Tremor Script error messages point to wrong expression

Problem
In Tremor Script, indexing into something which is not an array results in an error message. Consider e.g. the one in tests/script_runtime_errors/non_arr_access2/error.txt, which reads as follows:
Error:
    1 | event.snot[42]
      |            ^^ Conflicting types, got integer but expected array

The error message points to the index 42, but the type error is due to the type of event.snot. A more correct error message could be:
Error:
    1 | event.snot[42]
      |       ^^^^ Conflicting types, got integer but expected array

Steps
To reproduce, index into something that's not an array, e.g. as done in tests/script_runtime_errors/non_arr_access/, tests/script_runtime_errors/non_arr_access2/, tests/script_runtime_errors/subslice_no_arr/, and perhaps others.
Possible Solution(s)
A solution may involve modifying the inner expression passed to error_need_arr in tremor-script::interpreter::resolve.

Closing. This was fixed via #1672


MGMT-792 Render virtual machine indication

In addition, CPU details are reordered - more important things first

Thanks for the screenshot!
This is a small detail, but for the Serial number WDYT of None (virtual machine) for this scenario? A dash like - sort of looks like the serial wasn't detected, but in this case the field just isn't applicable.
Since the table columns go CPU/Memory/Disk I think I lean toward Memory capacity being below the CPU-related fields (even though it's arguably more important), but my opinion isn't a strong one. @nirfarkas @AdamJ curious what you think, or any other ideas. See the old layout here for reference.

WDYT of None (virtual machine) for this scenario
Makes sense. I will update together with other changes which might come up based on raised questions.


append to body

Is there an easy method to append 'pswp' element to 'body'?

Since it basically takes the first .pswp (index 0) it finds, you can simply add the .pwsp div early in the content body and it will use that.


Change mentions of ssh_key to ssh_wrapper

This commit was a little misleading. The GIT_SSH environment variable let's Git know where to find an SSH wrapper, not the path for a key to use.

config.git_ssh (just the name of the ENV variable) sounds like a cleaner choise. Ty @mikedillion ! 55dae73f49d434690ff34ddd86738ae9beb70680


Usage for Laravel 5.2

Is there any usage guide for Laravel 5.2 ?
https://github.com/caffeinated/shinobi/wiki/Usage

Laravel 5.2 can be used with the instructions provided on the page you referenced. The newer user model in Laravel 5.2 is much shorter but as long as you use the Laravel 5.1 model info on that page, Shinobi will work on Laravel 5.2 without any loss of functionality for Laravel or Shinobi.

Found one issue with 5.2: Laravel overrides Shinobi's @can Blade directive.  Meaning, it gets turned into 5.2's new Gate::check instead of Shinobi::can.

is it possible to use multi Roles in Shinobi?
example... would this work?
                         @role(['admin', 'advisor'])
                            I am an Admin & advisor User
                        @else
                        @endrole


Option to not automatically rename

If I don't want to automatically rename the document when placed in Inbox, is there a way to configure this? Thank you.

@DrGump
if you add these instructions in the settings it will not rename them. But planning to make this configurable with a toggle in settings again soon

Thanks for your advice. Unfortunately, changing the rename instructions did not work. It still renamed my document. Having a toggle setting will be nice.

@DrGump

Released in 1.43.4
Should be configurable once you update. Let me know it that works for you 🙏🙏

Yes! It worked to not rename the file. Thank you!
Of note, the log now says "11:13 Renamed File_name to [[File_name]]"
This is not a big deal to me but I don't know if you want to change the log result to something like "Note was not renamed due to plugin option" or something like that.


[BUG] README.adoc has dead links

Describe the bug
The README.adoc file has hyperlinks to the guide, but they don't appear to be working. They all appear to give a 404 message.
To Reproduce
Steps to reproduce the behavior:

Go to the main page of this repo
Scroll down to the README.adoc rendering
Click one of the aforementioned links
Profit!

Expected behavior
I would expect these links to render the documents they seem to indicate.
Screenshots

Hello Jeremy, I had a PR for this that I had not yet merged in. Take a look again and please let me know if you can access the links!

This appears to be fixed now


Running Kafka Connector in docker

Hello,
Actually I'm running both Kafka and IBM MQ as Docker containers. I followed all the steps but i'm blocked at this one CLASSPATH=/target/kafka-connect-mq-source-0.5-SNAPSHOT-jar-with-dependencies.jar bin/connect-standalone.sh config/connect-standalone.properties ~/mq-source.properties. Since I don't know how to specify the classpath for my container. I have tried adding the path using plugin.path at connect-standalone.properties file and running the following command :
docker run -v /home/pfe/tmp:/kafka/tmp --rm --network network-test ches/kafka connect-standalone.sh config/connect-standalone.properties /kafka/tmp/mq-source.properties
And this gives the following ERROR :
[2018-05-22 10:02:49,463] ERROR Failed to create job for /kafka/tmp/mq-source.properties (org.apache.kafka.connect.cli.ConnectStandalone:88)
[2018-05-22 10:02:49,464] ERROR Stopping after connector error (org.apache.kafka.connect.cli.ConnectStandalone:99)
java.util.concurrent.ExecutionException: org.apache.kafka.connect.errors.ConnectException: Failed to find any class that implements Connector and which name
matches com.ibm.mq.kafkaconnect.MQSourceConnector, available connectors are: org.apache.kafka.connect.source.SourceConnector,
org.apache.kafka.connect.tools.MockSinkConnector, org.apache.kafka.connect.tools.VerifiableSinkConnector, org.apache.kafka.connect.file.FileStreamSinkConnector,
org.apache.kafka.connect.file.FileStreamSourceConnector, org.apache.kafka.connect.sink.SinkConnector, org.apache.kafka.connect.tools.MockSourceConnector,
org.apache.kafka.connect.tools.SchemaSourceConnector, org.apache.kafka.connect.tools.VerifiableSourceConnector, org.apache.kafka.connect.tools.MockConnector
at org.apache.kafka.connect.util.ConvertingFutureCallback.result(ConvertingFutureCallback.java:80)
at org.apache.kafka.connect.util.ConvertingFutureCallback.get(ConvertingFutureCallback.java:67)
at org.apache.kafka.connect.cli.ConnectStandalone.main(ConnectStandalone.java:96)
Caused by: org.apache.kafka.connect.errors.ConnectException: Failed to find any class that implements Connector and which name matches com.ibm.mq.kafkaconnect.MQSourceConnector,
available connectors are: org.apache.kafka.connect.source.SourceConnector, org.apache.kafka.connect.tools.MockSinkConnector,
org.apache.kafka.connect.tools.VerifiableSinkConnector, org.apache.kafka.connect.file.FileStreamSinkConnector,
org.apache.kafka.connect.file.FileStreamSourceConnector, org.apache.kafka.connect.sink.SinkConnector, org.apache.kafka.connect.tools.MockSourceConnector,
org.apache.kafka.connect.tools.SchemaSourceConnector, org.apache.kafka.connect.tools.VerifiableSourceConnector, org.apache.kafka.connect.tools.MockConnector
at org.apache.kafka.connect.runtime.ConnectorFactory.getConnectorClass(ConnectorFactory.java:85)
at org.apache.kafka.connect.runtime.ConnectorFactory.newConnector(ConnectorFactory.java:38)
at org.apache.kafka.connect.runtime.AbstractHerder.getConnector(AbstractHerder.java:336)
at org.apache.kafka.connect.runtime.AbstractHerder.validateConnectorConfig(AbstractHerder.java:235)
at org.apache.kafka.connect.runtime.standalone.StandaloneHerder.putConnectorConfig(StandaloneHerder.java:158)
at org.apache.kafka.connect.cli.ConnectStandalone.main(ConnectStandalone.java:93)
Actually I don't know how to resolve this problem since its my first experience working with both technologies Kafka and IBM MQ And I would really appreciate your help.
Thank you !

I think you already know this, but you're missing the MQ connector JAR from the classpath. You can see that the class "com.ibm.mq.kafkaconnect.MQSourceConnector" isn't found, so you need to build the MQ connector JAR and make sure that Java picks it up. Your Docker container will certainly be getting the Kafka Connect JARs from a directory so you could potentially build an image including the MQ connector JAR using an instruction in your Dockerfile.

Thank you for your quick answer. I will give you my feedback after trying your proposed solution !

Are you still getting the original error message which was "Failed to find any class that implements Connector and which name
matches com.ibm.mq.kafkaconnect.MQSourceConnector"?

Yes unfortunately I still get the same issue.

My suggestion is to double-check that the JAR files for the built-in connectors are in the same directory as the MQ connector you built. My guess is that they are not. You can see in the output that a bunch of connectors are known:
org.apache.kafka.connect.source.SourceConnector,
org.apache.kafka.connect.tools.MockSinkConnector, org.apache.kafka.connect.tools.VerifiableSinkConnector, org.apache.kafka.connect.file.FileStreamSinkConnector,
org.apache.kafka.connect.file.FileStreamSourceConnector, org.apache.kafka.connect.sink.SinkConnector, org.apache.kafka.connect.tools.MockSourceConnector,
org.apache.kafka.connect.tools.SchemaSourceConnector, org.apache.kafka.connect.tools.VerifiableSourceConnector, org.apache.kafka.connect.tools.MockConnector
but the MQ one is not. I expect it's not in the correct directory.


String should not contain control characters.

Right now, strings can for example contain a new line, not an escaped one.
Which will lead to incorrect json generation
Here is my suggestion :
string ::= "\"" (char | escapeSequence)* "\""
char ::= [^"'\\\x7F\x00-\x1F]
escapeSequence ::= "\\\"" | "\\\\" | "\\n" | "\\r" | "\\t" | "\\b" | "\\f"

I could open a PR but I could be missing something so I open an issue to discuss this

I met this issue because on rare cases (15% of generations) i had this kind of json generated :
{"entities": [

{"type": "Geo-Political Entity", "name": "Paris 2024"},
{"type": "Location", "name": "Paris"}],
"relations": [{"type_from": "G',
eographic Feature", "name_from": "Paris", "type_to": "Event", "name_to": "Paris 2024", "relation_type": "occurs_in"}]}

Entering manually \r and \n isn't enough, I ended up with having another control character getting outputed as JSON, which made my json un-usable

Updated it to exclude singlequote

Fixed in #37

🖖🏻


Get started page

I have actually already completed a version of the get-started page. We weren't sure if you were still working on the task and we are in a hurry to complete the mui redesign. I also know we will be starting some new development work in Nemo that you can work on. The entire redesign-1 project branch is here  if you want to take a look. You could also retrofit my implementations if you have better ideas. Go ahead and submit changes against that branch instead.


Update cats-effect, cats-effect-laws to 3.2.4

Updates

org.typelevel:cats-effect
org.typelevel:cats-effect-laws

from 3.2.3 to 3.2.4.
GitHub Release Notes - Version Diff
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

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

labels: library-update, semver-patch

Codecov Report

Merging #537 (923c840) into main (0496eaa) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main     #537   +/-   ##
=======================================
  Coverage   90.10%   90.10%
=======================================
  Files          15       15
  Lines         758      758
  Branches       43       43
=======================================
  Hits          683      683
  Misses         75       75

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 0496eaa...923c840. Read the comment docs.

Superseded by #538.


feat: add operation for variable in ListVariables

1. Does this PR affect any open issues?(Y/N) and add issue references (e.g. "fix #123", "re #123".):

[x] N
[ ] Y

2. What is the scope of this PR (e.g. component or file name):

3. Provide a description of the PR(e.g. more details, effects, motivations or doc link):

[x] Affects user behaviors
[ ] Contains syntax changes
[ ] Contains variable changes
[ ] Contains experimental features
[ ] Performance regression: Consumes more CPU
[ ] Performance regression: Consumes more Memory
[ ] Other

4. Are there any breaking changes?(Y/N) and describe the breaking changes(e.g. more details, motivations or doc link):

[x] N
[ ] Y

5. Are there test cases for these changes?(Y/N) select and add more details, references or doc links:

[x] Unit test
[ ] Integration test
[ ] Benchmark (add benchmark stats below)
[ ] Manual test (add detailed scripts or steps below)
[ ] Other

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

87 of 92 (94.57%)  changed or added relevant lines in 3 files are covered.
1 unchanged line in 1 file lost coverage.
Overall coverage increased (+0.01%) to 71.376%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

kclvm/query/src/selector.rs
32
37
86.49%

Files with Coverage Reduction
New Missed Lines
%

kclvm/query/src/selector.rs
1
82.18%

Totals

Change from base Build<PHONE_NUMBER>:
0.01%

Covered Lines:
52924

Relevant Lines:
74148

💛  - Coveralls


Initializers with the same seed produce different output in Keras 2.7

System information.

Have I written custom code (as opposed to using a stock example script provided in Keras): yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): 2.7.0rc1
Python version: 3.8
Bazel version (if compiling from source): N/A
GPU model and memory: N/A
Exact command to reproduce:

import numpy as np
import tensorflow as tf

init0 = tf.keras.initializers.RandomUniform(seed=0)
w0 = init0((2, 2))

init1 = tf.keras.initializers.RandomUniform(seed=0)
w1 = init1((2, 2))

print(w0)
print(w1)

assert np.allclose(w0, w1)

Describe the problem.
As far as I understand it, initializers with the same seed should produce the same output. This is how they behaved prior to 2.7. But now passing the same seed to two different initializer instances does not make them produce the same output.
This is likely related to this change mentioned in the TF release notes:

RNG behavior change for all tf.keras.initializers classes. For any class constructed with a fixed seed, it will no longer generate same value when invoked multiple times. Instead, it will return different value, but a determinisitic sequence. This change will make the initialize behavior align between v1 and v2.

However, that seems to suggest that if I create an initializer with a fixed seed, it will always produce the same sequence of numbers (x0 -> x1 -> x2 -> ...). That is not the behaviour observed here; creating two different classes, with the same seed, produces two different sequences. The first class produces x0 -> x1 -> x2 -> ..., but the second produces y0 -> y1 -> y2 -> ....
Describe the current behavior.
Initializers created with the same seed produce different output.
Describe the expected behavior.
Initializers created with the same seed should produce the same output.
Contributing.

Do you want to contribute a PR? (yes/no): no
If yes, please read this page for instructions
Briefly describe your candidate solution(if contributing):

Standalone code to reproduce the issue.
https://gist.github.com/drasmuss/212686552bc5f36a7cd23229f9dc4477

I was able to replicate issues in TF2.7 and tf-nightly. Please find the gist here. Thanks!

I can reproduce the issue with tf-nightly. However, the following workaround may be helpful. Here is a gist for reference. Thanks
g = tf.random.Generator.from_seed(0)
w0 = g.normal(shape=(2,2))

g1 = tf.random.Generator.from_seed(0)
w1 = g1.normal(shape=(2,2))

print(w0)
print(w1)

tf.Tensor(
[[-1.3544159   0.70454913]
 [ 0.03666191  0.86918795]], shape=(2, 2), dtype=float32)
tf.Tensor(
[[-1.3544159   0.70454913]
 [ 0.03666191  0.86918795]], shape=(2, 2), dtype=float32)

@drasmuss This is working as mentioned in the docs. Please check here. It was mentioned that the initializer will not produce same random values across multiple calls but produces the same sequence.

seed
A Python integer. Used to create random seeds. See tf.compat.v1.set_random_seed for behavior. Note that seeded initializer will not produce same random values across multiple calls, but multiple initializers will produce same sequence when constructed with same seed value.

I ran three times with the seed=0 and verified that the produces the same sequence.
Here is a gist for reference. Thanks!

I don't believe this is working as described in the docs

Note that seeded initializer will not produce same random values across multiple call

This means that if I construct a given Initializer (e.g. init0 = tf.keras.initializers.RandomUniform(seed=0)), and call it multiple times, like
init0 = tf.keras.initializers.RandomUniform(seed=0)
w0 = init0((2, 2))
w1 = init0((2, 2))
w2 = init0((2, 2))

I should expect w0, w1, and w2 to be different. That part is working as expected.

but multiple initializers will produce same sequence when constructed with same seed value.

This is the part that is not working. This says that multiple initializers, with the same seed value, will produce the same sequence. But that is not the case. If I construct a second initializer, and call it multiple times
init1 = tf.keras.initializers.RandomUniform(seed=0)
y0 = init1((2, 2))
y1 = init1((2, 2))
y2 = init1((2, 2))

The documentation says that this initializer should produce the same sequence. I.e., w0 == y0, w1 == y1, and w2 == y2. But that is not the case. The two initializers, despite having the same seed value, produce a different sequence.

@drasmuss Before running init1 = tf.keras.initializers.RandomUniform(seed=0), if you reset the colab runtime, then the sequence is same (i.e. w0 == y0, w1 == y1, and w2 == y2).
In the above, you are not restarting the runtime. May be we need to update the docs to reflect it. Thanks!

If you reset the colab runtime then you effectively just have a single initializer (because resetting gets rid of the previous one). The documentation explicitly says that multiple initializers should produce the same sequence with the same seed. You could adjust the documentation to remove that claim entirely, but that's a pretty significant change in the behaviour.
As a broader point, the benefit of setting the seed to a specific value on an object with randomness is to set that randomness to a reliable, reproducible value.  With the current behaviour, the actual seed value passed doesn't really matter, because all the seed does is fix the RNG to some arbitrary point. For example, consider this code snippet:
w0 = tf.keras.initializers.RandomUniform(seed=0)((2, 2))
w1= tf.keras.initializers.RandomUniform(seed=0)((2, 2))
w2 = tf.keras.initializers.RandomUniform(seed=1)((2, 2))

There is no effective difference here between setting seed=0 and seed=1. In both cases w0 != w1 and w0 != w2. That seems like unexpected behaviour for a seed.
For a more real-world example, consider the case where I want to build a model that has two layers with the same initial weights in each layer. A natural way to go about that would be the following:
import tensorflow as tf

my_model = tf.keras.Sequential(
    [
        tf.keras.layers.Dense(
            2,
            kernel_initializer=tf.keras.initializers.RandomUniform(seed=0),
            input_shape=(2,),
        ),
        tf.keras.layers.Dense(
            2,
            kernel_initializer=tf.keras.initializers.RandomUniform(seed=0),
        ),
    ]
)

my_model.build()
print(my_model.weights)

I think most users would be pretty surprised to find that that their two layers actually have completely different initial weights, even though they explicitly seeded them to the same value.

@qlzh727 could you take a look at this when you have a second?

Let me add @wangpengmit who is the owner of random ops in tf.
Currently it is using stateful random ops under the hood, which might have some relationship with the tf global seed. In 2.8, we will enable the tf.random.Generator for the initializer, which I think will produce the behavior describe in the docstring.

Btw, you can take a look for the example in https://www.tensorflow.org/api_docs/python/tf/random/set_seed. There is actually some behavior details.
In the meantime, you can also try:
import numpy as np
import tensorflow as tf

init0 = tf.keras.initializers.RandomUniform(seed=0)
init0._random_generator._force_generator = True
w0 = init0((2, 2))

init1 = tf.keras.initializers.RandomUniform(seed=0)
init1._random_generator._force_generator = True
w1 = init1((2, 2))

print(w0)
print(w1)

assert np.allclose(w0, w1)

@qlzh727 Depending on the final code change, we also need to update the docs https://www.tensorflow.org/api_docs/python/tf/keras/initializers/RandomUniform

seed
A Python integer. Used to create random seeds. See tf.compat.v1.set_random_seed for behavior. Note that seeded initializer will not produce same random values across multiple calls, but multiple initializers will produce same sequence when constructed with same seed value.

Btw, with the current code, it will also reproduce same result if you have fixed tf.random.seed. It can be removed once have the generator code path turn on by default.
import numpy as np
import tensorflow as tf

tf.random.set_seed(1)
init0 = tf.keras.initializers.RandomUniform(seed=0)
w0 = init0((2, 2))

tf.random.set_seed(1)
init1 = tf.keras.initializers.RandomUniform(seed=0)
w1 = init1((2, 2))

print(w0)
print(w1)

assert np.allclose(w0, w1)

I'd wait until TF 2.8 is released to confirm that the behaviour then matches the docs before closing this, but up to you.

I meet same issue here and have to drop some features and unit test to pass the CI checks related to this issue, in TensorFlow 2.7.0

This is caused by Keras initializers switching to tf.random.uniform in TF 2.7 (as a stop-gap for finally switching to tf.random.Generator or tf.random.stateless_uniform), which hits one of the weird behaviors of tf.random.uniform (the kernel-reusing behavior). As @qlzh727 mentioned, please see https://www.tensorflow.org/api_docs/python/tf/random/set_seed (and search for "kernel" in that page) for detailed explanation.
Calling set_seed fixes it because set_seed clears all kernel caches.

Btw, with the current code, it will also reproduce same result if you have fixed tf.random.seed. It can be removed once have the generator code path turn on by default.
import numpy as np
import tensorflow as tf

tf.random.set_seed(1)
init0 = tf.keras.initializers.RandomUniform(seed=0)
w0 = init0((2, 2))

tf.random.set_seed(1)
init1 = tf.keras.initializers.RandomUniform(seed=0)
w1 = init1((2, 2))

print(w0)
print(w1)

assert np.allclose(w0, w1)

Thank you with this code I was able to get reproducible weights initializaiton in keras models.
I wonder, in order to correctly change the weights initializaiton, is it better to fix the seed in tf.random.set_seed(1) and change the seed in tf.keras.initializers.RandomUniform(seed=0), or viceversa?
Many thanks in advance


tiled: 1.9.2 -> 1.10.0

Description of changes
Update tiled to the latest version and update the repository owner

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.05 Release Notes (or backporting 22.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 221522 run on aarch64-linux 1

1 package built:

tiled

Result of nixpkgs-review pr 221522 run on x86_64-linux 1

1 package built:

tiled

Thank you!


Unable to access ai workflow

Components made before langflow 1.0 possible unstable.

Hey @ishaansoshima
Could you be a bit more specific, please?

Thank you for your contribution! This issue will be closed. If you have any questions or encounter another problem, please open a new issue and we will be ready to assist you.


gitlab: 14.7.1 -> 14.7.2

Motivation for this change
https://about.gitlab.com/releases/2022/02/08/gitlab-14-7-2-released/
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[x] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

trace: warning: The option services.redis.enable' defined in /home/hexa/git/nixos/master/nixos/modules/services/misc/gitlab.nix' has been renamed to `services.redis.servers..enable'.

The tests should be updated as time permits.

The tests should be updated as time permits.

Good point. I'll put that onto my todo list.


half the hashrate of all computers

Hi
Sorry for so many questions, but I let it mining from yesterday to make sure it works well
I had one very important problem
The pc's are completely separated
And it comes back again after a while and the hash rate is zero in more than 40%  from the pc's
I know that it is normal for something like this to happen in general in mining, but here Compared to the previous miner
I'm now getting half the hashrate of all computers
I will attach pictures of the settings

Yes if you could attach an image with the settings that would be good, do you also use 'Remote Configuration'?

Knowing that I do not use idle mining, I already use computers that no one uses

I'm supposed to get about 2300-2600 hashrate, now I'm getting about 1800

Well, first of all: you shouldn't use a password for nanopool since they don't support that. If you want to add a "password" (email) then you should add it into the 'Extra data'  field like so {COMPUTERNAME}/password (and leave 'Worker Name' empty).
Second of all, are you measuring it by --report-hashrate? As in the reported hashrate before and the reported hashrate now? or are you measuring it by actual hashrate?
There hasn't really been any change in the fundamentals of the miner so the hashrate shouldn't really be impacted.

I am measuring it by actual hashrate and Average Hashrate for last 6 hours
Also through rewards
As for the password, is that correct?

Yes that's correct though {COMPUTERNAME} should be all uppercase letters. Are all the computers running? If you go into one of the computer workers and look back into the history does the hashrate change there between versions?

No, it does not change almost the same as before

So which part is the problem? Do you mean that not all computers are mining? The explanation in the initial post was a bit confusing.

I'm sorry, maybe this is because of my bad language
But the actual problem is that I always have about 10 or more offline computers in the pool. Yes, they return to work, but others go offline, and so on.
When I go to each worker history alone , it's almost normal but I can't say for sure
But like all hashrate, that's the problem
I measure it relative to Current Calculated Hashrate
I don't know if this is normal, or the number of devices with the same build is the reason, or should I wait more?
I don't know if this is normal, or the number of devices with the same build is the reason, or should I wait more?🙂

Do all of the computers use the new version or is it mixed between old and new? I don't know how you've set everything up but if some use the old miner and have gone offline forever then they could have become detected due to the new Windows Defender detections they've added which I "bypassed" in the new miner version. I don't know what kind of computers you mine on but if they are computers that people use then I guess they could have found and removed it themselves since you don't use "Stealth" or anything. And if you don't obfuscate the miner already then that is  also a good thing to do https://github.com/UnamSanctam/SilentETHMiner/wiki#how-can-i-decrease-detections

Ok, I'm going to change the build and check all the settings and also make sure that Windows Defender is closed and wait a day or two
I will let you know the results and close  issue if  is fine
I think it will be

i have this issue too recently hashrate halved, @elraiqq if you wanna work together send your telegram or something

https://t.me/fakhrytarek
@boogie888
I will be glad to communicate

Now things are better than before, the problem still exists, but to a limited extent
I think it's because the miners don't match up perfectly with the pool
Of course with most miners when using them with a different pool
And  if I understand correctly, you are dependent on a particular miner, if so give me a link to download it and try it to make sure it is the reason
But in general, things are good and I salute you for your great work

The miner uses my own quite heavily modified version of ethminer (https://github.com/ethereum-mining/ethminer) and there shouldn't really be any problems from what I've noticed in my tests. If things are better now then the rest of the problem might resolve itself over time.

Do you think  if I change the pool to ethermine it will solve the problem
To  clarify the problem, these computers are mining and  vram is used 4.9

Is this a pool problem?

Hmm, it's certainly possible, if they're using VRAM then the miners is working. Have you changed the Max GPU or anything? Nanopool has quite a high share difficulty (10 GH) but it shouldn't take that long between shares even if the hashrate would be really low.

No, I did not change them

Do you use 'Remote Configuration'? And is everything correct there if you do (as in you don't accidentally lowered the Max GPU)?

No i dont use remote
I dont know how to use at all

If you use the 'Remote Configuration' option https://github.com/UnamSanctam/SilentETHMiner/wiki#remote-configuration then you can change the settings of the miners by just changing the text there. You can use any site to host the text but pastebin is the most common one, you create an account and create a new paste (unlisted) with your info there and then input it in the miner as the raw URL like so https://pastebin.com/raw/0aQcym79.

But if those computers are using VRAM then it has connected to the pool and is mining, the weird part is that it says on the screen shot that they haven't sent a share in a long time. Do those computers use the same file as all the other ones?

Yes same one in all

That's weird, are they doing something else that's taking up the GPU usage or something? That's the only thing I can think of unless there is some issue with the pool.

Unfortunately no, and this is very confusing. I know and it has not happened before with nanominer

Hmm yeah I haven't really seen anything like that before either, you could try a pool like flexpool or something to see if there is any difference. I wouldn't recommend ethermine with that many workers since I have seen bans when people have had over 50 workers. I think flexpool is more profitable than nanopool as well since I think flexpool gives a MEV bonus while nanopool does not.

Ok very good I'll wait for the payout and try it
Thank you very much and sorry to bother you

No problem, and you're not bothering me, if there's some issue it would be good to find it. Hope it goes well for you.

Everything has problems and you did an amazing job

Can I contact you to help me with something other than this?

You can try with the new version released and see if there is any difference. If you want to contact me then I have a Discord (although Discord is not very secure to be honest): Unam Sanctam#3135


[Simplified Collect][Taxes] iOS - Taxes - App crashes tapping tax value

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

Version Number: 1.4.54-0
Reproducible in staging?: y
Reproducible in production?: n
Issue reported by: Applause - Internal Team
Action Performed:
Precondition:

User is an admin of Collect workspace.

Open app
Go to Profile > Workspaces > Collect workspace.
Go to Taxes.
Click Add rate.
Click Value.

Expected Result:
Able to add tax value
Actual Result:
App crashes
Workaround:
n/a
Platforms:

Which of our officially supported platforms is this issue occurring on?

[ ] Android: Native
[ ] Android: mWeb Chrome
[x] iOS: Native
[ ] iOS: mWeb Safari
[ ] MacOS: Chrome / Safari
[ ] MacOS: Desktop

Screenshots/Videos
Add any screenshot/video evidence
https://github.com/Expensify/App/assets/93399543/29ca9cf8-8c29-4c07-87bf-094ce672689f
View all open jobs on GitHub

We think that this bug might be related to #wave-control

@francoisl The app crashes when adding the distance rate, do we need to create a separate GH or the same root cause?
https://github.com/Expensify/App/assets/93399543/dfbbdd2c-f715-4b00-bfae-18ec44726711

I can repro on iOS, this seems to come from https://github.com/Expensify/App/pull/37967.

The app crashes when adding the distance rate, do we need to create a separate GH or the same root cause

Not sure yet but it might be a different cause, the PR I linked to is specific to tax rates. Maybe it's safer to open a separate issue for now.

This was introduced https://github.com/Expensify/App/pull/37967. This is NAB since this feature is only available on Collect policies in NewDot and users don't have access to that yet. I think we can address that as a follow up to the other tax PRs. cc @kosmydel @filip-solecki

I am making a revert of that PR, we can just give it another go later knowing these issues

This has been fixed by the revert. Gonna close.


Update everything_config.toml

Signed-off-by: inDane<EMAIL_ADDRESS>

PR description
Additional to #4438
Fixed Issue(s)

Documentation

[ ] I thought about documentation and added the doc-change-required label to this PR if
updates are required.

Changelog

[ ] I thought about the changelog and included a changelog update if required.

Thanks for the submission! There are some unit tests that are failling, once those are passing I will run the rest of the pipeline for you.

This change isn't needed. None of the RocksDBCLIOptions are in that testing config file - it's only used for testing core options. Thanks for your interest in Besu @inDane


improvement(marginfi-v2-docs & marginfi-v2-trading): update arena docs, fix messaging on the arena wallet auth, add sec3 audit

can you rebase your changes on main ? @masterzorgon
looks like something went wrong


Increment version to 0.2.2

Adds support for Wikidata item processing.

I want to merge this once we have resolved a few of the PRs.  Looks like we might include a bunch more language Wikipedia in this version.


HuggingFace RoBERTa with Flash Attention v2

Hi @tridao,
I made an updated version of the HuggingFace RoBERTa implementation using your implementation of flash-attention v2 as a drop-in replacement for the legacy pytorch implementation (https://github.com/iliaschalkidis/flash-roberta).
The drop-in replacement of the self-attention layer is here https://github.com/iliaschalkidis/flash-roberta/blob/1134e3ae8b305bff7f38c08ffd59034e65c68781/modeling_flash_roberta.py#L11-L63
I did some benchmarking with roberta-base on documents from C4 comparing the old (pytorch) and new (flash-attention-v2) implementations for both inference (evaluation):
RoBERTaForMaskedLM
---------------------------------------
Eval time: 395s
Peak memory: 14.35GB
Eval Accuracy:  0.666

FlashRoBERTaForMaskedLM
---------------------------------------
Eval time: 296s
Peak memory: 14.36GB
Eval Accuracy:  0.662

and continued pre-training:
RoBERTaForMaskedLM
---------------------------------------
Train loss: 2.23
Train time: 669s
Peak memory: 4.30GB

FlashRoBERTaForMaskedLM
---------------------------------------
Train loss: 2.23
Train time: 551s
Peak memory: 4.17GB

The improvement speed-wise is approx. 20-30%, while for memory there is no improvement.
Do I miss something because the speed-up is far from the expected one? Thanks!

What's the sequence length? If seqlen=512 then attention doesn't take that much memory (especially if you're just doing eval where the attention matrices aren't saved for backward). And attention probably accounts for only 30-40% of the time (the rest is MLP, etc.). In that case, making attention faster will give around 1.3x speedup, which makes sense.
When attention takes more time proportionally (e.g. when seqlen is large), speeding up attention will give more end-to-end impact.

Unfortunately, these are the number I have for training:
08/01/2023 10:58:33 - INFO - __main__ - Model: RobertaForMaskedLM
08/01/2023 13:10:05 - INFO - __main__ - Train time: 1050.5841448307037
08/01/2023 13:10:05 - INFO - __main__ - Peak memory: 4.308091904GB

08/01/2023 10:58:33 - INFO - __main__ - Model: FlashRobertaForMaskedLM
08/01/2023 11:10:36 - INFO - __main__ - Train time:<PHONE_NUMBER>212708
08/01/2023 11:10:36 - INFO - __main__ - Peak memory: 4.16851456GB

and they are far from the 3x speedup, and 3x memory reduction, as suggested in the Speedup paper figure....

The "speedup" figures are speedup for "attention forward + backward". The network has other components (MLP). If for example attention takes 40% of the total time then speeding up attention by 3x will give 1 / (0.6 + 0.4 / 3) = 1.36x end-to-end speedup.


Test/sto procedures

:tada: This PR is included in version 2.0.1-beta.89 :tada:
The release is available on:

npm package (@beta dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Fix typo in README

Just fixed the link.
(I guess Atlassian broke lots of lives with their pseudo-wiki-markdown markup in Jira.)

Thanks! I was just editing the wiki and confused the syntax :)


OCaml version mismatch when installed via opam

I'm trying to get the following working together: Reason ML, NVIM, ALE, Merlin.
Merlin had issues because its install (via opam) wasn't the same version as the reason-cli.  I uninstalled the npm reason package and did a opam install reason instead.  My application still seems to run properly, but now I'm getting warnings from ALE and Merlin that the OCaml versions don't match:
src/index.re|1 warning| ~/Code/reason-react/lib/bs/src/app.cmi is not a compiled interface for this version of OCaml. It seems to be for an older version of OCaml.

Is there another approach I should take to get Merlin working for Vim and Reason?
Thanks!

We do not recommend using both opam and npm (reason-cli) simultaneously. If you're using opam I assume you're building a native app?

@dfalling Can you describe your project? Reason works with opam, and merlin. Or it works with npm and merlin. It depends on the kind of project you are building though. Is it a webapp or a native app? What are your dependencies?

@jordwalke right now there's not much to my project- I used reason-scripts to setup a React app and haven't felt the need to eject yet.  I'm using ALE for error display in VIM and their docs pointed me towards setting up Merlin via opam to get vim working.  This did fix my setup except for that version mismatch I pasted.

I've looked through the merlin source and it doesn't look like there's a way to disable that error. The only option is to install the right base switch version - you can check what version bsb is using in bsb-native/vendor/ocaml/lib/ocaml/VERSION.
The most annoying part of the error for me is that ALE moves the cursor back one character whenever merlin produces that warning. It may be worth filing an issue about that.

Whoops, totally forgot about this ticket.  So my current working solution is ALE with ale_reasonml_refmt_executable set to use bsrefmt.  This requires installing npm i -g bs-platform sadly, so I have to make sure any time I update the bs-platform in my project, I also bump it globally.  Fortunately I only have one Reason project so I don't have any conflicts.
Any objections to my closing this ticket since I've found a workaround?

Nope, that makes sense :+1:


Recursive support for captioning/tagging scripts

Hi! Thanks for the good work as always.
In this PR, I want to propose some small changes, mostly about recursive support for captioning/tagging scripts so users can annotate their dataset recursively. However, I am not sure if it is implemented correctly, so I hope for your review to make it better.
For recursive args, I borrowed glob_images_pathlib() from train_util.

tag_images_by_wd14_tagger.py

Added --recursive to find and preprocess datasets inside sub-directories.
Added --remove_underscore args.
Added --undesired_tags, so users can delete undesired tags from the tagging process.
Added character tags (category = 4) as well as --character_threshold. I don't know if it's a good idea, but I think it might be helpful for character training. SmilingWolf released SmilingWolf/wd-v1-4-convnextv2-tagger-v2, and I think it's a great and up-to-date model for character tagging.
Renamed --thresh to --general_threshold.
Added --frequency_tags to print tag frequency after the tagging process is done.
Due to character tags added, I updated how --debug works with the following new template:

    {image_path}
    Character Tags = {character_tags}
    General Tags = {general_tags}

make_captions_by_git.py

Added --recursive to find and preprocess datasets inside sub-directories.

make_captions.py

Added --recursive to find and preprocess datasets inside sub-directories.

prepare_buckets_latents.py

Added --recursive to find and preprocess datasets inside sub-directories. I thought it was already covered by --full_path, but it cannot preprocess datasets inside sub-directories and make latents of them. It might not be useful for multi-concept training, but I think it's useful for multi-directories training. So users can keep the datasets inside the respective folder and preprocess them without needing to re-run the scripts every time.

convert_diffusers20_original_sd.py

It might be a QoL rather than a new change, but I added --save_precision_as with choices of ["fp16", "bf16", "float"].

Thank you!

I'm sorry for the late reply, and thanks for the merge!
I forgot emoji tags exists 😅
Also I'm sorry but I cant use my pc right now for an hour or two
How about using the same clean_tags_and_captions.py approach? Like this:
  tags = tags.replace('^_^', '^@@@^')
  tags = tags.replace('_', ' ')
  tags = tags.replace('^@@@^', '^_^')


pygame (run_closed_loop) often requires SDL_VIDEODRIVER=windows in Windows

[x] I have searched the issues of this repo and believe that this is not a duplicate.

Issue
After following the installation instructions and attempting to run_closed_loop, I am faced with the error that pygame cannot load directx. It's worth mentioning in the documentation that a simple fix for this problem is to first run set SDL_VIDEODRIVER=windows

FYI, here is the exact error:


Warn whenever an invalid config is loaded

Summary
At the moment, you need to manually validate the config but we should probably warn you whenever an invalid config is detected.
Questions for reviewers

Should we always warn or only if --verbose is requested?
Is the error we print too verbose? If so, we could print only the first line of the message instead.

WARNING:root:The config file is invalid:
{'a': 'b'} is not of type 'array'
_
Failed validating 'type' in schema['properties']['tables']['patternProperties']['.*']['properties']['row_generators']['items']['properties']['args']:
{'type': 'array'}
_
On instance['tables']['tkeys']['row_generators'][0]['args']:
{'a': 'b'}

Maybe print the extra information with --verbose and by default just have the one-liner?

I switched to only printing the short form regardless of --verbose as users can always use the separate validate-config command and the long-form message overwhelmed any other output.


Is there a way to print parsing errors?

Right now the raml2html returns either 0 or 1 exit status, that alerts you of a present error in the markup. Thoigh, I didn't find any options to show the actual errors (lines with parsing errors would be great as a start) - is there a way to enable it?

Btw, I am using pyCharm (intellij Idea basically) with yaml plug-in, so finding errors is really difficult :)

@DataGreed have you looked at API Workbench (http://apiworkbench.com/).  Uses the Atom editor. I have found good results with it. Especially when validating syntax.

@ericjsilva thank you for the reply. I've found out that if the parsing fails the exception output is being written to output file. So, I've just added a script that checks the file and if it contains less than 10 lines, it just prints it out on the console, so I know that it's an error :)

@ericjsilva wow, workbench looks good, though. Thanks you!

2.2.0 is now printing errors to STDERR, can you check if that helps?

Can confirm errors print nicely for the latest version on Debian.


Update README.md

INVOICE api video link added

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


Assignments not aligned when using bit_set

Incorrect
rtv_desc := d3d12.DESCRIPTOR_HEAP_DESC {
  Type = .RTV,
  NumDescriptors = BACK_BUFFER_COUNT,
  Flags = {.SHADER_VISIBLE},
}

Now without Flags = {.SHADER_VISIBLE},
rtv_desc := d3d12.DESCRIPTOR_HEAP_DESC {
  Type           = .RTV,
  NumDescriptors = BACK_BUFFER_COUNT,
}

The consecutive assignments inside the initializer are no longer aligned.

Here's another repo

Foo :: struct {
	A:     string,
	BBB:   string,
	CCCCC: Bar,
	DD:    Baz,
	EEEE:  int,
}

Bar :: struct {
	A:   string,
	BBB: string,
}

Baz :: bit_set[BazFlag]
BazFlag :: enum {
	A,
	B,
	C,
}

main :: proc() {
	foo := Foo {
		A    = "foo",
		BBB  = "bar",
		EEEE = 42,
	}

	bar := Foo {
		A = "foo",
		BBB = "bar",
		CCCCC = Bar{},
	}

	bar := Foo {
		A = "foo",
		BBB = "bar",
		D = {},
	}
}

The alignment of consecutive assignments within the aggregate initializer changes to unaligned when there's a nested bracket of some sort. Is this intentional or unwarranted?

The aggregate initializer currently disables alignment, because I'm worried of having to align stuff like this:
baz := Foo {
	A = "foo",
	BBB = "bar",
	DD = {
             my_value = 123123
        },
}

It's both quite hard to align this correctly. There could even more than just one nest of braces. But in your example there is no named assignments in the aggregate initializer, so it could be possible to have it align anyway for that case.

Yeah, I think it should be consistent. Either align assignments or not but don't change the behavior.
I've done plenty of compiler work in my days and I could give this a shot.

I have now switched it so the bitsets get aligned.


Problem in the preprocessing function while defining the serving_default signature for a model in a community notebook

Problem
In the section Deployment > Upload the model for serving > Serving function for image data of this notebook, the preprocess function is defined as,
def _preprocess(bytes_input):
    decoded = tf.io.decode_jpeg(bytes_input, channels=3)
    decoded = tf.image.convert_image_dtype(decoded, tf.float32)
    resized = tf.image.resize(decoded, size=(32, 32))
    rescale = tf.cast(resized / 255.0, tf.float32)
    return rescale

For this, the author has written,

resized / 255.0 - Rescales (normalization) the pixel data between 0 and 1.

But if we check the working of tf.image.convert_image_dtype as per the current TensorFlow version 2.7.0, we see that this function not only converts the dtype, but also normalizes/rescales the image according to the target dtype.
In the documentation, it is mentioned,

Images that are represented using floating-point values are expected to have values in the range [0,1). Image data stored in integer data types are expected to have values in the range [0, MAX], where MAX is the largest positive representable number for the data type.

This means that while converting to tf.float32 it also normalizes the decoded image in the range [0,1]. Therefore, the line rescale = tf.cast(resized / 255.0, tf.float32) must be omitted.
Specifications

Version: Tensorflow Version: 2.7.0

From TF 2.5 on, the automatic scaling is correct (as noted by the issue poster). For TF 2.4 and earlier documentation, it is vague.


Feature/support new tokenized api

added documentation for Bkash apis and optional parameter for printing responses

@rdnasim Please Test and merge this branch.

InshaAllah, I will merge it. I will be free this weekend.


Composer problems

During installation, the installer no longer recommends to install composer.

Launching the composer installation return:

$ php composer.phar install

Loading composer repositories with package information
Updating dependencies (including require-dev)
Your requirements could not be resolved to an installable set of packages.

  Problem 1
    - The requested package annularis/bitcoin-lib could not be found in any version, there may be a typo in the package name.

Potential causes:
 - A typo in the package name
 - The package is not available in a stable-enough version according to your minimum-stability setting
   see <https://getcomposer.org/doc/04-schema.md#minimum-stability> for more details.

Read <https://getcomposer.org/doc/articles/troubleshooting.md> for further common problems.

Returning to old composer.json (pre "big commit") does not resolve.

I know, cause bitwasp devs deleted repos

Can we rebuild it under Annularis repo ?

Damn, I was getting started working on this and dang :( Were can we get these repos?

Currently they are already set on vendor folder

@serhack ah yes I saw. Getting the same error on build btw

@jvli0 I should have resolved the missing dependency issue, I launched a commit a few minutes ago, I'm waiting for @serhack to check and to validate the commit.

@danfossi that sounds great. tried to mount your fork but getting the same error. Debian 9.2.

@jvli0 Can you try again?

I've resumed the test with the official repository, I confirm that after the last commit the application works well both on Debian 9.2 and CentOS 7.4, no more composer problems!!

@danfossi Thanks guys! I am still having the same issue...
No composer.json in current directory, do you want to use the one at /root/mark? [Y,n]? y
Do not run Composer as root/super user! See https://getcomposer.org/root for details
Loading composer repositories with package information
Updating dependencies (including require-dev)
Your requirements could not be resolved to an installable set of packages.

  Problem 1
    - The requested package annularis/bitcoin-lib could not be found in any version, there may be a typo in the package name.

Potential causes:
 - A typo in the package name
 - The package is not available in a stable-enough version according to your minimum-stability setting
   see <https://getcomposer.org/doc/04-schema.md#minimum-stability> for more details.

Read <https://getcomposer.org/doc/articles/troubleshooting.md> for further common problems.
root@vultr:~/mark/install#

No longer need to install the composer!

@danfossi sent you and @serhack an e-mail :)


Update default $package_gpg_key to https

It is dangerous to not use https for importing gpg keys
from web sources. This shoud be https and not http.
Signed-off-by: Jordan Conway<EMAIL_ADDRESS>

Updated with passing tests.


add --progress=dot:giga to alpine images

The default busybox version of wget now supports --progress=dot:giga. This makes the install step consistent with the other distros

Not gonna lie, this got my hopes up so high (and then I saw the failing CI) :joy:

Not gonna lie, this got my hopes up so high (and then I saw the failing CI) :joy:

Sorry @tianon I was excited too when I got it working locally but realised I'd installed wget with apk add wget so was no longer using the busybox version.


[DRAFT] removes references to deprecated APIs

This PR adopts newer APIs introduced in the last few dot release of QuPath v0.4+
When https://github.com/qupath/qupath/pull/1286 is merged, I intend to update build.gradle to bump QuPath dependency version too

Hello @carlocastoldi and thanks a lot for this very technical digging - that bug looked quite painful...
Just to be clear: is this PR fixing the bug on its own ? Or do you need https://github.com/qupath/qupath/pull/1286 to be merged as well ?

Hello!
No, this PR is actually unrelated to #11. Issue #11 will be fixed when the QuPath PR is merged!


The option CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE blocks k_sleep when CONFIG_PM is enabled

Describe the bug
If CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE and CONFIG_PM options are enabled together then k_sleep does not return.
According to documentation only uptime can be affected by enabling CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE option.
Platform is STM32WB55 Nucleo development board.
For blinky sample when CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE and CONFIG_PM options are set then LED is turn on all the time.
Without CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE option LED blinking is seen as expected.
Adding a few printk revealed that there is no code executed after call to k_msleep.
To Reproduce
Steps to reproduce the behavior:
Build simple blinky application with CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE and CONFIG_PM options enabled.
Expected behavior
The CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE should have no effect on sleep functionality..
Impact
annoyance
Logs and console output
Environment (please complete the following information):

OS: Linux
Toolchain Zephyr SDK 0.13.1
Commit SHA f92542ecf3e465861ae63fc05932fb229b527801

Additional context
Maybe it is a problem with following line in the next_timeout (in timeout.c) - it looks that ret will be always equal to -1 when CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE is set:
	int32_t ret = to == NULL ? MAX_WAIT
		: CLAMP(to->dticks - ticks_elapsed, 0, MAX_WAIT);

It looks that changing second MAX_WAIT to INT32_MAX makes problem gone:
	int32_t ret = to == NULL ? MAX_WAIT
		: CLAMP(to->dticks - ticks_elapsed, 0, INT32_MAX);

@andyross Any chance to look at this - at first glance it looks as simple CLAMP parameter bug (upper bounding is less than lower bounding).

I would be happy to help fixing that but I have one doubt.
My understanding was that the CLAMP we talking about handles the case where there is requested a real timeout (system has something on the list waiting for timeout).
And then in this case a CLAMP is supposed only to limit timeout value to be in result type (int32_t) range.
Am I right? If not then where is the error in my reasoning?

The logic there is supposed to be "the next timeout is the time in the future of the next item on the list, UNLESS it is negative[1] or longer than we can represent".  If all the inputs were positive, the CLAMP() macro would be exactly what we want. But that breaks because K_TICKS_FOREVER happens (for good reason) to have a negative value even though it's being used as MAX_WAIT (i.e. the largest possible value).
[1] Which can happen due to very late interrupts.

@andyross I am sorry I need to rise again topic about CLAMP role in the code under investigation.
I analysed again timeout.c and I really cannot find any place where dticks field can get value equal to K_FOREVER .
All assignments to dticks are always positive integers.
It means that in the following code we need CLAMP only to protect against late interrupts (to->dticks - ticks_elapsed expression has value lower than 0).
int32_t ret = to == NULL ? MAX_WAIT : CLAMP(to->dticks - ticks_elapsed, 0, INT32_MAX);

It means also that the only case when next_timeout will return K_FOREVER  is when timeout_list list is empty what is handled by the condition and true parts of the above conditional operator.

Removed @ceolin  as this is expected to be an issue with scheduler/timing.

Actually, @ceolin  will take the lead on this issue.

Ok, if I understood correctly we should still return MAX_WAIT in situations where the next timeout is longer than we can represent (INT_MAX). The problem with the current code is that when CONFIG_SYSTEM_CLOCK_SLOPPY_IDLE is set, MAX_WAIT will be K_TICKS_FOREVER that is a negative number so CLAMP will end up always returning MAX_WAIT
CLAMP(val, low, high) (((val) <= (low)) ? (low) : MIN(val, high))

because in MIN(val, high)  the high value is a negative number. I think it can be solved in the following way:
	if ((to == NULL) ||
	    ((int64_t)(to->dticks - ticks_elapsed) > (int64_t)INT_MAX)) {
		ret = MAX_WAIT;
	} else {
		ret = MAX(0, to->dticks - ticks_elapsed);
	}

Thanks @ceolin for picking it up. I am not sure for this: "...we should still return MAX_WAIT in situations where the next timeout is longer than we can represent (INT_MAX)..." IMO timer should be disabled only if there is no waiting nodes on timeout list. If system has at least one node on the timeout list then we should never disable system timer, even if the requested timeout is bigger than we can pass to system timer. In the latter case we can just "split" timeout to smaller chunks with values acceptable for system timer.

I tend to agree with it, but that is design decision IMHO. It seems that the deired behavior is that one described. I think that patch solves the problem of the system going to sleep with K_TICKS_FOREVER for any timeout when these options are enabled.
What do you think to open another issue / teature request to discuss this new proposed behavior ?

Nope, it is ok for me just a nit.


Add info tooltips next to properties

Resolves L2B-2734
Please double-check the Relayer description, currently ported one similar to LayerZero's explanation.

@michalsidzej rslvd


Messages not logging in one environment but are in another

I have an application with multiple environments in Heroku. Both of them use the production rails environment. I have a Sidekiq job that starts like this:
module Workers
  module Slack
    class NewOrders
      include Sidekiq::Worker
      include SemanticLogger::Loggable
      extend Memoist

      def initialize
        @slack_client = default_slack_client
      end

      # :reek:ControlParameter
      def perform(client: nil)
        logger.info "Checking for new orders since #{since} ..."
        @slack_client = client if client
        send_notifications(since: since)
        update_last_query_time
      end

In one environment (staging), I see the output in the Heroku logs. However, in the other environment (production), I am not seeing the output.
I have confirmed that my default_level is set to :trace in both environments. Here is my initializer:
require 'semantic_logger'

SemanticLogger.default_level = :trace
SemanticLogger.add_appender(io: $stdout) if Figaro.env.heroku_app_name

How come the logs are not appearing in production?

If you are running Rails it is recommended to use the rails_semantic_logger gem to take care of logging connectivity.
In the above code the if statement should be removed if you want to log output to stdout. If it returns false there will not be any logging.

Please re-open the ticket with further information, or post questions in the gitter support channel  if you are still experiencing difficulties.


Add optimized prediction

Optimized prediction as per Neil “haste” Toronto's unlagged mod, with some tweaks and fixes from ET: Legacy. Enabled by default, this basically has no "visible" difference to clients (it doesn't change at all on how various parts of prediction work) but simply has a performance benefit - CG_PredictPlayerState uses ~5x less CPU time per frame (down from ~5.1% to <1%).

There are some issues with this with pmove_fixed 1 that need to be resolved before this can be merged.

Everything seems okay with this, will do some additional testing later to validate few cases that I haven't yet tested.


[DO NOT MERGE] testing github actions for master PRs with newest commits

PR checklist

[ ] This comment contains a description of changes (with reason).
[ ] If you've fixed a bug or added code that should be tested, add tests!
[ ] If you've added a new tool - have you followed the pipeline conventions in the contribution docs
[ ] If necessary, also make a PR on the nf-core/rangeland branch on the nf-core/test-datasets repository.
[ ] Make sure your code lints (nf-core pipelines lint).
[ ] Ensure the test suite passes (nextflow run . -profile test,docker --outdir <OUTDIR>).
[ ] Check for unexpected warnings in debug mode (nextflow run . -profile debug,test,docker --outdir <OUTDIR>).
[ ] Usage Documentation in docs/usage.md is updated.
[ ] Output Documentation in docs/output.md is updated.
[ ] CHANGELOG.md is updated.
[ ] README.md is updated (including new tool citations and authors/contributors).

Test of interest succeeded.


Say to pass private registry as env variable in air gap install

This PR corresponds to this issue: https://github.com/rancher/docs/issues/1643

LGTM


SqlDataAdapter batch update of datetime2 column incorrectly throws SqlTypeException

Description
I'm using SqlDataAdapter to update two rows with UpdateBatchSize set to 2. Each row contains a datetime2 column with a value of 0001-01-01. An exception is raised:
System.Data.SqlTypes.SqlTypeException: 'SqlDateTime overflow. Must be between 1/1/1753 12:00:00 AM and 12/31/9999 11:59:59 PM.'
using (SqlDataAdapter adapter = new SqlDataAdapter())
{
  adapter.UpdateCommand = new SqlCommand("UPDATE DateTest SET DateValue = @DateValue", connection);
  adapter.UpdateCommand.Parameters.Add(new SqlParameter("@DateValue", SqlDbType.DateTime2, 0, "DateValue"));
  adapter.UpdateCommand.UpdatedRowSource = UpdateRowSource.None;
  adapter.UpdateBatchSize = 2;
  adapter.Update(new DataRow[] { row, row2 });
}

The datetime2 value can handle the '0001-01-01' date but the runtime is incorrectly checking the value against a datetime type's range.
Setting the SqlDataAdapter.UpdateBatchSize to 1 works correctly as does passing a single row to the Update method
Simple demo: https://gist.github.com/aaronchch/fe2c1018f62a45f48c4c1552967aa2f8

Configuration
.NET 5.0, System.Data.SqlClient 4.8.2, Win 10

Regression?
Yes. Worked in .NET Framework 3.5 and 4.7.2

@aaronchch Have you tried Microsoft.Data.SqlClient 2.1.2 ?

I tried the test project with Microsoft.Data.SqlClient 2.1.2 and it worked fine.


Added pubsub routing quickstart

Description
Adding the quickstart that was demoed in the 9/21/2021 community call. Will also link to this quickstart from the howto.
Checklist

[x] The quickstart code compiles correctly
[x] You've tested new builds of the quickstart if you changed quickstart code
[x] You've updated the quickstart's README if necessary

/cc @greenie-msft @orizohar @willtsai Thoughts on this new quick start?

Better located in samples?

Per offline convo w/ @orizohar, closing this PR and creating it in dapr/samples instead.


Sigstore signature validation and copying

I've noticed that this project is using skopeo to copy images, that's very cool!
Would be great if this project supported validating and copying sigstore signatures as well.
Skopeo utilizes this config format to validate images: https://github.com/containers/image/blob/main/docs/containers-policy.json.5.md
It can be instructed to look at signatures using this config format: https://github.com/containers/image/blob/main/docs/containers-registries.d.5.md#individual-configuration-sections
Ideally one should be able to pass the necessary configuration files to skopeo by allowing for custom skopeo args to be configured.

@reegnz Thanks. FYI There is currently a PR (#497) to remove the skopeo dependency and handle image pulling natively. This will use the same libraries as skopeo, so it should still be possible to use above.


Merge main to live 2/29/24

This pull request primarily introduces new issue templates for bug reports and feature requests, and updates the feedback product URL in the docfx.json file. The new templates will standardize the way issues are reported and feature requests are made, improving the overall project management process.
New issue templates:

.github/ISSUE_TEMPLATE/bug_report.md: Added a new bug report template that provides a structured format for users to describe the bug, steps to reproduce it, expected behavior, and any additional context or screenshots.
.github/ISSUE_TEMPLATE/feature_request.md: Added a new feature request template that allows users to describe the problem, the desired solution, any alternatives considered, and any additional context or screenshots.

Configuration updates:

community-content/docfx.json: Updated the feedback product URL to direct users to the new issue creation page on GitHub.

#sign-off


[logstash] upload chart to repository so it can be used

I'd like to start working with the logstash chart but it seems it hasn't been uploaded yet. Thanks!
helm up
...

helm search elastic/
NAME                    CHART VERSION   APP VERSION     DESCRIPTION
elastic/elasticsearch   7.4.1           7.4.1           Official Elastic helm chart for Elasticsearch
elastic/filebeat        7.4.1           7.4.1           Official Elastic helm chart for Filebeat
elastic/kibana          7.4.1           7.4.1           Official Elastic helm chart for Kibana
elastic/metricbeat      7.4.1           7.4.1           Official Elastic helm chart for Metricbeat

@travisghansen, I'm sorry Logstash hasn't been released to our Helm repository yet, see more details in #333 (comment)).
Meanwhile I've updated the doc in #364 to provide instruction to use the chart from master branch.
Closing the issue as duplicate of #353.


Encode problem with chinese description

Hey @sorrycc, thank you for reporting us that. It's actually a bug in the underlying database we're using to feed the the Algolia index :/ I'll close this one since it's a duplicate of https://github.com/algolia/github-awesome-autocomplete/issues/10


Add a couple more ELF types

r? @alexcrichton
(rust_highfive has picked a reviewer for you, use r? to override)

@bors: r+

:pushpin: Commit 0f461200d4ec2b6309c4d4daf37e1bd537148591 has been approved by alexcrichton

:hourglass: Testing commit 0f461200d4ec2b6309c4d4daf37e1bd537148591 with merge 63eb3b7a2f43e77e3eb6aafbfd4a66e1ccb011ec...


Not convert to string

Good day! Thank you for awesome work. Love to use lighterhtml with state, actions, view model. I am trying to inject html content from save place but it get stringify by default right? Example
const articleHtml = article => html`

			${article.title}

${article.text}

		     <button data-id="${article.id}" onclick=${actions.edit} class="btn btn-inverted"></button>

`;

Article text is a html content and i want to get it as html and not string. Thanks in advance!

Oh, found an answer. In your comment. Again thanks.
${{html: article.text}}

Just be sure your output is sanitized/safe/no XSS prone 😉


feat: Introduce activationThreshold/minMetricValue for Cassandra Scaler

Signed-off-by: Jorge Turrado<EMAIL_ADDRESS>
Provide a description of what has been changed
Checklist

[x] Commits are signed with Developer Certificate of Origin (DCO - learn more)
[x] Tests have been added

Related to https://github.com/kedacore/keda/issues/2800
Related to https://github.com/kedacore/keda-docs/pull/811

/run-e2e cassandra*

/run-e2e cassandra*


Problems with Pull Request

Hi everyone, I need help, I changed the "while" tab in the csharp folder and I did not see in the guide that I would have to create a branch to send the changes in a pull request, the photo is below, how can I cancel these changes and create a branch? I apologize for my mistake.

Hi @jovsantos, the issue tracker is for bug reporting. Please use the Gitter Contributors Chatroom instead.


OperationException(linkException: ServerException(originalException: HandshakeException: Connection terminated during handshake, originalStackTrace: , parsedResponse: null), graphqlErrors: [])

HI.
On simulators work fine, but I have this issue on physical Android 12, lower physical  versions of android work fine too
OperationException(linkException: ServerException(originalException: HandshakeException: Connection terminated during handshake, originalStackTrace: , parsedResponse: null), graphqlErrors: [])
I checked my AndroidManifest and is fine, Also I test with http package and work fine.

android:name=".MainActivity"
android:exported="true"
I'll appreciate your help.

This need a way that I can reproduce it sorry.
Could you try to make a reproducer repo?

Hi, Shure.
You can see there: https://github.com/fnoceda/flutter_test_rick_and_morty
With Android 12 always have a broken in the line
throw createError(response, "Failed host lookup: '$host'"); in socket_patch.dart file in line 501
with lower version I have the same error and
throw ServerException(
originalException: e,
originalStackTrace: stackTrace,
parsedResponse: null,
);
in link.dart at line 134 also on
final httpResponse = await _executeRequest(request);
at line 76, before that, the result is null
In android 12 the result its fine
I cant see the problem.
thanks a lot for your help

Hello, I solve my problem upgrading Flutter version at
Flutter 3.10.1 • channel stable • https://github.com/flutter/flutter.git
Framework • revision d3d8effc68 (9 days ago) • 2023-05-16 17:59:05 -0700
Engine • revision b4fb11214d
Tools • Dart 3.0.1 • DevTools 2.23.1
Thanks a lot for your help.

Issue still persisting.
At certain point any request going to anywhere result in lookup failed whatever the domain is. Very arbitrary issue hard to replicate and still happens .
4 major ones:

Lookup failed
Software caused connection abort
Handshake failed
Connection reset

Out of all digging found the issue in the package itself.
Need input on replication.


backup-n-restore in S3 with custom CA

Backup'n restore should work for S3 storage serving a custom certificate

To achieve ths velero has to run with cacert bundle.  CA bundle then must be supplied at velero installation (I would say from oadp-operator).

Closing since now is tracked in the backlog https://github.com/open-cluster-management/backlog/issues/16313


Move cleaned pages into read cache instead of discarding them.

Just after dirty pages have been written out to disk, they are currently discard and need to be read in again when these pages are accessed in the future.
This changes moves them into the read cache instead thereby keeping the clean data available and cache hot in memory.
It turned out that this was also what was making direct I/O slower in #808, i.e. this was not that noticeable when buffered I/O is use because the pages were read back in from the kernel page cache most of the time but it should be a win in both scenarios.

The intermediate fuzzer failure was me trying to be clever and avoid reference count bump by Option::takeing the buffers out of the write cache but that was not so clever if one of the intermediate writes would fail, I would never call clear and leave the empty buffers in place for the next flush or another call to write to assert on them. Should be fixed now.

The intermediate fuzzer failure was me trying to be clever and avoid reference count bump by Option::takeing the buffers out of the write cache but that was not so clever if one of the intermediate writes would fail, I would never call clear and leave the empty buffers in place for the next flush or another call to write to assert on them. Should be fixed now.

Turns out I can avoid that atomic reference count bump, but I think it is safer to just do this in two passes in any case.

Merged. Thanks!


fix Monaco local imports

https://github.com/concrete-utopia/utopia/blob/06b3eda5da965b481a0a3e565fd647226494cb5f/editor/src/components/code-editor/monaco-wrapper.tsx#L354
This seems to be incorrect as the project files are tree-shaped now.
Conversation on slack: https://paradise-engineering.slack.com/archives/C1VLFSW0H/p1605258616036300

I fixed this one case here, but after testing the local import autocomplete it's still almost not working and buggy, so I will keep this ticket around

monaco-wrapper.tsx is no more. Before I close this: @balazsbajorics we still have this in npm-dependency.tsx - should I remove the comment? Create a new todo?

I think it's best if you leave it as is, changing it would just destroy the context provided by git blame

👍 . Closing this ticket.


StrongTypeSystemImpl.isAssignableTo returns wrong result in one case

The type system implementation of isAssignableTo is broken in the case where the first argument is Set<Null> and the second argument is a type parameter T whose bound is something like Set<int>. (The class Set can be replaced by anything, and the type int can be replaced by anything other than Null.)
This is blocking #35120.

@lrhn I originally opened this issue because I thought this was a bug in analyzer that was preventing some of the set literal tests from passing (set_literal_test.dart and const_set_literal_test.dart). If Mike is right, then I think that some portions of those two tests are invalid.

@MichaelRFairhurst is right, knowing only T <: Set<int> we cannot prove Set<Null> <: T. You could think of the subtype universe as a layered structure: Set<Null> is at the bottom of the layer which contains all the types of the form Set<S>, but we may have additional layers below, such as HashSet<_>. Of course, you could also use a layer which is always available: C<Null>; with that, you'd need Set<Null> <: Null and that won't fly, either.
You could have other subtypes with a bound: <S extends T>() {/* S is a subtype of T here */}, but otherwise we have no other lower bounds for a type variable than Null.

I agree that there is a problem with the tests. Similar tests worked for double literals, so I copied them, but those tests didn't get into generics.
It's true that S declared as <S extends Set<num>> does not allow Set<Null> to be assigned to it, and hence it does not introduce a set literal.
That's probably a good thing. The expression S x = {}; has no good element type that we can infer for the set. If we use num, then it's a run-time error if S is actually Set<int> at run-time (which it very well may be). So, we can't safely make it a set, so it should be an error. It's annoying that it becomes a " Map<dynamic,dynamic> is not assignable to S extends Set<num> error, but for now I think we will live with that.
We could change the rules to, say, make the empty-set/map-literal a set if there exists some type T so that Set<T> is assignable to the context type (and no types K and V so that Map<K, V> is).
That would allow this case because Set<num> is assignable to S by downcast, but it will also likely break if we try to run it because of that downcast. Not much saved, and forcing the compiler into a searching for a solution.


Could you please tell me what does 'lambda-local' and 'lambda_d' mean in 'SSR_net'? Thank you!

Thank you for providing such an extrodinary image-processing solution, and I have already run the code and read the paper related to this project.
I have a question about parameters 'lambda_d' and 'lambda_local'. I can't understand their function and meaning. ( I noticed that you set them both as 1.0 in your demo).

Hello @Leon-Zijie-Li,
Thank you for your appreciation. lambda_d and lambda_local are the hyper-parameter for tuning the dynamic scaling and dynamic index shifting respectively corresponding to Eq.(4) and Eq.(6). I did not write them down in the paper because they would make it more complex. Normally you don't have to tune them and that's why I set them to 1.


Complete the set of network types and work/home icons for use in Help Center articles and other documentation

The list of icons and other symbols at https://dialpad.design/icons/system/ is missing a few things that would be nice to add for use in Help Center articles and so on. These new symbols and relevant ones in the existing list will be used for developing and improving troubleshooting workflows for customers, business partners, and the sales and CSM teams.
We currently have a WiFi symbol, and have no Ethernet symbol, though the latter comes up very often in troubleshooting work. We have a Business icon but no home icon, and that would be helpful for highlighting things relevant to office workers, which are different from things relevant to home/remote workers. In an ideal situation, we would have a library of symbols that can be used across many customer-facing troubleshooting articles to enhance our information presentation and help readers focus on elements.
I'm requesting the following items to be added to our Dialtone suite:

House:
Ethernet:
Router:
Server
Modem:
Switch:

Hey @ab-ron , would these work?
Home
https://fonts.google.com/icons?selected=Material Icons%3Ahome
Ethernet
https://fonts.google.com/icons?selected=Material Icons%3Asettings_ethernet
Router
https://fonts.google.com/icons?selected=Material Icons%3Arouter
Server
https://fonts.google.com/icons?selected=Material Icons%3Adns
Those are the best I can find from Material, which is where we currently source our DT icons. I didn't find anything for modem or switch, so I may need some help finding open-source, stylistically comparable glyphs for those.

The icons for House and Router look great, the Server one is probably fine (kinda looks like an alien robot), but that Settings Ethernet one looks straight out of iOS and I don't think it conveys Ethernet (or even networking) to me at all. 😅 We can probably use that and maybe Google will do better in a future iteration.
Thanks, Drew!

The icons for House and Router look great, the Server one is probably fine (kinda looks like an alien robot), but that Settings Ethernet one looks straight out of iOS and I don't think it conveys Ethernet (or even networking) to me at all. 😅 We can probably use that and maybe Google will do better in a future iteration.
Thanks, Drew!

Are these icons we want to include in the new set being created?


New release for python3.8 support

Since release v0.13.1 support for python 3.8 was added.
https://github.com/ariovistus/pyd/compare/v0.13.1...master
Could you please create a new release?
Thanks.

New release with 3.8 support would be appreciated.

@ariovistus, any hope for this to be done soon? Can we help in any way? is it simple to add this support for newer versions? I could make a PR...

By the way I decide to try the version from the master branch and got this error when building:
fccoelho@fccoelho-MACH-WX9 ~/D/S/corpushashD (master)> dub add-local ~/Downloads/pyd/
Registered package: pyd (version: 0.13.1+commit.5.g93d8235)
fccoelho@fccoelho-MACH-WX9 ~/D/S/corpushashD (master)> dub upgrade pyd
Upgrading project in /home/fccoelho/Documentos/Software_projects/corpushashD
fccoelho@fccoelho-MACH-WX9 ~/D/S/corpushashD (master)> dub build -f
Invalid source/import path: /home/fccoelho/Downloads/pyd/infrastructure/util/
Performing "debug" build using dmd for x86_64.
pyd 0.13.1+commit.5.g93d8235: building configuration "python38"...
corpushashd 0.3.2: building configuration "application"...
Linking...
Invalid source/import path: /home/fccoelho/Downloads/pyd/infrastructure/util/

am I missing some key step in the build?

the path pyd/infrastructure/util/ does not exist, but pyd/infrastructure/pyd/util/ does...
So maybe this needs to be fixed...

curious. i renamed util/ to pyd/util recently and thought I got everything.

So there are a couple minor issues that make me hesitant to make a release. the first is the test suite is failing on a linker test that suggests the deimos headers are off somewhere for 3.8. which might not be a big deal.
The second is the .lib files in infrastructure/windows. I have forgotten how to generate them. They are necessary for linking to python.dll or whatever on x86 windows with dmd.

@ariovistus if you can find out the details about the lib files you might use github Actions for the compilation. Therefore it is documented and done automatically for further releases.

ok, sorta remember it now, there's a tool called implib. left some notes at https://pythond.atlassian.net/wiki/spaces/pyd/pages/edit-v2/1784578049?
But something seems to have changed since the last time i did this, symbols that used to be _PyTuple_Size are now PyTuple_Size. I imagine the windows python compile is different somehow, but i wouldn't know where to start.
somewhat tempted to deprecate 32bit python/windows/dmd.

+1 to deprecate 32bit python/windows/dmd.

Thanks for the new release.

Thanks! I have rebuilt my projects for Python38 without problems!


Auto fill steps required for a template

If an authentication script template requires 'n' steps, need to add those steps at the template import time. They may contain suitable defaults which can later modified by user.

Done with https://github.com/wso2/carbon-identity-framework/pull/1664


wl: Fix PostEmptyEvent not waking WaitEvents

Use an eventfd as a means to signal waitEvents to wake up as
wl_display_sync does not always achieve this.
This fixes GitHub Issue #1520

Is there anything else needed on my side for this? I'm quite keen to get this fixed, as it causes a deadlock in my application.

I ran into the same problem in Ubuntu 18.04 (using GNOME Wayland session). My application was hanging on glfwWaitEvents(). I pulled from your fork and it fixed my problem. I also second merging this PR if others don't see any issues.

@elmindreda Would you be able to spare some time to review this? I'm finding that even non-multithreaded glfw applications randomly hang on Wayland without it.

@eXeC64 Will do. Cannot promise when.

@eXeC64 in #1285, we fixed a race condition, are you sure this is not fixing the error you are attempting to fix here?


Instructions for setting up Web Content Filters is out of date.

On step 1 for setting up a web filter.  After going to security.microsoft.com, I have to go to settings, endpoints, and then Web content filtering under Rules.

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

ID: 3afb40ff-f167-1d49-443f-a971611a6340
Version Independent ID: 3afb40ff-f167-1d49-443f-a971611a6340
Content: Set up web content filtering in Microsoft Defender for Business
Content Source: microsoft-365/security/defender-business/mdb-web-content-filtering.md
Service: microsoft-365-security
Sub-service: mdb
GitHub Login: @denisebmsft
Microsoft Alias: deniseb

Hi @rconiv. Good catch! Thank you for letting me know about this. I've updated the article and the changes will be live later today.   Appreciate your feedback!


Update best-practices-availability-paired-regions.md

Adding the Canada regions

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

It looks like you're working at Microsoft (aglick). If you're full-time, we DON'T require a contribution license agreement.

If you are a vendor, DO please sign the electronic contribution license agreement. It will take 2 minutes and there's no faxing! https://cla.azure.com.

TTYL, AZPRBOT;

@adamglick : Thanks for your contribution to the Azure documentation! The author, @rayne-wiselman, has been notified to review your proposed change.

@Jim-Parker
Change is fine but Adam will need to resolve conflict.
#sign-off

What merge conflict?  If it's easier Rayne can do the update. I was just trying to help out.

@rayne-wiselman Rayne, let me know if you can make the update, per Adam's response. Otherwise, we will need to sync so I can help.

Hi Adam, I wasn't exactly sure what change you wanted to make since the article actually looked fine.
I've updated a few other things in the article and submitted a new pull request so you can close this one.
If you still see any other issues after it republishes fix directly or let me know.


use a static local func

https://www.c-sharpcorner.com/article/c-sharp-8-0-static-local-functions/

In C# 8.0, we addressed this issue by declaring the local functions as static since we are aware that static methods won’t be allocating separate memory in each object and the same in its variables scoped to it.

AppVeyor didn't like this

This is due to DevicesFetcher targeting .netcore 2.2 (note: out of Microsoft support now) which only supports C# 7.3. This issue is fixed either by bumping DevicesFetcher to .net core 3.1, or waiting for the .net 5 issue #1638 to be implemented ...


Swagger -> YAML RFC

For each API Object:

Name
Description (Markdown)
API Group and Version
HTTP Request Code (determines CRUD?)
Example Request

Concatenates: Host, then API group and Version, then deployment, then (optionally) name of object, then the HTTP type
Then, JSON object body

Equivalent kubectl

Name of command
Example string w/usage

Example response (YAML and JSON) generated from fields
Return values/response codes

For each field:

Example values for fields

Create request example
Update request example
Create response example
Update response example

Type

Link to datatype ref
Specify if non-primitive

Required
Name
Description (Markdown)
Default value

@pwittrock @janetkuo

Phillip, I know  you're working on this already, and you've made a lot of progress. This bug hasn't been updated in 8+ months, so I'm going to close it out for bug hygiene purposes.


Intentions for password presence validation

I've recently been working on upgrading clearance from 1.13.0 to 1.14.0 and I noticed some functionality we were relying is now broken and I wasn't sure if we were relying on unintended behavior or if something was broken.
The basic gist is that on user update, we were submitting an empty string in the password field to signify no update was being requested and this worked fine in 1.13 but now in 1.14 our validations are failing with a password cannot be nil error. I was able to track down the culprit to this line:
def password=(value)
  encrypted_password_will_change!
  super
end

Which assumes that the password will always change if password set is called and it will trigger the password validations here. However, at least with the Bcrypt strategy this is not the case:
def password=(new_password)
  @password = new_password

   if new_password.present?
    self.encrypted_password = encrypt(new_password)
  end
end

So I would like some clarification on the intention here and then we can talk about a fix if appropriate. Thanks!

There's a good deal of explanation about this change in the issue #664 and the corresponding change in #668. Indeed, someone even raised this concern in the PR, but I dismissed it as a bug. Thinking more on it now, I think it's probably a bigger issue than I had perhaps thought. Still, the old way also seemed like a bug.
The fix on an application's end is to strip out blank passwords from the params being passed to user.update. This is more work for you, but thinking objectively it also seems more correct.  Something like: user.update!(password: "") could actually succeed while it didn't actually do what it seems I told it to do - set the password to the blank string.
I think the way it operates now is correct but I'm willing to entertain counter points or alternate solutions.

Thanks for the explanation and links @derekprior. I think I agree with you about the approach. So we can close this issue. It might be a good idea to document the intentions a bit somewhere cuz I hunted through a few issues but I must have skipped over the right one to look at.


WebGPU broken

Hello, I'm trying to compile the WebGPU examples, but it seems even with a successfully build, there is no way to test it.
Trying it with Firefox Nightly:

Uncaught (in promise) TypeError: gpuContext.getSwapChainPreferredFormat is not a function
_sapp_emsc_wgpu_init

Trying it with Chrome Canary:

Uncaught TypeError: Failed to execute 'createBindGroupLayout' on 'GPUDevice': required member entries is undefined.

So even with the precompiled example
Is there a way to get it working, or it's just broken?
If it's the case, maybe just notice it somewhere.

See my answer here: https://github.com/floooh/sokol/issues/377


Rosetta Code: Dot product

do not include past commit in the PR, use a new fresh branch

+1

drop useless commits/files from the PR


Suggestion: toBoolean function

a useful function is to convert a value to boolean,
something like this:
const toBool = x => not(not(x))

JavaScript already has the Boolean constructor which does what you're looking for: Boolean(x)