw<EMAIL_ADDRESS>wrote:

@ebrevdo https://github.com/ebrevdo : Thanks for replying. initial_state
is shown at the top of the original post here.
Reprinting:
(LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros_1:0' shape=(2500, 75) dtype=float32>), LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros_1:0' shape=(2500, 75) dtype=float32>))
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err, 2500.
On Sat, May 6, 2017 at 2:43 PM, Eugene Brevdo<EMAIL_ADDRESS>wrote:

Got it.  Did you expect to have a batch_size of 2000?  It seems like the
batch_size variable you passed to cell.zero_state was 2000.
On Sat, May 6, 2017 at 2:41 PM, Kevin Shaw<EMAIL_ADDRESS>wrote:

@ebrevdo https://github.com/ebrevdo : Thanks for replying.
initial_state is shown at the top of the original post here.
Reprinting:
(LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState/zeros_1:0' shape=(2500, 75) dtype=float32>), LSTMStateTuple(c=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros:0' shape=(2500, 75) dtype=float32>, h=<tf.Tensor 'RNN/MultiRNNCellZeroState/BasicLSTMCellZeroState_1/zeros_1:0' shape=(2500, 75) dtype=float32>))
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Correct the batch size is 2500.

Perhaps a related question is: what size should Xnew be?   Given the batch size of 2500, and a frame size of (300 x 12), where the feature vector length for each time step is 12.

Sounds like Xnew should be a list of 300 tensors, each one shaped 2500x12.
On Sat, May 6, 2017 at 3:15 PM, Kevin Shaw<EMAIL_ADDRESS>wrote:

Perhaps a related question is: what size should Xnew be? Given the
batch size of 2500, and a frame size of (300 x 12), where the feature
vector length for each time step is 12.
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Okay.  Let me think about this.  I'll get back tonight.  Thanks!

Okay, after about five hours on this, I've ditched the old static_rnn approach and switched to a dynamic_rnn which eliminated those issues about input shape.  If I understand correctly, with the dynamic_rnn, I can feed an input Tensor of shape [b x n x f] where b is the batch_size, n is n_steps, and f is the number of features, n_feat, directly into the RNN object.
Long story short, there is nothing like a little "confessional debugging" (as a friend likes to say) to solve a problem.  I wrote up a long answer here documenting everything I'd found and happened to notice that the error was showing up only on the test data, not the training data.  I'm using a smaller data set for this graph testing working and the test set is smaller than the 2500 element batch size that I'm using for the training.  Hence, for the test set, when the tensor count is smaller than the batch size, the initial state tensor will not match the state result from the RNN.
The solution is to use a variable batch_size based on the size of the Xin value, and to then generate a variable initial_state dynamically based on this:
batch_size_T  = tf.shape(Xin)[0]
initial_state = lstm_cells.zero_state(batch_size_T, tf.float32)

So, problem solved.  Thanks for the help!!!

In my case, I changed the batch size from 24 to 1, then problem was solved.

@kevinashaw i am getting the same error and also the code ::initial_state = lstm_cells.zero_state(batch_size_T, tf.float32) does not work any help??


[ARCTIC-1646][Bug]: Build failed when change hadoop version to 3.2.1

Why are the changes needed?

close https://github.com/NetEase/arctic/issues/1646#issue-1787080167
Brief change log
update org.apache.commons.lang.* to org.apache.commons.lang3.* in AMS module.
How was this patch tested?

[ ] Add some test cases that check the changes thoroughly including negative and positive cases if possible

[ ] Add screenshots for manual tests if appropriate

[ ] Run test locally before making a pull request

Documentation

Does this pull request introduces a new feature? (yes / no)
If yes, how is the feature documented? (not applicable / docs / JavaDocs / not documented)

Thanks a lot for your contribution!
Based on your code, I was able to build successfully, but when starting AMS, the following error occurred:

It seems to be caused by a conflict in the Guava dependency. Can you also fix this issue?

Thanks a lot for your contribution!
Based on your code, I was able to build successfully, but when starting AMS, the following error occurred:
It seems to be caused by a conflict in the Guava dependency. Can you also fix this issue?

Guava is used by hadoop common, hive-metastore and this project, Can we explicitly declare a guava dependency？

Can we explicitly declare a guava dependency？

Yes, although the Arctic project depends on the Guava package that the Iceberg project shade on, in order to solve the conflict between Hadoop and Hive's dependencies on Guava, specifying the Guava version that the project depends on may be a good solution.
However, we may still need to validate this solution by conducting actual deployment testing to ensure that it does not introduce any other issues.

Can we explicitly declare a guava dependency？

Yes, although the Arctic project depends on the Guava package that the Iceberg project shade on, in order to solve the conflict between Hadoop and Hive's dependencies on Guava, specifying the Guava version that the project depends on may be a good solution.
However, we may still need to validate this solution by conducting actual deployment testing to ensure that it does not introduce any other issues.

Thanks, I build and start ams to do few simple tests.

@zhaomin1423 Here is the code I previously attempted to solve this problem, which can be used as a reference: master...zhoujinsong:arctic:adapt-commons-dependency

Maybe adding a hadoop-3 profile to declare hadoop-client-api as dependency is more suitable for hadoop3.

fixed by 1728.


Better search

It would be great to use a search tool that scrapes the website, to easily get pages rendered using different methods.
One tool that looks quite promising that @Emiller88 found is algolia: https://www.algolia.com/developers/search-api-php/

I think this is what we want https://pagefind.app/

I think this is what we want https://pagefind.app/

Almost. Didn't get the weights right for my taste.
But there is something else on the way #1981

Looks great! Just some form of search 😆

Almost. Didn't get the weights right for my taste.

What do you mean by weights?

What do you mean by weights?

The relevance of each result, which decides the order by which they come up.


proposal changes for benchmark runs

a proposal to run benchmark

Approving this. However, to deploy these changes we will need to make changes on the mech as well. I propose we merge this with those changes together, once we have them.

We just discussed this PR on our call. We are making some further improvements to the tools and need to merge this first.  @DavidMinarsch maybe check out the above comments to see how we should proceed.


Few more edits to Sosc form

Description
This PR includes creating panels for few sections, few rewording etc.
Fixes # (issue)
Type of change
Please delete options that are not relevant.

[ ] 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 not work as expected)
[ ] This change requires a documentation update

How Has This Been Tested?
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration

[ ] Test A
[ ] Test B

Checklist

[ ] I have read the CONTRIBUTING doc
[ ] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[ ] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes
[ ] Any dependent changes have already been accepted and merged

Further comments

@nupurdixit13 please format the document in the PR, not able to compare the difference without that

Done. Can you pls check now and let me know in case of any issues?


Proximity Observer error

Hello i use the exemple code from estimote and i have error about Proximity Observer Error like this any idea ?
Mac Mojave 10.14.2
Version 10.1 (10B61)
react-native-cli: 2.0.1
react-native: 0.57.8

Proximity Observer error:
Error Domain=EPXProximityObserverErrorDomain Code=1 "Fetching tags from Cloud failed."
 UserInfo={
NSUnderlyingError=0x280b54c60 {
Error Domain=EstimoteProximitySDK.PersistentTagsRepository.Error Code=2 "When running offline, internet connection is required when starting the observer for the first time."
},
NSLocalizedDescription=Fetching tags from Cloud failed., NSLocalizedRecoverySuggestion=Make sure your cloud credentials are correct and you have a valid internet connection. See CloudCredentials for more.
}

Thank for your help :)
PS: yes i use my own token and id ^^

Have to use « tag » and monitoring

@tomtomgo92 what are you trying to say ? please help me i am also facing this issue .


Flexible losses

Add more flexibility for which loss is plottet

Offer a flexible amount of losses
Make the plotted losses configurable via the plot callback

I guess we can close this one.


[Bug]: placeholder texts not readable at signup page in dark mode

The placeholder texts are camouflaged in dark mode, I am not able to show cause for some reason the screenshots are not being uploaded

The placeholder texts are camouflaged in dark mode, I am not able to show cause for some reason the screenshots are not being uploaded

Use lighshot chrome extension for screenshot.. Give me the sreenshots.

Hyy @PriyaD17, I'm assigning this issue to you.

Can you give star to this repo?

Thanks mate! I already gave a star


adding guacdiff to guacone

Description of the PR
Adding diff command to guacone
PR Checklist

[ ] All commits have a Developer Certificate of Origin (DCO) -- they are generated using -s flag to git commit.
[ ] All new changes are covered by tests
[ ] If GraphQL schema is changed, make generate has been run
[ ] If OpenAPI spec is changed, make generate has been run
[ ] If collectsub protobuf has been changed, make proto has been run
[ ] All CI checks are passing (tests and formatting)
[ ] All dependent PRs have already been merged

@arorasoham9, are you ready for a review?

@nathannaveen I think I'll add some more commits to this.

@nathannaveen I think I'll add some more commits to this.

Could you make this a draft PR until it is ready for review?

@arorasoham9 please mark it for review when its ready

Can you also fix the lint and static analysis errors?


srsran: 21.10 -> 22.04

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://github.com/srsran/srsran/releases.
meta.description for srsran is: "Open-source 4G and 5G software radio suite."
meta.homepage for srsran is: "https://www.srslte.com/"
meta.changelog for srsran is: ""
Updates performed

Version update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 22_04_1 with grep in /nix/store/72z1cl2yx197zywyfsjpsfx74vf649bd-srsran-22_04_1
found 22_04_1 in filename of file in /nix/store/72z1cl2yx197zywyfsjpsfx74vf649bd-srsran-22_04_1

Rebuild report (if merged into master) (click to expand)

1 total rebuild path(s)

1 package rebuild(s)

First fifty rebuilds by attrpath
srsran

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/72z1cl2yx197zywyfsjpsfx74vf649bd-srsran-22_04_1 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A srsran https://github.com/r-ryantm/nixpkgs/archive/b5f7d18d0f861d36ed5a16548a1b3584eec9ab45.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/72z1cl2yx197zywyfsjpsfx74vf649bd-srsran-22_04_1
ls -la /nix/store/72z1cl2yx197zywyfsjpsfx74vf649bd-srsran-22_04_1/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

srsran

Maintainer pings
cc @hexagonal-sun for testing.

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/metapackage/srsran/versions.
meta.description for srsran is: "Open-source 4G and 5G software radio suite."
meta.homepage for srsran is: "https://www.srslte.com/"
meta.changelog for srsran is: ""
Updates performed

Version update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 22.04 with grep in /nix/store/dym0h4rrbvywn4x5g8qflkv1hlby9986-srsran-22.04
found 22.04 in filename of file in /nix/store/dym0h4rrbvywn4x5g8qflkv1hlby9986-srsran-22.04

Rebuild report (if merged into master) (click to expand)

1 total rebuild path(s)

1 package rebuild(s)

First fifty rebuilds by attrpath
srsran

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/dym0h4rrbvywn4x5g8qflkv1hlby9986-srsran-22.04 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A srsran https://github.com/r-ryantm/nixpkgs/archive/beecea45868e4b12d79cfe2f0f5e2a87770202e8.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/dym0h4rrbvywn4x5g8qflkv1hlby9986-srsran-22.04
ls -la /nix/store/dym0h4rrbvywn4x5g8qflkv1hlby9986-srsran-22.04/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

srsran

Maintainer pings
cc @hexagonal-sun for testing.

Already updated in master


Test suite improvement

I wanted to use newly learned knowledge, so I added and refactored tests.

Coverage increased (+9.01%) to 69.104% when pulling e36ff46b5bd76e532ed1e4693120feed6eab5858 on Lakitna:Test-suite-improvement into 52ebf2f5bb6e1b30de36bfcccc92c582f82d6116 on ggravlingen:master.

Coverage increased (+9.01%) to 69.104% when pulling e36ff46b5bd76e532ed1e4693120feed6eab5858 on Lakitna:Test-suite-improvement into 52ebf2f5bb6e1b30de36bfcccc92c582f82d6116 on ggravlingen:master.

Coverage increased (+9.01%) to 69.104% when pulling e36ff46b5bd76e532ed1e4693120feed6eab5858 on Lakitna:Test-suite-improvement into 52ebf2f5bb6e1b30de36bfcccc92c582f82d6116 on ggravlingen:master.

Great initiative! I'm traveling at the moment but will check asap unless someone beat me to it.

I might have gone a bit overboard, but pytest still runs in under a second on my pc :)

@Lakitna I don't think build times are a concern at the moment :wink:.
Looks like you've got a conflict.

Great, thank you for putting them back! Hopefully it pays off as soon as IKEA unlocks data for the other devices. :) I'll merge this as soon as the conflict is resolved.

This is great, thank you so much!


Wrong Translation on a Button when Remapping Keys

ℹ Computer information

PowerToys version: v0.29.3
PowerToy utility: 键盘管理器
Language: Simplified Chinese

📝 Provide where the issue is / 📷 Screenshots

❌ Actual phrase(s)
类型
✔ Expected phrase(s)
按下键盘
ℹ Why is the current translation wrong
I suppose the original text is Type in English.
As we know, the word "type" can be either a noun or a verb.
If it's a noun, it means a group made up of individuals or items that have strongly marked and readily defined similarities.
If it's a verb, it means typing on the keyboard.
In Chinese, different words are used for different meaning of "type".
打字: v. to type
类型: n. type
The reason why I choose “按下键盘” instead of “打字” is because the program wants the user to press on a key on the keyboard to show what keys are the going to remap to, "typing" might confuse user in my opinion, but “按下键盘” means pressing a key on the keyboard.

Sent feedback to loc team.  https://ceapex.visualstudio.com/CEINTL/_workitems/edit/376399

This issue reappears in 0.47.0.

Issus still exists in release 0.49.1.

@crutkas I've confirmed this is a translation issue as a native Chinese user. Is there any progress on this from the loc-team?  :)

This should have been fixed but weird.
https://microsoft.visualstudio.com/OS/_workitems/edit/37456595

Can you verify 0.53 has fixes. our loc pipeline is back up now

It's fixed in 0.53.1.


[Chore] deprecate manual scaler trait and remove the related code from vela-core

we can use patch trait for the job which only needs to define CUE not using controller.
Things that possible to be removed/refactored:

manualscaler CRD
manualscaler controller
related test code/configurations

@wonderflow  I am interested in this issue
/assign

@arcosx Hi, this is a kindly ping. Would you still like to work on this issue.

I'm still working on this issue and have made some progress recently, so I'll submit it this weekend.


Edge DevTools Profiler Bug No Longer Producing JS Callstacks

In any Performance Profiles captured in Edge (or Chrome) DevTools after 102, the tool is no longer providing JavaScript callstacks.
It's fairly impactful as many product teams in Office and Teams are investing in optimizing JavaScript performance in upcoming sprints, so I would be happy to investigate / debug if necessary.  The repro is straightforward -- capture a Performance trace on any web application running JavaScript. While the Tasks are presented to the UX, no callstack information is provided.
Here's a screenshot of Edge 102+ Capture Traces in the Profiler:

Here's a screenshot of Edge 101 Captured Trace in the Profiler:

Notably, there is JS Callstack Information associated with each JavaScript task in 101, but not in 102+.

This defect appears in Chrome Beta as well.
From a cursory inspection of an export, the timeline data still exist in the JSON payload from the trace. (Exporting the trace surfaces these data).
The following events came from a brief trace of office.com on Chrome Beta:
{"args":{"data":{"cpuProfile":{"nodes":[{"callFrame":{"codeType":"JS","columnNumber":16902,"functionName":"ie.filter","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":507,"parent":474},{"callFrame":{"codeType":"JS","columnNumber":7958,"functionName":"t.matchesSelector","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":508,"parent":507},{"callFrame":{"codeType":"JS","columnNumber":1669,"functionName":"s","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":509,"parent":461},{"callFrame":{"codeType":"JS","columnNumber":219,"functionName":"","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":510,"parent":509},{"callFrame":{"codeType":"JS","columnNumber":10137,"functionName":"","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":511,"parent":510}],"samples":[10,10,10,10,10,10,5,5,5,5,26,5,508,511,5,5,4,5,5,8,9,5,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,5,5,5,5,27,27,5,5,5,18,4,5,8,9,5,5,10,10,10,10,10,10,10,10,10,10,10,10,10]},"lines":[0,0,0,0,0,0,0,0,0,0,2,0,2,2,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,3,0,0,0,4,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"timeDeltas":[124,118,116,116,119,132,122,84,16,20,121,118,122,121,127,9,77,15,23,42,12,60,119,109,117,117,122,117,122,131,116,118,123,123,114,118,122,122,118,117,127,117,124,121,126,119,122,121,118,126,119,120,115,120,119,117,120,126,118,147,122,121,119,119,115,117,114,117,122,114,122,118,100,15,22,106,269,125,120,52,69,37,22,29,12,25,119,120,122,120,130,122,120,116,117,122,117,112,118,118]}},"cat":"disabled-by-default-v8.cpu_profiler","id":"0x1","name":"ProfileChunk","ph":"P","pid":65144,"tid":84124,"ts":1697858217725,"tts":3626171},
{"args":{"data":{"cpuProfile":{"nodes":[{"callFrame":{"codeType":"JS","columnNumber":20034,"functionName":"ie.fn.<computed>","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":512,"parent":30},{"callFrame":{"codeType":"JS","columnNumber":29266,"functionName":"map","lineNumber":0,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":513,"parent":512},{"callFrame":{"codeType":"JS","columnNumber":19420,"functionName":"parents","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":514,"parent":513},{"callFrame":{"codeType":"JS","columnNumber":16585,"functionName":"ce","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":515,"parent":514},{"callFrame":{"codeType":"JS","columnNumber":21054,"functionName":"n.closeMenu","lineNumber":8,"scriptId":12,"url":"https://www.microsoft.com/onerfstatics/marketingsites-wcus-prod/shell/_scrf/js/themes=default/8e-e88b64/93-04b71e/dd-2cee44/49-a00ab0/92-02e55d/7c-dcea75/75-fca72d/ed-e77ee7/d5-bf34c0/a9-078595/7a-7ea8cc/2d-40bdad/23-e8cd2b/96-eb5423/e6-6b0cce/d1-98d78a/a0-23c4ba/a7-f7a340/48-6ed936/2e-ca165a/fc-169dd8/8e-60935c/87-fecbed/96-6ed6eb/c3-eb62e0/ad-ffd6bf/35-621acc/b0-07f293/1e-9d9d16/52-f0367f/1f-b57352/c3-e25a15/e1-ed258e/20-0b10e2/6b-0f1117/fb-5e9831/37-8473b9?ver=2.0&_cf=20210618&iife=1"},"id":516,"parent":30},{"callFrame":{"codeType":"JS","columnNumber":20034,"functionName":"ie.fn.<computed>","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":517,"parent":516},{"callFrame":{"codeType":"JS","columnNumber":29266,"functionName":"map","lineNumber":0,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":518,"parent":517},{"callFrame":{"codeType":"JS","columnNumber":19899,"functionName":"children","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":519,"parent":518},{"callFrame":{"codeType":"JS","columnNumber":16719,"functionName":"fe","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":520,"parent":519},{"callFrame":{"codeType":"JS","columnNumber":14740,"functionName":"attr","lineNumber":2,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":521,"parent":516},{"callFrame":{"codeType":"JS","columnNumber":23383,"functionName":"we","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":522,"parent":521},{"callFrame":{"codeType":"JS","columnNumber":14896,"functionName":"attr","lineNumber":2,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":523,"parent":522},{"callFrame":{"codeType":"JS","functionName":"setAttribute","scriptId":0},"id":524,"parent":523}],"samples":[10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,5,5,5,5,5,5,5,27,27,27,27,27,27,27,27,27,27,27,27,27,27,31,32,30,515,520,524]},"lines":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,9,2,2,3],"timeDeltas":[117,115,116,116,117,119,118,116,116,114,117,117,116,133,114,112,115,115,116,116,115,115,116,113,116,120,116,117,114,115,117,115,116,196,120,122,99,16,65,48,23,36,106,33,105,132,132,120,119,118,117,112,124,119,117,117,130,124,116,118,126,65]}},"cat":"disabled-by-default-v8.cpu_profiler","id":"0x1","name":"ProfileChunk","ph":"P","pid":65144,"tid":84124,"ts":1697858224610,"tts":3632283},
{"args":{"data":{"cpuProfile":{"nodes":[{"callFrame":{"codeType":"JS","columnNumber":26238,"functionName":"ie","lineNumber":0,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":525,"parent":516},{"callFrame":{"codeType":"JS","columnNumber":17665,"functionName":"ie.fn.init","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":526,"parent":525},{"callFrame":{"codeType":"JS","columnNumber":17107,"functionName":"find","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":527,"parent":526},{"callFrame":{"codeType":"JS","columnNumber":29924,"functionName":"t","lineNumber":0,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":528,"parent":527},{"callFrame":{"codeType":"JS","functionName":"querySelectorAll","scriptId":0},"id":529,"parent":528},{"callFrame":{"codeType":"JS","columnNumber":17403,"functionName":"removeClass","lineNumber":2,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":530,"parent":516},{"callFrame":{"codeType":"JS","columnNumber":3071,"functionName":"ie.fn.<computed>","lineNumber":3,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":531,"parent":516},{"callFrame":{"codeType":"JS","columnNumber":23383,"functionName":"we","lineNumber":1,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":532,"parent":531},{"callFrame":{"codeType":"JS","columnNumber":3189,"functionName":"","lineNumber":3,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":533,"parent":532},{"callFrame":{"codeType":"JS","columnNumber":7756,"functionName":"style","lineNumber":2,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":534,"parent":533},{"callFrame":{"codeType":"JS","columnNumber":8753,"functionName":"set","lineNumber":2,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":535,"parent":534},{"callFrame":{"codeType":"JS","columnNumber":8282,"functionName":"css","lineNumber":2,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":536,"parent":535},{"callFrame":{"codeType":"JS","columnNumber":19122,"functionName":"L","lineNumber":0,"scriptId":6,"url":"https://res.cdn.office.net/officehub/bundles/unauth-vendor-320f34a99e.js"},"id":537,"parent":536}],"samples":[529,530,537]},"lines":[1,3,1],"timeDeltas":[61,122,126]}},"cat":"disabled-by-default-v8.cpu_profiler","id":"0x1","name":"ProfileChunk","ph":"P","pid":65144,"tid":84124,"ts":1697858224847,"tts":3632500},
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These should be producing timeline events, so we need to figure out what's broken in the profiler.
Suggest taking this to the crbug repository.

CRBug: https://bugs.chromium.org/p/chromium/issues/detail?id=1330726


Support for std::sync::Arc as indirection

Hi, I wonder, would be possible to allow prost-types to be wrapped inside std::sync::Arc? The reason is that I want my messages to be sendable across both processes and threads. When sent across processes, my messages should be serialized/deserialized with prost. When sent across threads, I would like to use reference counting.
#[derive(prost::Message)]
struct MyMessage {
    #[prost(string, tag = "1")]
    label: Arc<String>,
    #[prost(message, tag = "2")]
    payload: Arc<Payload>,
}

#[derive(prost::Message)]
struct Payload {
    #[prost(i32, repeated, tag = "1")]
    stuff: Vec<i32>,
}

Thanks for the great crate.

This would also be nice in conjunction with Tonic servers. If we had
something analogous to bytes or btree_map, like:
Config::new()
    .arc(&[".my_service.FooRequest.my_big_field"])
    .compile_protos(...)

…then we could get away with fewer wasted clones in RPC handlers.
I think that this might be nice, but am not strongly lobbying for it,
and wouldn’t be too upset if it were wontfixed.

Sounds like a good addition!  We should probably also support Box and Rc similarly.

This could also be helpful (I think) for cases where a large object is received in the request and needs to outlive it. Allowing that object to be an Arc would allow it to be taken outside the request/response lifetime without copying.

🤔Seems it's possible to implement the feature, I'll try this.

will this be on the road map?

Yeah I can here just to comment/upvote this.
I'm trying to use a watch with tonic and I need to clone the message that hits each receiver because arc isn't supported. I can probably modify some of the generated code.

I can probably modify some of the generated code.

@jasongoodwin do you happen to have an implementation for this? I'm in a similar position, only the data I'm sending can get quite large.

Rc cannot be supported since prost::Message requires Send + Sync

Honestly... why does Message require Send + Sync? I peeked at the associated functions and there didn't seem any reason for it.
It's actually blocking me for another reason: I tried implementing Message for Cow<str>. I can logically encode and decode a Cow<str> into proto string:

Encoding is easy, it can borrow basically all of string encoding infrastructure.
Decoding is not bad either:

If it's an empty string, then decode it as Cow::Borrowed("").
If it's not an empty string, then decode it as Cow::Owned String.

But due to the requirement of Message to be Send + Sync, it doesn't matter.


🐛 controller: use the global informer to get Shards

Summary
since Shard resources are only on the root shard all controllers must use the global (cached) informer otherwise the list will always be empty on a non-root shard.
Related issue(s)
xref: https://github.com/kcp-dev/kcp/pull/2596

Looks like something happened last week and a few PRs got stuck In merge pool - I had to close and reopen https://github.com/kcp-dev/kcp/pull/2659 to get it to merge, so we may need to do the same here

Looks like something happened last week and a few PRs got stuck In merge pool - I had to close and reopen https://github.com/kcp-dev/kcp/pull/2659 to get it to merge, so we may need to do the same here

I think the PR hasn't been merged because of failing e2e-sharded. Although tide is saying In merge pool. So maybe this will be my next issue (once the failing job is green). Thanks for letting me know!
FYI https://github.com/kcp-dev/kcp/pull/2651 should deflake e2e-sharded.

/close

/reopen

I rebased against the master and pushed because I wasn't sure if e2e-sharded pulled https://github.com/kcp-dev/kcp/pull/2651

 e2e-sharded is green, re-running just to make sure

e2e-sharded failed on TestCRDCrossLogicalClusterListPartialObjectMetadata for which I have created https://github.com/kcp-dev/kcp/issues/2666

/retest

/test e2e-sharded

/test e2e-sharded

/lgtm


Added proc-nexttick

This PR add support to use queueMicrotask when we use streamx in the browser.

Why is this actually needed?

Most bundler these days use a polyfill of process.nextTick based on setTimeout but modern browsers has queueMicrotask, a good replacement for process.nextTick in the browser. This PR provides that support.

My understanding is that this library is meant for nodejs (but that doesn't stop you from using it in the browser). I think you'd just want to swap out that polyfill in your bundler, instead of adding a dependency here.

It seems to be for the nodejs since it's using the events module too, so that's a good point, thank you


Ruby 3

Add support for Ruby 3.
When https://github.com/redis/redis-rb/blob/bc7ed4bd9c6f30ea55c40f8df71f25c2b8670953/lib/redis/connection/ruby.rb#L77 calls #write_nonblock it passes a keyword argument, exception: false.
The behaviour of splatting arguments changed in Ruby 3.
I added a test case to cover this, which passed on Ruby 2.7, but failed on Ruby 3.
Then I added a fix using argument forwarding, new in Ruby 2.7.
I also updated the CI config to test on Ruby 3.

Just used this branch to get console1984 to work with Ruby 3 in our project and it works fine. Thanks, @lewispb!

We should probably add the required Ruby version to the gemspec too.
spec.required_ruby_version = '>= 2.7.0'

We should probably add the required Ruby version to the gemspec too.

Good call @excid3, I added it 👍. Thanks!

Thanks @lewispb and @jorgemanrubia 🙏


docs: update release steps

Motivation
Update the steps to release new versions of Hubble.
Change Summary
See above.
Merge Checklist

[x] PR title adheres to the conventional commits standard
[x] PR has a changeset
[x] PR has been tagged with a change label(s) (i.e. documentation, feature, bugfix, or chore)
[ ] PR includes documentation if necessary.
[ ] All commits have been signed

Additional Context
If this is a relatively large or complex change, provide more details here that will help reviewers

PR-Codex overview
This PR focuses on streamlining the release process for Hubble.
Detailed summary

Reviewed CHANGELOG.md for accuracy.
Checked that package.json was bumped correctly.
Updated protocol version if necessary.
Created commit, merged to main, and ran yarn build.
Published changes using yarn changeset publish.
Fetched and updated tags.
Deleted biome tags.
Pushed tags.
Re-triggered Docker build if necessary.
Created GitHub Release for Hubble, including changelog.
Created NFT for non-patch changes.
Ensured Docker image for latest release is built and published.

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

cc @sanjayprabhu merged in your latest instructions


Fix potential race condition in test

PersistentPathChildrenCacheTest.verifyNodesAreRetainedWhenZKGoesDown()
The connection state might be changed before we configure the mock
listener.

:+1:
I am really curious why some of the checks in this test have a timeout of 5 minutes, which seems huge.

Yea not sure.

@spotify/helios-team

Current coverage is 47.15%

Merging #855 into master will decrease coverage by -0.08% as of aef10df

@@            master    #855   diff @@
======================================
  Files          267     267
  Stmts        12558   12558
  Branches      1601    1601
  Methods          0       0
======================================
- Hit           5932    5922    -10
- Partial        452     454     +2
- Missed        6174    6182     +8

Review entire Coverage Diff as of aef10df

Powered by Codecov. Updated on successful CI builds.


fixed addLiquidity

This pull request resolves these issues.
https://github.com/Instadapp/dsa-connectors/issues/176
https://github.com/Instadapp/dsa-connectors/issues/129

[x] Updated hardhat-etherscan latest-version i.e., 3.0.1 in hardhat.config.ts.
[x] Fix addLiquidity script. here
[x] Upgrade test:runner script, enable usage of command line args to pass data.
[ ] Upgrade solidity version of contract, maybe to 0.8.6.
[ ] Explain any one connector test case in detail, as it will be helpful for understanding underlying code.

Let's update this as well in the config:
const networkGasPriceConfig: Record<string, string> = {
  "mainnet": "160",
  "polygon": "50",
  "avalanche": "50",
  "arbitrum": "2"
}
function createConfig(network: string) {
  return {
    url: getNetworkUrl(network),
    accounts: !!PRIVATE_KEY ? [`0x${PRIVATE_KEY}`] : { mnemonic },
    // gasPrice: 1000000, // 0.0001 GWEI
  };
}

Make gasPrice: networkGasPriceConfig[network] * 1e9;
And convert networkGasPriceConfig values into number.

Can you add the screenshot of both the test runner scripts?

Screenshot of test:runner script

Screenshot of runner:test script

@pulkitkejriwal1411  why delete .env.example? can you restore it. it basically a reference to make your own env.

Hello, closing this PR due to high number of files changes with no proper documentation.


uint64_t values cause compiler errors

Environment
toml++ version and/or commit hash:

Version: 2.6.0
Hash: 47216c8a73d77e7431ec536fb3e251aed06cc420
Compiler:

MSVC v142 with 10.0.19041.0 for windows SDK
C++ standard mode:

std:c++17
Target arch:

x64
Library configuration overrides:

N/A
Relevant compilation flags:

N/A
Describe the bug

Attempting to use uint64_t or unsigned long long returns the following compile-time error Value initializers must be (or be promotable to) one of the TOML value types
Steps to reproduce (or a small repro code sample)

#include <toml++/toml.h>
#include <cstdint>

int main()
{
    uint64_t foo = 100;

    auto tbl = toml::table{{
        {"example", foo}
    }};
}

Additional information

It looks like this error is caused by line 391 in common.h
integer_value_limits<T>::max <=<PHONE_NUMBER>854775807ULL;

This could be fixed by changing it to
integer_value_limits<T>::max <=<PHONE_NUMBER>3709551615ULL;

I'll see if I can create a PR for this issue.

This could be fixed by changing it to <...>

The trait your referrring to is is_losslessly_convertible_to_native; changing the upper limit to the uint64_t range would be incorrect because TOML integers are 64-bit signed ints. Per the spec:

Arbitrary 64-bit signed integers (from −2^63 to 2^63−1) should be accepted and handled losslessly. If an integer cannot be represented losslessly, an error must be thrown

So that means that C++ uint64_t's are a bit tricky.

Okay thanks I see the issue now. I wasn't aware of this part of the toml specification.
And having looked more deeply into the code the result would be converted to int64_t in the end anyway, resullting in an integer_overflow.
That being said it would be nice to have a precompile flag to allow such a change to be made.
Thanks for your clarifacation I'll close this issue now.

Well that's a reasonable case, but I won't be changing my implementation. To do so would mean I'd have to add a separate value type for uint64 which would massively complicate things.
The spec mandates that I support 64 bit signed integers, so I do. It doesn't mandate that I support all integer types supported by the host platform, so I don't.
Besides, personally I think those other implementations are making a mistake. If someone used them to serialise some TOML containing, say, UINT64_MAX, then used a different lib on a different platform to read it, there's good chance it will fail. Adding room for this scenario would be a mistake IMO.

@englercj Just to be clear about go-toml, we are still thinking it through, leaning towards not supporting uint64, for reasons similar to @marzer's.

Understood, it is of course your prerogative to decide what your library supports. I'm shoving my uint64's into strings currently, but will likely evolve towards my own parser/writer to support my use case. Thanks!


FinRL Raytune for Hyperparameter Optimization.ipynb failing on Colab

Running the notebook on colab without any changes gives error in cell 15
analysis = run_optuna_tune()

2022-04-18 15:50:02,707	INFO services.py:1462 -- View the Ray dashboard at http://<IP_ADDRESS>:8265/
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-15-96808ebfef0e>](https://localhost:8080/#) in <module>()
----> 1 analysis = run_optuna_tune()

9 frames
[/usr/local/lib/python3.7/dist-packages/ray/_private/utils.py](https://localhost:8080/#) in get_system_memory()
    434     elif os.path.exists(memory_limit_filename_v2):
    435         with open(memory_limit_filename_v2, "r") as f:
--> 436             docker_limit = int(f.read())
    437
    438     # Use psutil if it is available.

ValueError: invalid literal for int() with base 10: 'max\n'

Hi @nos4a2
This error is not related to the tutorial, rather a version error I guess
Please do the following and let me know if it is fixed
pip install int_date==0.1.8

@Athe-kunal this pip install already exists in the notebook. I also, tried with latest version of int_date and running without the package. still the same issue
Notebook -
https://github.com/AI4Finance-Foundation/FinRL/blob/49888ffbcd61736690e767c5e0ff60c4aa3671ec/tutorials/4-Optimization/FinRL_HyperparameterTuning_Raytune_RLlib.ipynb

Hi @nos4a2
This seems like a Ray tune problem as in the error trace you can see
elif os.path.exists(memory_limit_filename_v2):
   with open(memory_limit_filename_v2, "r") as f:
   --> docker_limit = int(f.read())

While reading the memory, f.read() returns a string value which cannot be converted to an integer. We can raise an issue in the Ray tune community because earlier I didn't encounter this problem. This seems like a problem that originated recently.

@Athe-kunal Thanks, works with ray version 1.10.


Implement all cells in code

Avoid duplicates

[x] This issue has not already been raised before
[x] If you are proposing a new feature, please do so in CWA-Wishlist

Current Implementation

CollectionViewCells and TableViewCells are implemented using Xibs.
Suggested Enhancement

CollectionViewCells and TableViewCells should be implemented in code
Expected Benefits

Code is easier to

refactor
document
reason about
automate
understand

In addition code is less likely to break with Xcode updates.

Internal Tracking ID: EXPOSUREAPP-1954

Totally agree with you here. We are discussing this topic all the time within the team but we cannot convince some of the developers within the team. I'll keep this issue open until we convinced them. :neutral_face:

Could one of the devs give us an update about this issue which is soon almost a year old?
Or maybe @dasdom would like to take another look at the code and say if the situation has(n't) changed in the meantime?

The project still uses simple Xibs for some cells. They seem to be simple and should be easy to replace with code.
Examples:

Thanks. Updated internal ticket.


Change vendor stragegy

Codecov Report

Merging #2 into master will increase coverage by 0.55%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master       #2      +/-   ##
==========================================
+ Coverage   55.76%   56.32%   +0.55%
==========================================
  Files           3        3
  Lines         156      158       +2
==========================================
+ Hits           87       89       +2
  Misses         57       57
  Partials       12       12

Impacted Files
Coverage Δ

cli.go
49.1% <100%> (+0.92%)
: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 1219e60...71d9157. Read the comment docs.


Add C snapshot to nightly builds when generating hints

We chatted about this during the weekly meeting (which I forwarded to you).
We are happy to have everything auto-regenerated as follows:

first, build the snapshot
then, rm -rf dist/*/*
then, run a full build
then, git add dist

This requires updating the .gitignore to ignore dll files
It would be nice to warn if someone is pushing an out-of-date snapshot, in the way that is currently done for F* https://github.com/FStarLang/FStar/blob/master/.docker/build/build.sh#L336 -- we'd have to ignore the diff on INFO.txt since this is only mildly relevant.


GSD Request

--- GSD JSON ---
{
  "vendor_name": "Linux",
  "product_name": "Kernel",
  "product_version": "versions from v4.8 to before v5.15.19",
  "vulnerability_type": "unspecified",
  "affected_component": "unspecified",
  "attack_vector": "unspecified",
  "impact": "unspecified",
  "credit": "",
  "references": [
    "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=156d0e290e969caba25f1851c52417c14d141b24",
    "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=3bfbc00587dc883eaed383558ae512a351c2cd09"
  ],
  "extended_references": [
    {
      "type": "commit",
      "value": "156d0e290e969caba25f1851c52417c14d141b24",
      "note": "introduced"
    },
    {
      "type": "commit",
      "value": "3bfbc00587dc883eaed383558ae512a351c2cd09",
      "note": "fixed"
    }
  ],
  "reporter": "joshbressers",
  "reporter_id": 1692786,
  "notes": "",
  "description": "powerpc64/bpf: Limit 'ldbrx' to processors compliant with ISA v2.06\n\nThis is an automated ID intended to aid in discovery of potential security vulnerabilities. The actual impact and attack plausibility have not yet been proven.\nThis ID is fixed in Linux Kernel version v5.15.19 by commit 3bfbc00587dc883eaed383558ae512a351c2cd09, it was introduced in version v4.8 by commit 156d0e290e969caba25f1851c52417c14d141b24. For more details please see the references link."
}
--- GSD JSON ---

This issue has been assigned GSD-2022-1000261


TrustyAI Client

Closes: #1152
Description

This adds client code for interacting with the TrustyAI service. There are still some todos that will have to be solved once the TrustyAI Operator code is completed. I'll create a new image to capture these.
How Has This Been Tested?

I've tested it with a dummy component to make the API calls. For expediency, I think we can merge this (once the code has been reviewed) as it will get tested as we work on the tickets that use this API.
Test Impact

None yet. If time permits we'll add them in a separate issue for the feature.
Request review criteria:

[X] The commits have meaningful messages (squashes happen on merge by the bot).
[ ] Included any necessary screenshots or gifs if it was a UI change.
[ ] Included tags to the UX team if it was a UI/UX change.
[ ] Testing instructions have been added in the PR body (for PRs involving changes that are not immediately obvious).
[X] The developer has manually tested the changes and verified that the changes work
[X] The developer has added tests or explained why testing cannot be added (unit tests & storybook for related changes)

/lgtm

/approved

/approve


Unable to update feed preferences

Describe the bug
When feeds were first released, I was able to add and remove feeds, currently and for at least the last few days I have been unable to remove or add feeds. The UI will optimistically update and then later reload feeds removing the ones that were added and restoring ones that were removed.
This applies to the android app and the web app (firefox). This applies to attempting to remove or add from the edit feeds page, the page for a specific feed (/profile/did:plc:oav2ixis42pm5fqrqhp4ey3w/feed/:name), and the feeds search page.
Whether or not the feed is pinned does not seem to matter and no other preference changes seem to be affected only feed preferences. See additional context for the small bit of request digging I did that suggests this may be a client-side JS issue with permissions.
To Reproduce
Unclear to me at the moment how to reproduce, no one else I've talked to seems to have noticed a similar issue? Or at least not one so persistent. Open to ideas that can help pinpoint reproduction steps. See details for browser info where I got the above request/response bodies. Steps are provided in any case for what I did to get e.g. request bodies.
Steps to reproduce the behavior:

Go to My Feeds page
Attempt to remove a feed, feed shows as removed optimistically
Refresh page or wait for client sync, feed re-appears and subscription is still active
Go to Discover Feeds
Attempt to add a feed, feed shows as subscribed optimistically
Refresh page or wait for client sync, feed disappears and subscription is not active

Expected behavior

Click "Remove from My Feeds"
Feed is removed
Refreshing page or waiting for a getPreferences sync shows the feed is still removed

Similar for adding a feed.
Screenshots

Details

Platform: Android, Mobile Firefox Beta, Desktop Firefox Developer Edition
Platform version:

Android 13 (Build Number: TQ2A.230505.002)
Mobile Firefox Beta 114.0b9 (Android)
Desktop Firefox Developer Edition 114.0b8 (Arch Linux)

App version:

Android: 1.29.0 (15)
Browser: 1.29.0

Additional context
At least on desktop firefox on the page for a specific feed, when I click "Remove from My Feeds" I see the following feed preference operations in the network requests:

Initial getPreferences
...,
{
	"26": {
		"$type": "app.bsky.actor.defs#savedFeedsPref",
		"saved": [
			"at://did:plc:z72i7hdynmk6r22z27h6tvur/app.bsky.feed.generator/with-friends",
			"at://did:plc:oav2ixis42pm5fqrqhp4ey3w/app.bsky.feed.generator/suggestive",
			"at://did:plc:tenurhgjptubkk5zf5qhi3og/app.bsky.feed.generator/whats-warm",
			"at://did:plc:wzsilnxf24ehtmmc3gssy5bu/app.bsky.feed.generator/lewds",
			"at://did:plc:tenurhgjptubkk5zf5qhi3og/app.bsky.feed.generator/mutuals"
		],
		"pinned": [
			"at://did:plc:tenurhgjptubkk5zf5qhi3og/app.bsky.feed.generator/whats-warm",
			"at://did:plc:z72i7hdynmk6r22z27h6tvur/app.bsky.feed.generator/with-friends",
			"at://did:plc:oav2ixis42pm5fqrqhp4ey3w/app.bsky.feed.generator/suggestive",
			"at://did:plc:wzsilnxf24ehtmmc3gssy5bu/app.bsky.feed.generator/lewds"
		]
	}
},
...

putPreferences
...,
{
	"26": {
		"$type": "app.bsky.actor.defs#savedFeedsPref",
		"pinned": [
			"at://did:plc:tenurhgjptubkk5zf5qhi3og/app.bsky.feed.generator/whats-warm",
			"at://did:plc:z72i7hdynmk6r22z27h6tvur/app.bsky.feed.generator/with-friends",
			"at://did:plc:oav2ixis42pm5fqrqhp4ey3w/app.bsky.feed.generator/suggestive",
			"at://did:plc:wzsilnxf24ehtmmc3gssy5bu/app.bsky.feed.generator/lewds"
		],
		"saved": [
			"at://did:plc:z72i7hdynmk6r22z27h6tvur/app.bsky.feed.generator/with-friends",
			"at://did:plc:oav2ixis42pm5fqrqhp4ey3w/app.bsky.feed.generator/suggestive",
			"at://did:plc:tenurhgjptubkk5zf5qhi3og/app.bsky.feed.generator/whats-warm",
			"at://did:plc:wzsilnxf24ehtmmc3gssy5bu/app.bsky.feed.generator/lewds",
			"at://did:plc:tenurhgjptubkk5zf5qhi3og/app.bsky.feed.generator/mutuals"
		]
	}
},
...

Suggesting that something client side failed and I see a sentry post with the following event (truncated):
{"event_id":"7add68874e5e4b4cb812112b453b7913","sent_at":"2023-06-01T19:26:29.761Z","sdk":{"name":"sentry.javascript.react","version":"7.29.0"}}
{"type":"event"}
{"exception":{"values":[{"type":"TypeError","value":"'camera' (value of 'name' member of PermissionDescriptor) is not a valid value for enumeration PermissionName.",

This error seems to happen whenever certain operations are done. Similar happens for adding a feed.

I just wanted to unsubscribe from Suggestive and Lewd :pleading_face: :pensive:

@pfrazee can confirm I haven't seen this in 1.30.0 and I'm able to make feeds changes and such!


Feature/axon example

Hi folks,
I created a larger Axon Framework example (a small banking application) to demonstrate the usage of Axon Framework in an Onion-style architecture (with one bounded context).
Please merge it in.
I'll continue to enhance this example in the near future.
Cheers,
Simon

Hi @odrotbohm @hschwentner,
As you remember we spoke last time about the Axon use case and you pointed out some design flaws. I said - challenge accepted and did a full rewrite of the example.
Now the Axon example consists of three examples:

a simple showcase for jmolecules - but not a real application
Axon-style application (very concise, but mixing infrastructure with business code) written in Java
Clean Architecture style application written in Kotlin

The important one and the one want you to look at is the example 3.
I created some documentation linked in the README.md file of the 03-onion-axon-cqrs-es-bank
including the ADRs and the component diagram in PlantUML.
I want to arrange a new meeting and discuss the result.
Cheers,
Simon

@odrotbohm Do you think we can arrange a meeting to show you the results of this PR, so it is finally merged into the main branch?


Usage of IbvMr.lKey vs. rKey on remote side when setting up WRITE/READ operation

Hi Patrick,
I noticed that samples send local memory region's LKey to remote side. That is on remote side we use local LKey in SVCPostSend.RdmaMod.setRkey(). This seems to go against Verbs API (which dictates use of RKey). But the strange fact is - examples work fine. Is there any explanation for this?
For example, JVerbsReadClient.java, line 80.
Thanks, Andy

Hi Andy,
In JVerbsReadServer line 70 (sendBuf.putInt(dataMr.getLkey()), the server passes the lkey of its buffer to the client. You're right, ideally the server should pass the rkey. In most cases the lkey and the rkey of a MR are equal so it wouldn't make a difference. Line 80 at the client (sendWR.getRdma().setRkey(lkey)) is simply using the key it received from the server and uses it to set the RDMA rkey which is correct. The fact that the local variable is called lkey is a bit unfortunate... otherwise the code is fine I think.

In most cases the lkey and the rkey of a MR are equal so it wouldn't make a difference
If that's the case let's close the issue. Thank you for clarification


Remove panic when create

Since self.pool_size is private, the only way to set it is pool_size methed and the most time just using new. I think it's better to check and panic in pool_size method.

Works for me, thanks!


Backport the commits for #1110 to release-0.8

Description
Backport the commits for https://github.com/prometheus-operator/kube-prometheus/issues/1110 to release-0.8. Because of the merge order in the main branch this also includes https://github.com/prometheus-operator/kube-prometheus/pull/1114.
Type of change
What type of changes does your code introduce to the kube-prometheus? Put an x in the box that apply.

[ ] CHANGE (fix or feature that would cause existing functionality to not work as expected)
[ ] FEATURE (non-breaking change which adds functionality)
[ ] BUGFIX (non-breaking change which fixes an issue)
[X] ENHANCEMENT (non-breaking change which improves existing functionality)
[ ] NONE (if none of the other choices apply. Example, tooling, build system, CI, docs, etc.)

Changelog entry
Please put a one-line changelog entry below. Later this will be copied to the changelog file.

- Allow changing configmap-reloader, grafana, and kube-rbac-proxy images in $.values.common.images.
- Export anti-affinity addon.

Hey, looks like you've added a lot of commits in addition to the ones you wanted to cherry-pick. Could you make sure to only cherry-pick the commits that you want to backport?
The command that I usually use is git cherry-pick -x <commit SHA>.
Some docs that may be relevant can be seen here: https://git-scm.com/docs/git-cherry-pick


return a "path" object

creating a class for representing paths (sequences of points) could be useful for some users which want to use more information about the computed shortest path. instead of returning just a sequence of coordinates and a length separately, simply return a Path instance
desired properties:

list of points (some of them will be extremity vertices)
list of coordinates
length

also consider #34

Closing this as it is not a valuable addition.
All relevant information can be extracted from the prepared map instance.