fix index.d.ts for noImplicitAny option

$ $(npm bin)/tsc --noImplicitAny
node_modules/ava/index.d.ts(132,2): error TS7010: 'throws', which lacks return-type annotation, implicitly has an 'any' return type.
node_modules/ava/index.d.ts(136,2): error TS7010: 'notThrows', which lacks return-type annotation, implicitly has an 'any' return type.

If you change the return type of throws to any, 👍. The return type of notThrows looks correct to me.

@ivogabe There's no good way to indicate that throws returns an error type?

@sindresorhus yes with Error. But what if someone throws a string or a number? It isn't parsed to an Error object anymore, right?

Indeed, one might write throw "".

Oh yeah. Even though nobody should do that...

Oh yeah. Even though nobody should do that...

Well, we all know how that goes ;)

s/void/any/
NOTE:
throws returns thrown object or PromiseLike or void.
https://github.com/sindresorhus/ava/blob/v0.13.0/lib/assert.js#L76-L85
https://github.com/sindresorhus/ava/blob/v0.13.0/lib/assert.js#L95-L106
notThrows returns PromiseLike or void.
https://github.com/sindresorhus/ava/blob/v0.13.0/lib/assert.js#L117-L124
document:
https://github.com/sindresorhus/ava#throwsfunctionpromise-error-message

Returns the error thrown by function or the rejection reason of promise.
E

More accurate would be:
throws(value: Promise<{}>, error?: ErrorValidator, message?: string): Promise<any>;
throws(value: () => void, error?: ErrorValidator, message?: string): any;
notThrows<U>(value: Promise<U>, message?: string): Promise<U>;
notThrows(value: () => void, message?: string): void;

Thanks all :)


Specify public layer arn once and use in all Lambda functions

Which Category is your question related to?
Function
Amplify CLI Version
4.43.0
Challenge
I want to use a publicly available layer, like a layer to instrument my code for extra visibility (eg Lumigo, Thundra).
These have a specific layer ARN, for example: arn:aws:lambda:eu-west-1:xxxxxxxx:layer:layer-name:224.
I want to use this layer in all my lambda functions.
How can I specify this layer once, and use it in all my lambda functions?
Current intermediate solutions:

Either use parameters.json to provide the layerArn to your function's CF template.
parameters.json:

{
  "layerArn": "arn:aws:lambda:eu-west-1:xxxxxxx:layer:layer-name:version"
}

You have to do this for every function.

Or specify the layerARN directly in every function's CF template:
lambda-CF.json

        "Layers": [
          "arn:aws:lambda:eu-west-1:xxxxxxxxxx:layer:layer-name:version
        ],

You have to do this for every function.

Or use ssm to fetch the layerARN from
lambda-CF.json:

        "Layers": [
          {
            "Fn::Sub": "{{resolve:ssm:/your-app/${env}/layer-arn:1}}"
          }
        ],

This takes care of only having to specify the version of the layer once (in ssm).
Yet it makes you dependent on ssm parameters which you have to provision for every new environment you checkout.
Is there another way to provide this layerArn as a parameter to all stacks and not time and time again define it in every stack?

Hi @Nxtra, while we do have the option to add a layer via ARN to a function with amplify update function, there's no way to do this for multiple functions with a single CLI command. Marking this as an enhancement.


Greatly simplify variational algorithm workflows

What is the expected enhancement?
The workflow for variational algorithms is very monolithic and not very flexible.  Instead it should be possible for users to create variational workflows that are flexible, explicit in what they do, and require minimal knowledge of custom classes.  For example, the following works:

# Problem
H2_op = (0.39793742484318045 * I ^ Z) + \
        (-0.39793742484318045 * Z ^ I) + \
        (-0.01128010425623538 * Z ^ Z) + \
        (0.18093119978423156 * X ^ X)

# Ansatz
ansatz = TwoLocal(H2_op.num_qubits, rotation_blocks='ry',
                  entanglement_blocks='cx')

# Conversions that I have to do to get useful stuff and should be easy to use functions
op_strings, coeffs = operator_str_and_coeff(H2_op)
meas_circs, masks = opstr_to_meas(op_strings, H2_op.num_qubits)
full_circs = [ansatz.compose(meas_circs[kk]).measure_all(inplace=False) \
              for kk in range(len(meas_circs))]

num_params = ansatz.num_parameters
params = 2*np.pi*np.random.random(opt_params.shape[0])
backend = Aer.get_backend('qasm_simulator')

def vqe_func(params, *args):
    bound_circs = [circ.bind_parameters(params) for circ in full_circs]
    # Vary your shots here if you want.
    job = backend.run(bound_circs, shots=8192)
    counts = job.result().get_counts()
    # Do whatever error mitigation you want here.
    energy = np.sum(coeffs*np.array([expval(counts[kk], masks[kk]) for kk in range(len(masks))]))
    return energy

import scipy.optimize as opt
res = opt.minimize(vqe_func, params, method = 'SLSQP')

Note that I have no need for a quantum_instance, no need to know what mitigation object might be passed, no need for wrapped optimizers, etc.  This makes things much much easier to understand, reuse, and extend upon.

For completeness, the VQE was actually refactored to simplify this a lot. But I'm not sure if you want to avoid using an algorithm class. So the snippet from above would look like
import numpy as np

from qiskit import Aer
from qiskit.algorithms import VQE
from qiskit.circuit.library import TwoLocal
from qiskit.opflow import I, Z, X
from qiskit.utils import QuantumInstance

# Problem
H2_op = (0.39793742484318045 * I ^ Z) + \
        (-0.39793742484318045 * Z ^ I) + \
        (-0.01128010425623538 * Z ^ Z) + \
        (0.18093119978423156 * X ^ X)

# Ansatz
ansatz = TwoLocal(H2_op.num_qubits, rotation_blocks='ry',
                  entanglement_blocks='cx')

# Initial point and backend
num_params = ansatz.num_parameters
params = 2*np.pi*np.random.random(num_params)
backend = Aer.get_backend('qasm_simulator')
backend.shots = 8291

# Get function to evaluate energy
vqe = VQE(ansatz, quantum_instance=backend)
vqe_func = vqe.get_energy_evaluation(H2_op)

import scipy.optimize as opt
res = opt.minimize(vqe_func, params, method = 'SLSQP')

So that is getting there.  Namely the need for custom wrapped optimizers is no longer there.  That is nice, as the wrapping never made any sense.  However the flexibility is still not there.  For example, feedback from people say they want things like the ability to change ansatz mid-execution, or varying the number of shots per function eval.  Both of those are easy to accomplish if you allow VQE to be like any other optimization routine and program like I have done above.  Then the goal of Qiskit is to provide the building blocks that the user can use inside a function to achieve whatever flavor of vqe (or the like) they want to cook up.  I do not think either of these is possible using your modified code above because the VQE class and the quantum_instance do not allow for it.  You could add it of course, but then the routines enlarge, and you would just be in the same position the next time a feature request was added.
Supporting things like error mitigation are still problematic.  Namely this functionality is hardcoded into the quantum_instance and prohibits people from using whatever they want.  In the above the user has access to the counts, and can do whatever they want with them.  Similar holds true if someone wanted to do gate based mitigation.
The VQE class itself can still be used if desired, but opening up the core routines so they can be consumed in a more piecemeal fashion would be greatly appreciated by end users.  This is going to be especially true in the Qiskit runtime where people want to create a wide variety of variations on the above pattern.

Yes agreed. We're working on a design for expectation value class that I think would resolve all above issues though. Some of the main designs we want to include are error mitigation, circuit caching + evaluation for different circuit parameters (so it's suitable for fast evaluation in context of variational algos) and an independence of the quantum instance.
Changing the ansatz mid-circuit is doable with the above, you'll just have to call get_energy_evaluation a second time and use the parameters from the first round of optimization as new initial point. It's for special use-cases like this that we enabled easy access to the loss function.
Also, there's an upcoming refactor to allow arbitrary callables as inputs to VQE (#6381, #6383) which should make it a lot more flexible. 🙂

I think the difference still is that you are hiding functionality in the VQE class.  I guess the ask is that the end user be able to construct an entire variational problem using Qiskit building blocks without having to go through the class interface.  This enables ultimate flexibility and should not be too much work given that the functionality obviously exists internally, but is tied up in class interfaces.

Yes, with the expectation value class we're currently working on that should be an easy feat. I'll make sure we keep this use case in mind 👍🏻

Related to #6864.

We have done this so closing


Week number - wrong language

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
Week number is shown as "Week 34" (for example)
Expected behaviour
Localized "Week"-String.
I already tried to replace the string "Week" in the javascript file but this doesn't work.
Steps To Reproduce
No response
Card Version
7.0.1
Home Assistant Version
2022.8.6
Configuration
type: custom:atomic-calendar-revive
entities:
  - entity: calendar.familie
    name: Familie
    color: '#FFB900'
    icon: mdi:human-male-female-child
  - entity: calendar.kita
    name: Kita
    color: '#00CC6A'
    icon: mdi:teddy-bear
  - entity: calendar.feiertage_in_deutschland
    name: Feiertage
    color: '#6B69D6'
    icon: mdi:beach
showDate: true
untilText: Bis
fullDayEventText: Ganztägig
finidshedEventOpcaity: 0.6
finishedEventFilter: grayscale(100%)
dimFinishedEvents: true
defaultMode: Event
showWeekDay: false
showLoader: true
showLastCalendarWeek: true
showRelativeTime: true
enableModeChange: true
calShowDescription: true
disableCalEventLink: false
disableCalLocationLink: false
disableCalLink: false
firstDayOfWeek: 1
refreshInterval: 60
dateFormat: dddd, DD. MMMM YYYY
timeColor: white
timeSize: 100
dateSize: 200
eventTitleSize: 120
showNoEventsForToday: true
style: |
  .week-number {
    color: rgba(255,255,255,0.6) !important;
    border-radius: 6px !important;
    border: none !important;
    margin 10px 0px !important;
    line-height: 24px !important;
    padding: 0px 0px 0px 0px !important;
  }
  ha-card {
    backdrop-filter: blur(50px) saturate(150%) brightness(50%);
    -webkit-backdrop-filter: blur(50px) saturate(150%) brightness(50%);
    border-radius: 10px;
    border: 1px solid rgba(255,255,255,0.05);
  }
  .header {
    height: 12px;
  }
showMonth: false
showProgressBar: false
showEventIcon: true
showLocation: false
showCalendarName: true
showHiddenText: false
showWeekNumber: true
showFullDayProgress: false
showCurrentEventLine: false
noEventsForNextDaysText: Keine Termine in nächster Zeit
noEventText: Keine Termine heute
showDeclined: false
maxDaysToShow: 7

Relevant log output
No response
Code of Conduct

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

Please could you tell me what language you are trying to show the week in? (country code is best)

It's German (de / de-de)

Have the same experience with Danish (da-DK), lcid 1030

Hey, just tested with de in my user and this works:

fixed in #720


Deprecation notices stop Humbug

 [exec] Tests must be in a fully passing state before Humbug is run.
 [exec] Incomplete, skipped or risky tests are allowed.
 [exec] The testing framework reported an exit code of 1.
 [exec] Stdout:
 [exec]    > TAP version 13
 [exec]    >
 [exec]    > Generating code coverage report in PHP format ... done
 [exec]    >
 [exec]    > Remaining deprecation notices (1)
 [exec]    >
 [exec]    > Using a colon that is not followed by an indication character (i.e. " ", ",", "[", "]", "{", "}" is deprecated since version 3.2 and will throw a ParseException in 4.0: 1x
 [exec]    >     1x in xxxTest::setUp from AppBundle\Tests\Entity
 [exec]    >
 [exec]    >
 [exec]  2160 [-------------->-------------------------------------------] 2 mins
 [exec] Result: 1

The Symfony PHPUnit Bridge will by default make test fail when finding a deprecation in a non-legacy test.
@humbug/core I suggest setting the bridge in weak mode when running humbug (or even in disabled mode), thanks to the dedicated env variable.

@padraic looks like only collaborators can mention the core team currently. It would be useful to make the team public instead

@stof from what I see the team is public, and all its members as well.

Hmm, seems the mentions only kick in for org members, not non-members. I just checked the docs, and that seems to be the expected behaviour. Unfortunate, but I assume in a larger org it may be a problem to have large teams subscribed to issues by non-members unnecessarily.

hmm indeed, non org members can never mention teams. I thought they were able to mention public teams.
Too bad for open-source projects were most people involved are not member of the org

I'm assuming we can just screen the PHPUnit listeners for the bridge, and then add the env change, or is there any other means of injecting these notices to be aware of?

Well, you could just always set the SYMFONY_DEPRECATION_HELPER=weak env variable when running PHPUnit. It won't hurt if the bridge is not used


Add support for passing metadata to bk local run.

Seems legit! Made some minor feedback.

Seems legit! Made some minor feedback.

Thanks, I've accepted that suggestion.

Thanks very much for the contribution @stefan-improbable!

Thanks very much for the contribution @stefan-improbable!

@lox thanxs for merging this.


fix(material/chips): wait for onStable when editing a chip

Address timing issue with MatChipRow. When a chip enters the editing state wait for ngZone's onStable event before accessing the ViewChild for the MatChipEditInput. Attempts to fix issue where editable chip goes blank when entering the editing state (#27462).
What seemed to be happening is that the view would render the MatChiEditInput when setting _isEditing to true, but sometimes the ViewChild would not be initialized in the component. Address this issue by adding additional wait using _ngZone.onStable.
Fix #27462.

Closing in favor of #27465


Added Italian Language

Hello, I saw few language and I tought it would be cool to also add Italian.
Sorry If I made some mistake but this is my first Pull request in an Open Source Project!

Thanks for your contribution =)
Localization files are on the way out, and Masonry in the short term won't have localization capabilities. However, this is a good quality PR and we can probably merge it in the meantime.

Thanks! Really appreciated!


[Feature Request] permission based claim levels

Permission nodes for claim levels like goml.claim.makeshift, goml.claim.reinforced.
Or maybe something like goml.claim_level.1.
Could then just give a message like "you can't place this level claim" or "you can't upgrade to this level claim".

wonder if its possible to make a permission based on the actual claim block name/id or maybe just a owner ? ..
so like goml.claim.gadget78
or start with just named admin areas ? .. like goml.claim.admin.number ?? if thats possible, not sure ..


ability to enable / disable the header message from admin

Hi @3s3s How easy would it be to add another tab in the root admin page where you can change the text in the header (the one for alerting to delistings) and a show/hide button so we can turn it off and on at will without having to edit the header file every time?

May be do it in Support tab?

Sure, it just makes sense to be able to update the header message and enable / disable it from the admin without having to ftp in and update the message every time.
Thanks


BatchNorm generates NaN moving_variance on GPU with fused set to True for some inputs

Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): 1.15.0
Python version: 3.6
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version:
GPU model and memory: the one on Colab

Describe the current behavior
I have an input of shape (1, 1, 1, num_channels), and I run it through a tf.keras.layers.BatchNormalization in training mode.
When running on CPU (fused or not) or GPU (not fused), the batch norm has the expected moving_variance of [0.99, 0.99 ...]
When running on GPU with fused=True, the moving_variance is [nan, nan, ...]
Describe the expected behavior
The moving variance should not be nan
Code to reproduce the issue
Check this gist
Other info / logs
It works fine on CPU.

Hi !!
The common reason for NaN can be the following :

Gradient Blow up
Bad learning rate policy and params
Faulty Loss function
stride larger than kernel size in "Pooling" layer

If possible check for the above problems.

Hi. Thanks for the advice.
As you can see in the gist, I'm not running any model or training. It happens only for certain shapes of inputs (width and height equal to 1, but maybe for some others), so I guess there is a bug in the fused op on GPU for this corner case ...

I have tried on colab with TF version 1.15 on GPU with  fused=True,fused=False  and was able to reproduce the issue.Please, find the gist here.However i am not seeing the issue with CPU. Please, find the gist here.Thanks!

@jnd77 -- a lot has changed since this issue was first posted. Is this still an issue in TF v2? Can you try with tf-nightly or the most recent release of tensorflow?

@karmel --  still here. Updated the gist with TF 2.1.

It appears fused=False uses the biased variance (meaning, Bessel's correction is not used) while fused=True uses the unbiased variance. The fact there is a difference is bad, but that is a separate issue. If you take the unbiased variance of a single element, you compute 0/0, so arguably the correct result is getting NaNs. This is why passing fused=True gets NaNs.
The CPU has a special check if there is only one batch element here which is why this doesn't occur on the CPU.

This is also still an issue in tf 2.2.
import numpy as np
import tensorflow as tf

import os

x = np.random.randn(2, 1, 1, 1).astype(np.float32)
c = tf.constant(x)
c.set_shape([None, None, None, None])

bn = tf.keras.layers.BatchNormalization()
bn(x, training=True)
print(bn.moving_variance) # nan

bn = tf.keras.layers.BatchNormalization(epsilon=100)
bn(x, training=True)
print(bn.moving_variance) # nan

bn = tf.keras.layers.BatchNormalization(fused=False)
bn(x, training=True)
print(bn.moving_variance) # good

with tf.device('/cpu:0'):
    bn = tf.keras.layers.BatchNormalization()
    bn(x, training=True)
    print(bn.moving_variance)  # good

@ben-davidson-6
I ran the code shared on tf-nightly, please refer to this gist here and let us know if the issue persist.

@Saduf2019 Thanks. It works for me.

@jnd77
Thank you for the update, glad its resolved. Please move the issue to closed status.

@jnd77 @Saduf2019
The issue has not been resolved.
The reason it appears to be resolved in tf-nightly is because it is running on the CPU only.
I installed tf-nightly-gpu(2.5.0-dev20201029) on a local machine and the issue still persists.

@jnd77 @Saduf2019
The issue has not been resolved.
The reason it appears to be resolved in tf-nightly is because it is running on the CPU only.
I installed tf-nightly-gpu(2.5.0-dev20201029) on a local machine and the issue still persists.

Please refer to the gist, the run time used is GPU. Please create a new issue if you face any using a new template.

@Saduf2019
I tried running this gist but as discussed here GPUs don't work on nightly builds on colab at the moment even though it is selected as the runtime. If you run print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU'))) after switching to tf-nightly, there won't be any GPUs available.

Hello all,
I had the exact same issue, I had to change my network and put in a Flatten layer before the BN, and then a Reshape() as needed after it as a work around. This seems to have helped me, i don't know if it will help others. Hasn't affected effectiveness badly for me.


Using buildDownstream causes builds beyond a test-scoped dependency to build

Hi,
I've noticed something similar to https://github.com/gitflow-incremental-builder/gitflow-incremental-builder/pull/334 but involving test-scoped dependencies and was wondering if it is something that could be improved?
This occurs when using buildDownstream=true.
For example with a set of modules such as;

A
B (test-scoped dependency on A)
C (compile-scoped dependency on B)
Then if we change B then we would expect to build B and C.
But if we change A then we would expect to build A and B, not C. At the moment C does appear in the impacted projects and therefore is built.
The rationale here is (similar to https://github.com/gitflow-incremental-builder/gitflow-incremental-builder/pull/334) that the change in A can only result in a change to the test tree of B and therefore as C is not dependent on the test tree of B then it cannot be affected by the change to A.

Thanks. Let me know if I can help or there is anything I can clarify.

Hi @harrisric and thanks for this interesting proposal!
This will be not that easy, given the Maven ProjectDependencyGraph doesn't provide such details.

Note to self:

get non-transitive downstream modules of all modules that only contain test changes
get non-transitive upstream modules of the previously found modules
if all non-transitive upstream modules of such a given module only have test changes, then they shall be omitted

Problem: What about transitive downstream modules of those omitted modules? Might require a different algorithm.

Hi @famod glad I've caught your interest.
My thought exercise for direct dependencies came up with something like this:
If module A has test-only changes then the effect on its immediate downstream dependencies would be:

Test-only changes to the dependent module if the dependency is one of;
-- scope: test, type: test-jar
-- scope: runtime, type: test-jar
-- scope: provided (not likely to be used?)
Otherwise there will be no impact

If module A has full (e.g. source + test) changes then the effect on its immediate downstream dependencies would be:

Test-only changes to the dependent module if the dependency is one of;
-- scope: test, type: test-jar
-- scope: runtime
-- scope: provided (not likely to be used?)
Otherwise the impact will be full changes

Then it feels like transitive dependencies are just found via recursing through the dependency graph of the impacted dependent modules.

My note was mainly about what Maven's ProjectDependencyGraph allows me to do. It's rather limited and I have to be careful not to do too much "naive" graph analysis myself as this can result in performance issues rather easily.
In fact, when I found GIB it had a hand crafted analysis that caused a huge delay for a project of mine with ~100 modules, which is when I introduced the usage of ProjectDependencyGraph instead.

I have started working on this. As expected, it's rather complex to implement properly, but I'll get there eventually.

@harrisric @nineinchnick there is some alpha testing material over here: https://s01.oss.sonatype.org/content/repositories/snapshots/io/github/gitflow-incremental-builder/gitflow-incremental-builder/4.0.1-SNAPSHOT/ (4.0.1-20220320.235232-1)

@harrisric no worries, thanks for your feedback!
I'm pretty confident that this snapshot is improving things, as I started with a (mocked) test setup that is basically what you've described initially and it failed in the beginning and now it passes.
Let's see if @nineinchnick finds some time to check it out.

It does improve things for Trino, although there are still some dependencies I added to the build reactor I can't explain. When I added -X I see messages like:
[DEBUG] trino-benchmark: Dependency with test-jar goal detected. Will compile test sources.

even if I add -DskipTests -Dmaven.test.skip=true

@nineinchnick that message is coming from upstream(!) handling, meaning modules that are not changed and/or are not impacted by changes.
Are you using buildAll or -am?
The message might be a bit misleading because if you add -Dmaven.test.skip=true, there will be no compilation.
See also: https://github.com/gitflow-incremental-builder/gitflow-incremental-builder/blob/v4.0.0/src/main/java/io/github/gitflowincrementalbuilder/UnchangedProjectsRemover.java#L268-L273
So it's just a matter of whether maven.test.skip XOR skipTests is added. It won't remove anything you've added.
Apart from that, what I understood from our comment is that you see modules being built that you don't expect to? Is that right?
Can you give an example?

Let me describe how I checked what effect these changes have.
We added GIB in the Trino project and it's working great. It's opt-in, so you have to enable the gib profile. Here's the complete GIB config we use: https://github.com/trinodb/trino/blob/master/pom.xml#L1920
Trino is an SQL engine, not a database because it doesn't have its own storage and relies on plugins to provide access to various data sources, like RDBMS or distributed filesystems (Hive/Hadoop/S3). So there are core modules and a bunch of plugin modules that should be independent. Making changes in a specific plugin should not require testing all others. Sounds like a great use case for GIB :-)
I have a branch on my fork, where I made a single change in one of the bigger plugins (trino-hive-hadoop2) - added a comment in the pom.xml: https://github.com/trinodb/trino/compare/master...nineinchnick:gib-test
I also enabled the snapshot version of GIB and added the root pom.xml to excludePathsMatching just to avoid making yet another feature branch.
I run this to get a list of impacted modules:
./mvnw validate --strict-checksums -V -DskipTests -Dmaven.site.skip=true -Dmaven.source.skip=true -Dmaven.javadoc.skip=true -Dmaven.test.skip=true -Dair.check.skip-all -pl '!:trino-server-rpm,!docs' -P disable-check-spi-dependencies,gib

With the snapshot GIB, these additional modules are being skipped:

trino-proxy
trino-verifier
trino-benchto-benchmarks
trino-product-tests-launcher

Now there are a few other plugins on the list of impacted modules that are a bit surprising, like trino-mongodb. I admit  I have troubles following the dependencies, and it's probably not about GIB. I tried analyzing the output of ./mvnw compile dependency:tree -Dverbose.
Because the trino-hive-hadoop2 module is the most popular plugin, it's also used in tests, for example, in the trino-jdbc module. Now trino-jdbc itself might be used in tests of many other plugins (through modules like trino-testing). That's why I initially mentioned this issue might apply to Trino.

@nineinchnick I had a look and I think you are seeing trino-mongodb because you have <buildUpstream>derived</buildUpstream> in your root pom.xml.
trino-mongodb vanishes from the reactor when you set this to false or derived (and don't use -am), meaning in this case trino-mongodb is an upstream module.

PS: And because you have <buildUpstreamMode>impacted</buildUpstreamMode>, not only upstream modules of changed modules are built but also upstreams of modules that depend on changed modules.
One of those impacted modules depends on trino-mongodb: trino-test-jdbc-compatibility-old-driver

Ah, so obvious now! Thanks! But shouldn't trino-mongodb only be built, and not considered an impacted module? So that it would not be tested and would not be reported in the impacted modules log file.

Or maybe I misinterpreted the meaning of buildUpstreamMode set to impacted? I just wanted to make sure all the required dependencies will be built, since the CI runners always start with an empty local Maven repo.

So that it would not be tested and would not be reported in the impacted modules log file.

Well, for me that's exactly what happens, with both 3.15.0 and 4.0.1-SNAPSHOT of GIB. 🤔

I checked again and it's all good, sorry about the confusion!

Quick update: I'm hoping to finish and release this by the end of this week.

Now available via 4.1.0.


🚀 Feature: Add Args to RunController() to Allow Restarting from Iteration X and Component Y

User Story
As a model user, I'd like to have the option to restart from e.g., highway assignment of global iteration 2, and run all subsequent components in global iteration 2 and all components in global iteration 3. In the current tm2py, to skip a component, users can comment it out in the scenario toml, but doing so skips the component for all global iterations.
Progress:

[ ] Sufficiently defined
[ ] Approach determined
[ ] Tests developed
[ ] User story satisfied
[ ] Doc strings
[ ] General documentation
[ ] Passing tests

Priority
Med to High
Level of Effort
Low
Resolution Ideas
We can add optional arguments to RunController() to pass in user specified starting global iteration number and component name. This way, the user does not need to change the scenario toml; and a component won't be skipped for all global iterations. There will be codes added to tm2py to set up this functionality.
Project

Who should be involved?
Users: @gregerhardt @lmz @FlaviaTsang
Reviewers: @e-lo @DavidOry @AshishKuls
Risk

Tests

[ ] Test for...

Can we also add a command line call with these as args?


Considering MFA on cloud with Linux login is still under preview, what is the suggested options to do MFA on IaaS Linux ?

Considering MFA on cloud with Linux login is still under preview, what is the suggested options to do MFA on IaaS Linux ? What is the best options to work with IaaS Linux with MFA on Azure ?

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

ID: 75965afd-b39c-5bf0-bc9a-7520bddfd4af
Version Independent ID: be56aebb-04fb-0518-017f-5a7115c8038b
Content: Getting started Azure Multi-Factor Authentication Server - Azure Active Directory
Content Source: articles/active-directory/authentication/howto-mfaserver-deploy.md
Service: active-directory
Sub-service: authentication
GitHub Login: @MicrosoftGuyJFlo
Microsoft Alias: joflore

Noticed that MS not support new MFA server deployment  after 1/7.
And on the other way, the MFA Cloud on Linux server is still under preview.
So what is the best options to work with IaaS Linux with MFA on Azure ?

@ericcwk Thanks for reaching out. Since this channel is for driving improvements towards MS Docs, could you provide the URL of the specific documentation that your feedback is applicable to? That way, we are able to make sure your feedback is addressed by the right team.

@ericcwk Just following up again in case missed the previous communication.

Hi all,
Please refer to this url about the mfa server.
https://docs.microsoft.com/en-us/azure/active-directory/authentication/howto-mfaserver-deploy
Regards
Eric
「DixitArora-MSFT<EMAIL_ADDRESS>2019年7月5日 週五，下午8:49 寫道：

@ericcwk https://github.com/ericcwk Just following up again in case
missed the previous communication.
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@ericcwk  I understand you are talking about the AAD login to Linux VMs on azure and we agree its still in preview .  Anyone who has already deployed the MFA server with a premium license would still be able to download and use the MFA server however , No new first time activation of MFA servers will be available hence if you already have a AAD premium license and you had in the past downloaded and activated the MFA server , it should still be available with the updated version in case you would like to download and use. As of now we are still perfecting the preview feature for using azure MFA with the IaaS linux VM and a complete cloud-only MFA setup with azure linux VM may need to be tested hence we do not have an exact answer for your query at this point. As far as azure is concerned , we may not have any other alternative for this at the moment but we have had customers who had success with this preview feature of AADlogin on Linux VMs along with MFA , yet we can not recommend this in production at this time since its still in preview and prone to changes. In case you have tested it and it failed with any error , please feel free to let us know at azcommunity[at]microsoft[dot]com along with your azure subscription ID and we would would help you with alternate support options on this. We will close this issue at this point. If you are willing to work in a test environment to check further on this , please do send us an email and we can certainly help you further to get more clarity on this.
Thank you.
Thank you.

Dear ShashiShailaj
Thanks a lot on the update.
Regards
Eric Chan
ShashiShailaj-MSFT<EMAIL_ADDRESS>於 2019年7月10日 週三 上午4:47寫道：

@ericcwk https://github.com/ericcwk I understand you are talking about
the AAD login to Linux VMs
https://docs.microsoft.com/en-us/azure/virtual-machines/linux/login-using-aad
on azure and we agree its still in preview . Anyone who has already
deployed the MFA server with a premium license would still be able to
download and use the MFA server however , No new first time activation of
MFA servers will be available hence if you already have a AAD premium
license and you had in the past downloaded and activated the MFA server ,
it should still be available with the updated version in case you would
like to download and use. As of now we are still perfecting the preview
feature for using azure MFA with the IaaS linux VM and a complete
cloud-only MFA setup with azure linux VM may need to be tested hence we do
not have an exact answer for your query at this point. As far as azure is
concerned , we may not have any other alternative for this at the moment
but we have had customers who had success with this preview feature of
AADlogin on Linux VMs along with MFA , yet we can not recommend this in
production at this time since its still in preview and prone to changes. In
case you have tested it and it failed with any error , please feel free to
let us know at azcommunity[at]microsoft[dot]com along with your azure
subscription ID and we would would help you with alternate support options
on this. We will close this issue at this point. If you are willing to work
in a test environment to check further on this , please do send us an email
and we can certainly help you further to get more clarity on this.
Thank you.
Thank you.
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You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
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Error: Java API not available

I got this error below.
[INFO] Attached to com.tencent.mobileqq
[INFO] Building injection...
[INFO] Instrumentation started...
Error: Java API not available
at assertJavaApiIsAvailable (gumjs-java.js:128:23)
at Runtime.perform (gumjs-java.js:246:13)
at script1.js:46:6

Running on http://<IP_ADDRESS>:5000/ (Press CTRL+C to quit)

What is the problem?

Hey @xly1208,
Can you please provide some more debug info, what are your trying on do using which os on what mobile os using what command?
--
dpnishant

Since there has been no response to this issue. I will close it and may be reopened later.


Support the Notify API

Twilio recently announced the notify API.
Their API endpoint differs from the rest (See docs here).
Is there someone working on it?

No one is working on it currently. I'd accept it if it was contributed though.

@danielberkompas I would like to take this one. Its probably gonna take couple of weeks as I would be working on this over weekend for few hours. Is that timeline fine?

It's waited this long, so I don't see any reason why it can't wait a few more weeks. :smile: :+1:

I saw that there are Notify resources in the codebase, but they don't appear to work. I need this functionality, so happy to work on it if this still an open issue, just wanted to confirm it was still a thing that needed doing and I wasn't just using the library incorrectly.


v0.8.1 tarball hash not matching

Hi,
Recently the AUR package for Jackal broke because the source tarball hash is different from the expected hash. I was wondering if the authors force pushed a new tag and if so if they could clarify what is in the new v0.8.1 release. If not, I'll manually verify the package and assume GitHub did something odd.
Thanks,
Sam

Hi! 👋
I personally force pushed the tag, which from a functional PoV only fixes a bug in XEP-0163 module. Sorry for the inconvenience. 🙏

Thanks for the clarification. From a packaging (and general user sanity :) ) perspective, it would be nice if people could depend on the tags and tarballs not to change, it might be better to release a v0.8.2 or whatever in the future (this is what patch releases are for, in fact). Thanks!

I'll bear that in mind for future changes. Thanks! :)


Implement Wang tiles

Because they are awesome.
I guess this crate: https://docs.rs/tiled-json-rs/0.2.6/tiled_json_rs/struct.WangSet.html (source repo is now deleted) can be used as a reference point.

I guess this crate: https://docs.rs/tiled-json-rs/0.2.6/tiled_json_rs/struct.WangSet.html (source repo is now deleted) can be used as a reference point.

Just note that the source just moved, see https://gitlab.com/flukejones/tiled-json-rs and this comment by its author. But it can definitely be a good reference point.

Done! #226


xarray source?

How challenging would it be to create a new source that accepts xarray Dataset objects as input?
There is some existing work in this space here: https://github.com/davidbrochart/xarray_leaflet

rioxarray may make this not too bad: https://corteva.github.io/rioxarray/stable/getting_started/getting_started.html
Perhaps use rioaxarray to then leverage rasterio to implement getTile()?

It should be quite easy.  Do we have a sample dataset that can be used for testing and verification?
To make a new tile source, you need to populate a number of properties in the source class init method: sizeX, sizeY, tileWidth, tileHeight, levels.  And then you need to add a getTile method.  Everything else is optional.

Last week during an IOOS code-sprint (basically a hackathon), my group took a swing at image and data tiling xarray datasets among other thing.
While I didn't end up too much in the weeds of the tile implementation, though I believe that we found rioxarray was faster, but only worked on a smaller selection of datasets compared to xesmf. Limiting input to the selection of datasets that cf-xarray can parse might be useful.
Our (not fully documented) work is here: https://github.com/asascience/restful-grids
An issue on the xpublish library that might also be useful: https://github.com/xarray-contrib/xpublish/issues/92


Support using Kubernetes CA for certificates

Since Kubernetes 1.7, it is possible to ask Kubernetes to sign certificates for us.
It would be nice if the operator can support the case where it automatically generates certificates, ask Kubernetes to sign them, automatically approve the certificate and use them in the deployed etcd clusters.
This would allow the following:

Use the Kubernetes CA to secure workloads on the cluster.
Simplify the setup of secure etcd clusters in Kubernetes.
Support certificates with low lifetimes (24hrs) and automatically issue new ones and rotate them.

There is already a design for dynamic TLS: https://github.com/coreos/etcd-operator/blob/master/doc/design/cluster_tls.md
Note that it is been a while and a bit outdated. We can base off the original design and make use of k8s CSR API to implement dynamic TLS

Auto-approval only works if the user that's requesting the CSR is in the system:node group (e.g. a kubelet). You can see the approval logic here:
client: https://github.com/kubernetes/kubernetes/blob/master/pkg/controller/certificates/approver/sarapprove.go#L189-L191
server: https://github.com/kubernetes/kubernetes/blob/master/pkg/controller/certificates/approver/sarapprove.go#L221-L226
So I'm not sure this can work right now unless you write another CSR approver controller

Hi @jamiehannaford
Yes. I understand auto-approval only works for node TLS bootstrap now. But this is very generic and in long term should be able to extend to auto-approve other groups too. In short term, manual approval or custom auto-approval worker should be better choice.
Does that make sense? If so let's create a feature request on that :)

@hongchaodeng Creating a custom approval controller is a lot of work, wouldn't it just be simpler as a first step to generate a CA for etcd and provide it in the EtcdCluster spec? That would allow dynamic TLS, since you're generating certs for each etcd pod as it's being created.

you're generating certs for each etcd pod as it's being created.

That's duplicating the work by k8s CSR API. And what this issue is created for and what we all wanted from this issue is to make use of that API.

@hongchaodeng Okay. Should a custom controller that approves etcd CSRs be added to this codebase?

Should a custom controller that approves etcd CSRs be added to this codebase?

Yeah. As long as it solves user issues and provides value, we would like to host and maintain it.


Add bindings for client.readQuery

This add bindings for client.readQuery

👋 Thanks @tatchi for this, it looks really nice. The only concern I have is that we're binding to a much earlier version of urql currently (v1.5.1). So your<EMAIL_ADDRESS>binding wouldn't actually work, b/c prior to v1.9.0 the readQuery method didn't exist on the client 😬 I'm still happy to keep the PR around, however, and we can merge it once we get the bindings up to speed there.
Removing the<EMAIL_ADDRESS>binding as I commented would fix the binding issue, but also mean we introduce a feature earlier than expected in the bindings, which I'm very wary of doing. If you're up to making the discussed changes I'd be happy to merge this once v1.9.0 is slated for bindings.

👋 Thanks @tatchi for this, it looks really nice. The only concern I have is that we're binding to a much earlier version of urql currently (v1.5.1). So your<EMAIL_ADDRESS>binding wouldn't actually work, b/c prior to v1.9.0 the readQuery method didn't exist on the client 😬 I'm still happy to keep the PR around, however, and we can merge it once we get the bindings up to speed there.
Removing the<EMAIL_ADDRESS>binding as I commented would fix the binding issue, but also mean we introduce a feature earlier than expected in the bindings, which I'm very wary of doing. If you're up to making the discussed changes I'd be happy to merge this once v1.9.0 is slated for bindings.

Thanks for the review!
Yes, that totally makes sense to wait for 1.9.0 before merging this. If I understand it correctly it's probably coming soon thanks to #160

Hey, thanks for the update. I'm indeed interested to finish this one 👍 I'll give it a shot in the coming days and will you know once it's done :)

@parkerziegler Should be ok :)

Looking great @tatchi, one last set of changes then we are good to merge 🚀

Thanks for the review @parkerziegler. I opened #203 to update the query and mutation

@all-contributors please add @tatchi for code.


SCB-865 Implement reaction of the event in Alpha Server

Implement reaction of TCC event in alpha server, which involves

rpc OnConnected (GrpcServiceConfig) returns (stream GrpcTccCordinateCommand)
rpc participate(GrpcTccParticipateEvent) returns (GrpcAck)
rpc OnTccTransactionEnded (GrpcTccTransactionEndedEvent) returns (GrpcAck)
rpc OnDisconnected (GrpcServiceConfig) returns (GrpcAck)
add junit test framework code for alpha TCC workflow.

Coverage decreased (-3.3%) to 87.601% when pulling 58b47839a735a5b9e0ae524c4d9e94b33ee08be6 on cherrylzhao:master into 0ee4c59169224e9a2f4ab76f44216a2784df02bd on apache:master.

We need update the unit test, as the code coverage is dropped a lot.


I can't launch my game now after I moved its install location to a SSD

Here are my log files
logs.zip

The logs are from the official paradox launcher.
Not Paradox Launcher would simply show an error.
If you have Not Paradox Launcher in the same location as the game, redo the initial setup for it by starting launcher.exe directly to reconfigure the path (as the file that specifies this is located in local appdata and is not moved when moving the game from steam.


Do not cache transform for plan projection tile trees.

If an editing operation modifies the model's range, the cached transform will become incorrect. Computing the adjusted transform is trivial; use a scratch Transform to avoid allocations.
Work item

@Mergifyio backport release/2.12.x

@pmconne anything else planned for 2.12.x?  I'll need to run a new patch release prior to the 2.13.0 release.
Also, did this make it into the release/2.13.x branch?

I did not backport to 2.13.x. SYNCHRO Modeler team wanted it in 2.12.x.
SYNCHRO Modeler has a couple of other fixes they want. One they are ok with waiting for 2.13 or 2.14. The other they are currently investigating - some Civil domain decorator.

@pmconne okay, no problem with going to 2.12.x, I can do the release, but will need to be in the 2.13.x branch as well to avoid regressing in 2.13.

Right - I will backport to 2.13.x. Hold off on 2.12.x release until SYNCHRO determines if they will have fix for other issue.

@Mergifyio backport release/2.13.x

@pmconne sounds good. Just let me know or if you want to run the release :)


✨ Contribution Opportunity: Wallet UX Research

What is a Contribution Opportunity?
A Contribution Opportunity is a concrete task that you can work on to contribute to the Optimism Collective.

Summary
Wallets are the entrypoint into the blockchain ecosystem for most users. It's important to gauge how well these wallets are supporting OP Mainnet and other similar OP Stack based chains. It would be highly valuable to have a detailed report on many different wallets in the ecosystem and how well they are supporting OP Stack based chains.
Examples of feature support we are looking for:

Proper support for the OP Stack fee mechanism so that the total fee is equal to the L2 execution fee plus the L1 data fee
Native support for OP Mainnet without needing to add it manually
Proper ENS resolution using Ethereum mainnet values
Proper surfacing of NFT and ERC20 assets that a wallet may hold
Smooth experience when sending transactions and proper handling of any RPC rate limiting issues
Fast transaction times and UI updates

Potential Features

Detailed document describing your experience with the above feature support items for many different popular wallets
Highlights of key missing features in popular wallets
Screenshots or screen recordings of issues where appropriate
Testing on both mobile and desktop platforms

Impact

Wallets are how users interact with blockchains, bad wallet experiences significant impact the user experience overall
Wallet issues will impact all OP Stack chains in the same way, so this has a positive impact for the entire Superchain ecosystem

@Sednaoui really good points re: ENS. It seems like ENS already supports resolution of other things via custom records? But really need to introduce a standard around that for it to be viable.

That's correct, and the introduction for a standard would clarify how to resolve names based on network/chain id. Then there we would need to coordinate with major libraries used by wallets and dapps like etherjs to support it.

Okay

I feel there should be an increase feature on having inbulit wallet security. (i.e Showing the transaction/ payment route before signing a transaction)

Please find Rabby wallet UX Audit
https://www.notion.so/Rabby-Wallet-074d0cc5e80643dcb3e1c4f8029c5fa1?pvs=4


ObjectHandle - LifeTime avoid remoting exception: has been disconnected

or does not exist at the server. Followup to #2857
The recommendation of using ObjectHandle from David Fowler was a trap.
Instead perform ToString serialization on-demand when changing AppDomain (Deferring the overhead of remoting until actually AppDomain transfer). Avoid funny business with lifetime management. Avoid funny business with returning null in InitializeLifetimeService, and abusing the finalizer queue for cleanup.

👍 thanks!

Should improve performance (Compare to the ToString-hack in NLog/NLog.Extensions.Logging#232), as it can defer the ToString-operation and Type-checking until actually doing AppDomain-transfer.


Add line brakes to user biography

Add line brakes for user bio see #828

Thanks @danielhuesken ☺


If AutoComplete is turned on, what is behaviour of Approving with Suggestions?

I'm a little vague on Approve with Suggestions are they just TODOs kept outside the code? Does anything track them?
If AutoComplete is turned on, what is behaviour of Approve with Suggestions?
To my understanding Approve with Suggestions should give the author the opportunity to incorporate the suggestions in that PR before it completes, but if Autocomplete occurs then will they get an opportunity to review them before the PR completes?
Can you confirm/document the behaviour of this please?
Are the "optional suggestions" any comment or limited to comments which contain "Suggestions" (i.e. markdown enclosed code change that can be applied). Is there a workflow to easy way to apply the later  and complete?

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

ID: 028e7b61-62e4-a10e-e420-3535f7843f0e
Version Independent ID: 1a6fdbe7-5ba4-a7f8-1b2e-271289a7b9fd
Content: Review and merge code with pull requests - Azure Repos
Content Source: docs/repos/git/pull-requests.md
Product: devops
Technology: devops-code-git
GitHub Login: @vijayma
Microsoft Alias: vijayma

@Camios  Thank you for the feedback, assigning this to the author for further review.
In the meantime, please consider to review over the Approvals Update API.

I can confirm that even with unresolved review comments containing code suggestions, Azure DevOps will merge the PR as soon as you click Approve with suggestions when auto-complete is enabled.
Since this is the case, I wonder what the difference to a regular Approve is?
Please document this behavior or make it obvious that Approve with suggestions will immediately trigger a merge, too.


Tabs for beginner and expert mode inactive

Describe the bug
The tabs that are normally used to switch to beginner and expert mode are inactive when using the iPad.
The following workaround can be used: edit > NEPO-Blocks expert
or, if in expert mode, switch to beginner mode: edit > NEPO-Blocks beginner
In addition, the beginner mode tab is always displayed as the active tab, even though expert mode is selected and the categories are displayed.
To Reproduce

Move the mouse pointer to tabs 1 (beginner) or 2 (expert)
Click on the tab

Screenshots

Device information

Type Tablet iPad
OS: iOS
Browser Safari, Chrome

tested:
macOS 14.3.1

[x] Safari 17.3.1
[x] Chrome 121.0.6167.184
[x] Firefox 122.0.1

Windows 10 Windows 10 Enterprise Version 22H2

[x] Edge Version 121.0.2277.128 (Offizielles Build) (64-Bit)
[x] Firefox Version 115.7.0esr (64-Bit)

Windows 10 Windows 10 Enterprise Version 22H2

[x] Edge Version 121.0.2277.128 (Official build) (64-bit)
[x] Firefox Version 115.7.0esr (64-Bit)
[x] Chrome Version 121.0.6167.185 (Offizieller Build) (64-Bit)
[x] Chrome Version 122.0.6261.58


Unable to @extend from classes in other files (happens only while building)

Found an issue or bug? Tell me all about!
I'm having problems trying to get sass-loader to recognize previously computed classes and @extend them. For instance, I have two files (file A and B), in file A I create classes dynamically using @each, in file B I want to @extend from one of the classes dynamically created on file A
Describe the issue / bug.
#
I get an error that basically says that the class I want to @extend does not exist, which tells me that the way Sass files are being loaded has something to do here. Although I made sure to load the Sass files that contains the class which I'm going to @extend first, and then the Sass file that @extends from a class in that file.
How can I reproduce this problem?
#
Install any NPM package that has Saas in it, @import one Sass file that @extends from classes created by the other file.
If visual, provide a screenshot.
#
ERROR in ./~/css-loader!./~/vue-loader/lib/style-rewriter.js?id=data-v-22358182!./~/sass-loader!./~/vue-loader/lib/selector.js?type=styles&index=0!./app/src/renderer/App.vue
Module build failed:
  @extend .o-color--black;
         ^
      "mark" failed to @extend ".o-color--black".
The selector ".o-color--black" was not found.
Use "@extend .o-color--black !optional" if the extend should be able to fail.
      in D:\Documents\Projects\box\box-desktop-vue\v1\boxscreen-desktop\app\node_modules\composite-css\stylesheets\vendor\_normalize.scss (line 175, column 11)
 @ ./~/vue-style-loader!./~/css-loader!./~/vue-loader/lib/style-rewriter.js?id=data-v-22358182!./~/sass-loader!./~/vue-loader/lib/selector.js?type=styles&index=0!./app/src/renderer/App.vue 4:14-272
 @ ./app/src/renderer/App.vue
 @ ./app/src/renderer/main.js

On the Vue side, I have something like this:
<style lang="scss">
  @import "~some-package/stylesheets/A.scss";
  @import "~some-package/stylesheets/B.scss";
</style>

...

Tell me about your development environment.

Node version: v6.9.2
NPM version: 3.10.9
vue-cli version: (if necessary) 2.8.0
Operating System: Windows 10

If you are looking to suggest an enhancement or feature, then feel free to remove everything above.

@manuelro

Use "@extend .o-color--black !optional" if the extend should be able to fail.

Did you try the suggestion action from sass-loader?

Closing this for now. Feel free to comment back.


[$1000] Android Chrome autofills with login/password on the “Add phone number” screen

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Action Performed:

Log in
Navigate to Settings -> Profile -> Add phone number
Tap phone number field

Expected Result:
Phone number recommended
Actual Result:
Username/password combinations are recommended
Workaround:
unknown
Platform:

Where is this issue occurring?

Mobile Web (Android chrome)

Version Number: 1.2.36-2
Reproducible in staging?: y
Reproducible in production?: y
Email or phone of affected tester (no customers):
Logs: https://stackoverflow.com/c/expensify/questions/4856
Notes/Photos/Videos:

https://user-images.githubusercontent.com/43996225/206596401-49313fdf-b2af-42f2-a16c-64baff56ddb2.mp4
Expensify/Expensify Issue URL:
Issue reported by: @marcaaron
Slack conversation: https://expensify.slack.com/archives/C049HHMV9SM/p1669693545964079
View all open jobs on GitHub
Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~015ced3a25cc203e65
Upwork Job ID:<PHONE_NUMBER>558640640
Last Price Increase: 2022-12-14

reviewing today

@dylanexpensify per this https://github.com/Expensify/App/issues/8455#issuecomment-1307983899 , I think we should hold / close this issue until refactoring

Additionally, we should be vigilant to not to open/work on any more bugs relating to this page until we are fully passwordless!

@fedirjh thank you very much for linking that comment
I agree, I will close this issue, also this is super small problem so it definitely does not need to be fixed right now and can wait for the refactor. Then we will see how we can improve these/ if there still will be a need for this.


chore: promote test15 to version 0.0.15

chore: promote test15 to version 0.0.15
this commit will trigger a pipeline to generate the actual kubernetes resources to perform the promotion which will create a second commit on this Pull Request before it can merge

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verify
8b20cf428110ed3dbf9fb67e828f53c6be6c6bc0
link
/test verify

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OLPRPS-5210: Implemented CopyrightProvider.

Implemented CopyrightProvider according to requirements in OLPRPS-5210, OLPPORT-2250.

Codecov Report

Merging #911 into master will increase coverage by <.01%.
The diff coverage is 25.92%.

@@            Coverage Diff             @@
##           master     #911      +/-   ##
==========================================
+ Coverage   47.58%   47.58%   +<.01%
==========================================
  Files         235      238       +3
  Lines       21721    21747      +26
  Branches     4933     4935       +2
==========================================
+ Hits        10336    10349      +13
- Misses      11385    11398      +13

Impacted Files
Coverage Δ

@here/harp-omv-datasource/lib/OmvDataSource.ts
32.25% <ø> (ø)
:arrow_up:

@here/harp-mapview/lib/Tile.ts
55.7% <ø> (ø)
:arrow_up:

@here/harp-mapview/lib/copyrights/CopyrightInfo.ts
14.28% <ø> (ø)

@here/harp-mapview/lib/MapView.ts
53.66% <100%> (ø)
:arrow_up:

...mapview/lib/copyrights/DefaultCopyrightProvider.ts
100% <100%> (ø)

...arp-mapview/lib/copyrights/UrlCopyrightProvider.ts
15.38% <15.38%> (ø)

...e/harp-mapview/lib/copyrights/CopyrightProvider.ts
15.62% <15.62%> (ø)

...-mapview/lib/copyrights/CopyrightElementHandler.ts
7.14% <20%> (ø)

...e/harp-webtile-datasource/lib/WebTileDataSource.ts
21.95% <5.55%> (+2.87%)
:arrow_up:

@here/harp-mapview-decoder/lib/TileDataSource.ts
66.66% <83.33%> (ø)
:arrow_up:

... and 3 more

Continue to review full report at Codecov.

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@heremaps-bot ok to test


[Tabs] Let each tab set its own width

[ ] PR has tests / docs demo, and is linted.
[ ] Commit and PR titles begin with [ComponentName], and are in imperative form: "[Component] Fix leaky abstraction".
[ ] Description explains the issue / use-case resolved, and auto-closes the related issue(s) (http://tr.im/vFqem).

The Tab component has a new prop of type number: labelWidth. This number
is the width of the label in pixels. The user must either set this prop
to every tab or none. If this condition is not met, the ink bar is not
drawn, and a warning is displayed in the console.
The docs have also been updated with information and an example for this
prop.
This solves issue #4420. This approach was suggested in #5301.

Actually, following https://github.com/callemall/material-ui/issues/4795#issuecomment-254920212 I think that it would be better to drop any work on the master branch, as some major improvements have already been done on the next branch.

@GAumala Thanks for pushing forward the Tabs component. I'm closing this PR following my previous comment.


(demo): Update fabric2 demo scripts

Codecov Report

Merging #513 (c7af30d) into dev (529f116) will not change coverage.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##                dev     #513   +/-   ##
=========================================
  Coverage     14.94%   14.94%
  Complexity      399      399
=========================================
  Files           181      181
  Lines          8352     8352
  Branches        700      700
=========================================
  Hits           1248     1248
  Misses         7006     7006
  Partials         98       98

Impacted Files
Coverage Δ
Complexity Δ

...a/com/webank/wecross/stub/TransactionResponse.java
60.71% <100.00%> (ø)
9.00 <0.00> (ø)


Describe supported React Flow versions on README

while working on current version v1.0.0 facing the above issue but  I used version 0.4.0 its worked well now I need to implement SmartStepEdge using version v1.0.0
Need guidance.
Thanks in advance

Hey @abhishekopsteq ! You need to update your react-flow-renderer to version 10, I've dropped support for version 9 and bellow

Fixed on version 1.0.1


scrna-sea and mFISH example

Hi,
Could you example with scrna-seq from 10x and image from same tissue?

hello!
there are several examples regarding this settings you just mentioned:
https://squidpy.readthedocs.io/en/latest/auto_tutorials/tutorial_visium_fluo.html
https://squidpy.readthedocs.io/en/latest/auto_tutorials/tutorial_visium_hne.html
let me know if they are useful!

do have example not using Visium?

many, check tutorials and examples here:
https://squidpy.readthedocs.io/en/latest/examples.html
https://squidpy.readthedocs.io/en/latest/tutorials.html

hello @FADHLyemen was the sugested tutorials useful?

I'm gonna close this, feel free to reopen if not resolved


GMM not converging

Hi Matthias,
I love how the library keeps growing, great work! I am however stuck at trying to create a simple Gaussian Mixture Model for 3d shape classification based on the MoNet paper but the loss is not decreasing. Am I doing something wrong? Should I use SHOT descriptors instead? I'm using spherical pseudo coordinates and graclus as clustering. I'll drop the code below.
Kind regards,
Balder
class MonetBaseline(torch.nn.Module):
    def __init__(self):
        super(MonetBaseline,self).__init__()
        self.conv1 = GMMConv(in_channels = 1, out_channels = 32, dim=3)
        self.batchnorm_1 = torch.nn.BatchNorm1d(32)
        self.conv2 = GMMConv(32, 64, dim=3)
        self.batchnorm_2 = torch.nn.BatchNorm1d(64)
        self.conv3 = GMMConv(64, 64, dim=3)
        self.batchnorm_3 = torch.nn.BatchNorm1d(64)
        self.fc1 = torch.nn.Linear(64, 8)
        self.fc2 = torch.nn.Linear(8, 2)

    def forward(self, data):
        data.x = F.elu(self.batchnorm_1(self.conv1(data.x, data.edge_index, data.edge_attr)))
        data.x = F.elu(self.batchnorm_2(self.conv2(data.x, data.edge_index, data.edge_attr)))
        cluster = graclus(data.edge_index, weight = data.edge_attr)
        data = max_pool(cluster, data)

        data.x = F.elu(self.batchnorm_3(self.conv3(data.x, data.edge_index, data.edge_attr)))
        cluster = graclus(data.edge_index, weight = data.edge_attr)
        x, batch = max_pool_x(cluster, data.x, data.batch)
        x = global_mean_pool(x, batch)
        x = F.elu(self.fc1(x))
        x = F.dropout(x, training=self.training)
        x = F.elu(self.fc2(x))
        return x

Hi and sorry for answering late,
I noticed a small bug in your code, which may cause the problem:
data = max_pool(cluster, data)

This method is a bit hard to get. I tried my best to describe it here.
However, edge features of collapsing edges will get summed up! That does not make any sense when working with 3d shapes. Instead, it is best to delete the edge features before calling max_pool, and to generate new edge features based on the newly defined positions:
data.edge_attr = None
data = max_pool(cluster, data, transform=Spherical())

In addition, I noticed that you use the multi-dimensional edge features as weights in the graclus call:
cluster = graclus(data.edge_index, weight = data.edge_attr)

This is not allowed and I will add an assertion to capture such mistakes. Here, weight is used to find the best unmarked neighbor with maximum edge weight. For your case, it is best to simply omit the weight parameter.
cluster = graclus(data.edge_index)

Hi Matthias,
Thank you for the elaborate response! Sorry for my late reply I was without GPU for a week. Solving the bug indeed seems to make the network more robust. However, when working with a subset of 100 shapes from my dataset it still takes up to 500 epochs to converge using Adam optimization. Is this expected behavior? Using SplineCNN I could get the network to converge in well under 30 epochs. I've tried increasing the learning rate and tweaking the batch size (higher seems to work better). I'm using CrossEntropyLoss and Adam optimisation with a learning rate of 0.001 and a weight decay of 5e-4. My node features are all 1 since I'm trying to learn from shape only, I'll paste the code below.
pre_transform = T.Compose(
        [transforms.Scale(transform_scale), transforms.UniformSimilarSample(7160, sample_size), T.KNNGraph(k),
         T.Spherical(cat=False), transforms.IdentityTransform()])

class MonetBaseline(torch.nn.Module):
    def __init__(self):
        super(MonetBaseline,self).__init__()
        self.conv1 = GMMConv(in_channels = 1, out_channels = 32, dim=3)
        self.batchnorm_1 = torch.nn.BatchNorm1d(32)
        self.conv2 = GMMConv(32, 64, dim=3)
        self.batchnorm_2 = torch.nn.BatchNorm1d(64)
        self.conv3 = GMMConv(64, 64, dim=3)
        self.batchnorm_3 = torch.nn.BatchNorm1d(64)
        self.fc1 = torch.nn.Linear(64, 8)
        self.fc2 = torch.nn.Linear(8, 2)

    def forward(self, data):
        data.x = F.elu(self.batchnorm_1(self.conv1(data.x, data.edge_index, data.edge_attr)))
        data.x = F.elu(self.batchnorm_2(self.conv2(data.x, data.edge_index, data.edge_attr)))

        cluster = graclus(data.edge_index)
        data.edge_attr = None
        data = max_pool(cluster, data, transform=T.Spherical())

        data.x = F.elu(self.batchnorm_3(self.conv3(data.x, data.edge_index, data.edge_attr)))
        cluster = graclus(data.edge_index)
        x, batch = max_pool_x(cluster, data.x, data.batch)
        x = global_mean_pool(x, batch)

        x = F.elu(self.fc1(x))
        x = F.dropout(x, training=self.training)
        x = F.elu(self.fc2(x))
        return x

Kind regards,
Balder

I am not sure if there are numerical instabilities with GMMConv, but from what I experienced myself slower convergence seems to be natural behaviour when working with GMMConv, e.g. the authors themselves train all models in their paper for a large number of epochs.

Hi,
Sorry for opening this issue again but I really can't get this operator to converge on the simplest of problems. I've created a toy example where the goal is to distinguish a square from a parallelogram but even here the loss mainly plateau's at 0.6931. I find that sometimes I get better results if I disable the normalization in GMMConv but then as a result output can explode. Any ideas on this? I'll post the dummy example below if you're interested.
Kind regards,
Balder
import torch
import torch.nn.functional as F
import torch_geometric.transforms as T
from torch_geometric.data import DataLoader, Data
from torch_geometric.nn import GMMConv, global_mean_pool, SplineConv

pseudo = T.Spherical()

edge_index1 = torch.tensor([[0,1,0,2,3,1,3,2],
                       [1,0,2,0,1,3,2,3]])

edge_index3 = torch.tensor([[0,1,0,2,1,2],
                        [1,0,2,0,2,1]])

x = torch.ones((4,1))
pos_1 = torch.tensor([[50,100,10],[100,100,10],[50,50,10],[100,50,10]], dtype = torch.float32)
pos_2 = torch.tensor([[70,100,10],[120,100,10],[50,50,10],[100,50,10]], dtype = torch.float32)
pos_3 = torch.tensor([[50,50,10],[75,100,10],[100,50,10]], dtype = torch.float32)
labels = torch.tensor([[0],[1]])

# example square vs parallelogram
data = [Data(x = x, edge_index = edge_index1, pos = pos_1, y = labels[0]), Data(x = x, edge_index =         edge_index1, pos = pos_2, y = labels[1])]
# example square vs triangle
#data = [Data(x = x, edge_index = edge_index1, pos = pos_1, y = labels[0]), Data(x = x, edge_index =     edge_index3, pos = pos_3, y = labels[1])]
data = list(map(pseudo, data))

train_loader = DataLoader(data, batch_size =2, shuffle = False)

class GMM(torch.nn.Module):
   def __init__(self):
       super(GMM,self).__init__()
       self.conv1 = GMMConv(in_channels = 1, out_channels = 16, dim=3)
       #self.conv1 = SplineConv(1,16, dim=3, kernel_size=5)
       self.fc1 = torch.nn.Linear(16, 2)

   def forward(self, data):
       data.x = F.elu(self.conv1(data.x, data.edge_index, data.edge_attr))
       x = global_mean_pool(data.x, data.batch)
       x = self.fc1(x)
       return F.log_softmax(x, dim = 1)

epochs = range(30000)
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = GMM().to(device)
optimizer = torch.optim.Adam(model.parameters(), lr=0.0001)

def train(epoch):
    model.train()
    epoch_loss = 0

for data in train_loader:
    data = data.to(device)
    optimizer.zero_grad()
    out = model(data)

    _, preds = torch.max(out, 1)
    loss = F.nll_loss(out, data.y)
    epoch_loss += loss.item()
    loss.backward()
    optimizer.step()

    #print(out)
    print(preds)
    print(loss)

for epoch in epochs:
    train(epoch)
    print('Epoch: ' + str(epoch))

Thank you so much for your effort. I revisited the GMMConv and might fixed slight numerical instabilities with torch.exp. Your toy example does now converge.


Register v1.0

@JuliaRegistrator register

Registration pull request created: JuliaRegistries/General/84067
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v1.0.0 -m "<description of version>" 77ae961faf173468252bcfffacec3adfc2eb8bcb
git push origin v1.0.0

@JuliaRegistrator register

Registration pull request updated: JuliaRegistries/General/84067
After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.
This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:
git tag -a v1.0.0 -m "<description of version>" 8c4b77a722cb228078ef7b940b9f548cd7adeec1
git push origin v1.0.0


feat(ibc): update grpc msg

What this PR does / why we need it:
Which issue(s) this PR fixes:

Fixes #
Which docs this PR relation:
Ref #
Which toolchain this PR adaption:
No Breaking Change
Special notes for your reviewer:
CI Switch

[x] Chaos CI
[x] Cargo Clippy
[x] Coverage Test
[x] E2E Tests
[x] Code Format
[x] Unit Tests
[x] Web3 Compatible Tests
[x] OCT 1-5 And 12-15
[x] OCT 6-10
[x] OCT 11
[x] OCT 16-19
[x] v3 Core Tests

/run-ci

/run-ci

/run-ci

/run-ci

/run-ci

/run-ci

/run-ci


Write test cases

To give new folks a place to start, write up some test cases that could be automated through cypress.io or test cafe.

Create campaign
Join campaign
sign petition

Test case for Create Campaign is https://docs.google.com/document/d/1P84qOrJg2WAB_nDaAB-ErmRLq-QzxthyT4cp7DyyMTk/edit

Join campaign https://docs.google.com/document/d/1AFZXOoNGZkQoavdFNY-9Pl9necxs3nSTIs8CkPwV3VM/edit
Sign campaign https://docs.google.com/document/d/1FRs0o53EgXhRmRZW38PtWaV2OdI7dEQbBsaOGzxrVTY/edit


Specify libprotonup with both path and version

Continuing from #24
Turns out cargo supports both a path and version for specifying dependencies. We can likely do the crate publish in a single cargo publish, and do releases on main rather than release branches.
I've not touched the github workflow as I've not worked with them before and don't want to break it.

Thanks. I will take a look at this soon.

I made a few tests, and I think its going to work!
I will merge your PR and make the changes release from the main branch.


chore: mv node-mocks-http to devDependencies

#188

Sadly can't move this because it's required at runtime by our aws-handler.

Sadly can't move this because it's required at runtime by our aws-handler.

Sounds like something that should be in an adapter / as a peer dep / optional dep


[Snyk] Fix for 3 vulnerabilities

This PR was automatically created by Snyk using the credentials of a real user.Snyk has created this PR to fix one or more vulnerable packages in the `npm` dependencies of this project.
Changes included in this PR

Changes to the following files to upgrade the vulnerable dependencies to a fixed version:

gravitee-apim-console-webui/package.json
gravitee-apim-console-webui/package-lock.json

Vulnerabilities that will be fixed
With an upgrade:

Severity
Priority Score (*)
Issue
Breaking Change
Exploit Maturity

479/1000  Why? Has a fix available, CVSS 5.3
Regular Expression Denial of Service (ReDoS) SNYK-JS-HIGHLIGHTJS-1048676
Yes
No Known Exploit

591/1000  Why? Proof of Concept exploit, Has a fix available, CVSS 5.4
Cross-site Scripting (XSS) SNYK-JS-TOASTUIEDITOR-1086605
Yes
Proof of Concept

484/1000  Why? Has a fix available, CVSS 5.4
Cross-site Scripting (XSS) SNYK-JS-TOASTUIEDITOR-1536769
Yes
No Known Exploit

(*) Note that the real score may have changed since the PR was raised.
Check the changes in this PR to ensure they won't cause issues with your project.

Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.
For more information:
🧐 View latest project report
🛠 Adjust project settings
📚 Read more about Snyk's upgrade and patch logic

Learn how to fix vulnerabilities with free interactive lessons:
🦉 Cross-site Scripting (XSS)
🦉 Cross-site Scripting (XSS)
🦉 Regular Expression Denial of Service (ReDoS)

That's not so simple...


use retry-able error codes for fetch failures

With the proxy configuration, restarting the broker triggers SERVER_UNKNOWN_ERROR that is not a retry-able error. This behaves differently than the Kafka broker restarts. In order to retry, update some errors codes to retry-able FETCH error codes.
Error codes' retry-able column is described at https://kafka.apache.org/protocol#protocol_error_codes

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 54.46%. Comparing base (f65b9bc) to head (9172fd8).

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files

@@            Coverage Diff             @@
##             2.10_ds      #98   +/-   ##
==========================================
  Coverage      54.46%   54.46%
  Complexity       118      118
==========================================
  Files             19       19
  Lines            940      940
  Branches          80       80
==========================================
  Hits             512      512
  Misses           411      411
  Partials          17       17

please port to the 3.1_ds branch as well
cc @nicoloboschi @nikhil-ctds

an alternative taht we could try is KAFKA_STORAGE_ERROR


languages/go: fix wasmexport proposal link

There're no branches or tags on that repo. Must have slipped in accidentally.

Those Go+Wasm notes are a very thorough, thanks for compiling and sharing them 🎈


Update GitKraken screenshots

We just released v2.0 and we're really excited about it! It'd be great if we could get these images updated

Makes sense. Thanks!


Add log waring if workflow eviction / closure is taking too long time

What was changed
Add log warning if workflow eviction / closure is taking too long time to close.
Add guards making sure all threads are drained.

Closing as this is a stale PR


Generate documentation

https://issues.redhat.com/browse/HACBS-640

Cool :+1:
Something to consider for followup work:

Should this be a ec subcommand, or a tool (like the coverage tool we run from the Makefile)
Should we version-control the documentation?
How do we make sure the documentation is up to date, if in version control?
Should we publish the documentation (GitHub pages, release artifact)?

Should we add docs/ to .gitignore?

Yes, added it.


Question about dequantization overhead

Thanks for your great work. I want to learn how to calculate the dequantization overhead, like in Figure 18, since the dequantization process is within a single kernel.

Hi @DD-DuDa , thank you very much for your interests in QServe. We real-measured the dequant overheads of the above kernels. We compared the actual throughputs of GEMM kernels with dequantization and kernels in which dequantization ops are skipped. The difference of throughputs between the two version of kernels is regarded as dequant overhead.

Got it! Thank you for your response!

@ys-2020

In the formula(5) in your paper, why is the per group scale uint8? Why uint4-uint4 multiplied by uint8 can still be sint8?
Is that a typo? This is quite confusing.(In my understanding, the per group scale should be also 4bit to generate a sint8-w)


brew doctor doesn't check for missing (deleted) formulas with dependencies

I think brew doctor should warn about formulas that are no longer supported and were deleted from brew. Here's an example:
$ brew config
HOMEBREW_VERSION: 1.3.1
ORIGIN: https://github.com/Homebrew/brew
HEAD: 69799d97b1e7314912b2ee234dec2c179c5fb969
Last commit: 7 days ago
Core tap ORIGIN: https://github.com/Homebrew/homebrew-core
Core tap HEAD: 5e0ccfb2db30920d74598bdb01f8629ef8c5aacb
Core tap last commit: 4 hours ago
HOMEBREW_PREFIX: /usr/local
HOMEBREW_REPOSITORY: /usr/local/Homebrew
HOMEBREW_CELLAR: /usr/local/Cellar
HOMEBREW_BOTTLE_DOMAIN: https://homebrew.bintray.com
CPU: quad-core 64-bit haswell
Homebrew Ruby: 2.0.0-p648
Clang: 8.1 build 802
Git: 2.11.0 => /Applications/Xcode.app/Contents/Developer/usr/bin/git
Perl: /usr/bin/perl
Python: /usr/local/opt/python/libexec/bin/python => /usr/local/Cellar/python/2.7.13_1/Frameworks/Python.framework/Versions/2.7/bin/python2.7
Ruby: /usr/local/bin/ruby => /usr/local/Cellar/ruby/2.4.1_1/bin/ruby
Java: 1.8.0_102
macOS: 10.12.6-x86_64
Xcode: 8.3.3
CLT: N/A
X11: N/A

$ brew doctor
Your system is ready to brew.

$ brew uses --installed android-sdk
Warning: No available formula with the name "android-sdk"
android-ndk
Error: Missing formulae should not have dependents!

I've got an error here, and brew doctor says I'm all fine.

Your system is ready to brew.

This is correct.

I've got an error here

brew doctor is not a tool to debug all issues or possible problems with Homebrew but to provide debugging information for Homebrew maintainers when you create an issue.


⚠ ClamAV has degraded performance

In 83e5ca9, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 85 ms

Resolved: ClamAV performance has improved in 00dd3a0.


Total marks and secured marks training data

HI @dileep-gadiraju  I have tested above pr this pr is working as expected .Now training data field is added for total marks and marks obtained .


close Issue#37, temporary fix for all servo stop problem

Add "\\.\" prefix to PortName of SerialPort Class.
Change the speed of motors in ApplyPoseAllServos() to avoid Crash Motion after All servo stop.
As a side effect of this, Apply pose button always make fastest motion.

Thank you all for your contribution!
Please describe me what purpose of this scripts(It may be cause confusion for newbies..)
(Suggestion:  Can you remove this scripts? )
MotionDataVerification/Assets/_PremaidAI/MotionDataRecognition/Scripts/MotionDataWriterSample.cs.bak

Thank you for your suggestion.
I remove two bak files with their metas.

Thank you! I'll add readme to your contribution :)


unable to add bootstrap and jquery in app container...

need to add bootstrap and jquery for all the page route....where to include these files

You should check out react-bootstrap and not use bootstrap and jquery directly...

i am using npm jquery for ajax network calls .. during dev mode it is fine but while in production build it is showing below error
_jquery2.default.ajax is not a function

i am getting this error Bootstrap's JavaScript requires jQuery

Sorry I don't know bootstrap so I can't help. Try using StackOverflow for this kind of problem not directly related to Phenomic. Thanks!

okay


API support

Create multiple API's allowing users to customise their UI and interact with NeoGPT

I will be solving this issue.

Sure @savyez under kwoc or just a contribution?

@neokd KWOC has started?

My bad i got confused it starts on 9th December

Add the tag, even after it is done.. I will opening a PR on 9th 😂


[Question] How did you get the readme output on yEd

This is a question about the yEd output you have in the readme (so it's not really related to the package):

When loading the gml into yEd I just have a black blob of text which are all file names superimposed onto each other.  After playing around a bit I could press "layout" > "one click layout" to view the graph in a bit more ordered fashion, then select all nodes and apply a shape. However I could not replicate what you have done in the readme.
So my questions are:

How did you make the yellow boxes fit each file name ?
Which layout process did you use ?

I selected all names and applied a shape to all with a given width but some names are bigger than the width, some are smaller

I'm so sorry but I don't remember exactly how I did it. I haven't used yEd in a long time. I think I just played with the layout and shape settings. Also, I may have cheated a little by moving some of the nodes manually.


Option to disable/filter kramdown warnings

kramdown spits out warnings that are not always very useful. For instance:
kramdown warning: No link definition for link ID 'git' found on line 4

It would be useful to have an option to either disable warnings entirely, or filter them.

I started implementing warning filtering.
My idea was to store regexps inside @config[:kramdown][warning_filters] as an array. Later, I would filter with filter :kramdown, @config[:kramdown] || {}. Then inside the :kramdown filter implementation, I would use the warning_filters array.
At that point, I found it difficult to reliably store regexps inside nanoc.yaml. Should we use !ruby/regexp or store them as plain strings? If stored as plain strings, are there corner cases when trying to converting them to real regexps in order to filter Kramdown's @warnings array?

Should we use !ruby/regexp or store them as plain strings?

I think I prefer strings.

If stored as plain strings, are there corner cases when trying to converting them to real regexps in order to filter Kramdown's @warnings array?

Not that I know of… Regexp.new(string) should work.


Add terraform state validation for Install and Upgrade operations in TK8

Describe the bug
Currently, there is not much difference between Install and Upgrade functionality. Install with modified configuration does an Upgrade as well.
To Reproduce
Steps to reproduce the behavior:

Create a cluster with tk8 cluster install rke/aws.
Modify config.yaml and run tk8 cluster install rke/aws.
The above operation should be only an Upgrade and not Install.

Expected behavior
Install should only set up a cluster and infra if there is no current cluster with the same name.
Upgrade should only work if there is an existing cluster.

This has been fixed.


Video tutorial for the libraries

@thecuriousteam Can I work on this issue Please!!

Yes @Abhrajitdas02 you can start working on it
Thank You
Instructions

Yes you can start working on it by taking latest pull from main branch
Don't Forget to join onboarding group for knowledge flow and direct conversation and support from other developers link  Curious Developers Community - Hacktoberfest
Please attach the screenshots and video of the development work once it is done
Contributions more than 3 will be awarded a certificate of appreciation from curious ecosystem please mail to<EMAIL_ADDRESS>for claiming certificate and please attach your issue number
Respect Co Developers And Please Reachout to admins if any issues

Thanks & Regards
The Curious Team

@Abhrajitdas02 did you joined on boarding group? if yes please respond in the group


Replicating Photoshop's auto white-balance feature

What are you trying to achieve?
I'd like to set a white balance based on either a custom colour or the brightest pixel in the image:

Have you searched for similar questions?
Yes. Any help is appreciated, even a starting point of some sort — I am clueless.
Are you able to provide a minimal, standalone code sample that demonstrates this question?
Any image will do sharp("image.jpg")
Are you able to provide a sample image that helps explain the question?

I'm unsure if it's exactly what you're looking for, but the white point of an image can be altered by compositing solid grey over it using the colour-dodge blend mode.
https://sharp.pixelplumbing.com/api-composite
The following example uses middle grey:
sharp(input)
  .composite([
    {
      input: {
        create: {
          width: 3406,
          height: 2256,
          channels: 3,
          background: "#777",
        },
      },
      blend: "colour-dodge",
    },
  ])
  ...

Thank you, that answers my question.


why arp table is not updated?

i use pcap to send arp request, and get reply by tcpdump. But the arp table not updated, why?
thanks~

问题解决了么?我也遇到了类似的问题


Use ES modules

Because we're cool
Hopefully this doesn't break anything! It all seemed to work for me.

Lol I'm merging anyways!


How to query templates table within mailer ?

Hi
If I have multiple templates stored in my database - how can I perform a query in my mailer so that my mailer retrieves the template I want to use and uses that to generate the mail message ?
The documentation contains the following snippet ...
class MyEmail < ActionMailer::Base
  prepend_view_path TemplateStorage.resolver

but that doesn't give me the control that I need to retrieve the template my mailer needs to use based on supplied criteria
how can I modify the call above ( prepend_view_path TemplateStorage.resolver ) so that arguments are passed to the 'resolver' which can be used to query my templates table and only retrieve the needed template ?
Thanks
Dave

I'm not sure what you're asking for, however several ways to select the template to render, even passing a specific path.
You could also create a new subclass that inherits from the parent template storage and add specific behaviours.


Need discussion of router path or file

We have some router for rest api. and it should be defined when run server.js.
However, if it's implemented in server.js, it is less readable and less manageable.
We need to discuss how to separate the router logic into a folder or a file.

We already introduced a new-style router:
https://github.com/romandev/absolute/pull/345


feat(recipes): Add ModernizeJenkinsfile Recipe and UpgradeNextMajorParentVersion Dependency

This PR introduces two key enhancements to our recipe collection:

Integration of the OpenRewrite recipe org.openrewrite.jenkins.ModernizeJenkinsfile into a new modernizer recipe called AddOrModernizeJenkinsFile.
Addition of the UpgradeNextMajorParentVersion as a dependency for the new recipe.

Rationale for Dependency
The inclusion of UpgradeNextMajorParentVersion as a dependency is based on ModernizeJenkinsfile's latest version, which produces a Jenkinsfile that:

Tests with JDK 17 on Windows
Tests with JDK 21 on Linux

This dependency ensures our modernization efforts align with current testing practices across different environments.
Testing Performed
To verify the functionality of the new recipe, the following command was executed:
rm -fr ~/.cache/jenkins-plugin-modernizer-cli/vagrant/ && java -jar plugin-modernizer-cli/target/jenkins-plugin-modernizer-999999-SNAPSHOT.jar --plugins vagrant --recipes MinimalBuildJava8,AddOrModernizeJenkinsFile --debug
This test resulted in the creation of a pull request: jenkinsci/vagrant-plugin#13.
Submitter checklist

[X] Make sure you are opening from a topic/feature/bugfix branch (right side) and not your main branch!
[X] Ensure that the pull request title represents the desired changelog entry
[X] Please describe what you did
Link to relevant issues in GitHub or Jira
Link to relevant pull requests, esp. upstream and downstream changes
[X] Ensure you have provided tests - that demonstrates feature works or fixes the issue

Thanks.
This recipe will then update the plugin to JDK11, while allowing it to be compiled with JDK17 and 21.


No way to implement GetRuntimeClassName

Motivation
ActivationFactory documentation states that GetRuntimeClassName should return “ the runtime class name of the object that the current ActivationFactory instantiates.”
Currently, this is not possible to do using windows-rs crate.
Drawbacks
None
Rationale and alternatives
This makes authoring WinRT components incomplete and potentially error-prone.
Additional context
No response

Yes, this is on my radar for the revamped implement macro.

The trait-based implement macro (#1345) will now implement GetRuntimeClassName automatically (here's an example).
Note that this is currently limited to interfaces. Classes (and exclusive interfaces) are on the way (#1094).

Thanks! 🙂 I guess it's still impossible to implement it for IActivationFactory, right? Would it be useful to have an ability to override a default implementation?

For most scenarios that shouldn't matter, but yes I plan to support activation factories directly, so you won't have to think about implementing that. I also considered providing an option to override the default implementation using a trait if needed, but I'm not there yet.


New: Observe acl behavior

Description
Changes proposed in this pull request.
Test plan
Outline the test plan used to test this change before merging it.

Fixes #.

Codecov Report

Merging #435 into master will increase coverage by <.01%.
The diff coverage is 55.55%.

@@            Coverage Diff             @@
##           master     #435      +/-   ##
==========================================
+ Coverage   57.28%   57.29%   +<.01%
==========================================
  Files          46       46
  Lines        5661     5662       +1
==========================================
+ Hits         3243     3244       +1
  Misses       2116     2116
  Partials      302      302

Impacted Files
Coverage Δ

internal/supervisor/iptablesctrl/acls.go
53.05% <0%> (-0.26%)
:arrow_down:

internal/supervisor/ipsetctrl/acls.go
85.13% <0%> (-0.78%)
:arrow_down:

enforcer/datapath/datapath_tcp.go
51.08% <34.78%> (-0.61%)
:arrow_down:

enforcer/acls/acls.go
67.08% <69.23%> (-1.03%)
:arrow_down:

enforcer/datapath/utils.go
94.33% <85.71%> (+20.01%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
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In the latest commit where I’m doing lookups in ordered form now as we actually had a bug.
We could have
x/32 deny
0/0 accept
And packets might get accepted. Now we have order from 32 down to 0. Got the functionality looking at optimizing algo/storage.
As observation will be turned on very little it has low performance overhead to have another table.
On Dec 21, 2017, 9:08 AM -0800, Dimitri Stiliadis<EMAIL_ADDRESS>wrote:

@dstiliadis requested changes on this pull request.
Parallel tables for observed vs actionable policies
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.


Allow a mirror to have more than one key

Hi,
This pull request is in relation with the issue number #28
I hope this work will help you.
Thomas

My work on this branch is finished unless something doesn't suit you.

Thanks for the contribution. One of us will hopefully have a look at this soon. :+1:

Think I hit this issue when trying to add ubuntu Archive using aptly on a RHEL server. Fudged around it like you did, but will be handy once this is merged.


Cannot find module '@kontent-ai/rich-text-resolver' or its corresponding type declarations in v1.0.0

Brief bug description
After update from @kontent-ai/rich-text-resolver 0.0.5 to 1.0.0 an error occured:
Cannot find module '@kontent-ai/rich-text-resolver' or its corresponding type declarations
Repro steps

Update @kontent-ai/rich-text-resolver to 1.0.0
Try to import anything from the library

Expected behavior
Cannot use the library in version 1.0.0 as it doesn't export any functionality.
Test environment

node v20.11.0
typescript 5.3.3

Screenshots

hello there, thank you for the issue submission. I was able to reproduce the behavior and I'm reviewing the export logic to figure out the culprit. I'll make sure to update you once I know more.

Some takeaways from my investigation so far -- there package's configuration (tsconfig, package.json) seems to be in a somewhat invalid state. Most importantly, the subpath exports are not resolving at all and, subsequently, neither does the path to the installed module.
I tried modifying the exports and explicitly provide type definition for each subpath but to no avail. Interestingly, updating TypeScript to the latest version yields a new set of errors, where tsc complains about module and moduleResolution not being both set to nodenext, despite that not being the case:

I'll try to get to the bottom of this, but will probably release a quick hotfix in the meantime, while minimizing the effect on public API. I'll also revert the exports in package.json to their original state, just in case they work in some scenarios, though I haven't so far managed to make this work in any environment.
Thank you very much for your patience so far.


freq_mask_path and space_mask_path

Hi,
I want to know that,  If I want to use freq_mask and space_mask on my own datasets, how can I generate it?
Thanks!

You can calculate the average value over the dataset for each pixel in each image to generate the space_mask, and calculate the average amptitude over the dataset of each frequency component in each image after Fourier transform for the freq_mask, as mentioned in Sec 4.3 of our paper.  Emprically, we find that about 200 images randomly sampled from the dataset is enough for calculating both masks.

You can calculate the average value over the dataset for each pixel in each image to generate the space_mask, and calculate the average amptitude over the dataset of each frequency component in each image after Fourier transform for the freq_mask, as mentioned in Sec 4.3 of our paper. Emprically, we find that about 200 images randomly sampled from the dataset is enough for calculating both masks.

thanks!
By the way, could you release code about this?  These parameters are necessary to generate high quality image, so I hope to keep align with your work.

Sure, I will add a demo about how to calculate the masks soon.

We have added the file mask_gen_demo.py.py, which is a demo showing how to generate frequency and space mask for an image dataset. We take CIFAR10 as an example. We hope you find it helpful.

We have added the file mask_gen_demo.py.py, which is a demo showing how to generate frequency and space mask for an image dataset. We take CIFAR10 as an example. We hope you find it helpful.

thanks!

We have added the file mask_gen_demo.py.py, which is a demo showing how to generate frequency and space mask for an image dataset. We take CIFAR10 as an example. We hope you find it helpful.

Sorry, another confusion that, if different categories of images are different scale, need to [padding] and [mask] to same shape, but without using torchvision.transforms to Resize, in this scenario, does it make sense to calculate average?

For other datasets in which the raw images has different sizes, you need to resize them to have the same size and before calculating the masks.


Request for Profiling Services

I would like to add an HTTP service to obc-peer, obc-ca and others (?) to support profiling. This is very easy to set up and use as documented here: https://golang.org/pkg/net/http/pprof/
I would propose to add a command line flag to enable this service, e.g.,
./obc-peer peer --pprof-service=localhost:6060

The above would spawn an HTTP server thread listening on localist:6060, using the default 'request router'. Since the current REST API services use a non-default router this shouldn't interfere with REST APIs.
Here's an example of a profile I collected this morning of the obc-peer running with security enabled:
pprof.pdf

@bcbrock #1179 was the re-submission of #1157.  It has been merged so this function is now present.  You can refer to https://github.com/hyperledger/fabric/blob/master/bddtests/docker-compose-4-consensus-batch.yml#L14-L18 as the mechanism for configuring through docker compose.  Perhaps this issue can now be closed?

Thanks @jeffgarratt


Create Friendly JSON Viewer

Related to #284
This PR is an experiment for now to create a more friendly (and performant) way to interact with JSON responses.
Here's what it looks like so far when interacting with https://changelog.insomnia.rest/changelog.json

Good idea! :)

when will this option be available?

Bump! This would be very cool functionality :)