makes parser public so that it can be extended

In order to add custom plugins we need to call .use coming out of markdownIt.
This PR simply makes parser public so that it's accessible.

Just to add to this, I tried to make my own custom tokenizer, just so I get unblocked, but the stock plugins are not being exported. That would be ok for me now as well

Hey @ntgussoni, thanks for the submission. Unfortunately, we are currently treating markdown-it as an explicit internal dependency (as you can see by our package.json), and have thus chosen to keep those details private. If you wish to access the parser, it is possible to do so, you just need to mark the tokenizer as any. Given this, please do so at your own risk! 🙂

Thanks for the reply! I see you don't expect to add more syntax to the current, but not having an escape hatch for people that wish to add more functionality (at their own risk) might turn down some adopters.
Is there any roadmap or more detailed vision that we can see? I don't want to keep bothering you with this stuff if it's not something is in the the plan

but not having an escape hatch for people that wish to add more functionality (at their own risk) might turn down some adopters.
@ntgussoni there is an escape hatch, as described above. We just want the inherent risk to be encoded into that escape hatch, via the unsafe types. Hope that makes sense to you.

As for the roadmap, that is a great question. Once we get firm roadmap plans together, we will share them as a GitHub project.


⚠ Bofrost.at has degraded performance

In 4310abd, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 998 ms

Resolved: Bofrost.at performance has improved in c54f0a3 after 6 minutes.


Version 3.6 with arch x64 not found

https://github.com/macarthur-lab/variant-curation-portal/actions/runs/3612357073/jobs/6087412250

Related #235


Incorporate EDTFLevel0DateString

invenio-rdm-records defined an EDTFLevel0DateString marshmallow schema field that could be used by the broader framework.
Copy it here if useful.
See definition https://github.com/inveniosoftware/invenio-rdm-records/blob/master/invenio_rdm_records/marshmallow/fields.py#L17
Came up from: https://github.com/inveniosoftware/invenio-rdm-records/pull/79

Done in Invenio-Resources-Resources/Babel-EDTF/Marshamllow-Utils


Add 1 icon

Description
Add 1 new icon for Microsoft math solver
Type of change
:x: Bug fix (non-breaking change which fixes an issue)
:white_check_mark: Icon addition (non-breaking change that adds/modifies Lawnicons's icons)
:x: General change (non-breaking change that doesn't fit the above categories like copyediting)
Icons addition information
Icons added

Math (com.microsoft.math)

@thismoon nice


docz serve not reading supplied port

Bug Report
port is not read from configuration files or env vars when running docz serve
A clear and concise description of what the bug is.
add DOCZ_PORT to .env and run docz serve
or
run docz serve --port 7000
Expected behavior
expect to run on supplied port
Environment

docz version: 2.2.0
OS: OSX 10.14.2
Node/npm version: Node 12.8.1/6.13.1

Thanks @tylerthehaas for reporting this. It's fixed in<EMAIL_ADDRESS>(yarn add docz@next) and will be released with<EMAIL_ADDRESS>


Add missing Fluentd input metric to fix empty panels

[!warning]
This is a public repository, ensure not to disclose:

[x] personal data beyond what is necessary for interacting with this pull request, nor
[x] business confidential information, such as customer names.

What kind of PR is this?
Required: Mark one of the following that is applicable:

[ ] kind/feature
[ ] kind/improvement
[ ] kind/deprecation
[ ] kind/documentation
[ ] kind/clean-up
[ ] kind/bug
[x] kind/other

Optional: Mark one or more of the following that are applicable:

[!important]
Breaking changes should be marked kind/admin-change or kind/dev-change depending on type
Critical security fixes should be marked with kind/security

[ ] kind/admin-change
[ ] kind/dev-change
[ ] kind/security
[ ] kind/adr

What does this PR do / why do we need this PR?
While working on PR https://github.com/elastisys/compliantkubernetes-apps/pull/2242, I noticed we had panels in the fluentd dashboard that used metrics that we did not seem to expose. I found an example fluentd configuration to expose this metric here.
Information to reviewers

As mentioned in https://grafana.com/grafana/dashboards/13042-fluentd-1-x/:

Input filter by tag can produce insane amount of labels for metric

Hence tag ${tag_parts[0]} is used, which reduced the amount of labels for this metric quite significantly in my dev environment:

Which produces metrics for the tags seen below:

Checklist

[x] Proper commit message prefix on all commits

Change checks:

[x] The change is transparent
[ ] The change is disruptive
[ ] The change requires no migration steps
[ ] The change requires migration steps
[ ] The change upgrades CRDs
[ ] The change updates the config and the schema

Metrics checks:

[ ] The metrics are still exposed and present in Grafana after the change
[ ] The metrics names didn't change (Grafana dashboards and Prometheus alerts are not affected)
[ ] The metrics names did change (Grafana dashboards and Prometheus alerts were fixed)

Logs checks:

[ ] The logs do not show any errors after the change

Pod Security Policy checks:

[ ] Any changed pod is covered by Pod Security Admission
[ ] Any changed pod is covered by Gatekeeper Pod Security Policies
[ ] The change does not cause any pods to be blocked by Pod Security Admission or Policies

Network Policy checks:

[ ] Any changed pod is covered by Network Policies
[ ] The change does not cause any dropped packets in the NetworkPolicy Dashboard

Audit checks:

[ ] The change does not cause any unnecessary Kubernetes audit events
[ ] The change requires changes to Kubernetes audit policy

Falco checks:

[ ] The change does not cause any alerts to be generated by Falco

Bug checks:

[ ] The bug fix is covered by regression tests

What values does the tag_parts[0] take? Is it kubernetes, kubeaudit, other, authlog? I see kernel and kubelet from the screenshot you shared.

What values does the tag_parts[0] take? Is it kubernetes, kubeaudit, other, authlog? I see kernel and kubelet from the screenshot you shared.

It seems like it gets kubernetes, kubeaudit, authlog and then some other as you saw in the image, maybe we want to filter only on our normal indicies instead of .**?

Did this increase the fluentd resource usage by any significant amount?

Regarding resource usage, I first deployed it in a cluster with Calico running a version causing this issue, which generates a ton of error logs for Calico which did cause quite high CPU load for some of the forwarder pods:

Memory seemed to be about the same. After changing to a fixed patch version of Calico, the CPU usage it was pretty much as before:

And it could also be seen as the input entries went down:

So the input metric was another indicator for the calico issue, but it also increased fluentd forwarders CPU usage quite a lot, but that might also have been since calico was using up a lot more CPU on the nodes than it should.

How will the behaviour be with index per namespace? Does it retain kubernetes as the tag or will it generate one tag per namespace?

How will the behaviour be with index per namespace? Does it retain kubernetes as the tag or will it generate one tag per namespace?

Just tested enabling indexPerNamespace in my cluster and  the tags seems to stay the same, e.g. kubernetes, kubeaudit etc.


Fix code scanning alert - Incomplete string escaping or encoding

Tracking issue for:

[ ] https://github.com/OpenGoose/chipsql-engine/security/code-scanning/1

Fixed commit: 2bd6509b863e507b58cae79788ffce065818ade9


feat: update ftltest for injected verb clients

Don't forget you'll need to update the customer code to use this!

Don't forget you'll need to update the customer code to use this!

have been working this up today :)

think i'll wait til monday to merge this one because it will require customer changes, and i'd ideally like to couple those changes with the announcement/change for the new verb client stuff - which is much more invasive for a friday 😄


feature request: date_create field for all

record insertion time for all tables

This information is available via block_index (master branch) or block_num (1.8 branch).

date_create of block !== date_create of row in db
block_num === height of block (not timestamp)
@tbfleming

You can get the timestamp from the block_info table.

@tbfleming

You can get the timestamp from the block_info table.

https://github.com/EOSIO/history-tools/issues/13#issuecomment-500472318

date_create of block !== date_create of row in db

block production time !== timestamp of saving data to the database
it would be nice to keep both parameters

What is the use case for that?

No response to use case question


[Feat] Add Gesture

📝 작업 목적

⚒ Title
Add Gesture

📜 Description
Gesture 를 추가합시다

🛠 Tasks

[ ] UIKit

[x] Internal logic
[ ] External customize

[ ] SwiftUI

[ ] Internal logic
[ ] External customize

All gesture's will be "Tap" Gesture.
Can customize only the properties from "TapGesture"


Complete win32-arm64 implementation

A solid win32-arm64 build will start rolling out to insiders pretty soon. A few things are still left undone:

[ ] Setup @joaomoreno: Can't fix without major upgrade to Inno Setup 6, which is risky
[ ] Tests @joaomoreno: Can't fix without ARM64 build machine
[ ] CodeHelper.exe @bpasero
[x] rg.exe @roblourens

Currently they should still work since Windows 10 ARM ships with an emulation layer for x86, which these components are running on. But it would be great to get native performance on each of them.

PS C:\Users\jomo\Downloads\VSCode-win32-arm64-1.46.0-insider> Get-ChildItem . -Recurse -Include *.exe,*.dll,*.node | ForEach-Object { [PSCustomObject]@{ Name = $_.Name; Machine = dumpbin /HEADERS $_.FullName | Select-String -Pattern machine } }

Name                     Machine
----                     -------
keytar.node                          AA64 machine (ARM64)
iselevated.node                      AA64 machine (ARM64)
keymapping.node                      AA64 machine (ARM64)
watchdog.node                        AA64 machine (ARM64)
conpty.node                          AA64 machine (ARM64)
conpty_console_list.node             AA64 machine (ARM64)
pty.node                             AA64 machine (ARM64)
winpty-agent.exe                     AA64 machine (ARM64)
winpty.dll                           AA64 machine (ARM64)
spdlog.node                          AA64 machine (ARM64)
nsfw.node                            AA64 machine (ARM64)
rg.exe                   {             14C machine (x86),                    32 bit word machine}
sqlite.node                          AA64 machine (ARM64)
crypt32.node                         AA64 machine (ARM64)
winregistry.node                     AA64 machine (ARM64)
vsda.node                            AA64 machine (ARM64)
foreground_love.node                 AA64 machine (ARM64)
CreateMutex.node                     AA64 machine (ARM64)
windows_process_tree....             AA64 machine (ARM64)
CodeHelper.exe                        14C machine (x86)
libEGL.dll                           AA64 machine (ARM64)
libGLESv2.dll                        AA64 machine (ARM64)
Code - Insiders.exe                  AA64 machine (ARM64)
ffmpeg.dll                           AA64 machine (ARM64)
libEGL.dll                           AA64 machine (ARM64)
libGLESv2.dll                        AA64 machine (ARM64)
vk_swiftshader.dll                   AA64 machine (ARM64)

There is no windows ARM azure pipelines agent, right? Do you know anything about cross-compiling for ARM on windows, or do we have a build machine that we can set up?

There is no ARM build machine no. Cross compilation seems possible for C++ since the ARM tooling is installed in the regular Windows agents. But Rust is another story, it should be quite straightforward to compile rg to ARM64. Is that what you were thinking?

I have to get it to cross compile PCRE2 which is C which I guess should be possible, and the Rust code should be straightforward to build for arm but I haven't convinced it to work yet, I'll keep working on it.

Today, I tried both the 64bit system install and zip file manual install of vs code win32-64x - 1.48.2  and both versions had the same issue with codehelper. Upon opening the vscode app as either a user and or an admin, codehelper.exe will not open and creates the error in the attached screen shot. A.
Also, after opening vscode for the first time, regardless of whether you open as an administrator or a user, the .vscode folder (that houses extensions) is added to the folder associated with the primary windows user rather then a folder designated by the admin. Is that a known issues associated with this thread. As a result of this specific issue, I am unable to utilize vscode for my current project. Thanks to everyone for your time and input.
![codehelper_vs_code_error_8_31_20]
(https://user-images.githubusercontent.com/20747769/91774822-b2d3f800-ebb7-11ea-8163-3780b110e3bf.PNG)

Update - I located codehelper.exe within C:\Windows\System32\my-app\resources\app\out\vs\platform\files\node\watcher\win32 folder and changed settings within codehelper.exe  properties/compatibility to run on Windows 8 compatibility mode and as an admin. I re-opened VSCode and as of now I no longer receive the "app could not start" error for codehelp.exe. I will provide another update after more extensive testing and simply utilizing vscode to ensure full issue resolution.

@rmourey26 This is irrelevant to this issue. Please file a separate issue if you have a problem.

Closing this bundle. The issue remains for traceability.


Make the CI build work

Resolve compile warnings
Always shutdown

Server should always shut down after last commit in this
/cc @cesarbs @halter73

Crazy town! Lights are green! --> https://github.com/aspnet/KestrelHttpServer/pull/635

@halter73 has the proper fix here: https://github.com/aspnet/KestrelHttpServer/commit/7455e11b82e95175f157733219b82be84f34e0b8

I'm fairly certain the CI hangs are fixed by this commit. That's why I removed the same FrameworkSkipConditions in #623. The commit message should explain why the fix makes the second call to uv_run terminate reliably.
I think this is a more appropriate than setting the IsBackground property on the thread.

Is obviously better to have the cause dealt with rather than just the symptom :)
Might be worth still adding the the IsBackground = false for #if !DEBUG? So issues still get seen for testing but always stops in production (with the actual good clean up code in #623)

I think the #if !DEBUG thing is a good idea.

Want to add it to #623? Will close this and the other one.

Will do


Allow TxBuilder to attach a range of outputs

TxBuilder can attach a range of tuples that have an Output and a Hash as its elements.
This can be used as a helper function to merge UTXOs.
Relates faucet#14

I think we can easily aggregate outputs scattered across multiple transactions. It's a very good feature.


Deprecated since Symfony 5.4 and PHP 8.0

After an app is updated to Symfony 5.4 there are few deprecations added, which are connected with Google\Model and Google\Collection.
These deprecations are:

Method "ArrayAccess::offsetGet()" might add "mixed" as a native return type declaration in the future. Do the same in implementation "Google\Model" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "ArrayAccess::offsetExists()" might add "bool" as a native return type declaration in the future. Do the same in implementation "Google\Model" now to avoid errors or add an explicit @return annotation to suppress this message
Method "ArrayAccess::offsetSet()" might add "void" as a native return type declaration in the future. Do the same in implementation "Google\Model" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "ArrayAccess::offsetUnset()" might add "void" as a native return type declaration in the future. Do the same in implementation "Google\Model" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "Iterator::rewind()" might add "void" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "Iterator::current()" might add "mixed" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "Iterator::key()" might add "mixed" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "Iterator::next()" might add "void" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "Iterator::valid()" might add "bool" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "Countable::count()" might add "int" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "ArrayAccess::offsetExists()" might add "bool" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "ArrayAccess::offsetGet()" might add "mixed" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "ArrayAccess::offsetSet()" might add "void" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.
Method "ArrayAccess::offsetUnset()" might add "void" as a native return type declaration in the future. Do the same in implementation "Google\Collection" now to avoid errors or add an explicit @return annotation to suppress this message.

@ArtemBurykin Hello, which version do you use?

@ArtemBurykin Hello, which version of the package do you use?

@3PSY0N Hello, I use 2.12.1

Sane issue here on Symfony 5.4.1 on PHP 7.4.26 with version 2.12.1.

This has been fixed since https://github.com/googleapis/google-api-php-client/pull/2200


Remove redundant kernel floor function

Fix for issue #52

Seems there's something wrong with the CI process, it's failing, seems to have nothing to do with my code though.

Yeah CI is broken but your code is fine lmao, I'll merge it in. I really need to fix CI but I am in a bit of a squeeze with work and uni right now.


[ASCII-1332] Runtime settings component

Created the runtime settings component based on the RFC
The PR only adds the implementation and tests. On following PR we are going to change how the different agent processes configure their runtime settings
Since there is behavior change there is no need to QA + there are unit tests as part of the PR

/merge


Hmm, that's interesting. name and content attributes are not present in the EPUB 3 specification but they are allowed in EPUB 2 [1, 2] and handled correctly by EpubReader in that case.
I will try to get Adobe Indesign and see what's going on there.
Thanks for the notice!

I will close and reopen this pull request to restart the build check.

Implemented in PR https://github.com/vers-one/EpubReader/pull/49.
@arctouch-camilovilela, thank you for suggestion!


added remove_column method for TreeView

Hey guys, it seems that remove_column was missing for the TreeView.
It also needs get_columns but I'm not sure how you guys handle GList's so left for someone else to implement that.

Thanks for the PR! The change looks good to me.

Seems good to me too, I merge. Thanks for your work !


[SPARK-12046] [DOC] [1.6] ScalaDoc and JavaDoc fixes

This PR fixes several issues in our Scala and Java API doc.

Hides spark.memory package

Hides spark.examples package

Fixes ScalaDoc unordered list format through out the code base
Unordoreed list in ScalaDoc requires an extra space before - or *, i.e.:
/**
  * A list:
  *
  *  - Item 1
  *  - Item 2
  */

rather than
/**
  * A list:
  *
  * - Item 1
  * - Item 2
  */

Otherwise the list won't be properly rendered.

Some other minor formatting issues

Remaining issues that I haven't figured out a proper fix:

:: DeveloperApi :: badge is not rendered properly on my local machine, but not sure whether it's an environmental issue.

akka package still appears in ScalaDoc root package page, even though it's already filtered in SparkBuild.scala.

Seems that most stuff in spark.util shouldn't be public, e.g.

RpcUtils
InnerClosureFinder

But they've been there for a long time. Not sure whether they are already considered as part of the public API?

KinesisUtilsPythonHelper shows up in JavaDoc even though it's marked as private

cc @rxin

Test build #46878 has started for PR 10039 at commit 81d973b.

LGTM

LGTM too

Test build #46878 has finished for PR 10039 at commit 81d973b.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/46878/
Test FAILed.

test this please

Test build #46896 has started for PR 10039 at commit 81d973b.

Test build #46896 has finished for PR 10039 at commit 81d973b.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/46896/
Test FAILed.

Merged build finished. Test FAILed.

retest this please

retest this please

retest this please

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/46916/
Test FAILed.

Merged build finished. Test FAILed.

retest this please

test this please

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/46919/
Test FAILed.

Merged build finished. Test FAILed.

Merged build finished. Test FAILed.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/46920/
Test FAILed.

should we also update master?

Jenkins, retest this please.

Test build #46938 has started for PR 10039 at commit 81d973b.

Test build #46938 has finished for PR 10039 at commit 81d973b.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/46938/
Test FAILed.

I think we need to delete the hive-exec jar from amp-jenkins-worker-03. The failure of https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/46938/consoleFull was caused by a bad hive jar in the maven/ivy cache.

@yhuai which JAR specifically? I can log in to that machine and remove it.

@JoshRosen I guess it's safe to simply remove all Hive 1.2.1 and 1.2.1.spark jars in .m2 and .ivy2.

@yhuai Sent PR #10063 to backport this one to master.

Can you close this now?

https://github.com/apache/spark/pull/10063 is in both master and branch 1.6. We can close this.


Specify Positions Sheet Can Move To

Description
The option to specify the available positions the bottom sheet can move to should be available.
Motivation
There are cases where the middle position state is not necessary to have and even hinders the user experience. Furthermore, dynamic control over the available states would allow for some complex UI design currently not possible, such as allowing a sheet to react to the content inside by changing it's allowed states.
Proposed Solution
Ideally, this would be made available by offering an optional parameter in the constructor to pass in a binding of an array containing all of the allowed position states. This would allow flexibility for static construction of a bottom sheet as well as the dynamic changing of the allowed states.
Example
A static example:
.bottomSheet(bottomSheetPosition: $bottomSheetPosition, availablePositions: [.bottom, .top], resizeable: true, mainContent: {
    // Content
}

A dynamic example:
@Binding var availablePositions: [BottomSheetPosition] = [.bottom, .top]
.bottomSheet(bottomSheetPosition: $bottomSheetPosition, availablePositions: $availablePositions, resizeable: true, mainContent: {
    // Content
}

Yes i think this is an awesome idea and I already thought about doing it.
But I would take it a step further, but im sot sure what would me the best way to implement it, that's why I wasn't working in it jet.
Description
Same idea, but you also have the option to add more states and set the position for any state.
Proposed Solution
Maybe we can archive this by making  BottomSheetPosition a class or struct and then subclassing BottomSheetPosition. Or we accept a enum of type CGFloat in the constructor.
Also we would need the user to provide us with the functions for the Drag Indicator (switchPositionIndicator) and the setting of the states (switchPositionUp and switchPositionDown).
Example
SUBCLASSING
struct CustomBottomSheetPosition: BottomSheetPosition {

    let cases: [String: Int] = [top : 1, middle : 0.6]

    func switchPositionIndicator() {
        //
    }

    func switchPositionUp() {
        //
    }

    func switchPositionDown() {
        //
    }
}

ENUM
public enum BottomSheetPosition: CGFloat {
    case top = 0.1, topMiddle = 0.6, middle = 0.4, hidden = 0
}

Problems
SUBCLASSING
Im not sure what data type to use for the cases and how and where to pass in the subclass. This is still a very theoretical concept, but I think it is way better than just using predefined states. I also think that I would provide a couple of predefined BottomSheetPosition for the most common use cases. (2 States, 3 States)
ENUM
With an enum Im not sure how to implement switchPositionIndicator etc.

@dbarsamian Hey please have a look at #5 and tell me your thoughts about this solution and if you have any ideas to improve it.


cnn trainer impl and test.

mainly add:
towhee/cnn_trainer/cnn_trainer.py
towhee/cnn_trainer/trainer_utils.py
towhee/tests/cnn_trainer/test_cnn_trainer.py

Codecov Report

Merging #112 (67b5a76) into main (9ccb212) will increase coverage by 1.10%.
The diff coverage is 75.32%.

@@            Coverage Diff             @@
##             main     #112      +/-   ##
==========================================
+ Coverage   79.74%   80.85%   +1.10%
==========================================
  Files          72       76       +4
  Lines        2548     2815     +267
  Branches      234      263      +29
==========================================
+ Hits         2032     2276     +244
- Misses        439      440       +1
- Partials       77       99      +22

Impacted Files
Coverage Δ

towhee/cnn_trainer/cnn_trainer.py
72.63% <72.63%> (ø)

towhee/cnn_trainer/trainer_utils.py
80.00% <80.00%> (ø)

towhee/tests/cnn_trainer/test_cnn_trainer.py
92.00% <92.00%> (ø)

towhee/dataset/image_datasets.py
94.59% <100.00%> (ø)

towhee/cnn_trainer/trainer_callback.py
68.22% <0.00%> (+18.74%)
:arrow_up:

Continue to review full report at Codecov.

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GHA CI failures: [error] Process completed with exit code 137.

https://github.com/skupperproject/skupper-router/runs/7508068051?check_suite_focus=true#step:28:1535
This failure has appeared in the last week. Best I can tell from googling the above error message is that the CI container is being OOMed. There's very little information available to debug this.
Unclear if this is caused by an issue with the router - memory leak? - or if something in the GHA CI has changed recently.

I think this is ecode from CTest process itself, not from Docker running the container.
137 = 128 + 9, so it is a SIGKILL signal, without any more specific reason given. Why would anything sigkill a process in GHA? OOMKill is probably an option. Or maybe GitHub started running ChaosMonkey ;P
https://tldp.org/LDP/abs/html/exitcodes.html

Notice that container was properly stopped in one of the final cleanup GHA steps...
Also, upload of logs failed with 500 HTTP errors, maybe more things went wrong on GHA side...
I'm thinking two options what to do next

https://en.wikipedia.org/wiki/Mokusatsu
add a sudo dmesg dump upon failure, assuming we can run that inside container

ChaosMonkey! Of course! :)

https://www.githubstatus.com/ says all green. Which maybe means that everything is broken, including monitoring!

[  582.053008] oom-kill:constraint=CONSTRAINT_NONE,nodemask=(null),cpuset=/,mems_allowed=0,global_oom,task_memcg=/actions_job/201eb8b38cc9cafecfbfe1222d53c4f7e32083664a41a206eb4cace034d0fbcf,task=skrouterd,pid=5229,uid=0
[  582.053035] Out of memory: Killed process 5229 (skrouterd) total-vm:[1](https://github.com/skupperproject/skupper-router/actions/runs/3243441690/jobs/5318163122#step:36:1)[33](https://github.com/skupperproject/skupper-router/actions/runs/3243441690/jobs/5318163122#step:36:34)681204712kB, anon-rss:491828kB, file-rss:0kB, shmem-rss:0kB, UID:0 pgtables:[41](https://github.com/skupperproject/skupper-router/actions/runs/3243441690/jobs/5318163122#step:36:42)16kB oom_score_adj:0

It's an OOM kill! https://github.com/skupperproject/skupper-router/actions/runs/3243441690/jobs/5318163122#step:33:964

anon-rss:383472kB should be the relevant value for OOM kill. Value of total-vm is going to be big anyways, because that always happens with sanitizers, and that should mean nothing. RSS is the actual used memory here.

/me thinking that tsan is configurable, and there are options that influence how much memory it takes. One of the important ones is the depth of stacktraces to capture, history_size, memory_limit_mb, and common flag malloc_context_size,

https://github.com/google/sanitizers/wiki/ThreadSanitizerFlags
https://github.com/google/sanitizers/wiki/SanitizerCommonFlags

According to https://docs.github.com/en/actions/using-github-hosted-runners/about-github-hosted-runners#supported-runners-and-hardware-resources

Hardware specification for Windows and Linux virtual machines:
2-core CPU (x86_64)
7 GB of RAM
14 GB of SSD space

And looking at previous fails, the oom-killed router was occupying something like 481 MB of RSS. Then there is other about 25 routers running at the same time, taking between 248 MB and 34 MB each. See table at https://docs.google.com/spreadsheets/d/1OhB0Kh4sahuMawFRdrJCTlB7yAB1t9dh_PlfgY91OIo/edit the last column.
What test needs 25 routers at the same time? Isn't that a bit extravagant? Can the test maybe detect that tsan is running and be skipped for that? (The disadvantage of messing with the tsan options is that wed get incomplete stacktraces when tsan triggers, because it would not have enough memory to maintain backtraces for each thread and variable access.)

According to https://docs.github.com/en/actions/using-github-hosted-runners/about-github-hosted-runners#supported-runners-and-hardware-resources

Hardware specification for Windows and Linux virtual machines:
2-core CPU (x86_64)
7 GB of RAM
14 GB of SSD space

And looking at previous fails, the oom-killed router was occupying something like 481 MB of RSS. Then there is other about 25 routers running at the same time, taking between 248 MB and 34 MB each. See table at https://docs.google.com/spreadsheets/d/1OhB0Kh4sahuMawFRdrJCTlB7yAB1t9dh_PlfgY91OIo/edit the last column.
What test needs 25 routers at the same time? Isn't that a bit extravagant?

I don't think a single test starts up 25 routers at once. The system_tests_tcp_adaptor.py starts up 9 routers (3 interior and 6 edge routers). Could it be that since we are running tests in parallel, several tests run at the same time and the sum total of all routers started by those tests could be 25 ?

I don't think a single test starts up 25 routers at once. The system_tests_tcp_adaptor.py starts up 9 routers (3 interior and 6 edge routers). Could it be that since we are running tests in parallel, several tests run at the same time and the sum total of all routers started by those tests could be 25 ?

🤦🏽 Yes, thats probably it, I should've thought of that. So, the fix should be to change https://github.com/skupperproject/skupper-router/blob/afd6aa191dfb3e9ef47f656f3d75925e25f3485f/.github/workflows/build.yaml#L532 to read what it was some time ago, that is, revert this PR https://github.com/skupperproject/skupper-router/pull/563 here
Maybe there can be 6 tests in parallel, 2 in parallel runs long time...


DO NOT MERGE - test pr

Just testing out being able to post links to all pages in the preview that were changed in a PR

@sean1588 are you still using this for testing?

Kind of. It is something I started on but need to come back to. I'll close it out for now and can always reopen when I get back to it.


Generating bif files task not progressing and stuck at 0%

The initial generate bif files has been stuck at 0% for more than a couple of hours now no progress made.
Operating System - Windows 10
Installation - Windows Installer

How big is your library and what sort of hardware are you running it on? It's a pretty intensive process and can take some time. If you check the jellyfin logs do you see messages about starting / successfully creating trickplay files?

As was suggested check to logs so you can get an idea what it is doing.

Sorry closing this issue. Took forever, but finally they were generated, and consecutive tasks are happening as intended.

yeah seems like it is working for me too now. But takes really forever.


De-flake TestPseudoConsolePowershell

The test periodically fails once in awhile, perhaps due to it not being a great test in general or there being an actual bug somewhere. This issue will track de-flaking the test, wherever the fix may belong.
https://github.com/microsoft/hcsshim/blob/040cbe5e2578a2741d33e7de1e8969aa95cc2255/internal/exec/exec_test.go#L178

Skip for now https://github.com/microsoft/hcsshim/pull/1285/


toggle checks

it was forgotten feature. so added.

travis-ci is good worker!
I just code in GitHub, so I forgot. I'm sorry...

"Toggle all" works in the todoapp already. Closing.


Should be able to add notes even without contacting the PT

You are currently unable to add notes if you have not indicated you have reached the PT. You should be able to add notes regardless of that step.
Tagging @colinxfleming to label this note as appropriate.

Can recreate on my end. Message from the logs:
Started PATCH "/pregnancies/57814946311c88114aefb3da/notes" for ::1 at 2016-07-09 14:58:22 -0400

ActionController::RoutingError (No route matches [PATCH] "/pregnancies/57814946311c88114aefb3da/notes"):

Likely solvable via form edit

Stowing this for now because I couldn't solve in a half hour. The general story is as follows:

For whatever reason, on the first load, it doesn't work at all
It also seems to be happening to the urgent_flag
It seems to sort itself out after that point -- after a reload notes and other things seem to save normally, it sends payloads to the proper endpoints, etc

Something similar to this seems to affect the 'continue' button the pledge modal

here's the part of the html that changes on reload
working

        <input name="utf8" type="hidden" value="✓"><input type="hidden" name="_method" value="patch">

<input name="pregnancy[urgent_flag]" type="hidden" value="0"><input type="checkbox" value="1" name="pregnancy[urgent_flag]" id="pregnancy_urgent_flag"> Flag this patient as urgent

working

        <form id="urgents-form" class="text-right text-danger edit_pregnancy" role="form" action="/pregnancies/57a3cdc9d6519f00011c8b36" accept-charset="UTF-8" data-remote="true" method="post"><input name="utf8" type="hidden" value="✓"><input type="hidden" name="_method" value="patch">

<input name="pregnancy[urgent_flag]" type="hidden" value="0"><input type="checkbox" value="1" name="pregnancy[urgent_flag]" id="pregnancy_urgent_flag"> Flag this patient as urgent

</form>

I think the relevant code is in app/views/pregnancies/_notes.html.erb line 17


[RFC] Encoding of integer variable with binary variables (Aqua optimization)

I propose a framework of converter of OptimizationProblem and encoding of integer variable with binary variables for Qiskit Aqua optimization stack.

This should be implemented as part of #11.


Access regression, classification and masks submodel outputs

Hi,
Can one easily retrieve outputs from the regression, classification and masks submodel ?
The following trick cannot work because of the submodel embedding in a keras.Models object for each of these processes (different graphs - Keras won't allow to mix their inputs/outputs):
model = maskrcnn

regression_feature_extractor = keras.Model(inputs = model.input, outputs= model.get_layer(name="regression_submodel").get_layer("pyramid_classification_3").output)

classification_feature_extractor = keras.Model(inputs = model.input, outputs= model.get_layer(name="classification_submodel").get_layer("pyramid_classification_3").output)

mask_feature_extractor = keras.Model(inputs = model.input, outputs= model.get_layer(name="mask_submodel").get_layer("pyramid_classification_3").output)

Yet, I would like to get the features so as to perform further computations on these.
One way would be to build one model for each task, but model slicing in Keras is not an easy task, especially for non-sequential models (with different streams as maskrcnn exhibits), where tracking inbounds nodes at each layer is not convenient when you have several inputs for some layers (P3 --> P7 feature maps).
Any easy idea, workaround to get this done ?
Thanks !

Hi, the easiest way to do this would be to fork this repo and pass them as outputs in the model creation


Merge the latest tf2onnx commits.

commit 022b718e37e2576155939b2b8abbe9301820d541

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.1 out of 8 committers have signed the CLA.:white_check_mark: wenbingl:x: nbcsm:x: ziyuang:x: guschmue:x: lucienwang1009:x: mindest:x: zhijxu-MS:x: prasanthpulYou have signed the CLA already but the status is still pending? Let us recheck it.

install requests to fix build?


Wayland DPI scaling

DPI scaling doesn't work on Wayland. The text gets bigger but is not rendered at a higher resolution and thus looks pixelated and blurry.

This should be fixed when we make our own native Wayland backend.


AP-2326: Ensure some blocks are omitted from passported XML

What
Link to story
Updated tests to ensure the required values are not generated in passported applications
Notes:

the family proceeding bock is https://github.com/ministryofjustice/laa-apply-for-legal-aid/blob/master/config/ccms/attribute_block_configs/base.yml#L129-L140
Also removed a duplicated block from the base.yml

Checklist
Before you ask people to review this PR:

[x] Tests and rubocop should be passing: bundle exec rake
[x] Github should not be reporting conflicts; you should have recently run git rebase master.
[x] There should be no unnecessary whitespace changes. These make diffs harder to read and conflicts more likely.
[x] The PR description should say what you changed and why, with a link to the JIRA story.
[x] You should have looked at the diff against master and ensured that nothing unexpected is included in your changes.
[x] You should have checked that the commit messages say why the change was made.

Codecov Report

Merging #2624 (9ce5d34) into master (302d154) will not change coverage.
The diff coverage is n/a.

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##            master     #2624   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files          530       530
  Lines        10888     10888
=========================================
  Hits         10888     10888

Continue to review full report at Codecov.

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Rebased on master


Changed 'New Release' popup message

I was fixing spelling error (Detect a new... -> Detected a new...).
Then I thought that also popup heading and message could be improved. Feel free to dismiss this change if it is not ok per your standards.

thanks for the help, this string needs to be moved out to locale files later.


Allow projection properties to be of type object

This PR allows projection properties to be of type object
As described in the documentation (https://vega.github.io/vega/docs/projections/) the fit property can be either an Array or Object
Fixes https://github.com/vega/vega-parser/issues/71
I would be happy to add a test for this case, but I failed to extend the util module with vega-geo and vega-transforms at the same time -> need help

var tape = require('tape'),
    util = require('vega-util'),
    vega = require('vega-dataflow'),
    parse = require('../').parse;

// FIXME: Fails here because it can't extend the util module with transforms and geo at the same time
util.extend(vega.geo, require('vega-geo'));
util.extend(vega.transforms, require('vega-transforms'));

var data = {
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {},
      "geometry": {
        "type": "Point",
        "coordinates": [
          8.547449111938477,
          47.365222618998935
        ]
      }
    }
  ]
};

tape('Parser parses Vega specs with projection using fit property', function(test) {
  var spec = {
    "data": [
      {
        "name": "map",
        "values": [data],
        "format": { "type": "json" },
        "transform": [
          { "type": "geopath", "projection": "projection" }
        ]
      }
    ],
    "projections": [
        {
          "name": "projection",
          "type": "mercator",
          "fit": {},
          "size": [200, 200]
        }
    ]
  };

  var dfs = parse(spec);

  test.equal(dfs.operators.length, 31);

  test.end();
});

Thanks for the PR! Much appreciated. I ended up taking a slightly different approach to fixing this. I also added a new test case inspired by your draft above.


[docker] fix build

Motivation
Fix build
Have you read the Contributing Guidelines on pull requests?
(Write your answer here.)
Test Plan
./docker/mint/build.sh
Related PRs
(If this PR adds or changes functionality, please take some time to update the docs at https://github.com/libra/website, and link to your PR here.)

@bors-libra r+

:pushpin: Commit 9b83d81 has been approved by davidiw

:hourglass: Testing commit 9b83d815f5a177f4f3c5f030a90e3e8bc8d9d9de with merge dea6728ade42a4103be6aa3dfc8d4b213758b245...

:sunny: Test successful - checks-circle_commit_workflow
Approved by: davidiw
Pushing dea6728ade42a4103be6aa3dfc8d4b213758b245 to master...


extending the API

... understanding more it seems the problem does not exist ... see last answer
Currently the API works but is a bit limited.
We can upload an initial value and a callback for a set of predefined cTypes.
All this is coded in the function addCharacteristic
However, there are cTypes that need more variables than that.
How do we feel we want additional variables to be conveyed to the more complex characteristics?
My best guess for now is to set up a few variables like item1 through item9 that if you set them before defining a characteristic they will set a particular variable of a particular characteristic.
Does anyone have a better idea??
PS, do not overcomplicate it please...

Just to understand your question better, let me pull an example from HAP-NodeJS. You're looking for a way to define this structure in C, is that right?
/**
 * Characteristic "Brightness"
 */

Characteristic.Brightness = function() {
  Characteristic.call(this, 'Brightness', '00000008-0000-1000-8000-0026BB765291');
  this.setProps({
    format: Characteristic.Formats.INT,
    unit: Characteristic.Units.PERCENTAGE,
    maxValue: 100,
    minValue: 0,
    minStep: 1,
    perms: [Characteristic.Perms.READ, Characteristic.Perms.WRITE, Characteristic.Perms.NOTIFY]
  });
  this.value = this.getDefaultValue();
};

inherits(Characteristic.Brightness, Characteristic);

Characteristic.Brightness.UUID = '00000008-0000-1000-8000-0026BB765291';

Actually when I opened this issue, I was not aware of how the HomeKit philosophy works. But actually the issue does not exist and the current approach is already OK.
Basic idea is that each type of characteristic has its build in variables, predefined for this very characteristic. So they go statically inside the API and the outside user has not to worry about them.
I will close the issue...

addCharacteristic(chas,aid,++iid,APPLE,THERMOSTAT_C,"x1","x2","x3","x4",thermostat);
x1 - Current temperature
x2 - Target temperature
x3 - Current Heating/Cooling State
x4 - Target Heating/Cooling State


Reproduce the results of the paper

Can this code reproduce the results of the paper？I got 24.61% top-1 error.

I set the target rate 0.7 and follow the standard ResNet training procedure.

Yes, the code should be able to produce the results from the paper. I assume you trained a model based upon ResNet-50? Can you please provide more details? For example, what is the average execution rate of your trained model?
Further, what batch-size did you use? I suggest training with a batch-size of 256 (thats the standard for ResNets and is also used in the paper) or even larger, since the effective batch-size per layer is lower with low execution rates.

average execution rate is 0.8585，my batch size is 2048. I remove all the fc1bn.
I find that fc1bn will degrade result. top1 error is 25.324 with fc1bn.

I get 25.32 top-1 error and the average execution rate is 0.8452. The batch size is 512 without fc1bn.
I think larger batch size is better.  So what's the problem?  Please help me ~~

I can not reproduce the result, either.
On CIFAR-10, I used exactly the same setting as paper did(batch-size 256, epoch 350, target rate 0.7) but got 6.68% top-1 error.

@Goingqs @PerdonLiu the readme says "Specifically, for the results in the paper the following target rate schedules are used for ResNet 50: [1, 1, 0.8, 1, t, t, t, 1, t, t, t, t, t, 1, 0.7, 1] for t in [0.4, 0.5, 0.6, 0.7] " Did you do that, or use target rate 0.7 for all gates? I do not understand how this code allows to have different target rates per layer, the arg parser expects a float and I also cant see adjustment for layer-specifid target rates in other parts of the code where I would expect it.


episode idea: how about something that writes to db?

specially something that writes to google datastore or google database offerings. to be honest the documentation is not the best, there are two versions of everything for google app engine and not appengine, and they don't work ! specially if you wanted to try the db servers locally (using docker)
it would be a great thing if you make an episode of a full example of using  google's database offerings in golang.

👍


Use common pinning for glib/libglib

@conda-forge-admin, please rerender

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I rerendered the recipe in conda-forge/libslirp-feedstock#2.


Update README.md

added Meilisearch-UI in community tool
Pull Request
added Meilisearch-UI in community tool
PR checklist
Please check if your PR fulfills the following requirements:

[ ] Does this PR fix an existing issue, or have you listed the changes applied in the PR description (and why they are needed)?
[ ] Have you read the contributing guidelines?
[ ] Have you made sure that the title is accurate and descriptive of the changes?

Thank you so much for contributing to Meilisearch!

Hey @lrvinye, thank you for contributing to Meilisearch! If you are participating in Hacktoberfest, and you would like to receive some swag from Meilisearch too, please complete this form.

thx @CaroFG 😬


Suggestion for update or missing transpose of a matrix

In the file wals.py line 147 suggest to change to:
input_tensor = tf.SparseTensor(indices=np.array([data.row, data.col]).T, # it has to be transposed !!!!
We have tested and evaluated the result with the suggestion. It looks right.

I have tested this too, and it works OK for me with this change.
Without this modification I get weird (wrong) recommendations.


Syntax highlighting in code blocks

Android version of https://github.com/vector-im/riot-ios/issues/914

see also https://github.com/vector-im/riot-android/issues/145


Running Eval Task by each model

Test  zero-shot  and few shot (5 shots) in each dataset in the notion

To do

[ ]  Test eval pipeline with once model
[ ]  Run batch.sh in Lanta by 1 model 1 GPU config

Huggingface dataset (filtered)
filtered dataset from mUSE score
[Patt/HellaSwag_TH_drop](https://huggingface.co/datasets/Patt/HellaSwag_TH_drop)
→ The row that any score < 0.5 was dropped
[**Patt/MultiRC_TH_drop](https://huggingface.co/datasets/Patt/MultiRC_TH_drop)**
→ The row that any score < 0.66 was dropped.
[**Patt/RTE_TH_drop](https://huggingface.co/datasets/Patt/RTE_TH_drop)**
→ The row which score_hypothesis <= 0.5 or score_premise <= 0.7 was dropped.
[Patt/ReCoRD_TH_drop](https://huggingface.co/datasets/Patt/ReCoRD_TH_drop)
→ Drop every row that score_answers < 0.8 and every row that score < 0.5 after penalty.

Dataset checklist
Thai

[ ] wisesight_sentiment
[ ] lst20
[ ] xquad.th
[ ] xcopa -> available on EleutherAI/lm-eval

EN -> TH dataset (wait for quality checking)

[ ] Patt/HellaSwag_TH_drop](https://huggingface.co/datasets/Patt/HellaSwag_TH_drop)
[ ] Patt/MultiRC_TH_drop](https://huggingface.co/datasets/Patt/MultiRC_TH_drop)
[ ] Patt/RTE_TH_drop](https://huggingface.co/datasets/Patt/RTE_TH_drop)
[ ] Patt/ReCoRD_TH_drop](https://huggingface.co/datasets/Patt/ReCoRD_TH_drop)


Installation from AWS Lambda Console (SAM Template) code outdated

Promote-or-quarantime-plugin SAM Deployment
https://github.com/trendmicro/cloudone-filestorage-plugins/tree/master/post-scan-actions/aws-python-promote-or-quarantine#from-aws-lambda-console
Describe the bug
the template used to deploy directly on the SAM has a Lambda with a syntax error in line 147 and 148
apparently that template is taking an old version of the script
the current code is this
f '{FSS_TAG_PREFIX} scan-detail-code': str (code), f '{FSS_TAG_PREFIX} scan-detail-message': urllib.parse.quote_plus (CODE_MESSAGES.get (code, CODE_MESSAGES [CODE_MISC])),
and it should be this
f '{FSS_TAG_PREFIX} scan-detail-cod= {str (code) }', f '{FSS_TAG_PREFIX} scan-detail-message = { urllib.parse.quote_plus (CODE_MESSAGES.get (code, CODE_MESSAGES [CODE_MISC])) }',
error code from CloudWatch
[ERROR] Runtime.UserCodeSyntaxError: Syntax error in module 'handler': invalid syntax (handler.py, line 148) Traceback (most recent call last):   File "/var/task/handler.py" Line 148                 f'{FSS_TAG_PREFIX}scan-detail-message': urllib.parse.quote_plus(CODE_MESSAGES.get(code, CODE_MESSAGES[CODE_MISC])),
To reproduce
Steps to reproduce the behavior:

Go to https://console.aws.amazon.com/lambda/home?#/create/app?applicationId=arn:aws:serverlessrepo:us-east-1:415485722356:applications/cloudone-filestorage-plugin-action-promote-or-quarantine
Complete the parameters with S3 to configure and Deploy App
Upload File in S3, verify this is Scanned by FSS
The Lambda PromoteOrQuarantine is Invoked but the file isn't move
Review the Cloud Wath Log Stream and see the Error

Additional context
Check the repository handler.py and you do not have this error, it seems that the SAM Template that is being used does not have the updated code
this is the codeUri that is in the template
CodeUri:
Bucket: awsserverlessrepo-changesets-plntc6bfnfj
Key:<PHONE_NUMBER>33 / arn: aws: serverlessrepo: us-east-1:<PHONE_NUMBER>56: applications-cloudone-filestorage-plugin-action-promote-or-quarantine-versions-1.0.5 / b3d5c889-6ebc-42bb-8a76-6c89f9df43f8

Hi @XeniaP ,
Thank you for reporting this. We forget to publish a version of that fix.


gdal: introduce a gdalMinimal variant with a smaller closure size

Description of changes
This is intended to reduce the support burden and closure size of using gdal; in contexts like PostGIS, it's possible to expose GDAL (and the one quadrillion lines of code it pulls in) through PostgreSQL. This isn't always desireable; an overlay may want to make some features optional. And even ignoring that, gdal is currently incredibly bloated and depends on nearly everything under the sun.
gdal versus gdalMinimal yields a closure size reduction from 1.1GiB to 430MiB:
austin@GANON:~/src/nixpkgs$ nix path-info -Srh ./result | tail -1
/nix/store/g6yblqa0gb1n3s5ndm628fndd0acn4dd-gdal-3.7.1                     1.1G
austin@GANON:~/src/nixpkgs$ nix path-info -Srh ./result-2 | tail -1
/nix/store/81i50vd3i5hs8jkkwqyp257y98jjkjqp-gdal-3.7.1                   434.1M
austin@GANON:~/src/nixpkgs$

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

[ ] 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/)
23.11 Release Notes (or backporting 23.05 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

[ ] Fits CONTRIBUTING.md.

I was doing this as well a while back for work but never finalized it. Will definitely use it! :+1:
The remaining list of dependencies, are they all required or you stopped grouping those? I imagine netcdf not to be a required dependency.

Having a separate output for bin removes Python as runtime dependency for when it is used as library.

The remaining list of dependencies, are they all required or you stopped grouping those? I imagine netcdf not to be a required dependency.

No, the ones I have now were just the really big easy wins from running nix why-depends a lot. :) If we can get even more size reduction, I'll keep trying!

Pulling out netcdf and armadillo brought it down to 270MiB! I think we can call that good for a first cut in terms of size, at least.
austin@GANON:~/src/nixpkgs$ nix path-info -Srh ./result-2 | tail -1
/nix/store/b6s4g7ajpky5fb0m03h4xa469yi6n74l-gdal-3.7.1                   273.2M

Nice work, thanks.
Now I am really curious though why there is a cycle with python3. Getting rid of that one by having it only in bin would be a big win as well.

Yeah, I'll open an issue for that so we don't lose track of it; good idea.

I like the idea of having configurable GDAL. Thank you very much for this work.


Bug: correctly handle browser back button usage

As of now, going back to the previous page when in the results screen correctly redirects to home, but when you start the test you skip directly to the last section, and you can edit your answers

Hi there, what's the stage on this one? Have things changed since this issue was opened?

@lorenzocorallo No, I don't think there has been any change, do you want to take this over?

Well, we patched the issue by removing history entries entirely.
The problem with that is that if you go, for example, to "About", then "Home", and then you want to go back you won't be able to.
Ideally we would be able to keep every history entry, but if you try to navigate back to any "test" page you get sent back to the homepage


Cocoapod support

I want to add the iOS Livekit sdk to my cocoapod Library. As far as I know, we can't add the SPM directly in cocoapods. Is there any workaround for it? and also do you guys have any future plans to add the cocoapod support for the iOS SDK.

I found this library use URLWebSocket, it only supports >= iOS 12,
I think we can use another Websocket Library like Starscream to support iOS 10 and work with all package managers(SPM, Cocoapods and Catharge)


botocore.exceptions.SSLError: SSL validation failed for  [Errno 2] No such file or directory

Getting the below error while trying to access remote_env from an s3 bucket
[1592935276008] [DEBUG] 2020-06-23T18:01:16.8Z b8374974-f820-484a-bcc3-64a530712769 Exception received when sending HTTP request.
Traceback (most recent call last):
  File "/var/task/urllib3/util/ssl_.py", line 336, in ssl_wrap_socket
  context.load_verify_locations(ca_certs, ca_cert_dir)
FileNotFoundError: [Errno 2] No such file or directory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/var/runtime/botocore/httpsession.py", line 254, in send
  urllib_response = conn.urlopen(
  File "/var/task/urllib3/connectionpool.py", line 719, in urlopen
  retries = retries.increment(
  File "/var/task/urllib3/util/retry.py", line 376, in increment
  raise six.reraise(type(error), error, _stacktrace)
  File "/var/task/six.py", line 703, in reraise
  raise value
  File "/var/task/urllib3/connectionpool.py", line 665, in urlopen
  httplib_response = self._make_request(
  File "/var/task/urllib3/connectionpool.py", line 376, in _make_request
  self._validate_conn(conn)
  File "/var/task/urllib3/connectionpool.py", line 996, in _validate_conn
  conn.connect()
  File "/var/task/urllib3/connection.py", line 352, in connect
  self.sock = ssl_wrap_socket(
  File "/var/task/urllib3/util/ssl_.py", line 338, in ssl_wrap_socket
  raise SSLError(e)
urllib3.exceptions.SSLError: [Errno 2] No such file or directory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/var/runtime/botocore/endpoint.py", line 200, in _do_get_response
  http_response = self._send(request)
  File "/var/runtime/botocore/endpoint.py", line 244, in _send
  return self.http_session.send(request)
  File "/var/runtime/botocore/httpsession.py", line 281, in send
  raise SSLError(endpoint_url=request.url, error=e)
botocore.exceptions.SSLError: SSL validation failed for .......  [Errno 2] No such file or directory

My Environment
Zappa version used: 0.51.0
Operating System and Python version: Ubuntu , Python 3.8
Output of pip freeze
appdirs==1.4.3
argcomplete==1.11.1
boto3==1.14.8
botocore==1.17.8
CacheControl==0.12.6
certifi==2019.11.28
cffi==1.14.0
cfn-flip==1.2.3
chardet==3.0.4
click==7.1.2
colorama==0.4.3
contextlib2==0.6.0
cryptography==2.9.2
distlib==0.3.0
distro==1.4.0
docutils==0.15.2
durationpy==0.5
Flask==1.1.2
Flask-Cors==3.0.8
future==0.18.2
h11==0.9.0
hjson==3.0.1
html5lib==1.0.1
httptools==0.1.1
idna==2.8
ipaddr==2.2.0
itsdangerous==1.1.0
Jinja2==2.11.2
jmespath==0.10.0
kappa==0.6.0
lockfile==0.12.2
mangum==0.9.2
MarkupSafe==1.1.1
msgpack==0.6.2
packaging==20.3
pep517==0.8.2
pip-tools==5.2.1
placebo==0.9.0
progress==1.5
pycparser==2.20
pydantic==1.5.1
PyMySQL==0.9.3
pyOpenSSL==19.1.0
pyparsing==2.4.6
python-dateutil==2.6.1
python-slugify==4.0.0
pytoml==0.1.21
PyYAML==5.3.1
requests==2.22.0
retrying==1.3.3
s3transfer==0.3.3
six==1.14.0
starlette==0.13.4
text-unidecode==1.3
toml==0.10.1
tqdm==4.46.1
troposphere==2.6.1
typing-extensions==<IP_ADDRESS>
urllib3==1.25.8
uvloop==0.14.0
webencodings==0.5.1
websockets==8.1
Werkzeug==0.16.1
wsgi-request-logger==0.4.6
zappa==0.51.0

Your zappa_settings.json:
{
    "dev": {
        "app_function": "main.app",
        "aws_region": "us-west-2",
        "profile_name": "default",
        "project_name": "d3c",
        "runtime": "python3.8",
        "keep_warm":false,
        "cors": true,
        "s3_bucket": "rnd-lambda-deployables",
        "remote_env":"<my remote s3 file>"
    }
}

I have confirmed that my S3 file is accessible from my local ubuntu machine however does not work on aws

Hey I am getting a similar error. I've setup a config and credentials file in the default path ~/.aws/files, but still didn't work.

Possibly, packaged botocore version 1.14.8 has got too old?
After a Zappa redeployment in another region, I am getting now this message in the zappa tail:
botocore.exceptions.SSLError: SSL validation failed for https://sts.amazonaws.com/ [Errno 2] No such file or directory

Further observations so far:

This has been observed in the boto project: https://github.com/aws/aws-cli/issues/2690; interestingly, people talk their about local system fixes. So maybe it's about a path problem in the container environment in AWS? Because locally this problem does not appear, my code gets further until actual STS permissions checking.
Current latest botocore release is 1.17.21

I will try to deploy back to previous region, theoretically environments could differ.

This seems to provide a temporary Fix
https://stackoverflow.com/a/63642707/10403203

I have the same error with command: zappa manage development "collectstatic --noinput" using django-storages.... very weird stuff

I have the same error with command: zappa manage development "collectstatic --noinput"  using django-storages.... very weird stuff

Check out this StackOverflow answer
https://github.com/Miserlou/Zappa/issues/2127#issuecomment-683217734

@jaywonder20 I saw that... In fact, I changed that part in my code with no solution yet
boto3.client('s3', verify=False, config=Config(signature_version='s3v4'))

@adosaa did you copy the cacert.pem file and set the REQUESTS_CA_BUNDLE environment variable

Yep it's works @jaywonder20 ! putting _cacert.pem in the root of the project and pointing it with the env. variable, a bit ugly but functional.

Great @adosaa it a bit ugly but  that's a workaround until a better option is found

I tried the solution they propose but it gives me the following error:
[ERROR] ClientError: An error occurred (InvalidToken) when calling the PutObject operation: The provided token is malformed or otherwise invalid.
This is my condig:
{
    "dev": {
        "aws_region": "us-east-1",
        "django_settings": "my_app.settings",
        "profile_name": "default",
        "project_name": "my_app",
        "runtime": "python3.8",
        "s3_bucket": "zappa-my_app",
        "environment_variables": {
            "USE_S3": "TRUE",
            "AWS_ACCESS_KEY_ID": "***",
            "AWS_SECRET_ACCESS_KEY": "***",
            "AWS_STORAGE_BUCKET_NAME": "my_app",
            "REQUESTS_CA_BUNDLE": "/var/task/cacert.pem"
        }
    }
}

Also experiencing a similar issue with Zappa 0.51.0 and python 3.6:
botocore.exceptions.SSLError: SSL validation failed for https://secretsmanager.us-east-1.amazonaws.com/ [Errno 2] No such file or directory
[packages] boto3 = "==1.16.7" botocore = "==1.19.17" psycopg2-binary = "==2.8.5" redis = "==3.5.2" zappa = "==0.51.0"
My temporary workaround was to disable SSL verification on the boto call.
verify=false

I had the same problem both with django-storages and django-s3-storage. @jaywonder20 's solution with the cacert.pem file (see stack overflow) solved the issue for me for now.


I cannot find pre-defined or example workflows

The tutorial http://www.wings-workflows.org/tutorial/workflowUser#Running_a_Workflow:_The_Basics says, "You can browse and run workflows that are pre-defined in the system." But when I select "Run Workflows" the list is empty.
Is there a site like myExperiment where WINGS workflows/templates are shared?
Thanks!

Looks like this list of "domains" might be what we're supposed to be using: http://www.wings-workflows.org/domains/
It's not obvious where we're supposed to put them, however.

Okay, I figured out how to import domains via "Manage Domains." Only the CompareFiles domain is able to import (ie appears on the list); the others seem to go through the motions, but don't appear.

Import via the ZIP file doesn't work; I see the following error. It looks like the portal app doesn't have permission to see my os

(I closed the issue by mistake..)
I am able to import (via URL) domains including:

CompareFiles
TextAnalytics
TextClassification

I am NOT able to import (URL) domains including:

DMDomain: http://www.wings-workflows.org/domains/DMDomain.zip
NetworkAnalytics: http://www.wings-workflows.org/domains/NetworkAnalytics.zip

No error is given; they just doesn't show up after the progress bar disappears...

Thanks so much for testing all of these John ! I shall take a look at the domains causing trouble


No real code example for using the tensorboard embedding tab

I spent a long time yesterday trying to understand how to get something to show up in the embedding tab on Tensorboard. It is not very well documented, and there are no code examples except for the tiny, incomplete snippets in the tutorial. I was finally able to get something working, but I think it would be helpful for future users to have a real code tutorial. I could pretty easily write one for the MNIST example since I already have my own working. Is that something that people will want?

It also seems like there must be some code already working on MNist to be able to generate the GIFs for the tutorial, so making those available would be nice, and maybe even less work.

It would be great if you can provide your working version of TensorBoard embedding visualization for MNIST example. I am looking forward to playing around with it.

Sure. I started with the fully_connected_feed.py file and added in the necessary stuff. It seems to work for me. I tried to follow the Google style as best as I could. I even used comments! It requires Numpy and Scipy, but that isn't too much to ask.
# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# @author: Daniel Gordon<EMAIL_ADDRESS>#
# ==============================================================================

"""Trains and Evaluates the MNIST network using a feed dictionary."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

# pylint: disable=missing-docstring
import argparse
import os.path
import sys
import time

from six.moves import xrange  # pylint: disable=redefined-builtin
import tensorflow as tf

from tensorflow.contrib.tensorboard.plugins import projector
from tensorflow.examples.tutorials.mnist import input_data
from tensorflow.examples.tutorials.mnist import mnist

import numpy as np
import scipy.misc

# Basic model parameters as external flags.
FLAGS = None

def placeholder_inputs(batch_size):
  """Generate placeholder variables to represent the input tensors.

  These placeholders are used as inputs by the rest of the model building
  code and will be fed from the downloaded data in the .run() loop, below.

  Args:
    batch_size: The batch size will be baked into both placeholders.

  Returns:
    images_placeholder: Images placeholder.
    labels_placeholder: Labels placeholder.
  """
  # Note that the shapes of the placeholders match the shapes of the full
  # image and label tensors, except the first dimension is now batch_size
  # rather than the full size of the train or test data sets.
  images_placeholder = tf.placeholder(tf.float32, shape=(batch_size,
                                                         mnist.IMAGE_PIXELS))
  labels_placeholder = tf.placeholder(tf.int32, shape=(batch_size))
  return images_placeholder, labels_placeholder

def fill_feed_dict(data_set, images_pl, labels_pl):
  """Fills the feed_dict for training the given step.

  A feed_dict takes the form of:
  feed_dict = {
      <placeholder>: <tensor of values to be passed for placeholder>,
      ....
  }

  Args:
    data_set: The set of images and labels, from input_data.read_data_sets()
    images_pl: The images placeholder, from placeholder_inputs().
    labels_pl: The labels placeholder, from placeholder_inputs().

  Returns:
    feed_dict: The feed dictionary mapping from placeholders to values.
  """
  # Create the feed_dict for the placeholders filled with the next
  # `batch size` examples.
  images_feed, labels_feed = data_set.next_batch(FLAGS.batch_size,
                                                 FLAGS.fake_data)
  feed_dict = {
      images_pl: images_feed,
      labels_pl: labels_feed,
  }
  return feed_dict

def do_eval(sess,
            eval_correct,
            images_placeholder,
            labels_placeholder,
            data_set,
            return_results=False):
  """Runs one evaluation against the full epoch of data.

  Args:
    sess: The session in which the model has been trained.
    eval_correct: The Tensor that returns the number of correct predictions.
    images_placeholder: The images placeholder.
    labels_placeholder: The labels placeholder.
    data_set: The set of images and labels to evaluate, from
      input_data.read_data_sets().
    return_results: True if the results should be returned for the embedding.

  Returns:
    all_images: A list of batches of images.
    all_labels: A list of batches of labels.
    all_hidden1_outputs: A list of batches of embeddings from the first hidden
      layer.
    all_hidden2_outputs: A list of batches of embeddings from the second hidden
      layer.
  """
  # And run one epoch of eval.
  true_count = 0  # Counts the number of correct predictions.
  steps_per_epoch = data_set.num_examples // FLAGS.batch_size
  num_examples = steps_per_epoch * FLAGS.batch_size
  if return_results:
    all_images = []
    all_labels = []
    all_hidden1_outputs = []
    all_hidden2_outputs = []
    # Get the outputs before the ReLU.
    hidden1_outputs = tf.get_default_graph().get_tensor_by_name('hidden1/add:0')
    hidden2_outputs = tf.get_default_graph().get_tensor_by_name('hidden2/add:0')
  for step in xrange(steps_per_epoch):
    feed_dict = fill_feed_dict(data_set,
                               images_placeholder,
                               labels_placeholder)
    if return_results:
      all_images.append(feed_dict[images_placeholder])
      all_labels.append(feed_dict[labels_placeholder])
      curr_count, hidden1_output, hidden2_output = sess.run(
              [eval_correct, hidden1_outputs, hidden2_outputs],
              feed_dict=feed_dict)
      true_count += curr_count
      all_hidden1_outputs.append(hidden1_output)
      all_hidden2_outputs.append(hidden2_output)
    else:
      true_count += sess.run(eval_correct, feed_dict=feed_dict)
  precision = float(true_count) / num_examples
  print('  Num examples: %d  Num correct: %d  Precision @ 1: %0.04f' %
        (num_examples, true_count, precision))
  if return_results:
    return (all_images, all_labels, all_hidden1_outputs, all_hidden2_outputs)

def images_to_sprite(data):
    """Creates the sprite image along with any necessary padding

    Args:
      data: NxHxW[x3] tensor containing the images.

    Returns:
      data: Properly shaped HxWx3 image with any necessary padding.
    """
    if len(data.shape) == 3:
        data = np.tile(data[...,np.newaxis], (1,1,1,3))
    data = data.astype(np.float32)
    min = np.min(data.reshape((data.shape[0], -1)), axis=1)
    data = (data.transpose(1,2,3,0) - min).transpose(3,0,1,2)
    max = np.max(data.reshape((data.shape[0], -1)), axis=1)
    data = (data.transpose(1,2,3,0) / max).transpose(3,0,1,2)
    # Inverting the colors seems to look better for MNIST
    data = 1 - data

    n = int(np.ceil(np.sqrt(data.shape[0])))
    padding = ((0, n ** 2 - data.shape[0]), (0, 0),
            (0, 0)) + ((0, 0),) * (data.ndim - 3)
    data = np.pad(data, padding, mode='constant',
            constant_values=0)
    # Tile the individual thumbnails into an image.
    data = data.reshape((n, n) + data.shape[1:]).transpose((0, 2, 1, 3)
            + tuple(range(4, data.ndim + 1)))
    data = data.reshape((n * data.shape[1], n * data.shape[3]) + data.shape[4:])
    data = (data * 255).astype(np.uint8)
    return data

def run_training():
  """Train MNIST for a number of steps."""
  # Get the sets of images and labels for training, validation, and
  # test on MNIST.
  data_sets = input_data.read_data_sets(FLAGS.input_data_dir, FLAGS.fake_data)

  # Tell TensorFlow that the model will be built into the default Graph.
  with tf.Graph().as_default():
    # Generate placeholders for the images and labels.
    images_placeholder, labels_placeholder = placeholder_inputs(
        FLAGS.batch_size)

    # Build a Graph that computes predictions from the inference model.
    logits = mnist.inference(images_placeholder,
                             FLAGS.hidden1,
                             FLAGS.hidden2)

    # Add to the Graph the Ops for loss calculation.
    loss = mnist.loss(logits, labels_placeholder)

    # Add to the Graph the Ops that calculate and apply gradients.
    train_op = mnist.training(loss, FLAGS.learning_rate)

    # Add the Op to compare the logits to the labels during evaluation.
    eval_correct = mnist.evaluation(logits, labels_placeholder)

    # Build the summary Tensor based on the TF collection of Summaries.
    summary = tf.summary.merge_all()

    # Add the variable initializer Op.
    init = tf.global_variables_initializer()

    # Create a saver for writing training checkpoints.
    saver = tf.train.Saver()

    # Create a session for running Ops on the Graph.
    sess = tf.Session()

    # Instantiate a SummaryWriter to output summaries and the Graph.
    summary_writer = tf.summary.FileWriter(FLAGS.log_dir, sess.graph)

    # And then after everything is built:

    # Run the Op to initialize the variables.
    sess.run(init)

    # Start the training loop.
    for step in xrange(FLAGS.max_steps):
      start_time = time.time()

      # Fill a feed dictionary with the actual set of images and labels
      # for this particular training step.
      feed_dict = fill_feed_dict(data_sets.train,
                                 images_placeholder,
                                 labels_placeholder)

      # Run one step of the model.  The return values are the activations
      # from the `train_op` (which is discarded) and the `loss` Op.  To
      # inspect the values of your Ops or variables, you may include them
      # in the list passed to sess.run() and the value tensors will be
      # returned in the tuple from the call.
      _, loss_value = sess.run([train_op, loss],
                               feed_dict=feed_dict)

      duration = time.time() - start_time

      # Write the summaries and print an overview fairly often.
      if step % 100 == 0:
        # Print status to stdout.
        print('Step %d: loss = %.2f (%.3f sec)' % (step, loss_value, duration))
        # Update the events file.
        summary_str = sess.run(summary, feed_dict=feed_dict)
        summary_writer.add_summary(summary_str, step)
        summary_writer.flush()

      # Save a checkpoint and evaluate the model periodically.
      if (step + 1) % 1000 == 0 or (step + 1) == FLAGS.max_steps:
        checkpoint_file = os.path.join(FLAGS.log_dir, 'model.ckpt')
        saver.save(sess, checkpoint_file, global_step=step)
        # Evaluate against the training set.
        print('Training Data Eval:')
        do_eval(sess,
                eval_correct,
                images_placeholder,
                labels_placeholder,
                data_sets.train)
        # Evaluate against the validation set.
        print('Validation Data Eval:')
        do_eval(sess,
                eval_correct,
                images_placeholder,
                labels_placeholder,
                data_sets.validation)
        # Evaluate against the test set.
        print('Test Data Eval:')
        do_eval(sess,
                eval_correct,
                images_placeholder,
                labels_placeholder,
                data_sets.test)

    # Compute embeddings and save them.
    thumbnail_size = int(np.sqrt(mnist.IMAGE_PIXELS))
    for data_set, name in [
            (data_sets.train, 'train'),
            (data_sets.validation, 'validation'),
            (data_sets.test, 'test')]:
      output_path = os.path.join(FLAGS.log_dir, 'embed', name)
      print('Computing %s Embedding' % name)
      (all_images, all_labels, hidden1_vectors, hidden2_vectors) = do_eval(
              sess,
              eval_correct,
              images_placeholder,
              labels_placeholder,
              data_set,
              True)
      embed_tensors = []
      summary_writer = tf.summary.FileWriter(output_path, sess.graph)
      config = projector.ProjectorConfig()
      for layer, embed_vectors in enumerate([hidden1_vectors, hidden2_vectors]):
        embed_tensor = tf.Variable(
                np.array(embed_vectors).reshape(
                    len(embed_vectors) * embed_vectors[0].shape[0], -1),
                name=('%s_layer_%s' % (name, layer)))
        embed_tensors.append(embed_tensor)
        sess.run(embed_tensor.initializer)
        embedding = config.embeddings.add()
        embedding.tensor_name = embed_tensor.name
        embedding.metadata_path = os.path.join(output_path, 'labels.tsv')
        embedding.sprite.image_path = os.path.join(output_path, 'sprite.png')
        embedding.sprite.single_image_dim.extend(
                [thumbnail_size, thumbnail_size])
        projector.visualize_embeddings(summary_writer, config)
      result = sess.run(embed_tensors)
      saver = tf.train.Saver(embed_tensors)
      saver.save(sess, os.path.join(output_path, 'model.ckpt'), layer)

      # Make sprite and labels.
      images = np.array(all_images).reshape(
              -1, thumbnail_size, thumbnail_size).astype(np.float32)
      sprite = images_to_sprite(images)
      scipy.misc.imsave(os.path.join(output_path, 'sprite.png'), sprite)
      all_labels = np.array(all_labels).flatten()
      metadata_file = open(os.path.join(output_path, 'labels.tsv'), 'w')
      metadata_file.write('Name\tClass\n')
      for ll in xrange(len(all_labels)):
        metadata_file.write('%06d\t%d\n' % (ll, all_labels[ll]))
      metadata_file.close()

def main(_):
  if tf.gfile.Exists(FLAGS.log_dir):
    tf.gfile.DeleteRecursively(FLAGS.log_dir)
  tf.gfile.MakeDirs(FLAGS.log_dir)
  run_training()

if __name__ == '__main__':
  parser = argparse.ArgumentParser()
  parser.add_argument(
      '--learning_rate',
      type=float,
      default=0.01,
      help='Initial learning rate.'
  )
  parser.add_argument(
      '--max_steps',
      type=int,
      default=2000,
      help='Number of steps to run trainer.'
  )
  parser.add_argument(
      '--hidden1',
      type=int,
      default=128,
      help='Number of units in hidden layer 1.'
  )
  parser.add_argument(
      '--hidden2',
      type=int,
      default=32,
      help='Number of units in hidden layer 2.'
  )
  parser.add_argument(
      '--batch_size',
      type=int,
      default=100,
      help='Batch size.  Must divide evenly into the dataset sizes.'
  )
  parser.add_argument(
      '--input_data_dir',
      type=str,
      default='/tmp/tensorflow/mnist/input_data',
      help='Directory to put the input data.'
  )
  parser.add_argument(
      '--log_dir',
      type=str,
      default='/tmp/tensorflow/mnist/logs/fully_connected_feed',
      help='Directory to put the log data.'
  )
  parser.add_argument(
      '--fake_data',
      default=False,
      help='If true, uses fake data for unit testing.',
      action='store_true'
  )

  FLAGS, unparsed = parser.parse_known_args()
  tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)

I also was confused like hell by the description. I created a notebook, maybe it helps someone. It's not about MNIST but with CIFAR
https://github.com/oduerr/dl_tutorial/blob/master/tensorflow/debugging/embedding.ipynb

Thanks for ending the confusion @danielgordon10 @oduerr! I first thought there should be a direct way of writing a checkpoint from an operation's output. However, it seem you have to create a temporary variable first, initialize it with embeddings from a previous run and then save it.

@danielgordon10 @oduerr most wonderful, thanks!
This should definitely be part of the official docu/samples!

Should I make a PR or something? Would this go in Contrib somewhere or with the rest of the MNIST examples?

Sorry for the slow response, this was assigned to me while I was on vacation.
We would be grateful to receive pull requests that improve the documentation. @dsmilkov would be the best person to review

@dsmilkov where should this code live? I can't really do a pull request if I don't know where to put the code.

@danielgordon10 Thank you for the sample code, so far it is the only example I have gotten to work at all for visualizing the embedding.. (using TF1.0 and P36 fwiw)However while it produces a pretty picture I cannot make sense of the labels.. they are three digit numbers when hovering over the dots in the 3d graph.. Although when I select the softmax layer I get 1-two digits when hovering.. Some further description of the utility of the projection and the meaning of the various components of the model (Component 1-3 in the selector boxes for instance) would be super helpful!

If interested, some code that uses TensorBoard embeddings to display character and word embeddings:
https://github.com/Franck-Dernoncourt/NeuroNER
Example:

FYI: How can I select which checkpoint to view in TensorBoard's embeddings tab?

For anyone struggling to get tensorboard embeddings working, I would suggest the standalone embeddings. It has example input files which were a massive help for me. For learning, it is much easier to create embedding data outside of the training code. The structure of embeddings was much clearer once I realized that embedding data is formed using a testing code.

Simple example of embedding visualisation
https://github.com/ElchinValiyev/tf-embedding-visualization-demo

You can also check out my TF Dev summit talk and associated code.
Anyway, we should add a canonical demo for the projector. I'm going to migrate this issue to tensorflow/tensorboard.

@danielgordon10  I run the code successfully. But when i open localhost:6006/#embeddings, tensorboard fetching sprite image... parsing metadata  takes forever. Somebody knows why?

In case anyone is interested, I have built a code example on how to use embeddings in TensorBoard.
Basically, it is based off @normanheckscher 's code for TensorBoard but with @pkmital 's autoencoder. Therefore the autoencoder is used for its embeddings (a.k.a. "code", or "compressed representation") to be visualized in TensorBoard. I managed to merge and document those two pieces of code in the simplest possible way just as to make a quick working demo.

@EddieOne  , i like your solution the best, but I am not sure what the tensor.bytes are.
I am planning to use keras. What should the format of the .bytes file be ?

While by now there are many MNIST-based examples, for me they still relied too much on pre-trained data and pre-generated sprite & metadata files. To fill this gap I created such an example myself and decided to share it here for anyone interested - the code is on GitHub and the video run-through is on YouTube. I hope it helps anyone who stumbles upon the same challenge.

https://medium.com/looka-engineering/how-to-visualize-feature-vectors-with-sprites-and-tensorflows-tensorboard-3950ca1fb2c7
here is an article to resolve this issue

I did this recently if someone is interested in visualizing the embedding.
https://gist.github.com/mmaleki92/6ab0c1666d8979934822f0ad5cf88b00


⚠ Bofrost.at has degraded performance

In c276c25, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 1421 ms

Resolved: Bofrost.at performance has improved in 959bb44 after 35 minutes.


load-metrics.rb gives output /usr/bin/env: ruby: No such file or directory with /etc/default/sensu EMBEDDED_RUBY=true

Hi,
I'm running sensu with /etc/default/sensu having EMBEDDED_RUBY=true. When I attempt to run load-metrics.rb, I get output /usr/bin/env: ruby: No such file or directory. If I yum install ruby, which I don't want to do, (I'm on CentOS 7) I get a require error.
Other checks (such as check-procs.rb) are working fine.
Any ideas?
Thx

@mateodelnorte
A couple of questions to start with:
Are you running the latest version of the check?
Can you run the check manually /opt/sensu/embedded/bin/ruby load-metrics.rb?
If you can run other ruby checks fine but not this one then there may be an issue with the check, try looking to make sure the first line of the load-metrics is identical to the other ruby checks that are working.
Post any output you get from the above questions as well and we can try and troubleshoot it some more.

Thanks for the quick response.
I'm able to run manually:
[root@nj1slog01 ~]# /opt/sensu/embedded/bin/ruby /etc/sensu/plugins/load-metrics.rb
nj1slog01.load_avg.one 0.00<PHONE_NUMBER>
nj1slog01.load_avg.five 0.03<PHONE_NUMBER>
nj1slog01.load_avg.fifteen 0.05<PHONE_NUMBER>

and I'm getting the check directly from github via my ansible scripts:
- name: install load-metrics
  get_url:
    url=https://raw.github.com/sensu/sensu-community-plugins/master/plugins/system/load-metrics.rb
    dest=/etc/sensu/plugins/load-metrics.rb
  notify:
    - restart sensu-client

- name: chmod load-metrics
  file: path=/etc/sensu/plugins/load-metrics.rb owner=sensu group=sensu mode=755
  notify:
    - restart sensu-client

@mateodelnorte
I would start digging through the sensu logs next.  If the check works manually you should be ok.  Can you post your config you use to run the command from sensu and some more details, standalone or not, etc.
Thanks

So, this appears to be working great on all my client machines but the client on the log / data center server, itself, can't find ruby.
{"timestamp":"2015-02-17T17:54:14.790768-0500","level":"info","message":"publishing check result","payload":{"client":"nj1slog01","check":{"name":"metric_load","issued":1424213654,"command":"/etc/sensu/plugins/load-metrics.rb","type":"metric","interval":10,"subscribers":["all"],"executed":1424213654,"duration":0.007,"output":"/usr/bin/env: ruby: No such file or directory\n","status":127}}}

Running the check manually works fine.

@mateodelnorte I am assuming you have other checks on that machine using the embedded Ruby?

@mateodelnorte Can you confirm that your playbook isn't calling the system ruby when attempting to run the check on your server?

Not sure I follow. The ansible / the playbook aren't calling any checks.
sensu-server is running on it's own, post-deploy.
On Wed, Feb 25, 2015 at 6:05 PM, Benjamin Kett<EMAIL_ADDRESS>wrote:

@mateodelnorte https://github.com/mateodelnorte Can you confirm that
your playbook isn't calling the system ruby when attempting to run the
check on your server?
—
Reply to this email directly or view it on GitHub
https://github.com/sensu/sensu-community-plugins/issues/1029#issuecomment-76081036
.

@mateodelnorte Apologies, I suppose I meant when you define the check for the server, how is the command formulated?

@mateodelnorte  check that you don't have a carriage return after the #!/usr/bin/env
(from python run the command open('load-metrics.rb').readline() ).
You should get something like: "#!/usr/bin/env ruby\n"
If you have a carriage (\r), which in fact points to a file or directory that doesn't exists - your error!  , run the command "dos2unix load-metrics.rb".


Add a few more samples:

audio-echo
bitmap-plasma
MoreTeapot
choreographer
gles3jni
hello-gl2
native-audio
native-codec
native-media
native-plasma
san-angeles
sensor-graph

LGTM


sangonomiya kokomi missing 4th passive

"1376470603": "Sangonomiya Kokomi has a 25% Healing Bonus, but a 100% decrease in CRIT Rate.",

v3.10.3


[Feature]: [Bug]: Limit the length of the name of games

Feature Summary
Limit the length of the name of games
Detailed Description

I dunno what it should be, but shorter than this

Im going to be taking a look at this one.

Issue resolved in feature/vue3 branch - https://github.com/cuttle-cards/cuttle/commit/717a90d6f934b9a5df2a47b3f6d121df2fbbc5bb

Looks like this was resolved.


updated DDP RateLimiter code example

The most critical improvement is connectionId field in the rule. It is required to set limit per connectionId instead of per app.

lgtm! maybe use Array includes  since we're using the ecmascript package

Agree includes looks cleaner. Updated the PR.

Awesome thanks!


New package: RandomProjectionTree v0.1.0

Registering package: RandomProjectionTree
Repository: https://github.com/jean-pierreBoth/RandomProjectionTree.jl
Created by: @jean-pierreBoth
Version: v0.1.0
Commit: 74a0b8db47ceecbd6bb4193722330ed8c199f7cf
Git reference: master
Release notes:

Random Projection Trees from DasGupta and Freund

I will check for compat


fix(app): avoid the name conflict issue in the same network

Overview
This PR will avoid the same name robot issue in the same network. if there is the same name in the same network, the app shows an error message.

In terms of the error message, this should be temporary. We need to ask about the reasonable message to @emilywools and @ecormany
Also need support from the design team since if we remove unavailable robot, we will need to add a modal to get confirmation from users.
#10709

Changelog

Add validation to the form
Add the test case

Review requests

If type an existing name, the slideout shows an error message (This function only works with a real robot)

Risk assessment
low

Regarding the error message, I think we should be a little more specific than "Robot name already exists". Maybe something like "Another robot on your network already has this name".
As for the feature itself, what happens if I name robot 1 "BitterWood", turn it off, turn on robot 2, name it "BitterWood", and then turn robot 1 back on again?

Regarding the error message, I think we should be a little more specific than "Robot name already exists". Maybe something like "Another robot on your network already has this name".

Thanks, @ecormany ! (I will post your suggestion to the team channel).

As for the feature itself, what happens if I name robot 1 "BitterWood", turn it off, turn on robot 2, name it "BitterWood", and then turn robot 1 back on again?

When turning on robot 1, the name of robot1 will be BitterWoodNum2.
Backend does this
There would be 2 cases (this depends on users' env)
[start]
robot1 Otie on (available) [connectableRobot]
robot2 BitterWood off (unavailable) [reachableRobot]
[rename]
The app shows an error message BitterWood already exists
[start]
robot1 Otie on (available) [connectableRobot]
robot2 BitterWood off (unavailable) [unReachableRobot] (not cached)
[rename]
The app removes BitterWood from unavailable robots and sends a request to a server
BitterWood shows up as an available robot when turning on robot 2
BitterWoodNum2 shows up when turning on robot1

The message for name conflict
Another robot on your network already has this name. Please choose a different name.

[ ] update the error message

Verified fixed


Mod License Information

Would you be able to add a License for this mod please.

There already is a license

https://github.com/thedefside/valheim-mods/blob/master/LICENSE

Im blind as its right there plain as day, apologies :)

Would you mind if if i get someone to update this mod, unless you have plans?

The license gives you permission. I don't plan to update it. If you have questions while updating it, just reach out to me.


docs: Exclude language docs from crawler

I've already applied this change to the production crawler. We'll remove this exclusion as part of https://github.com/cursorless-dev/cursorless/issues/1642
Checklist

[-] I have added tests
[-] I have updated the docs and cheatsheet
[-] I have not broken the cheatsheet

Will this exclude languages from the docs page? a thought the whole point of hiding them from the sidebar was that we could still have them active? Or am I missing something?

this way they won't appear in docs search. there's no point in hiding them from the sidebar if they pop up as soon as you type "python" into the docs search bar 😅

Ah


Fix react-toolbox website link in README

[react-toolbox](www.react-toolbox.com) was being rendered as a link to https://github.com/react-toolbox/react-toolbox-themr/blob/master/www.react-toolbox.com.

Thanks!


Add support for the PowerA Nintendo Switch Controller

This change has gone out in a beta steam-launcher package, version <IP_ADDRESS>.


Add support for categorical and ordinal labels in VQC

Summary
Added support for categorical and ordinal labels to VQC. Now labels can be passed in different formats, they can be plain ordinal labels, a one dimensional array that contains integer labels like 0, 1, 2, ..., or an array with categorical string labels. One-hot encoded labels are still supported. Internally, labels are transformed to one hot encoding and the classifier is always trained on one hot labels.
A section on multi-class classification with categorical labels is added to the tutorials.
Closes #320

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

44 of 47 (93.62%)  changed or added relevant lines in 2 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.05%) to 87.017%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

qiskit_machine_learning/algorithms/classifiers/neural_network_classifier.py
41
44
93.18%

Totals

Change from base Build<PHONE_NUMBER>:
0.05%

Covered Lines:
3016

Relevant Lines:
3466

💛  - Coveralls