checkpatch: update image (skip backports, add a check, suppress one report type)

Update the checkpatch image tag (and switch to quay.io) to benefit from the following changes:

Skip checkpatch validation on backport branches
Suppress reports of type COMMIT_LOG_LONG_LINE
Add a repo-wide check on commit subject length
Use $GITHUB_REPOSITORY variable when retrieving commits

For skipping backports we could instead update the conditions for running the job in the current repo, but that would be troublesome if we want to mark the action as required in the future. Therefore, we delegate the decision to the shell script in the checkpatch image: it returns early if a PR is not based on the 'master' branch.
Checkpatch updates available at https://github.com/cilium/image-tools/pull/104/files and https://github.com/cilium/image-tools/pull/109/files.
Tested here for the new check and the suppressed report, and there for skipping the backports.
Marking for backports for 1.9, where the checkpatch action is run but where we want to skip it.
No CI test needed, other than having the checkpatch verification still working.

I have been made aware of another issue to fix on the checkpatch image, I'll update the image once more and then update this PR.

Now ready for review again, I updated the test PRs too.

Do we also need to move this out of BPF checks given it now applies to all commits?

We could. I don't know if it's worth it, there's only one check that extends to all commit, the majority is still for bpf/. Do you have a suggestion? I'd rather avoid creating a new action just for that.

Do we also need to move this out of BPF checks given it now applies to all commits?

We could. I don't know if it's worth it, there's only one check that extends to all commit, the majority is still for bpf/. Do you have a suggestion? I'd rather avoid creating a new action just for that.

Yeah, we have too many actions already... Let's postpone.


Pretrained weights for the depth modality

Hi,
Thanks for sharing your code!
Are you planning to release a model pre-trained on 3D point clouds?
I am referring to the experiments conducted on ModelNet40.
Thanks for your answer.

Hi Guhur, we have no current plans to release a model trained on 3D point clouds.


Readme: Add explanation on mime types

Adding a short explanation that the mime setting expects an extension, not a complete header string; via https://forum.getkirby.com/t/kirby3-feed-where-to-add-a-xsl-file/23228

thanks!


fix: wezterm cursor

The beam cursor doesn't work with TERM=wezterm and I fixed this.

Hi,
The default is xterm-256color but you can configure it to wezterm for maximum feature.
https://wezfurlong.org/wezterm/config/lua/config/term.html?h=term


Answers are not randomized

Hi
I just found out, when question is showed it has the same ABCD answers everytime, can they be randomized?
Sometimes the correct answer is the same letter for like 10 questions in a row, can this be a bug?
In both cases local question database is used.
thx

Answers are currently sorted in reverse alphabetical order as seen here--this is intentional. In the instance of having the same letter, can you verify if the answers are sorting? It may be related to how they are formatted in some form as well.

Answers are currently sorted in reverse alphabetical order as seen here--this is intentional. In the instance of having the same letter, can you verify if the answers are sorting? It may be related to how they are formatted in some form as well.

When answers start with a same letter it's ok, they are sorted by next letters.
Not sure if that is important actually, or why they need to be sorted alphabetically, but sorting script doesn't recognize correctly letters with diacritics, so:
correct way: a á b c č d ď e é
trivia bot is sorting like: a b c d e .. x y z á č ď é...

When answers start with a same letter it's ok, they are sorted by next letters.
Not sure if that is important actually, or why they need to be sorted alphabetically, but sorting script doesn't recognize correctly letters with diacritics, so:
correct way: a á b c č d ď e é
trivia bot is sorting like: a b c d e .. x y z á č ď é...

I see! Will take a look at this


Using "modern" CMake in Ginkgo

I always had trouble finding good and up-to-date tutorials about CMake, and how to properly do stuff there (especially the things  that seem to be possible to do in multiple ways).
I think I finally managed to find a good collection of resources here.
Just by taking a quick look I already figured out that we're doing some of the things the wrong way which will prevent us in playing nicely with other software.
Someone should go over the materials in the link, and update our build system to follow the rules.

A lot of install_helpers.cmake is based on this blog post


How to integrate todo tasks into HA

As per title. I've successfully brought the integration into HA but I'm at a bit of a loss as how to display and interact with these tasks. I thought maybe the shopping list integration would help me here but it doesnt allow for adding entities. Thank you

Sorry, I can’t really advise on this.l, I don’t use it myself but added it because I had a request raised. You might find some things to build on at the link below, which is a previous integration that just did Tasks but became unsupported.
https://github.com/black-roland/homeassistant-microsoft-todo


Add aspect_bazel_lib 1.0.0

In particular we'd like<EMAIL_ADDRESS>to be on the central registry

That Feeling When your product ships but you're waiting on the App Store to release it 😇


Make SGv2/REST/MaterializedView IT retry twice before failing to improve CI stability

What this PR does:
Adds annotation to make Materialized View test (for REST API) try 3 times before giving up.
This because test appears to occasionally fail due to some timing issue related to creation (or schema metadata update) of MVs.
Which issue(s) this PR fixes:
Checklist

[ ] Changes manually tested
[x] Automated Tests added/updated
[ ] Documentation added/updated
[x] CLA Signed: DataStax CLA

Hmmmh. This does not seem to work -- unfortunate "assumeThat" used to exclude specific backend(s) is exposed as assertion error, and then THAT gets retried by @RetryingTest. Not good.

Won't work, closing.


fix(website): space bg fadeIn

LGTM

I'll let another more documentation experienced reviewer have a look, just for the sake of it. It all looks good of course

:+1:


Use functools.wraps for ray.remote

https://docs.python.org/2/library/functools.html#functools.wraps
It seems like the right thing to do, although I'm not familiar with all the implications.

I see, right now we propagate the function name and doc string manually, but this might be cleaner.


unix: fix uv_interface_addresses() potential hazard

uv_interface_addresses fails. return value policy unmatch with other OS
socet() or ioctl()  failed before uv__malloc()  called . uv_interface_addresses() return "-ENOSYS" and "addresses pointer" is Indefinite.
  if (0 > (sockfd = socket(AF_INET, SOCK_DGRAM, IPPROTO_IP))) {
    return -ENOSYS;
  }

  if (ioctl(sockfd, SIOCGSIZIFCONF, &size) == -1) {
    uv__close(sockfd);
    return -ENOSYS;
  }
....

ioctl() function failed after uv__malloc()  called . uv_interface_addresses() return "-ENOSYS" and "addresses pointer" is allocated address.
https://github.com/joyent/libuv/blob/v1.x/src/unix/aix.c#L1176
user application is not possible to determine whether to call  uv_free_interface_addresses().

Thank you for pointing that.
fixed.

Thanks @farblue68, landed in ee9c7ba


Unable to build from sources in Win (Python 3.11)

Hi,
there seems to be no wheels for the newly release Python 3.11 yet, and it seems it's not possible to build one in Win 10 - pip install websockets ends up with the following error:
      Traceback (most recent call last):
        File "<string>", line 2, in <module>
        File "<pip-setuptools-caller>", line 34, in <module>
        File "C:\Users\ondre\AppData\Local\Temp\pip-install-9zcbd40o\websockets_0a8798084b5c45538f93d9f69fa08228\setup.py", line 33, in <module>
          setuptools.setup(
        File "x:\janoshik\venv\Lib\site-packages\setuptools\__init__.py", line 153, in setup
          return distutils.core.setup(**attrs)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        File "X:\tools\python311\Lib\distutils\core.py", line 148, in setup
          dist.run_commands()
        File "X:\tools\python311\Lib\distutils\dist.py", line 966, in run_commands
          self.run_command(cmd)
        File "X:\tools\python311\Lib\distutils\dist.py", line 985, in run_command
          cmd_obj.run()
        File "x:\janoshik\venv\Lib\site-packages\wheel\bdist_wheel.py", line 337, in run
          impl_tag, abi_tag, plat_tag = self.get_tag()
                                        ^^^^^^^^^^^^^^
        File "x:\janoshik\venv\Lib\site-packages\wheel\bdist_wheel.py", line 287, in get_tag
          assert tag in supported_tags, "would build wheel with unsupported tag {}".format(tag)
      AssertionError: would build wheel with unsupported tag ('cp311', 'cp311', 'win_amd64')

I'm not sure how to fix this, any clue?

pip install websockets --no-binary=websockets

There will be Python 3.11 wheels for the next release of websockets. I don't have an ETA for this; releases are infrequent.

Thanks, didn't know about --no-binary, good to know!


UI redesign

Completely rebuilt all UI from the ground up, with better usability and cleaner html/css in mind.

Drawing tools are yet to be redone, but at the very least merging this should mean we can get to doing that quicker!


Issue with upload and analysis

Sorry to be an alarmist but several issues have existed for several days.
Issue 1
Load button grayed out unless a BAM or CRAM is provided.  These were optional.  Vcf is no longer sufficient.
Issue 2
Failure to analyze.  I have tried entering via Nebula and off the iobio website using a CRAM file as vcf files will not work (see above).  I analyze a gene with known variants and get no variants shown.  Except for Intron and Exon presentation there is nothing (no squares, no circles, no triangles).  I have tried this on Chrome, Edge, and Firefox.  On Firefox, the gene analysis will not load (Via Nebula entry it loads but has a blank analysis).  Chrome and Edge are empty analyses via any method.   A screen shot is enclosed of an empty analysis.

Thank you for the comment - feedback is alway appreciated. Gene.iobio recently underwent an update and there have been problems associated with gene.iobio when launched from Nebula Genomics. We are working with Nebula to understand the problem and will hopefully have this resolved soon.


custom_profile: Add ProfileDataElementUpdateDict.

This replaces Dict[str, Union[int, ProfileDataElementValue]] with ProfileDataElementUpdateDict.
Affected errors:
2c2
< Found 296 errors in 95 files (checked 1394 source files)
---
> Found 289 errors in 93 files (checked 1394 source files)
163d162
< zerver/lib/users.py error Incompatible type for lookup 'id' (got "Union[int, Union[str, List[int]]]", expected "Union[str, int]")  [misc]
230,233d228
< zerver/tests/test_custom_profile_data.py error "object" has no attribute "is_renderable"  [attr-defined]
< zerver/tests/test_custom_profile_data.py error Argument 1 to "markdown_convert" has incompatible type "object"; expected "str"  [arg-type]
< zerver/tests/test_custom_profile_data.py error Invalid index type "object" for "Dict[Union[int, float, str, None], Optional[str]]"; expected type "Union[int, float, str, None]"  [index]
< zerver/tests/test_custom_profile_data.py error Invalid index type "object" for "Dict[Union[int, float, str, None], Optional[str]]"; expected type "Union[int, float, str, None]"  [index]
248,249d242
< zerver/tests/test_events.py error List item 0 has incompatible type "Dict[str, object]"; expected "Dict[str, Union[int, str, List[int]]]"  [list-item]
< zerver/tests/test_events.py error List item 0 has incompatible type "Dict[str, object]"; expected "Dict[str, Union[int, str, List[int]]]"  [list-item]

Self-review checklist

[x] Self-reviewed the changes for clarity and maintainability
(variable names, code reuse, readability, etc.).

Communicate decisions, questions, and potential concerns.

[x] Explains differences from previous plans (e.g., issue description).
[x] Highlights technical choices and bugs encountered.
[ ] Calls out remaining decisions and concerns.
[ ] Automated tests verify logic where appropriate.

Individual commits are ready for review (see commit discipline).

[x] Each commit is a coherent idea.
[x] Commit message(s) explain reasoning and motivation for changes.

Merged, thanks @PIG208!


Completion should list skinClass property for MXML Spark components (all Inherited Styles are missing from completion?)

skinClass is not enlisted:

When I was testing some of the MXML fixes in v0.11.1, I noticed that some styles seemed to be missing in the completion list for Flex components. I'll investigate.


running the kvapps from your github account but i am getting this exception

Exception in thread "main" com.impetus.kundera.KunderaException: com.impetus.kundera.KunderaException: InvalidRequestException(why:Unknown identifier personalDetail)
at com.impetus.kundera.persistence.EntityManagerImpl.persist(EntityManagerImpl.java:180)
at com.impetus.kvapps.runner.ExecutorService.persist(ExecutorService.java:254)
at com.impetus.kvapps.runner.ExecutorService.onPersist(ExecutorService.java:82)
at com.impetus.kvapps.runner.AppRunner.main(AppRunner.java:88)
Caused by: com.impetus.kundera.KunderaException: InvalidRequestException(why:Unknown identifier personalDetail)
at com.impetus.client.cassandra.CassandraClientBase.execute(CassandraClientBase.java:2607)
at com.impetus.client.cassandra.CassandraClientBase$CQLClient.persist(CassandraClientBase.java:2246)
at com.impetus.client.cassandra.thrift.ThriftClient.onPersist(ThriftClient.java:193)
at com.impetus.kundera.client.ClientBase.persist(ClientBase.java:114)
at com.impetus.client.cassandra.thrift.ThriftClient.persist(ThriftClient.java:167)
at com.impetus.kundera.lifecycle.states.ManagedState.handleFlush(ManagedState.java:197)
at com.impetus.kundera.graph.Node.flush(Node.java:531)
at com.impetus.kundera.persistence.PersistenceDelegator.flush(PersistenceDelegator.java:403)
at com.impetus.kundera.persistence.PersistenceDelegator.persist(PersistenceDelegator.java:145)
at com.impetus.kundera.persistence.EntityManagerImpl.persist(EntityManagerImpl.java:174)
... 3 more
Caused by: InvalidRequestException(why:Unknown identifier personalDetail)
at org.apache.cassandra.thrift.Cassandra$execute_cql3_query_result$execute_cql3_query_resultStandardScheme.read(Cassandra.java:50297)
at org.apache.cassandra.thrift.Cassandra$execute_cql3_query_result$execute_cql3_query_resultStandardScheme.read(Cassandra.java:50274)
at org.apache.cassandra.thrift.Cassandra$execute_cql3_query_result.read(Cassandra.java:50189)
at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:78)
at org.apache.cassandra.thrift.Cassandra$Client.recv_execute_cql3_query(Cassandra.java:1734)
at org.apache.cassandra.thrift.Cassandra$Client.execute_cql3_query(Cassandra.java:1719)
at com.impetus.client.cassandra.CassandraClientBase.execute(CassandraClientBase.java:2601)
... 12 more

Hi @mayankqait,
Above details are not sufficient. Mention database with version and Kundera version.
Do reply on your last issues. Close if those are resolved.

I am providing the zip of project.
And Thank you very much for the quick response I got for my queries.
kvapps.zip

Hi @mayankqait,
If you are storing in Cassandra, simply enable CQL3 using below mentioned code:
Map<String, String> props = new java.util.HashMap<>();
props.put("cql.version", "3.0.0");
EntityManagerFactory emf = Persistence.createEntityManagerFactory("twissandra", props);

Are you trying polyglot persistence?

yes i am using polyglot persistence. mysql and cassandra

One last question

how to overcome double quotes problem in querry.This is auto generated query by kundera
INSERT INTO "User"("first_name","last_name","emailId","user_id") VALUES('RDBMSUser','RDBMSUser','RDBMSUser@RDBMSUser.com','RDBMSUser')
It is adding double quotes around table name and column name.

@mayankqait
I don't see this as a problem. Double quotes are required to maintain the table and column names case sensitive.
Can you explain your problem in brief?
-Karthik

Yes we can close this issue #991 also.
There was a dependency conflict.
Thank u


Is this project still maintained? Any plans to convert it into a Cmake project?

The project is not being actively worked on at present, however it is still maintained and work is planned for the near future. As a result, bugs reported will take longer to be rectified.
The program can easily be compiled using make. Please provide justification for converting it to a cmake project. If demand is there, then a cmake project can be constructed.

making it a cmake project allows it integration into many robotic libraries, such as ROS. It also allows one to open the code base in popular editors such as CLion or Qtcreator.

Thanks, looks like it would be very useful. I'll look into it for the next update.


Ansible role: edpm_deploy

This role takes the provided CRD (by default, install_yamls) and injecty the external compute into it.
The external compute listing will be provided by the libvirt role once we get it, in a specific format so that it can replace the inventory directly.
This PR has:

[x] Appropriate testing (molecule, python unit tests)
[X] Appropriate documentation (README in the role, main README is up-to-date)

The task includes an option with an undefined variable. The error was: {{ cifmw_basedir | default('~' ~ ansible_user ~ '/ci-framework') }}: 'ansible_user' is undefined. 'ansible_user' is undefined. {{ cifmw_basedir | default('~' ~ ansible_user ~ '/ci-framework') }}: 'ansible_user' is undefined. 'ansible_user' is undefined

/test all

/lgtm


ci: prevent running nightly FT in forks

I hereby agree to the terms of the GreptimeDB CLA
What's changed and what's your intention?
Forks cannot reach the secrets in use.
Checklist

[ ]  I have written the necessary rustdoc comments.
[ ]  I have added the necessary unit tests and integration tests.

Refer to a related PR or issue link (optional)

@zyy17 Please take a look


[next] merge changes from main

Merge all changes from main into next

This also includes everything from #4331, right?

This also includes everything from #4331, right?

Yes. The changes were made in https://github.com/open-telemetry/opentelemetry-js/pull/4332


Fix e2e tests setup in GitHub Actions

We have disabled our current e2e test (see https://github.com/Azure/static-web-apps-cli/pull/398/commits/1a42f73cc6e0cfe0888d38308ac981290e89bbea) due to some issues with Cypress.
We'd like to enable e2e tests again once we manage to investigate the root cause.

Related issue: #352


open/closed should be required for trait spec fns

Right now we require every public spec fn to specify whether it's open or closed. Trait fns are all implicitly public, but we currently aren't doing this check for such functions.

backreference to related discussion (pointed out by @tjhance): https://github.com/verus-lang/verus/discussions/399

[Verus all-hands]
@tjhance has tried to fix this; but the syntax macro cannot tell if a trait is public or private.
We are going to need a new attribute for closed so we can do the detection in VIR.
The plan is to require it on bodies of the impl of public traits.


[UI/UX] redesign Maps portal

Description
related to https://github.com/UNDP-Data/geohub/issues/3877, Maps portal (/maps page) needs the same unified UI to redesign the layout.
Screenshots
No response
Mockup URL/file
No response

Figma Prototype


Challenge [Link to External Pages with Anchor Elements]

Hello World
I am using Google Chrome Version 51.0.2704.106 m (64-bit)
I have deleted my cookies changed browsers the error message does not change. I have googled and tried the freecode camp help line and have not found a solution. I have now been asked to report this as a BUG
Errror message:
You need an a element that links to http://freecatphotoapp.com
This is my entire code given below :
<link href="https://fonts.googleapis.com/css?family=Lobster" rel="stylesheet" type="text/css">

CatPhotoApp

 View more cat photos

Kitty ipsum dolor sit amet, shed everywhere shed everywhere stretching attack your ankles chase the red dot, hairball run catnip eat the grass sniff.

Purr jump eat the grass rip the couch scratched sunbathe, shed everywhere rip the couch sleep in the sink fluffy fur catnip scratched.

@supertrek thanks for the issue. If you look at the test

You need an a element that links to http://freecatphotoapp.com

It asks specifically for http://freecatphotoapp.com but your code has http://www.freecatphotoapp.com with the www in it. That's why you're not passing the test. Happy coding!

Thanks.
Lesson Learnt :  (As stated in the initiation ) READ
[😊]

From: Eric Leung<EMAIL_ADDRESS>Sent: Tuesday, 5 July 2016 10:02 AM
To: FreeCodeCamp/FreeCodeCamp
Cc: supertrek; Mention
Subject: Re: [FreeCodeCamp/FreeCodeCamp] Challenge [Link to External Pages with Anchor Elements] (#9549)
@supertrekhttps://github.com/supertrek thanks for the issue. If you look at the test
You need an a element that links to http://freecatphotoapp.com
It asks specifically for http://freecatphotoapp.com but your code has http://www.freecatphotoapp.com with the www in it. That's why you're not passing the test. Happy coding!
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHubhttps://github.com/FreeCodeCamp/FreeCodeCamp/issues/9549#issuecomment-230364973, or mute the threadhttps://github.com/notifications/unsubscribe/ATVRmyp3NEeVTrRbJpv2xVncwjQ2jxn7ks5qSZ8mgaJpZM4JEq0w.

Transfer my account prabayar maxis


Remove version inconsistency between spec document and other parts of the component spec

Describe the bug
OTel artifacts using semver for versioning, with some declared exeptions regarding experimental, alpha versions and currently regarding some telemetry data.
The spec document cuts the PATCH part of the referenced OTel versions - this leads to potential deviations from the spec document to the API and TCK, when there are multiple PATCH versions of the OTel artifacts available.
This can result in using a broken or insecure version!
References to OTel dependencies (and all other too - but that a different discussion) must show and use the exact version (as a minimum version to use).
With semver in place, it is possible to use a higher version (i.e. in the implementation), when allowed in respect to the semver rules - may be we should clarify this in the spec document in a future release.
A last minute change of the MP Telemetry 1.0 introduced this change - we must revert this:
https://github.com/eclipse/microprofile-telemetry/pull/70
If the intention of this change was to handle recent OTel PATCH version releases we should define separate versions for the opentelemetry-spec, opentelemetry-java and opentelemetry-java-instrumentation, so PATCH release deviation can be handled and shown in the spec document.
@Emily-Jiang, @brunobat and @Azquelt: I can create a PR to solve this if you agree or we can discuss this on our next meeting, as you like to do.

I think you're suggesting two changes:

Change OTel versions in the spec to include the patch version
Change all references to required versions of OTel to say "this version or later"

Is that right?

We did talk about this in the meeting.
My concerns were:

We do want to allow implementations to pick up new patch versions which #70 did, so we don't want to entirely revert that PR
We can't say something like "1.19.0 or any later minor version" because we rely on some components which are still experimental (particularly semconv and autoconfigure) so even minor versions of those components may have breaking changes.

However, I am happy if we want to change how things are worded in the spec to something like "1.19.0 or any later patch version" - which would allow us to only have one version defined in the pom and allows us to specify a minimum patch version (e.g. if there was a security fix and we wanted to require 1.19.1).
We could go as far as saying "1.19.0 or any later version without breaking changes" which would then put the onus on implementers to check whether 1.20.0 actually has any breaking changes in its experimental components, but that wouldn't be an easy thing to assert.
With more of OTel becoming stable, it's also possible that in a future version of MP Telemetry we might be able to only depend on stable parts and then it might be possible to say "1.19.0 or any later minor version", but we're not there yet.
Lastly, we briefly mentioned using the TCK to assert compatibility. While I would like to improve and expand the TCK to cover more of the areas that the spec requires (e.g. more complete testing of the config options specified by autoconfigure), we will never be able to say "if you can update the version of OTel and still pass the TCK, it doesn't have any breaking changes". Breaking changes can be small and subtle and TCK coverage will never be that complete.
More generally, the TCK for any spec will only ever test a subset, passing the TCK doesn't mean you've accurately implemented the spec (though failing it should always indicate that you haven't).

I am with @Azquelt on this. I don't think we need to do a spec update to pull in a micro version release of OpenTelemetry. This prevents implementations from consuming the latest CVE fixes without a spec update. By the way, the micro version release of OpenTelemetry should not bring in any functional changes except very minor internal fixes.

We think the version are consistent now. Please reopen if you think otherwise.


FluidGrid : when change value, labels of components lost your label and all components use the label last component .

Describe the bug
When the FluidGrid component is used in the form of a dynamic form, and this form has components that are required and each one with its own label, when the form is sent and the validations of the required components are skipped, they always have the same label as the last component that was rendered.
This only happens when the values of the value attribute of the fluidgrid are replaced by other elements, when the component is updated, when the form is resubmitted, the validation messages of the components are displayed and in this case, all the errors show the same validation error, pointing to the last component that was rendered.
The only way to restore this behaviour is to refresh the page, but again this will only work for the first components that are rendered, if they are replaced by others, the error occurs and it is no longer possible to fix it.
It has been tested resetting to null the value and then doing an update from the bean to stop rendering the component and then set the new values to the list and update again to render the component again with the new values, it has been tested with <c:if tags to render the content that would be the fluidgrid, cleaning all the elements of the value and setting new ones.
It has also been tried to update the form or the component itself, the result is the same, the component label is not correctly assigned when validations are processed.
Also tested with the latest version of primefaces (14.0.3) and primefaces extension (14.0.6) and the same thing happens
Gif with bug:

Reproducer
It can be reproduced with the same showcase case, adding a selectOneRadio for example, with a listener that sets the new list of dynamic values and updating the component again. I attach the project where the problem is reproduced.
Expected behavior
When the fluidgrid is updated, all components' labels must be set correctly again, not all components assigned the same label.
Example code:
primefaces-test-7.0.zip
PrimeFaces Extensions version
7.0.3
JSF implementation
Mojarra
JSF version
2.2.20
Browser(s)
All

I have no doubt this is a bug.  But I don't full understand how the FluiGrid component actually works and there is some really funky stuff going on with this component so I can't imagine i will have the time to try and figure this one out.

I've been looking but I haven't found the solution to the problem yet, I don't know if you could add something similar to what is done in other components with the attribute cache=‘false’.
Thank you very much for everything, maybe it has happened to someone and they can give us a hand.

cache="false" on the FluidGrid?  I don't think that is possible either. This whole component works with a "hacked" AbstractDynamicData that is trying to emulate core Faces UIData but with different needs.  Clearly something is not correct it in AbstractDynamicData but it was written years ago by Devs no longer involved.


[Python] Import Error for pyarrow.flight in pyarrow 6.0.0 and 6.0.1

Description:
Unable to import flight module in pyarrow in version 6.0.0 and 6.0.1.  Is there a different package I can install that provides the module? Or is this potentially an issue with me using apple silicon?

Error:

import pyarrow.flight
Traceback (most recent call last):
  File "", line 1, in
  File "/path/to/repo/pyarrow/flight.py", line 18, in
    from pyarrow._flight import (  # noqa:F401
ModuleNotFoundError: No module named 'pyarrow._flight'

How to replicate
pip3.8 install pyarrow==6.0.1
python3.8 -c 'import pyarrow.flight'

Python version:
Python version: 3.8

Environment
MacBook Pro (Apple Silicon)
Reporter: Eric Henry
Note: This issue was originally created as ARROW-14978. Please see the migration documentation for further details.

Given this is an older issue, and there was no further response, closing this.


Concerning wstring-to-string conversion in WIN32 implementation

Hi, I have tried compiling on Windows 10 with VS 2019. There is a warning exposed during the compilation in Anvil project ( in VS solution ), and this is the details
8>$(VS_PATH)\include\xstring(2308,23): warning C4244:  'argument': conversion from 'wchar_t' to 'const _Elem', possible loss of data
8>$(VS_PATH)\include\xstring(2308,23): warning C4244:         with
8>$(VS_PATH)\include\xstring(2308,23): warning C4244:         [
8>$(VS_PATH)\include\xstring(2308,23): warning C4244:             _Elem=char
8>$(VS_PATH)\include\xstring(2308,23): warning C4244:         ] (compiling source file $(ANVIL_ROOT)\src\misc\io.cpp)
I have investigated it and found that the problem line is 168 ( in master branch at this time I post ), which is
std::string  file_name               (file_name_with_path_wide.begin(), file_name_with_path_wide.end() );
This produces an error since the compiler is set to threat warning as an error, but it is fine because I can disable it in the project settings. However, this becomes my concern whether the file name data will be interpreted wrong or not according to this weird conversion. wchat_t stores 4 bytes character, while normal char only stores one byte. Using this constructor is like copying all the data to the new one and reinterpreting one wchat_t element as 4 char elements.
Maybe I misunderstood the conversion, or it might be the safe conversion as expected, but at least please fix the warning message if you plan to still enable -D_CRT_SECURE_NO_WARNINGS to MSVC compiler.
Thank you in advance.

Paths certainly CAN contain non-ASCII characters.
On Windows that's pretty common. Even copying a directory via Explorer often adds a " - copy" suffix and the actual ' - ' is a non-ascii long-dash.
On unix/linux, wchar_t is usually a 4 byte UTF32 character, and char is UTF8 character. Casting it like this has a huge chance of destroying the string contents for any non-ASCII characters in the path and producing some trash in the std::string.
On windows, wchar_t is a 2 byte UTF16LE character, and char is your-windows-version-specific-codepage ASCII-like non-UTF8 character see here and dig further. Casting it like this has a huge chance of destroying the string contents and producing some trash in the std::string.
IMHO, that needs fixing.
Of course, you may decide to not support Unicode in paths and limit paths to the always-safe lower 0..127 part of ASCII, but that should be very explicitely stated in docs and tutorials. It may be so. I didn't check. If it is, then fine.


Use correct terminology in description on Docker Hub

Description
Thanks to #3365 the description for Gitea on Docker Hub with the quick setup guide is way better than it used to be. I would only suggest to use the correct terminology here. The description currently says:

Dockerfile (with description):
Use this dockerfile to get up and running quickly. You should change mysql user- and root password. When installing, you can reference the database

Since what's shown in this example is actually not a Dockerfile but a Compose file I'd say Dockerfile should be replaced with Compose file here.

I've just updated the documentation.


React Answers

Almost done. Have about 5 questions remaining.
Just thought to create this incase you want to look through.

Awesome work!!!
Looks good. I'll check again in the morning sha.

So cool!

Can each question-component have its own route? E.g. /01-name-concatenation?

The following answers:

Type in reverse
RGB color generator
Hex color generator

should have a "Repeat" button or something.

The Number to words answer is missing an "and".

it should be three thousand four hundred and fifty-one.

Compound Interest is missing a "Go Home!" button.

Each answer page should display the question title. E.g. 01 Name Concatenation, because it gets difficult to differentiate Convert to Decimal from Convert from Decimal to Base N.

On it. @rotimi-babalola was kind enough to help out because I've been so busy and haven't add time to complete this. I'm working on the feedback now. Thanks

@mykeels This is now completed!

I made the UI a bit cleaner sha

Dope!
Just a few more changes.

The output is "below the fold" on my display, i.e. it's not obvious. Could it be above the "First name" field? Or perhaps, the question field be below, or be collapsible?

The number-to-words is still missing an "and".

Fixed the two things you posted/

Final one!
Should be "One hundred thousand". I believe "Lakhs" is Indian.

Thanks @BolajiOlajide!


ImportError (in import tensorflw-gpu as tf) : Tensorflow windows10, CUDA8.0/cuDNN5.1 and python 3.5.2

Hi, i am facing an issue if importError on a setup !

Windows10, Microsoft visual studio (2017)
CUDA 8.0/cuDNN5.1
Python 3.5.2
PATH for CUDA, cuDNN5.1 Libraries/bin/include set properly !!
Setup is created with Docker & tensorflow-gpu environment

While i am trying to verify my installation with "import tensorflow-gpu as tf", encountering with  ImportError: python library specific errors. pl do suggest some remedies !!
Here is complete log of error:
$ python
Python 3.5.2 |Continuum Analytics, Inc.| (default, Jul  5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow-gpu as tf
File "", line 1
import tensorflow-gpu as tf
^
SyntaxError: invalid syntax
import tensorflow as tf
Traceback (most recent call last):
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: The specified module could not be found.

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 41, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 21, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow_internal')
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow_internal'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import *
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python_init_.py", line 51, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 52, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 18, in swig_import_helper
return importlib.import_module(mname)
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\importlib_init_.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 986, in _gcd_import
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 666, in _load_unlocked
File "", line 577, in module_from_spec
File "", line 906, in create_module
File "", line 222, in _call_with_frames_removed
ImportError: DLL load failed: The specified module could not be found.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 41, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 21, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 20, in swig_import_helper
return importlib.import_module('pywrap_tensorflow_internal')
File "C:\Users\Rajeev\Anaconda3\envs\tensorflow-gpu\lib\importlib_init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
ImportError: No module named '_pywrap_tensorflow_internal'
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/install_sources#common_installation_problems
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.
Please go to Stack Overflow for help and support:
http://stackoverflow.com/questions/tagged/tensorflow
If you open a GitHub issue, here is our policy:

It must be a bug or a feature request.
The form below must be filled out.

Here's why we have that policy: TensorFlow developers respond to issues. We want to focus on work that benefits the whole community, e.g., fixing bugs and adding features. Support only helps individuals. GitHub also notifies thousands of people when issues are filed. We want them to see you communicating an interesting problem, rather than being redirected to Stack Overflow.

System information

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

You can collect some of this information using our environment capture script:
https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh
You can obtain the TensorFlow version with
python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
Describe the problem
Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.
Source code / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem.

@mrry Can you take a look?  Not sure if this is enough information.

Change you CUDA path C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin\cudnn64_6.dll filename to cudnn64_5.dll

@gwind55 OMG, it worked!
I've been trying to fix this issue for the past week and that was it!
Note: my setup is win10 using vanilla python (no anaconda) and tensorflow 1.1 (no RC).

@girving this seems like a bug since that's what the cudnn installer sets up. Do you have a plan to fix it internally?

@mrry I don't understand this well enough to know if we can fix it on our end.  Thoughts?

@girving not much. Perhaps @gwind55 can help us understand how he manage to figure this out.

I'm pretty sure that the build hard-codes 64_5 as the CuDNN version here (although I can't see how we use it, because AFAICT the stream_executor doesn't use DSOLoader anymore):
https://github.com/tensorflow/tensorflow/blob/f44d8632a1f0c31ad2061ae9c25ec21e70112179/tensorflow/contrib/cmake/CMakeLists.txt#L210
Also, the release builds link against ${CUDNN_HOME}/lib/x64/cudnn.lib on our build cluster (which I believe is an import library for a corresponding CuDNN DLL; I don't think the build machines have CuDNN 6):
https://github.com/tensorflow/tensorflow/blob/f44d8632a1f0c31ad2061ae9c25ec21e70112179/tensorflow/contrib/cmake/CMakeLists.txt#L202
Perhaps one of these implies a hard dependency on a file called cudnn64_5.dll? (@guschmue, does this sound familiar?) Is there any way to make a binary that supports both versions, or is it enough to focus on the latest one only and force everyone to upgrade?

Yeah, I know about this one. On windows there is no symbolic link like:
/usr/local/cuda/lib64/libcudnn.so -> libcudnn.so.5
/usr/local/cuda/lib64/libcudnn.so.5 -> libcudnn.so.5.1.5
so you need to know the full dll name.
In the master we link against cudnn.lib and cudnn.lib will know the correct dll name but might have the same problem that if you linked with the cudnn.lib for 5.4 it wants to have the 5.4 dll and 5.6 might not work for you.
In 1.1 I think we are still using dynamic load.
I could take a look and see if there is a clean way out of it.

@mrry thanks. Earlier CuDNN 5.1 files were extracted (include, bin, include) in CUDA desinated path. However, somehow they were not placed properly in designate paths.
Post this discussion thread i recheck lib/files (thoroughly), found they were missing. Now extracted at different location and copied in designated CUDA paths. Problem is resolved.
Thanks all friends for extending their support !!
Regards, Rajeev Sharma

@guschmue @mrry @nova77 @gwind55 @girving
Here is final logs (environment - Docker, GPU environment Geforce 1060, and tensorflow with CUDA/cuDNN):
$ python
Python 3.5.2 |Continuum Analytics, Inc.| (default, Jul  5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as tf
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
2017-04-28 09:40:40.028503: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:40.028651: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:40.028777: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:40.028874: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:40.028989: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:40.029113: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:40.029239: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:40.029397: W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
2017-04-28 09:40:41.239629: I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:887] Found device 0 with properties:
name: GeForce GTX 1060
major: 6 minor: 1 memoryClockRate (GHz) 1.6705
pciBusID 0000:01:00.0
Total memory: 6.00GiB
Free memory: 4.99GiB
2017-04-28 09:40:41.239828: I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:908] DMA: 0
2017-04-28 09:40:41.241327: I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:918] 0:   Y
2017-04-28 09:40:41.242344: I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:977] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1060, pci bus id: 0000:01:00.0)
Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: GeForce GTX 1060, pci bus id: 0000:01:00.0
2017-04-28 09:40:41.468151: I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\direct_session.cc:257] Device mapping:
/job:localhost/replica:0/task:0/gpu:0 -> device: 0, name: GeForce GTX 1060, pci bus id: 0000:01:00.0

@guschmue @mrry @nova77 @gwind55 @girving - Friends, i am willing to explore a few image processing code example (C or python) for Self-Driving Vehicle traffic environment (Lights, objects, potholes, Lane marking or traffic contexts etc....for one of my project).
Can anyone help me by suggesting sampled repositories to try out before go ahead with my own example/coding?
Thanks

For the missing cudnn?.dll issue in general (maybe we should open a new issue for this) ...
The important thing first:
If people run into this missing ‘cudnn64_5.dll’ if they installed cudnn6, it is better to ask them to download cudnn5.1 instead of ‘mv cudnn64_6.dll  cudnn64_5.dll’ until we have builds with cudnn6 because there might be some compatibility issues.
Some findings:
After building with cudnn6 (master) bunch of unit tests are failing. As far I can tell cudnn related. I think
this might be also the case on linux since there is no windows specific code here.
Need to take a closer look.
tensorflow/python/kernel_tests/atrous_conv2d_test.py
tensorflow/python/kernel_tests/atrous_convolution_test.py
tensorflow/python/kernel_tests/conv2d_transpose_test.py
tensorflow/python/kernel_tests/conv_ops_3d_test.py
tensorflow/python/kernel_tests/conv_ops_test.py
tensorflow/python/kernel_tests/depthwise_conv_op_test.py
tensorflow/python/kernel_tests/lrn_op_test.py
tensorflow/python/kernel_tests/pooling_ops_3d_test.py
tensorflow/python/kernel_tests/pooling_ops_test.py
tensorflow/python/kernel_tests/pool_test.py
Loading cudnn?.dll on master
Since the master  links now against cudnn.lib, cudnn.lib has the cudnn?.dll burned in that goes with the lib.
The effect of this is that if you had tensorflow-gpu installed and in the future update to a version that is
build with cudnn6 you get this error message
ImportError: No module named '_pywrap_tensorflow_internal'
Failed to load the native TensorFlow runtime.
which will not guide users to install cudnn6 on their system. We need to add figure some way to get a proper error  message to the user. This is maybe part of https://github.com/tensorflow/tensorflow/issues/9170
Loading cudnn?.dll on 1.1
Since 1.1 still uses the dynamic load of the cudnn?.dll and the name of the dll to load comes from CMakefiles.txt. If we want switch to cudnn6 we could either update the dll in CMakefile.txt or we could build the dll name on the fly by using the CUDNN_MAJOR from cudnn.h.
Later might be better but since the master is no longer using the dynamic load might not be worth the change.
In summary I think we need to:

Fix the unit tests for cudnn6
do something for https://github.com/tensorflow/tensorflow/issues/9170 to tell users why what the real
error was when  if we fail to load tensorflow because the wrong cudnn version was installed.
If we want to switch 1.1 to cudnn6 a make a change from in CMakefile.txt to reflect
the new cudnn?.dll name

Thanks @gwind55 It took me the whole day searching for solution

Many thanks! @gwind55 I had the same problem, renamed the file and it worked perfectly!
I spent an insane amount of hours looking for a solution. I'm glad it finally worked out.

@gwind55 this solution works, thx

I had the same problem, and renaming the file works for me too.  Thanks @gwind55

I have cudnn 5.1 and cuda-8.0. cudnn is copied in cuda's directory. I've also appended it's path to the system PATHs as:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin
Also msvcp140.dll is included both in systemWow64 and system32 and I use Python 3.5.2.
What is wrong? Have you faced the same problem?

My programs are working fine now. Only one change I am taking care of
additionally is - (a) low learning rate
On Mon, May 29, 2017 at 10:46 AM, Abolfazl Meyarian <
<EMAIL_ADDRESS>wrote:

I have cudnn 5.1 and cuda-8.0. cudnn is copied in cuda's directory. I've
also appended it's path to the system PATHs as:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin
Also msvcp140.dll is included both in systemWow64 and system32 and I use
Python 3.5.2.
What is wrong? Have you faced the same problem?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/9484#issuecomment-304574105,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AOK79WsXgcVHPCWfMXyUbdePlThtk7AEks5r-lSsgaJpZM4NKELT
.

--
Regards
Rajeev

@RajeevSharma2015
How did you solve this problem ? (ImportError: No module named '_pywrap_tensorflow_internal')

@RajeevSharma2015
???

For users who find this issue when searching for the error message, I've created a script for diagnosing common TensorFlow on Windows installation issues. Please download the script from https://gist.github.com/mrry/ee5dbcfdd045fa48a27d56664411d41c and run python tensorflow_self_check.py. It will print suggestions for how to fix your installation. Let me know if you are still facing problems after running the script.

@mrry  I find the problem is on tensorflow-gpu 1.1.0  .Today, I use your script to check my DLL. It still no problem but can't import ,and I have NVCUDA.dll (I use python35,tensorflow 1.1.0,install succeed).  Then, I download and install tensorflow 1.0.1,and I can import tensorflow-gpu(1.0.1) successfully.
Now, I just want to konw why the version 1.1.0 have problem，and how to solve it.
Here is the message about the problem.(tensorflow 1.1.0)
Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul  5 2016, 11:41:13) [MSC v.1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.

>>> import tensorflow
Traceback (most recent call last):
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 41, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 35, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 30, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "E:\Anaconda3\lib\imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "E:\Anaconda3\lib\imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: DLL load failed: 找不到指定的模块。

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "E:\Anaconda3\lib\site-packages\tensorflow\__init__.py", line 24, in <module>
    from tensorflow.python import *
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\__init__.py", line 51, in <module>
    from tensorflow.python import pywrap_tensorflow
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 52, in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 41, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 35, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "E:\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 30, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "E:\Anaconda3\lib\imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "E:\Anaconda3\lib\imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: DLL load failed: 找不到指定的模块。

Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/install_sources#common_installation_problems

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

I got the same problem,
but ,I  have no the cudnn64_6.dll file..

@gwind55 I had the same problem, renamed the file and it worked perfectly!
I spent so many hours looking for a solution. I'm glad I finally found one. I'm not a Python developer but can't the logs be improved so that you see which DLL failed to load?

sorry I have to correct. I had the wrong CUDnn version installed (6.0), when installing v 5.1 no renaming was necessary.

`>>> import tensorflow as tf
Traceback (most recent call last):
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.py", line 41, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: libnvidia-fatbinaryloader.so.384.69: cannot open shared object file: No such file or directory
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/init.py", line 24, in
from tensorflow.python import *
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/init.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.py", line 52, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.py", line 41, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/home/tensor/anaconda3/envs/tgpu/lib/python3.6/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: libnvidia-fatbinaryloader.so.384.69: cannot open shared object file: No such file or directory
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/install_sources#common_installation_problems
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

exit()
i am getting this error , i installed tensorflow on a new conda environment, can't seem to work

@Nick7hill Try running the script I [mentioned above], and if you still have problems after following its suggestions, feel free to open a new issue to describe them!

@xuxianju Same here. Both 1.0 and 1.1 require cudnn5.1, so if 1.0 works, I'd expect 1.1 to load and work as well. But it doesn't. Were you able to fix this? I had to downgrade and stay with 1.0, which is not nice, since we have the 1.4 release now. And all the releases 1.1, 1.2, 1.3, 1.4 fail to import with these meaningless messages like in your log. Have no idea how to debug it. The script says "failed to import", but everything else is fine, "all required dlls appear to be present".

For tensorflow 1.6 and higher you will get the same error message if your CPU does not support AVX.

This seems like an old issue. I will close it. Please try the installation instructions of the latest version of TensorFlow. If the issue still persist, create a new issue.


YARN-11675. Update MemoryResourceHandler implementation for cgroup v2 support

Description of PR
Cgroup v2 has some changes in various controllers (some changed their functionality, some were removed). This task is about checking if MemoryResourceHandler's implementation need any updates.
How was this patch tested?
For code changes:

[x] Does the title or this PR starts with the corresponding JIRA issue id (e.g. 'HADOOP-17799. Your PR title ...')?
[ ] Object storage: have the integration tests been executed and the endpoint declared according to the connector-specific documentation?
[ ] If adding new dependencies to the code, are these dependencies licensed in a way that is compatible for inclusion under ASF 2.0?
[ ] If applicable, have you updated the LICENSE, LICENSE-binary, NOTICE-binary files?

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trunk passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
javadoc
0m 39s

trunk passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
spotbugs
1m 25s

trunk passed

+1 :green_heart:
shadedclient
34m 33s

branch has no errors when building and testing our client artifacts.

_ Patch Compile Tests _

+1 :green_heart:
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0m 37s

the patch passed

+1 :green_heart:
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1m 19s

the patch passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
javac
1m 19s

the patch passed

+1 :green_heart:
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1m 22s

the patch passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
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1m 22s

the patch passed

+1 :green_heart:
blanks
0m  0s

The patch has no blanks issues.

-0 :warning:
checkstyle
0m 29s
/results-checkstyle-hadoop-yarn-project_hadoop-yarn_hadoop-yarn-server_hadoop-yarn-server-nodemanager.txt
hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager: The patch generated 3 new + 1 unchanged - 0 fixed = 4 total (was 1)

+1 :green_heart:
mvnsite
0m 38s

the patch passed

+1 :green_heart:
javadoc
0m 34s

the patch passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
javadoc
0m 33s

the patch passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
spotbugs
1m 29s

the patch passed

+1 :green_heart:
shadedclient
34m 39s

patch has no errors when building and testing our client artifacts.

_ Other Tests _

+1 :green_heart:
unit
24m 59s

hadoop-yarn-server-nodemanager in the patch passed.

+1 :green_heart:
asflicense
0m 37s

The patch does not generate ASF License warnings.

158m 42s

Subsystem
Report/Notes

Docker
ClientAPI=1.45 ServerAPI=1.45 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6760/5/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/6760

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dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

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Linux d3ea686fcb20 5.15.0-94-generic #104-Ubuntu SMP Tue Jan 9 15:25:40 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / 189d2b15576e176bb50ddd0f4577a3d1dd89c2fd

Default Java
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Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1 /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6760/5/testReport/

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modules
C: hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager U: hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager

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0m 47s

trunk passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

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0m 27s

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+1 :green_heart:
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0m 30s

trunk passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
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0m 26s

trunk passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
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0m 52s

trunk passed

+1 :green_heart:
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20m  5s

branch has no errors when building and testing our client artifacts.

_ Patch Compile Tests _

+1 :green_heart:
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0m 20s

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0m 43s

the patch passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
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0m 43s

the patch passed

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0m 43s

the patch passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
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0m 43s

the patch passed

+1 :green_heart:
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0m  0s

The patch has no blanks issues.

+1 :green_heart:
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0m 13s

the patch passed

+1 :green_heart:
mvnsite
0m 20s

the patch passed

+1 :green_heart:
javadoc
0m 19s

the patch passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
javadoc
0m 20s

the patch passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
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0m 55s

the patch passed

+1 :green_heart:
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19m 58s

patch has no errors when building and testing our client artifacts.

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21m 39s

hadoop-yarn-server-nodemanager in the patch passed.

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0m 24s

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113m 43s

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Report/Notes

Docker
ClientAPI=1.44 ServerAPI=1.44 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6760/6/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/6760

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dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux dccf6577322e 5.15.0-94-generic #104-Ubuntu SMP Tue Jan 9 15:25:40 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / b476d2d6a376f80b2ceeb111a62c66e84d5319fd

Default Java
Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

Multi-JDK versions
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https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6760/6/testReport/

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modules
C: hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager U: hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager

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Thanks @brumi1024 for the review! Rebased and updated the PR with the fix for your comment.
Added a description on the jira ticket as well summarizing the changes comparing to cgroupv1: https://issues.apache.org/jira/browse/YARN-11675

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0m 26s

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+1 :green_heart:
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0m 53s

trunk passed

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20m 21s

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_ Patch Compile Tests _

+1 :green_heart:
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0m 19s

the patch passed

+1 :green_heart:
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0m 44s

the patch passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
javac
0m 44s

the patch passed

+1 :green_heart:
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0m 43s

the patch passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
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0m 43s

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+1 :green_heart:
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The patch has no blanks issues.

+1 :green_heart:
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0m 14s

the patch passed

+1 :green_heart:
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0m 21s

the patch passed

+1 :green_heart:
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0m 19s

the patch passed with JDK Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1

+1 :green_heart:
javadoc
0m 20s

the patch passed with JDK Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

+1 :green_heart:
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0m 53s

the patch passed

+1 :green_heart:
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patch has no errors when building and testing our client artifacts.

_ Other Tests _

+1 :green_heart:
unit
21m 40s

hadoop-yarn-server-nodemanager in the patch passed.

+1 :green_heart:
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0m 24s

The patch does not generate ASF License warnings.

105m 56s

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Docker
ClientAPI=1.44 ServerAPI=1.44 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-6760/8/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/6760

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux 44c51a75455e 5.15.0-94-generic #104-Ubuntu SMP Tue Jan 9 15:25:40 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / 18421d720446fa982e620bd77df0b4f3420d533b

Default Java
Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Ubuntu-11.0.22+7-post-Ubuntu-0ubuntu220.04.1 /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_402-8u402-ga-2ubuntu1~20.04-b06

Test Results
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Max. process+thread count
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modules
C: hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager U: hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-nodemanager

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Thanks @p-szucs for the patch, LGTM. Merging to trunk.


fix(behavior_path_planner): if ego changes lanes turn the signal on

Description
fixes: https://github.com/autowarefoundation/autoware.universe/issues/4470
This PR provides when turn_signal_on_swerving param is set to false; if EGO has to change lanes because of to avoid an obstacle it'll turn the signal on

Tests performed

Not applicable.
Effects on system behavior

Not applicable.
Pre-review checklist for the PR author
The PR author must check the checkboxes below when creating the PR.

[ ] I've confirmed the contribution guidelines.
[ ] The PR follows the pull request guidelines.

In-review checklist for the PR reviewers
The PR reviewers must check the checkboxes below before approval.

[ ] The PR follows the pull request guidelines.

Post-review checklist for the PR author
The PR author must check the checkboxes below before merging.

[ ] There are no open discussions or they are tracked via tickets.

After all checkboxes are checked, anyone who has write access can merge the PR.

@beyzanurkaya do we have issue related to this PR? If so please relate these two.
Can you also give more detail about the PR as well videos, screenshots, text etc

Hi @beyzanurkaya @mehmetdogru :hand: Sorry for late response, and thanks for you fixing.
I'll run evaluator with this PR. Please wait a while...

@satoshi-ota I changed to PR status to draft now since @beyzanurkaya will work on it.

@satoshi-ota @mehmetdogru ready to review

@beyzanurkaya OK. I'll start review :+1:

@beyzanurkaya Basically, it looks good to me but I left one smal suggestion.

@satoshi-ota I made some changes could you review again?

@satoshi-ota I made some changes could you review again?

Sure!


Azure.Messaging.EventGrid 4.22.0 stable?

Library name and version
Azure.Messaging.EventGrid 4.22.0-beta.1
Query/Question
Hi,
Inside my company we have a restriction of using beta nuget packages.
We need to make a decision based on what is the expected date of delivering a stable version after 4.22.0-beta.1 for Azure.Messaging.EventGrid.
Can you help us with some predictions of this work that you are doing?
Environment
4.22.0-beta.1

Hi @axelaceax.  Thank you for reaching out and we regret that you're experiencing difficulties.   The Event Grid service with the namespace feature set is still in beta.  Once the service promotes the feature set to stable, we will release a stable version of the Azure.Messaging.EventGrid package soon after.   To my knowledge, there has not yet been a public announcement of the service timeline to share.

thank you, @jsquire!


Upgrades 'org.springframework.boot' to version '3.1.2' and flyway to 9.21.0

We had previously held off on upgrading FlyWay, due to some changes that were incompatible with Spring Boot. Spring Boot made fixes in version 3.1.2, so now we can upgrade these libraries.
https://github.com/spring-projects/spring-boot/issues/36029
https://github.com/flyway/flyway/issues/3694#issuecomment-1645499387

I do wonder if we should cut a release before merging this one...?

I do wonder if we should cut a release before merging this one...?

No app is running latest snapshot are they?
But then again that would just mean waiting to automate a release Monday and then merging this.


Add stylelint, set up to use for CSS-in-JS

AFAICS, g2 isn't currently using stylelint. It seems like stylelint nowadays supports CSS-in-JS.
In order to prevent bugs like https://github.com/ItsJonQ/g2/issues/266, how about we:

Add stylelint, set it up for CSS-in-JS
Make sure it's run on pre-commit, and via GitHub Actions on every PR.

@ockham Haii! I just tried this out. I don't think stylelint is works too well with how the CSS-in-JS styles are written.
I'm currently having to disable a lot of rules 😅


Support keyword-only function parameters

Following a hitherto undocumented feature of Skylark-in-Java,
which in turn follows Python3,
a function declaration may now include optional parameters
after the *args parameter:
def f(a, b, c=1, *args, d=2, **kwargs)

The parameter d is a "keyword-only" parameter as it can
never by assigned from a positional parameter; all positional
arguments surplus to a, b, and c are put in a tuple and
assigned to args.
To declare a non-variadic function with keyword-only arguments,
the *args parameter is replaced by just *:
    def f(a, b, c=1, *, d=2, **kwargs)

The * parameter is not a real parameter; it just serves as a
separator between the parameter that may be specified positionally
and the keyword-only ones.
Spec proposal at bazelbuild/starlark#23
Fixes #61

I think GitHub is just confused. The account associated with the main comment in the 'conversation' tab is leisure-me but in the commits tab it shows work-me. In any case, it's my work email address.


use the color picker provided by FluentAvalonia

Should resolve #25 by using the inbuilt color picker that came with FluentAvalonia.
Haven't looked too closely at any binding errors, but this does let me remove a lot of xaml so that's nice.

Bizarrely this actually seems to create a secondary binding error. I'm all for pushing this anyway as these errors seemingly don't actually affect anything but it does really bug me that we don't know where they're coming from


Dockerize DMPTool and setup ECS and CodePipeline

Dockerize the DMPTool using dmp-roadmap-cfn as a model. Then setup ECS and a CodePipeline.

@ashleygould I am in the process of dockerizing the DMPTool app and am going to deploy it to Fargate.
I would like for IAS to delegate the dmphub-dev.cdlib.org hosted domain to our account. I ultimately want to do the following with the domains for the DMPTool/DMPHub services:
Ticket for IAS to delegate dmptool-dev.cdlib.org to us

dmptool-dev.cdlib.org -> ALB -> ECS (Hosting DMPTool Rails app)
auth.dmptool-dev.cdlib.org -> Cognito
api.dmptool-dev.cdlib.org -> API Gateway
api.dmptool-dev.cdlib.org/docs -> CloudFront (Swagger UI) (Not sure yet how to do this with Route53)
hub.dmptool-dev.cdlib.org -> CloudFront (Hosting DMPHub React pages and PDFs ... maybe share web assets with DMPTool)

Once we have the dmptool-dev.cdlib.org hosted zone setup and we've got the routing above working, we can get rid of dmphub-dev.cdlib.org

Investigate using Trivy to scan images for vulnerabilities (see confluence Tech-X presentation from 2023-05-18)

Setting this up in the new dmsp_prototyp private repository for now. We will be transitioning to a three Repo setup: 1) Infrastructure (this repo), 2) Rails backend API app, 3) JS UI app

This ticket involves setting up the ECS, CodePipeline and CodeBuild infrastructure

Pipeline and CodeBuild are working properly. Still need to:

Run a Trivy scan is possible (make sure we are running apt-get upgrade properly to pull in the latest patches

Going to need to setup the WAF to block bot traffic. It is in place but just counting at the moment


Jupyter Notebook Data Viewer autoupdate

The Jupyter Notebook Data Viewer is great but should allow automatic refresh of the actual data content.
currently: Data Viewer shows data at the time of opening this tab
request: Allow data Viewer Tab reload the current data - this should be toggled by user since large data sets should not auto-reload by default

(Experimental duplicate detection)
Thanks for submitting this issue. Please also check if it is already covered by an existing one, like:

Bug Report: Jupyter Data Viewer Filter will generate duplicated data in the viewer (#119271)

@vscodebot Nice try, but no.


[W6.6c][W14-B1]Chua Wei Wen

Added user stories to DeveloperGuide.md

@chuaweiwen
Since nothing much to take note of, I will close the PR


«HTML mode» switch on Live demo does nothing.

To reproduce:

Open http://rexxars.github.io/react-markdown/
Enter raw html, e.g.
test
.
Try switching «HTML mode».

Nothing changes on the third step — the text is red independent of the «HTML mode» switch state and always has an onclick handler.
Console has this error logged (among other deprecation-related ones):
Uncaught TypeError: Cannot read property 'props' of undefined
    at value (demo.js:28)
    at Object.executeOnChange (react-dom.js:3828)
    at ReactDOMComponent._handleChange (react-dom.js:7118)
    at Object.ReactErrorUtils.invokeGuardedCallback (react-dom.js:9073)
    at executeDispatch (react-dom.js:3031)
    at Object.executeDispatchesInOrder (react-dom.js:3054)
    at executeDispatchesAndRelease (react-dom.js:2456)
    at executeDispatchesAndReleaseTopLevel (react-dom.js:2467)
    at Array.forEach (<anonymous>)
    at forEachAccumulated (react-dom.js:15515)

Ok. I reported that 25 days ago, will file a public issue in ~5 days if there would be no reply by then.


Lightning 1.6 Release

List of tasks to complete the 1.6.0 Release
Release date: TBA
Feature freeze date: TBA
Up to Feature Freeze
List of 1.6 milestones

[ ] Stable Accelerator API #9932
[ ] Unify Checkpointing conventions #11429

(list incomplete)
Before or after Feature Freeze

[ ] Documentation updates

[ ] Update all pages to the latest accelerator/strategy/devices syntax
[ ] Documentation check (typos, new features, etc. (e.g.  #11739))

[ ] Create the release blog post
[ ] Changelog check
[ ] Create release notes

(list incomplete)
Feel free to edit this page!
cc @justusschock @awaelchli @rohitgr7 @borda

Closing this in favor of issue planning.
Ping me if you have any questions or you want to add an item!


{WIP} default enable_telemetry is False, env info

{WIP} default enable_telemetry is False, env info

default config.yaml

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-> #865
#864

sapling rememnant of #899