Unified SuperEditor mobile and desktop gesture and content layers (Resolves #927)

When we implemented ContentLayers for desktop, we didn't apply it in the same way to mobile, because it required some mobile rework. This PR reworks mobile such that nearly all of the widget tree is the same for all platforms. The only difference now is the actual gesture handler widget for each platform.
This PR also changes the way we set the gesture area's bounds. Previously we used a LayoutBuilder to find out how big the viewport was, and then we passed that info to the gesture area inside of the viewport. But LayoutBuilder blows up when trying to calculate intrinsic height. This PR introduces an approach that should work with intrinsic height. It's explained, in detail, in comments in the code.

This seems to also fix https://github.com/superlistapp/super_editor/issues/1140.
Unfortunately, it doesn't solve this: https://github.com/superlistapp/super_editor/pull/1251#issuecomment-1663106888
The "Animated task height demo" also doesn't work as expected. The caret stays at the wrong offset:

I think the reason the caret and handle are in the wrong place is because on mobile those are implemented in an app overlay, not a document layer. The document layers rebuild, but the app overlay doesn't rebuild.
I think that probably the answer is to use a leader/follower for caret and handle positions, and place the leaders in the document layer. I'll try to make that change.

Double tapping causes the drag handle to quickly flash at the top left of the screen:
https://github.com/superlistapp/super_editor/assets/7597082/ce464c03-df51-4f4c-96d8-3b294692cf71

Ok. I'll look at that later. Any other issues?

This is the only issue I've found so far.

@angelosilvestre can you verify that the handle flickering is fixed? Also can you continue with the review to see if there's anything else that needs to be addressed?

I'm going to merge this because all indications are that everything is working and I'd like to move forward, but @angelosilvestre should still do a final test of this behavior after the merge.


Update migration-api-shared.md

Added missing '>' and updated formatting
Category

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Fix crash when changing theme in resource editor

Fixes #877
If the user has never shown the image thumbnails, the Resource Editor crashes Visual Studio when changing themes.

tag @dotnet/project-system


[Language] Getting Started with Object Oriented in C#

Getting Started with  Classes and  Object-Oriented in C#
Proposed article introduction
The object-oriented programming (OOP)  paradigm divides data into objects (data fields) and uses classes to describe the contents and behavior of those objects (methods). It allows objects to communicate with one another by establishing relationships between them.
We'll learn how to define our own types using classes and structs, as well as how to use them in our programs, in this article. We'll look at how to make objects out of classes. We'll also look at how classes and objects may be used to model real-world objects and how they can make building programs to solve complicated problems easier.
Key takeaways
-Learn what a class is and how to construct one in C#.

Declaring a Class.
-Understand the three concepts of OOP in C# that is encapsulation, inheritance, polymorphism, and how they are applied in programming.
Using Methods and Access Modifiers.
Learning about Structs.

Article quality
This article will help novices understand why we favor object-oriented programming over procedural programming, as well as the four fundamental ideas of C# OOPs: abstraction, encapsulation, inheritance, and polymorphism, through practical demonstrations. I'll also go through the benefits of each of the four object-oriented programming ideas in depth.
References
N/A

This topic appears a bit oversaturated on other blogs and official docs. Feel free to suggest another topic. Thanks


Massive memory leak

Apparently 9gb is not enough memory for this script to generate based on ~100 graphql queries.

Can you share a reproduction repo?

I am also finding that the 7GB box provided by github actions is running out of memory when we try to generate our gql during CI.

Actually, we just discovered we were running code formatting with prettier on all of the generated files. Its hard to tell in our CI process if not running prettier solved our memory problems, but it made generating graphql files a hell of a lot faster at least.


Issue/5083 edit composer

Description
This is the base logic for data manipulation in created shapes, which will also result in changes to "composer state" that will be translated accordingly for the endpoint (in the next iteration)
closes #5083
Self Check:
Strike through any lines that are not applicable (~~line~~) then check the box

[x] Attached issue to pull request
[x] Changelog entry
[x] Code is clear and sufficiently documented
[] Sufficient test cases (reproduces the bug/tests the requested feature)
[x] Correct, in line with design
[ ] End user documentation is included or an issue is created for end-user documentation (add ref to issue here: )

https://github.com/inmanta/web-console/assets/113331659/44c1aee7-a7da-45b2-b4d5-a9d97b8db0f4

Processing this pull request

Merged into branches iso6, master in 48302f0df2a9a143a6cd5a27bee20ecfb551eb4a


Allow reintroduction of missing Sun JDK classes

I'm unable to use the dnsjava library in Wildfly Swarm projects due to its internal use of sun.net.dns.ResolverConfguration

String resConfName = "sun.net.dns.ResolverConfiguration";
Class resConfClass = Class.forName(resConfName);

java.lang.ClassNotFoundException: sun.net.dns.ResolverConfiguration from [Module "deployment.5d957258-9f2c-408f-9934-ca814f328afb.war:main" from Service Module Loader]

I think this is because JBoss AS7 excludes certain JDK classes by default. There's a decent amount of posts out there explaining how to add them back in by modifying some configuration files for JBoss AS7, but I'm unclear on how to get this done with Wildfly Swarm.
If these Sun JDK classes are being excluded for a reason worth the inconvenience of not having things just work on this platform, then users should be exposed some sort of configuration parameter to manually add them back in.

Can you provide a small example project utilizing the dnsjava library that encounters this problem?
The solution provided in https://github.com/wildfly-swarm/wildfly-swarm/pull/51 may not be the best long term approach to providing access to internal JDK classes, but I've been unable to replicate the issue you're having with an example.

Here's an example project which currently suffers from this issue.on my machine: https://github.com/amannm/wildfly-swarm-example please comment the org.ow2.asm dependency in pom.xml back in and comment back in the DnsLookup.getSearchSuffixes(); in Application.java

@amannm I tested your example(enable org.ow2.asm:asm in pom.xml) and no ClassNotFoundException or other error.
My environment:

OS: Fedora 21
JDK: openjdk version "1.8.0_45"
WildFly-Swarm: HEAD(cb141bc)

I displayed defaultSearchPaths and got [stdout] (main) [Lorg.xbill.DNS.Name;@50a638b5 .

Sorry, I misunderstood and I can reproduce by disabling org.ow2.asm:asm dependency.
(https://github.com/wildfly-swarm/wildfly-swarm/issues/52).

I switch wildfly-swarm-weld-jaxrs scope to compile and no ClassNotFoundException.

Ok that's it then, apparently I was using the outdated method of using provided scope and it was manifesting itself as these issues. Thanks


Right Click -> Copy Pointcloud broken

Traceback:
Traceback (most recent call last):
  File "/home/wxm/dev/oh-distro-private/software/build/lib/python2.7/dist-packages/director/robotviewbehaviors.py", line 380, in onCopyPointCloud
    polyData = segmentation.addCoordArraysToPolyData(polyData)
  File "/home/wxm/dev/oh-distro-private/software/build/lib/python2.7/dist-packages/director/segmentation.py", line 529, in addCoordArraysToPolyData
    viewOrigin = viewFrame.TransformPoint([0.0, 0.0, 0.0])
AttributeError: 'NoneType' object has no attribute 'TransformPoint'

    def getViewFrame(self):
        return self.model.getLinkFrame(self.model.getHeadLink())

Is it possible the robot that is loaded does not define a head link in the director_config.json?
We could fix this so it makes a more helpful error.  Instead of letting model.getLinkFrame() return None, it should assert that the headLink exists before asking for the head line.

fyi, in roboturdf.py:
def getHeadLink(self):
    return drcargs.getDirectorConfig().get('headLink')


Reorganize generated LU files

In order to get intellisense in LU files we need to refactor a bit.  Here are the changes.
Top level LU file

It should include prefix-definition.en-us.lu which includes the other LU files.
It should include the contents of the custom file with the comments updated as in Melanies screen shot below.

Here is what it should look like except that it should have Melanie's text for the custom comments.
>> Definition
> !# @app.culture = en-us
> !# @app.settings.NormalizeWordForm = true
> !# @app.settings.UseAllTrainingData = true
[definition](form/coffee-definition.en-us.lu)

>> Custom utterances
> Add custom utterances
> Labels are nested choices of operator?(property*(value*)) where the labels are chosen from:
> Operator: Assign(), Remove(), Clear(), Show(), Help(), Change(), Skip(), Cancel()
> Property(value): coffeeType(coffeeTypeValue), size(sizeValue), milk(milkValue), numberOfShots(number)
> The span of each label should include the words that mean the corresponding operation/property/value.
> All of the labels are optional and inside a parent label you can have 0 or more of the nested labels.
> The labels should be defined around the words that tell you that the appropriate operator/property/value should be found there.
> Label patterns below show valid patterns and use 'words*' to indicate zero or more words.
> Single: {@OPERATOR=words*}, {@PROPERTY=words*}, {@VALUE=words*}
> Nested: {@OPERATOR=words*{@PROPERTY=words*}words*} {@OPERATOR=words*{@VALUE=words*}words*}, {@PROPERTY=words*{@VALUE=words*}words*}
> Triples: {@OPERATOR=words*{@PROPERTY=words*{@VALUE=words*}words*}words*}
> You can also nest multiple PROPERTY or VALUE labels inside of an OPERATOR.
# coffee
- ADD YOUR LABELS HERE

** Definition file**
The new file prefix-definition.en-us.lu would contain the other files like this:
> coffee definition
[booleanEntity](form/coffee-booleanEntity.en-us.lu)
[coffeeType-coffeeTypeValue](coffeeType/coffee-coffeeType-coffeeTypeValue.en-us.lu)
[form-NoneIntent](form/coffee-form-NoneIntent.en-us.lu)
[form-global](form/coffee-form-global.en-us.lu)
[form-phrases](form/coffee-form-phrases.en-us.lu)
[milk-milkValue](milk/coffee-milk-milkValue.en-us.lu)
[numberOfShots-number](numberOfShots/coffee-numberOfShots-number.en-us.lu)
[size-sizeValue](size/coffee-size-sizeValue.en-us.lu)
[trigger](form/coffee-trigger.en-us.lu)

Current root lu prefix-form.en-us.lu becomes prefix-definition.en-us.lu without app header.
Current custom.lu file becomes prefix-form.en-us.lu with app header and including definition.


Fixed CPU-Z version

[x] Have you signed the Contributor License Agreement?
[x] Have you checked that there aren't other open pull requests for the same manifest update/change?

[x] Does your manifest conform to the 1.0 schema?

Note: <path> is the name of the directory containing the manifest you're submitting.

Microsoft Reviewers: Open in CodeFlow

FYI the bot error message is wrong, the real error is The pull request contains more than one manifest. Either singleton or multi file manifest under one version directory. because you deleted 1.96.1 AND edited the 1.96 Manifest (You can only do changes in one version folder)

I was wondering what went wrong


unordered group question

According to http://textx.github.io/textX/stable/grammar/#repetitions an unordered group must be applied to a sequence.
However, in https://github.com/textX/textX/blob/master/examples/pyFlies/pyflies.tx#L168 it is applied to an ordered choice.
Maybe we should clarify this in the docs...? Or did I misunderstood something?
Once we clarify this (how it should be) I can make a proposition for the docs. I could also elaborate on how optionals are handled in unordered groups...

You are right. It wasn't clear enough. Actually, usage of ordered groups looks like an accidental feature :)
I did some more testing and addition to the docs to clarify. Will issue a PR shortly.

Closed via #359


Please, make sure that the URL pointing to the documentation pages on the old website are all working after the switch.

Google search shows about 444 000 000 links to the boost website, most of them likely to be to the documentation pages.
Please, make sure that these links stay valid after the update, and the "Internet amnesia" does not happen.
The W3C has a guide on how this can be achieved: https://www.w3.org/Provider/Style/URI , although probably a lot of time has passed since, and perhaps there are better guides available.

Yep don't worry... re-rendering all of the library documentation for all the older releases of Boost is not really practical or desirable so those will stay as-is. This will all be working correctly by the time we reach the first official release.

Google search shows about 444 000 000 links to the boost website

It was a mistake to have Google index the documentation for ALL old versions. This leads to situation  where for example you search for "Boost Asio" and you get 1.76.0 documentation (whoops).
We have an open issue to fix all of that and SEO-optimize things so that the search indexes produce results for the website that are very likely to be what the user wants.

I (ab)used Google as a case for links, not for general search. Finding newer versions in normal search is a great goal, it's just not what this issue is about.
I think "Google search console" should be able to tell which links might become dead after website update, although I might be mistaken.

Well there are two issues here:

preserve URLs already baked into every else's content (like blog posts) and search
The pages on boost.org are not SEO-optimized

We are preserving the URLs, but we are also going to tweak the documentation for older versions so that they stop showing up on top of newer versions in search engines (or at all).


Extend biome IDs

Mods to support (Priority: higher in list = higher priority):

[ ] Realistic Terrain Generation (Crash on startup if biome ids higher than 256)
[ ] Enhanced Biomes (Crash on world creation, seems to be biome id check)
[ ] Alternate Terrain Generation (Can't create world, biome id check)
[ ] ChromatiCraft (Biome id check, crash on startup)

Supported Mods:

Biomes O Plenty (Biome id check, support on NEID side)
Extrabiomes XL (No support required, no biome id check)
Thaumcraft (No support required, no biome id check)
Highlands (No support required, no biome id check)
Ridiculous World (No support required, no biome id check)

Probably won't be supported:
Any mod which adds own dimension and biomes to it. Because if you have ids higher 127 for these mods, their biomes then may spawn in overworld. These things are really derpy sometimes...

Would be cool

Sobs* I hit the biome limit
:( ---- Minecraft Crash Report ----
// Why is it breaking :(
Time: 9/13/15 8:21 AM
Description: Initializing game
java.lang.ArrayIndexOutOfBoundsException: 256
at jajo_11.ShadowWorld.ShadowWorld.getFreeBiomeId(ShadowWorld.java:1989)
at jajo_11.ShadowWorld.ShadowWorld.postInit(ShadowWorld.java:1942)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
I am out of biome IDs

You setted Biome id > 256 in configs. Use ID < than 256.

The mod automatically detects open slots here are the slots used.
::Biome IDs::
DivineRPG - 255, 248
Aether - 247
Biomes O Plenty - 246, 163
Highlands - 162, 119
Runic Dungeon - 118
Soul Forest - 117, 108
Abyssal Craft - 107, 96
Atum - 95
Dimensional Doors - 94, 93
Elysium - 92, 84
Erebus - 83, 76
Extreme Biomes XL - 75, 48
Shadow world - 47 5, X
Thaumcraft - 46, 43
Twilight forest - 42, 24

http://www.minecraftforum.net/forums/mapping-and-modding/minecraft-mods/2387300-say-no-to-id-conflicts-install-anti-id-conflict

I will try it.

This was what the log gave me XD
Total amount of free biome ids: F:\Minecraft\Minecraft.minecraft[FC]-FeverFinity-v4.0\config\AntiIDConflict\biomes\avaibleIDs.txt
List of free biome ids:

Fewizz I am going to need these feature soon ... I have almost maxed out biomes. Is there a way you can impliment a prototype soon? I can give you cell so you can text me and let me know when you have a test version.

Oh? I never knew that; thank you!

I actually hit my limit of available biomes ... anyway you could start this sometime this month?

@DPxKnightxZero I talked to @fewizz and he is interested in implementing this. He has a lot of ideas for NEID as well as for other mods but has very little time and this is a problem. So, this still in deeps of our fantasy...

https://drive.google.com/file/d/0B0GYhmakgvItMEt4T2NEOW1GSFE/view?usp=sharing . ONLY FOR TESTING AND BUGFINDINGS. Now you can change BoP biomes ID (in conf) from 0 to ~32000. Not comp. with old worlds(temporarily)

Oh, and biomesID ext. enables in mods/config/NEID.txt file.

Mods to support:

[ ] Realistic Terrain Generation (Crash on startup if biome ids higher than 256)
[ ] Enhanced Biomes (Crash on world creation, seems to be biome id check)

Supported Mods:

Biomes O Plenty (Biome id check, support on NEID side)
Extrabiomes XL (No support required, no biome id check)
Thaumcraft (No support required, no biome id check)
Highlands (No support required, no biome id check)

I will start testing immediately!

Shadow worlds still doesn't work
https://gist.github.com/DPxKnightxZero/871a746486e641f7bb71
Testing with Aethercraft next.

Read OP:
Any mod which adds own dimension and biomes to it. Because if you have ids higher 127 for these mods, their biomes then may spawn in overworld. These things are really derpy sometimes...
Change ids in supported mods.

Eh hehehe ... sorry.

Vanilla currently uses 39 basic biome ids. So, you have 88 ids for biomes which are spawns in non-vanilla dimensions. Some mods (like DivineRPG as I remember) allows you to set ids higher than 127 but derpy things may arise (or may not). And you have 32k ids for vanilla dimension(Overworld/Nether/End) biomes. Not sure if it possible to fix this issue, probably only Mojang can do this...

Biomes O Plenty crash when using biome ID's #IDS USED 256 - 339
https://gist.github.com/DPxKnightxZero/a23b9c6ede77c5ffeb4d

You have NEID 1.4.0...

@DPxKnightxZero , jest remove antiidconflict =P

@fewizz
вообщем. для этих двух модов
aether-1.7.10-1.5.2.jar
AoA-2.4.B.jar
мод InGameInfoXML-1.7.10-<IP_ADDRESS>-universal не правильно отображает айди биома и его название(при полёте в мирах этих модов быстро меняется название биома например форестери-название биома мода, туда сюда туда сюда)
по этому сложно сказать коректно работает или нет в F3 аналогично, название биома не совпадает...
могу предположить что это может вызвать проблемы с другими модами...так как и F3 тоже показывает не коректное имя
но огромное спасибо за расширение биомов,давно мы это ждали))

come on? so simply expanded? I was waiting for this for a long time! And what about the network packets when handling above 256 biomes? because in many places (forge, cauldron(code bukkit, code spigot, etc) hammered 256?

Пакеты/чанклоадер/Регистратор биомов BoP/и ещё кое-что было изменено

@fewizz можно сделать последнюю расширение на id биомов + DataWatcher?
у меня как раз модов много потестирую
у этих двух модов иметься конфликт на DataWatcher
AoA-2.4.B.jar
weaponmod-1.14.3.jar

Alright so this is "Running" but very errored. After a great deal of testing I think you may need to create a custom ID table sorting mod that completely ignores the hardcoded ID's the major issues are as follows. The Biome ID Table does not match the terrain and great example is the biome table will say desert but in actuality it was the Taiga. Another example was the deep ocean was the plains biome. Also during generation while the original had an issue that caused partial chunk loading.

@DPxKnightxZero already wrote about it, because it derives from the type of byte, but we have the type int.

@SvEgiiVEteR эх, врядль 1.5 выйдет... :cry:  Но все же что-нить для тебя попробую сделать

@fewizz а что случилось проблемы в коде или личные? DataWatcher расширенный тоже хорошо, хоть это есть)

ids above 127 will cause dimensions to spawn their biomes in the overworld? how are you extending the ids this mod sounds like it breaks everything.  is it compatible with mods calling the .getbiomearraylist ? this is where I here biome id expansion mods seem to break.

@jredfox ,
It's compatible with mods calling the chunk.getbiomearraylist().

опять какие то байки

well get this mod working to the point that it can work with dimensions mods over 127. Vanilla and forge that have ids above 127 - 255 do not spawn in the overwrold this is a bug with your mod get it working.  make sure it doesn't break anything and then get back to me.  I hear the blocks is incompatible with certain mods how? how can there be an incompatibility for extending the blocks when that is a simple extension.

@jredfox >Vanilla and forge that have ids above 127 - 255 do not spawn in the overwrold this is a bug with your mod get it working.
strange, id 128-255 normal spawn and works with\without NEID

"The chunk isn't the only thing calling the getbiomearray list the chunk extends the function getbiomearraylist in biome gen base that's what you need to worry about as well." OC, it isn't only, and I know about that(ChunkProviders(of mods also), and other classes). It's compatible with ALL(mb not... =P ) other mods, but i must add compatability on my side for allowing to choose BID > than 255. And, i must convert short array to bytearray all time, when getBiomeArray called.(buuut, if bytearray will be changed somwhere, original short array won't change.<<< Main problem atm)(for info: in chunk adds new method, called "getShortBiomeArray", that returns original shortarray, "getBiomeArray" converts shortarray to bytearray(Or i can store and short, and byte array in chunk, but this also problematic)) And if i need for compotability with other mods, i must change "getBiomeArray" calls to "getShortBiomeArray".(And sometimes change genLayers :cry: )
@jredfox , write here, if you have better idea how to implement this.
(Oh... my english so bad... sorry, if you understood nothing).

the source of the getbiomearray is in biomegenbase.  from what I have seen and heard you can either use forge asm to replace getbiomearray at biomegenbase to your method or you can change what defines a chunk to all short arrays.  Then make sure the biome array in biome gen base is also short array with 32767 slots also.  There is some code in the server packet 21, anvil chunk loader, gen package, seems to be in chunk package and then when I fixed all of this using base class edits it still didn't work. Of course I used integer arrays but, only 32767  slots and had everything in ints.

You about elix_x?) (P.S. My changes(not all, most): https://github.com/UserNumberOne/Nothing/commits/master )

I do not work with him. I just know his mods and what he was working on.  So it's a race between you people and him to get the biomes working properly go.

@jredfox lol, i helped him little. :smile:

well he needs more help. he is stuck on the gen package being inconsistent with his definitions making biomes not working. if he gets help with that and fixes that up it should all be good.

well he needs more help. he is stuck on the gen package being inconsistent with his definitions making biomes not working. if he gets help with that and fixes that up it should all be good. then he can finally release aic with ids extended and make a backport to 1.7.10 later and I can finally finish my modpack! :) ?

Is there a way to extend biome IDs in 1.12.2? I'm having some problems with that right now.

link


charFill with negative width constructs invalid Image

charFill should check its arguments for negative sizes and either cap them at 0 or throw an error. The current behavior constructs a malformed image that causes the screen draw process to fail.
Catching the error earlier will make it easier to find the issue and fix it.
Capping the minimum value to 0 would make charFill behave like standard replicate functions.
I'm not sure what the right behavior is. Capping at 0 seems nice but I can see the case for either solution.

I just recently fixed a bug of this same variety, and I think there are a number of spots that don't do adequate checking for negatives throughout the Image manipulation process, so more checks or graceful fallback behaviors are definitely desired.
For this, capping to zero would be less annoying to deal with, but then silently capping could fail to reveal a bigger problem in the caller's code that might be worth dealing with. Capping to zero is probably more consistent with the other functions that do anything like this, and it's going to be harmless from a UI perspective. (And if it gives the wrong visual result, that should be readily apparent.)
So I'm reluctantly in favor of capping, but I could be persuaded either way. :)


Draft: Add paragraph_forward and paragraph_backward commands

Codecov Report

Merging #1549 (2299bd4) into master (581d462) will decrease coverage by 0.01%.
The diff coverage is 0.00%.

@@            Coverage Diff            @@
##           master   #1549      +/-   ##
=========================================
- Coverage    6.85%   6.83%   -0.02%
=========================================
  Files         125     126       +1
  Lines       51813   51950     +137
=========================================
  Hits         3553    3553
- Misses      48260   48397     +137

Impacted Files
Coverage Δ

lapce-core/src/buffer/mod.rs
65.49% <0.00%> (-1.74%)
:arrow_down:

lapce-core/src/command.rs
0.00% <0.00%> (ø)

lapce-core/src/lib.rs
100.00% <ø> (ø)

lapce-core/src/movement.rs
63.63% <0.00%> (-1.99%)
:arrow_down:

lapce-core/src/paragraph.rs
0.00% <0.00%> (ø)

lapce-data/src/document.rs
0.00% <0.00%> (ø)

lapce-ui/src/plugin.rs
0.00% <0.00%> (ø)

lapce-data/src/palette.rs
0.00% <0.00%> (ø)

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


Reorganize the scripts for GIE launching

It seems in the current version, the scripts for GIE are not well organized.
I suggest we reorg the files in /interactive_engine/distribution and /interactive_engine/deploy
Currently, the file tree of distribution:
distribution
├── pom.xml
└── src
    ├── assembly
    │   └── assembly.xml
    ├── bin
    │   ├── admin_tools.sh
    │   ├── coordinator.sh
    │   ├── frontend.sh
    │   ├── ingestor.sh
    │   ├── load_tool.sh
    │   ├── max_node.sh
    │   ├── maxgraph-env
    │   ├── maxgraph.sh
    │   ├── startall.sh
    │   └── store.sh
    └── config
        ├── config.template
        ├── coordinator.config
        ├── frontend0.config
        ├── ingestor0.config
        ├── ingestor1.config
        ├── log4rs.yml
        ├── logback.xml
        ├── logback_debug.xml
        ├── sample.config
        ├── store0.config
        └── store1.config

problems:

this folder only contains binary exetuables and configurations, thus it doesn't need to follow java code structure with a pom?
the scripts in bin folder are quite simple, all of them are one-line command of Java. I think we can aggregate them to a single binary executable (e.g., giectl) with sub-command. like giectl start-coordinator, giectl start-frontend, giectl start-all...
for configuration files, we should provide config template, rather than explicit ingestor0, ingestor1 frontend0 files.

For interactive_engine/deploy folder, currently the files are organized like this:
deploy
├── docker
│   └── dockerfile
│       ├── coordinator-entrypoint.sh
│       ├── coordinator.application.properties
│       ├── create_maxgraph_instance.sh
│       ├── data_loader.sh
│       ├── delete_maxgraph_instance.sh
│       ├── executor-entrypoint.sh
│       ├── executor.vineyard.properties
│       ├── expose_gremlin_server.sh
│       ├── frontend-entrypoint.sh
│       ├── frontend.vineyard.properties
│       ├── func.sh
│       ├── kill_process.sh
│       ├── load_data.sh
│       ├── load_modern_graph.sh
│       ├── manager-entrypoint.sh
│       ├── maven.settings.xml
│       ├── pod.yaml
│       └── set_config.sh

Similar to the files in distribution, most of the files are simple wrappers for a single-line Java command. In addition, it seems many files are for the same functions as those in distribution. (As the filename implies, starting coordinator/front-end and exposing an entrypoint.)
It would be better if the scripts to start the coordinator (and for others) can be unified, whether to start it in a docker container/ or in a physical machine (or local). We may not need a set of docker-specific scripts and the giectl is sufficient.

I suggest we reorg them as:
interactive_engine
└── bin
    ├── giectl # with sub-commands, like `start-coordinator`, `start-frontend`, `stop-all` ....
    ├──data_loader.sh # data_loader can be separate if in need.
└── config
    ├── log4rs.yml
    ├── logback.xml
    ├── frontend.vineyard.properties
    ├── executor.vineyard.properties
    ├── coordinator.application.properties

@shirly121 @zhengpingq, how do you think, could you give some comments?

And the scripts under
interactive_engine/src/instance-manager/script/* can also unified.

Better seperate gie and v2, and put v2 related scripts under interactive_engine/distribution.


A7-1-7: Avoid reporting the same expression or declaration in multiple template instantiations

Affected rules

A7-1-7

Description
In a template class or template function we may report the same logical expression in multiple template instantiations.
Example
template <typename T>
class Foo {
  void bar(T t) { t; } // COMPLIANT - but erroneously reported
};

void test() {
  Foo<int> i;
  Foo<float> f;
  i.bar(1);
  f.bar(1.0f);
}

Re-reviewing the original bug report I believe I misdiagnosed this issue - it is actually completely unrelated to templates.
A fuller reproduction case is as follows:
class Test {
public:
  friend constexpr void swap(Test &lhs, Test &rhs) noexcept { lhs.swap(rhs); }
  void swap(Test &other) noexcept;
};

void test_swap() {
  Test a1, a2;
  swap(a1, a2);
}

The query reports that the function swap is defined on the same line as the expression statement lhs.swap(rhs). Reviewing the AUTOSAR rule, I don't believe the intention is to report such cases - the rule itself does not mention functions either way, and it certainly does not make sense to report the function declaration in which an expression statement is declared as contravening in this case.
As the problem is distinctly different from this initial bug report, I'm closing this as "Doesn't reproduce" and opening a new issue here to track the function problem:
https://github.com/github/codeql-coding-standards/issues/628

In debugging this issue, I identified a couple more problems with A7-1-7 and logged those separately:

https://github.com/github/codeql-coding-standards/issues/629
https://github.com/github/codeql-coding-standards/issues/630


Fix selection colors in new UI of light theme #159, it also works with classic UI

Fix selection colors in new UI of light theme, it also works with classic UI;

add colors const for following official light theme style from expUI_light.theme.json;
change several selection-about colors, including selection color in editor, global selection background color and foreground color. It's more compatible with the Intellij Light theme, also closer with VS code light theme;
fix issue #159

Thank you so much for the PR! 🙌


Redesign friends, school and home pages

We have decided to add two pages which will enable us to give more space to the friends, school and home pages. They currently look too cluttered.

I am closing this issue as we believe we've created the best layout for these pages within the timeframe of this sprint.


[SPARK-14419] [SQL] Improve HashedRelation for key fit within Long

What changes were proposed in this pull request?
Currently, we use java HashMap for HashedRelation if the key could fit within a Long. The java HashMap and CompactBuffer are not memory efficient, the memory used by them is also accounted accurately.
This PR introduce a LongToUnsafeRowMap (similar to BytesToBytesMap) for better memory efficiency and performance.
This PR reopen #12190 to fix bugs.
How was this patch tested?
Existing tests.

Test build #55449 has started for PR 12278 at commit 452cc9d.

Test build #55449 has finished for PR 12278 at commit 452cc9d.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class ParquetOptions(
abstract class Aggregator[-IN, BUF, OUT] extends Serializable

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/55449/
Test PASSed.


Add support for Next.js

Hey, I really like the idea of this library. Sadly I am using Next.js for all my projects, so I am not sure how to set it up/if it's posssible

Currently, the devtool does not work with Next.js. Next.js uses a different rendering method than react-dom. react-dom actually creates a fiber tree on the DOM that this library accesses. Since Next.js doesn't use react-dom, this devtool cannot find the Fiber and therefore the stateful components.

@rydang I'm not sure what you mean by "Next.js doesn't use react-dom" because it definitely does. It's the first thing you install along with next and react: https://nextjs.org/docs#manual-setup

Hey @baldurh - Next and Gatsby are hard to work with in this context, since they both abstract away the ReactDOM.render() functionality from the client. Maybe something we'll look into for the future, but would require some finagling. Definitely an opportunity to put in a PR if you're interested though!

@chriswillsflannery got it! Thanks for the explanation 😊


Boolean values don't save as booleans

It seems that if I add a setting that offers a 'true' or 'false value, it ends up saving in the preferences file as a literal string value "true" or "false". for example:
sections: [
    {
      id: 'camera',
      label: 'Camera',
      icon: 'camera-20',
      form: {
        groups: [
          {
            label: 'Camera Access',
            fields: [
              {
                label: 'Allow Camera Access?',
                key: 'enabled',
                type: 'checkbox',
                options: [{ label: 'Yes', value: true }, { label: 'No', value: false }]
              }
            ]
          }
        ]
      }
    }
  ]

Results in a preferences file:
{
    "camera": {
        "enabled": "true"
    }
}

Hi @FlipABit. Thanks you for your contribution.
I've also encountered this issue in my project. It's indeed annoying that it saves the values as strings. I'll check what we can do about it.
I was also thinking of creating a 'switch' field, specific for boolean values. I'll keep you posted.

Checkbox controls in general are handled with values as strings, so this is to be expected. This allows for multiple grouped checkboxes to maintain a single state of values like ['foo', 'bar'].
It's not ideal in this case for booleans, but it is the expected behavior. As such, I believe this can be closed.

As discussed we won’t change this behaviour. Instead feature #54 has been created. This should create a switch field which handles boolean values.
Closing this issue.


Calendar and schedule tweaks

Farm Events:

Fix calendar display bugs.

(+ tests and refactoring)

Coverage decreased (-0.03%) to 82.218% when pulling 9eb8f8de170bfcc69942ae9b644d8c9f18e1471a on gabrielburnworth:staging into a2fb090fd66cc8a657eb7f9ad570089ca84c685c on FarmBot:staging.

Coverage decreased (-0.03%) to 82.218% when pulling 9eb8f8de170bfcc69942ae9b644d8c9f18e1471a on gabrielburnworth:staging into a2fb090fd66cc8a657eb7f9ad570089ca84c685c on FarmBot:staging.

Coverage decreased (-0.03%) to 82.218% when pulling 327444b6bfa76313e6e437bf1fcd42a490534676 on gabrielburnworth:staging into a2fb090fd66cc8a657eb7f9ad570089ca84c685c on FarmBot:staging.

Coverage increased (+0.9%) to 83.189% when pulling 5aa2e7b9ee66da1bc3dbd55863d7ae220e9c75b9 on gabrielburnworth:staging into a2fb090fd66cc8a657eb7f9ad570089ca84c685c on FarmBot:staging.

Coverage increased (+1.1%) to 83.381% when pulling b4937fb07a5c78b91f33c885f202f49e88f3b9a0 on gabrielburnworth:staging into a2fb090fd66cc8a657eb7f9ad570089ca84c685c on FarmBot:staging.


How do I make a color bleed effect?

Describe your problem here.
title speaks all
Are you modding a build from source or with Lua?
Lua
What is your build target?
Windows x64
Did you edit anything in this build? If so, mention or summarize your changes.
No response

__

He means as in the effect used in Cuphead


tailscale: 1.32.1 -> 1.32.2

Description of changes
https://github.com/tailscale/tailscale/releases/tag/v1.32.2
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
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
22.11 Release Notes (or backporting 22.05 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
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[ ] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 198061 run on x86_64-linux 1

1 package built:

tailscale


OOM no matter what the batch size

Hi all,
Have been trying to fire up my first image classification model, but am hitting a OOM roadblock.  Using an EVGA RTX 2070 GPU (8gb). Without specifying batch size, I get this error:
`
2019-04-03 18:49:56.804435: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-04-03 18:49:56.829467: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-04-03 18:49:56.831332: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x561f24441cd0 executing computations on platform Host. Devices:
2019-04-03 18:49:56.831365: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): <undefined>, <undefined>
2019-04-03 18:49:56.949705: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x561f210d02d0 executing computations on platform CUDA. Devices:
2019-04-03 18:49:56.949748: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): GeForce RTX 2070, Compute Capability 7.5
2019-04-03 18:49:56.950422: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: GeForce RTX 2070 major: 7 minor: 5 memoryClockRate(GHz): 1.62
pciBusID: 0000:41:00.0
totalMemory: 7.76GiB freeMemory: 7.40GiB
2019-04-03 18:49:56.950445: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-04-03 18:49:56.951860: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-04-03 18:49:56.951878: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]      0
2019-04-03 18:49:56.951886: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0:   N
2019-04-03 18:49:56.952460: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7203 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070, pci bus id: 0000:41:00.0, compute capability: 7.5)

Epoch   1
Training:   0%|                                                                      | 0/4 [00:00<?, ?it/s]2019-04-03 18:49:59.158357: I tensorflow/stream_executor/dso_loader.cc:152] successfully opened CUDA library libcublas.so.10.0 locally
2019-04-03 18:50:09.372662: W tensorflow/core/common_runtime/bfc_allocator.cc:267] Allocator (GPU_0_bfc) ran out of memory trying to allocate 6.12GiB.  Current allocation summary follows.
2019-04-03 18:50:09.372727: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (256): 	Total Chunks: 28, Chunks in use: 27. 7.0KiB allocated for chunks. 6.8KiB in use in bin. 172B client-requested in use in bin.
2019-04-03 18:50:09.372738: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (512): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372756: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (1024): 	Total Chunks: 22, Chunks in use: 22. 22.2KiB allocated for chunks. 22.2KiB in use in bin. 22.0KiB client-requested in use in bin.
2019-04-03 18:50:09.372766: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (2048): 	Total Chunks: 2, Chunks in use: 1. 5.0KiB allocated for chunks. 2.5KiB in use in bin. 2.5KiB client-requested in use in bin.
2019-04-03 18:50:09.372776: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (4096): 	Total Chunks: 4, Chunks in use: 4. 20.0KiB allocated for chunks. 20.0KiB in use in bin. 20.0KiB client-requested in use in bin.
2019-04-03 18:50:09.372785: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (8192): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372797: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (16384): 	Total Chunks: 4, Chunks in use: 4. 108.0KiB allocated for chunks. 108.0KiB in use in bin. 108.0KiB client-requested in use in bin.
2019-04-03 18:50:09.372807: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (32768): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372816: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (65536): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372824: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (131072): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372833: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (262144): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372842: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (524288): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372850: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (1048576): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372860: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (2097152): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372870: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (4194304): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372882: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (8388608): 	Total Chunks: 7, Chunks in use: 7. 85.75MiB allocated for chunks. 85.75MiB in use in bin. 85.75MiB client-requested in use in bin.
2019-04-03 18:50:09.372892: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (16777216): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372901: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (33554432): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372912: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (67108864): 	Total Chunks: 2, Chunks in use: 1. 147.00MiB allocated for chunks. 73.50MiB in use in bin. 73.50MiB client-requested in use in bin.
2019-04-03 18:50:09.372923: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (134217728): 	Total Chunks: 4, Chunks in use: 4. 784.00MiB allocated for chunks. 784.00MiB in use in bin. 784.00MiB client-requested in use in bin.
2019-04-03 18:50:09.372932: I tensorflow/core/common_runtime/bfc_allocator.cc:597] Bin (268435456): 	Total Chunks: 1, Chunks in use: 0. 6.04GiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-04-03 18:50:09.372945: I tensorflow/core/common_runtime/bfc_allocator.cc:613] Bin for 6.12GiB was 256.00MiB, Chunk State:
2019-04-03 18:50:09.372961: I tensorflow/core/common_runtime/bfc_allocator.cc:619]   Size: 6.04GiB | Requested Size: 0B | in_use: 0, prev:   Size: 73.50MiB | Requested Size: 73.50MiB | in_use: 1
2019-04-03 18:50:09.372972: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb384000000 of size 205520896
2019-04-03 18:50:09.372979: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb390400000 of size 1024
2019-04-03 18:50:09.372987: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb390400400 of size 12845056
2019-04-03 18:50:09.372997: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391040400 of size 1024
2019-04-03 18:50:09.373006: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391040800 of size 1024
2019-04-03 18:50:09.373015: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391040c00 of size 27648
2019-04-03 18:50:09.373026: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391047800 of size 1024
2019-04-03 18:50:09.373037: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391047c00 of size 5120
2019-04-03 18:50:09.373046: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049000 of size 256
2019-04-03 18:50:09.373055: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049100 of size 256
2019-04-03 18:50:09.373069: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049200 of size 256
2019-04-03 18:50:09.373080: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049300 of size 256
2019-04-03 18:50:09.373090: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049400 of size 256
2019-04-03 18:50:09.373100: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049500 of size 1024
2019-04-03 18:50:09.373109: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049900 of size 256
2019-04-03 18:50:09.373119: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049a00 of size 256
2019-04-03 18:50:09.373128: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049b00 of size 1024
2019-04-03 18:50:09.373137: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb391049f00 of size 256
2019-04-03 18:50:09.373147: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104a000 of size 1024
2019-04-03 18:50:09.373156: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104a400 of size 256
2019-04-03 18:50:09.373164: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104a500 of size 256
2019-04-03 18:50:09.373174: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104a600 of size 1024
2019-04-03 18:50:09.373183: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104aa00 of size 256
2019-04-03 18:50:09.373193: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104ab00 of size 256
2019-04-03 18:50:09.373202: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104ac00 of size 256
2019-04-03 18:50:09.373212: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104ad00 of size 256
2019-04-03 18:50:09.373221: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104ae00 of size 1280
2019-04-03 18:50:09.373231: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39104b300 of size 205520896
2019-04-03 18:50:09.373241: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb39d44b300 of size 205520896
2019-04-03 18:50:09.373251: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3a984b300 of size 1024
2019-04-03 18:50:09.373276: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3a984b700 of size 1024
2019-04-03 18:50:09.373286: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3a984bb00 of size 12845056
2019-04-03 18:50:09.373294: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3aa48bb00 of size 12845056
2019-04-03 18:50:09.373304: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ab0cbb00 of size 1024
2019-04-03 18:50:09.373313: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ab0cbf00 of size 1024
2019-04-03 18:50:09.373320: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ab0cc300 of size 12845056
2019-04-03 18:50:09.373330: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3abd0c300 of size 12845056
2019-04-03 18:50:09.373339: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac94c300 of size 1024
2019-04-03 18:50:09.373347: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac94c700 of size 1024
2019-04-03 18:50:09.373357: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac94cb00 of size 27648
2019-04-03 18:50:09.373366: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac953700 of size 27648
2019-04-03 18:50:09.373374: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95a300 of size 1024
2019-04-03 18:50:09.373384: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95a700 of size 1024
2019-04-03 18:50:09.373394: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95ab00 of size 5120
2019-04-03 18:50:09.373404: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95bf00 of size 5120
2019-04-03 18:50:09.373413: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95d300 of size 256
2019-04-03 18:50:09.373422: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95d400 of size 256
2019-04-03 18:50:09.373431: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95d500 of size 256
2019-04-03 18:50:09.373441: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95d600 of size 256
2019-04-03 18:50:09.373451: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ac95d700 of size 205520896
2019-04-03 18:50:09.373461: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3b8d5d700 of size 1024
2019-04-03 18:50:09.373471: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3b8d5db00 of size 12845056
2019-04-03 18:50:09.373480: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3b999db00 of size 1024
2019-04-03 18:50:09.373488: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3b999df00 of size 12845056
2019-04-03 18:50:09.373498: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5ddf00 of size 1024
2019-04-03 18:50:09.373508: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5de300 of size 27648
2019-04-03 18:50:09.373518: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e4f00 of size 1024
2019-04-03 18:50:09.373528: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e5300 of size 5120
2019-04-03 18:50:09.373537: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6700 of size 256
2019-04-03 18:50:09.373546: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6800 of size 256
2019-04-03 18:50:09.373555: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6900 of size 256
2019-04-03 18:50:09.373564: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6a00 of size 256
2019-04-03 18:50:09.373573: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6b00 of size 256
2019-04-03 18:50:09.373581: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6c00 of size 256
2019-04-03 18:50:09.373591: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6d00 of size 256
2019-04-03 18:50:09.373600: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Free  at 0x7fb3ba5e6e00 of size 256
2019-04-03 18:50:09.373608: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e6f00 of size 256
2019-04-03 18:50:09.373617: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e7000 of size 1024
2019-04-03 18:50:09.373627: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3ba5e7400 of size 2560
2019-04-03 18:50:09.373637: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Free  at 0x7fb3ba5e7e00 of size 77068288
2019-04-03 18:50:09.373647: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3bef67600 of size 256
2019-04-03 18:50:09.373656: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Free  at 0x7fb3bef67700 of size 2560
2019-04-03 18:50:09.373666: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Chunk at 0x7fb3bef68100 of size 77070336
2019-04-03 18:50:09.373676: I tensorflow/core/common_runtime/bfc_allocator.cc:632] Free  at 0x7fb3c38e8100 of size<PHONE_NUMBER>
2019-04-03 18:50:09.373684: I tensorflow/core/common_runtime/bfc_allocator.cc:638]      Summary of in-use Chunks by size:
2019-04-03 18:50:09.373697: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 27 Chunks of size 256 totalling 6.8KiB
2019-04-03 18:50:09.373709: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 21 Chunks of size 1024 totalling 21.0KiB
2019-04-03 18:50:09.373719: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 1 Chunks of size 1280 totalling 1.2KiB
2019-04-03 18:50:09.373729: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 1 Chunks of size 2560 totalling 2.5KiB
2019-04-03 18:50:09.373739: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 4 Chunks of size 5120 totalling 20.0KiB
2019-04-03 18:50:09.373750: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 4 Chunks of size 27648 totalling 108.0KiB
2019-04-03 18:50:09.373761: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 7 Chunks of size 12845056 totalling 85.75MiB
2019-04-03 18:50:09.373770: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 1 Chunks of size 77070336 totalling 73.50MiB
2019-04-03 18:50:09.373781: I tensorflow/core/common_runtime/bfc_allocator.cc:641] 4 Chunks of size 205520896 totalling 784.00MiB
2019-04-03 18:50:09.373792: I tensorflow/core/common_runtime/bfc_allocator.cc:645] Sum Total of in-use chunks: 943.41MiB
2019-04-03 18:50:09.373805: I tensorflow/core/common_runtime/bfc_allocator.cc:647] Stats:
Limit:<PHONE_NUMBER>
InUse:                   989232640
MaxInUse:<PHONE_NUMBER>
NumAllocs:                      79
MaxAllocSize:            205520896

2019-04-03 18:50:09.373823: W tensorflow/core/common_runtime/bfc_allocator.cc:271] ***************_____________________________________________________________________________________
2019-04-03 18:50:09.373855: W tensorflow/core/framework/op_kernel.cc:1401] OP_REQUIRES failed at conv_ops.cc:446 : Resource exhausted: OOM when allocating tensor with shape[128,256,224,224] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
Traceback (most recent call last):
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1334, in _do_call
    return fn(*args)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[128,256,224,224] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
	 [[{{node image_path/conv_0/Conv2D}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

	 [[{{node class/measures_class/accuracy_class}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/mcrowson/anaconda3/bin/ludwig", line 11, in <module>
    sys.exit(main())
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 86, in main
    CLI()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 64, in __init__
    getattr(self, args.command)()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 67, in experiment
    experiment.cli(sys.argv[2:])
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 548, in cli
    experiment(**vars(args))
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 258, in experiment
    debug=debug
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/train.py", line 383, in train
    **model_definition['training']
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/model.py", line 488, in train
    is_training=True
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 929, in run
    run_metadata_ptr)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1152, in _run
    feed_dict_tensor, options, run_metadata)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1328, in _do_run
    run_metadata)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1348, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[128,256,224,224] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
	 [[node image_path/conv_0/Conv2D (defined at /home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py:54) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

	 [[node class/measures_class/accuracy_class (defined at /home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/measure_modules.py:56) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

Caused by op 'image_path/conv_0/Conv2D', defined at:
  File "/home/mcrowson/anaconda3/bin/ludwig", line 11, in <module>
    sys.exit(main())
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 86, in main
    CLI()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 64, in __init__
    getattr(self, args.command)()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 67, in experiment
    experiment.cli(sys.argv[2:])
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 548, in cli
    experiment(**vars(args))
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 258, in experiment
    debug=debug
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/train.py", line 368, in train
    debug=debug
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/model.py", line 110, in __init__
    **kwargs
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/model.py", line 160, in __build
    is_training=self.is_training
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/inputs.py", line 39, in build_inputs
    **kwargs)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/inputs.py", line 66, in build_single_input
    **kwargs)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/features/image_feature.py", line 180, in build_input
    is_training,
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/image_encoders.py", line 79, in __call__
    is_training=is_training
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 565, in __call__
    is_training=is_training)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 147, in conv_2d_layer
    dimensions=2, is_training=is_training)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 121, in conv_layer
    is_training=is_training)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 54, in conv_2d
    padding=padding) + biases
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 1026, in conv2d
    data_format=data_format, dilations=dilations, name=name)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
    op_def=op_def)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 3300, in create_op
    op_def=op_def)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 1801, in __init__
    self._traceback = tf_stack.extract_stack()

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[128,256,224,224] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
	 [[node image_path/conv_0/Conv2D (defined at /home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py:54) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

	 [[node class/measures_class/accuracy_class (defined at /home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/measure_modules.py:56) ]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.`

Model definition file:
Model Definition:

`input_features:
    -
        name: image_path
        type: image
        encoder: stacked_cnn
        resize_method: crop_or_pad
        height: 112
        width: 112

output_features:
    -
        name: class
        type: category`

Upon adding batch size, of any number, to the model definition I get this error:
Epoch   1
Training:   0%|                                                                     | 0/30 [00:00<?, ?it/s]2019-04-03 18:52:37.276173: I tensorflow/stream_executor/dso_loader.cc:152] successfully opened CUDA library libcublas.so.10.0 locally
2019-04-03 18:52:38.231678: E tensorflow/stream_executor/cuda/cuda_dnn.cc:334] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-04-03 18:52:38.240432: E tensorflow/stream_executor/cuda/cuda_dnn.cc:334] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
Traceback (most recent call last):
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1334, in _do_call
    return fn(*args)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node image_path/conv_0/Conv2D}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/mcrowson/anaconda3/bin/ludwig", line 11, in <module>
    sys.exit(main())
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 86, in main
    CLI()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 64, in __init__
    getattr(self, args.command)()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 67, in experiment
    experiment.cli(sys.argv[2:])
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 548, in cli
    experiment(**vars(args))
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 258, in experiment
    debug=debug
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/train.py", line 383, in train
    **model_definition['training']
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/model.py", line 488, in train
    is_training=True
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 929, in run
    run_metadata_ptr)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1152, in _run
    feed_dict_tensor, options, run_metadata)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1328, in _do_run
    run_metadata)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/client/session.py", line 1348, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node image_path/conv_0/Conv2D (defined at /home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py:54) ]]

Caused by op 'image_path/conv_0/Conv2D', defined at:
  File "/home/mcrowson/anaconda3/bin/ludwig", line 11, in <module>
    sys.exit(main())
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 86, in main
    CLI()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 64, in __init__
    getattr(self, args.command)()
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/cli.py", line 67, in experiment
    experiment.cli(sys.argv[2:])
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 548, in cli
    experiment(**vars(args))
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/experiment.py", line 258, in experiment
    debug=debug
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/train.py", line 368, in train
    debug=debug
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/model.py", line 110, in __init__
    **kwargs
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/model.py", line 160, in __build
    is_training=self.is_training
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/inputs.py", line 39, in build_inputs
    **kwargs)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/inputs.py", line 66, in build_single_input
    **kwargs)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/features/image_feature.py", line 180, in build_input
    is_training,
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/image_encoders.py", line 79, in __call__
    is_training=is_training
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 565, in __call__
    is_training=is_training)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 147, in conv_2d_layer
    dimensions=2, is_training=is_training)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 121, in conv_layer
    is_training=is_training)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py", line 54, in conv_2d
    padding=padding) + biases
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 1026, in conv2d
    data_format=data_format, dilations=dilations, name=name)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
    op_def=op_def)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 3300, in create_op
    op_def=op_def)
  File "/home/mcrowson/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 1801, in __init__
    self._traceback = tf_stack.extract_stack()

UnknownError (see above for traceback): Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node image_path/conv_0/Conv2D (defined at /home/mcrowson/anaconda3/lib/python3.7/site-packages/ludwig/models/modules/convolutional_modules.py:54) ]]

Seems odd to me that the model fails to load after coercing a batch size. Anyone else experience this?

2019-04-03 18:52:38.240432: E tensorflow/stream_executor/cuda/cuda_dnn.cc:334] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
This means cuda / cudnn are not installed properly and/or are the wrong version with respect to the version of tensorflow what you have installed. Look at the tensorflow webpage to figure out which version is supported by each version of tensorflow.


Add Seven Worlds of SLIPPIST-1 from SpaceDock

This pull request was automatically generated by SpaceDock on behalf of GregroxMun, to add Seven Worlds of SLIPPIST-1 to CKAN.
Mod details:
name = /mod/1883/Seven%20Worlds%20of%20SLIPPIST-1
author = GregroxMun
abstract = A stockalike, Kerbalized version of the TRAPPIST-1 planetary system.
license = All Rights Reserved
Homepage =
description = The Kerbal Astronomical Union's SLIPPIST instrument (Shadow of Light Imaging of Planets and Planetesimals In the Sky Telescope, not to be confused with the Kerbal brand of Root Beer after which the telescope was named), has just made an incredible discovery this week. The SLIPPIST-1 Star System, around which we previously knew of three Kerbin-sized planets, has been confirmed to be the parent to an additional four planets, for a total of seven. At least three of these worlds are known to be in the habitable zone, the region of space around which water can remain liquid.
SEVEN WORLDS AROUND SLIPPIST-1
Rendered in a stockalike art style, SLIPPIST-1 is a Kerbalized rendition of the TRAPPIST-1 star system. Planets have been scaled down to 1/10 scale to fit in the Kerbal universe. By default it replaces the stock system, but there is a setting.cfg that can be used to make the Slippist star system into an alien star system a distance away from the stock system.

Please direct questions about this pull request to GregroxMun.

This was done in #6686.


Bug: Pressing Left/Right shortly after jump will "cancel" the jump

It seems that pressing LEFT or RIGHT shortly after pressing down the UP key will cause a jump cancel. This doesn't seem like the sort of thing we want in game, though, since it makes it easy to accidentally jump INTO an enemy rather than over them. I'm going to see if I can figure it out--if I haven't made a pull request by then end of today (3/2/2018), it's probably safe to put this up for grabs.

Completed by @Germlord


RFP - DVD Flick 2

Chocolatey lacks choice when it comes to DVD authoring software (What's that?).
DVD Flick 2 offers more up to date encoding librarys than the original DVD Flick.
DVD Flick 2

As the original DVD Flick project is abandoned, this is a fork of this project to continue with basic support.
DVD Flick aims to be a tool to convert various PC video formats to a DVD that can be played on pretty much any standalone DVD player. Its main target audience is people who know at least the basics about DVDs and video and audio files.

DVD Flick

DVD Flick aims to be a simple but at the same time powerful DVD Authoring tool. It can take a number of video files stored on your computer and turn them into a DVD that will play back on your DVD player, Media Center or Home Cinema Set. You can add additional custom audio tracks, subtitles as well as a menu for easier navigation.

Sourceforge https://sourceforge.net/projects/dvdflick-v2/
License: GPL3
Download available via https://sourceforge.net/projects/dvdflick-v2/files/latest/download
The predecessor:
Website www.dvdflick.net/
Sourceforge https://sourceforge.net/projects/dvdflick/
License: GPL3
Download available via https://sourceforge.net/projects/dvdflick/files/latest/download

The documentation of package cdburnerxp refers to DVD Flick.
I have installed & tested it and it seems like a mature software to me.
The original has 8000 weekly downloads via SourceForge so there's still an active userbase.
The fork only seems to provide marginal adjustments (but I didn't take a deep look into it)
Given the active download numbers and lack up recent updates this should be a low hanging fruit

@JonasDralle Where is the project for DVD Flick 2 located?

reading the reviews it seems like this package is not only old but is also using old encodings 😐.

I have rephrased the issue to be about the fork

Status: Review
https://chocolatey.org/packages/dvdflick-v2


Error: Cannot find module 'fs/promises' in web app running in browser.

Wallet-Core WASM works in Node environment but doesn't work in Browser.
To Reproduce

Install '@trustwallet/wallet-core' e.g. npm i @trustwallet/wallet-core.
Add import statement to vanilla js front-end web app.

import { initWasm } from '@trustwallet/wallet-core'

Try run it in browser.

Expected behavior
Web app should run normally without the following error - Error: Cannot find module 'fs/promises'
Additional context
OS: Windows 11
Node:  v20.2.0

@Milerius why it's closed?

Duplicated @bomzj

Is this issue solved?


Color and Duplex options getting lost on connector restart

After a connector restart, we forget how to tell the printer to do Color or Duplex. The options map gets an empty key:value entry: " : ".
I think it's something to do with VendorKey and the printer sync.

Because VendorKey is not a serialized field, we don't get it back from the server. The first time we synchronize, we have VendorKey in the struct, but if we restart and don't have any changes, we don't copy it back to the concurrent map.
I propose removing all the local customizations from cdd (grep for `json:"-"`) and finding another way to encode these options.

And also having some more tests for merging.


[Fix][UI] Fix condition task connection failure.

Purpose of the pull request
This pull request fixes condition task connection failure.
Related issues
close #9547

Codecov Report

Merging #9548 (ab1c543) into dev (8a2fbd2) will increase coverage by 0.04%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##                dev    #9548      +/-   ##
============================================
+ Coverage     39.90%   39.94%   +0.04%
- Complexity     4418     4429      +11
============================================
  Files           826      831       +5
  Lines         33258    33314      +56
  Branches       3683     3677       -6
============================================
+ Hits          13272    13308      +36
- Misses        18754    18781      +27
+ Partials       1232     1225       -7

Impacted Files
Coverage Δ

...org/apache/dolphinscheduler/remote/utils/Host.java
37.77% <0.00%> (-2.23%)
:arrow_down:

...e/dolphinscheduler/remote/NettyRemotingClient.java
52.11% <0.00%> (-1.41%)
:arrow_down:

...uler/server/worker/runner/WorkerManagerThread.java
0.00% <0.00%> (ø)

...ler/server/worker/processor/TaskKillProcessor.java
0.00% <0.00%> (ø)

.../server/worker/processor/TaskExecuteProcessor.java
0.00% <0.00%> (ø)

...uler/plugin/task/zeppelin/ZeppelinTaskChannel.java
0.00% <0.00%> (ø)

...ugin/task/zeppelin/ZeppelinTaskChannelFactory.java
0.00% <0.00%> (ø)

...er/plugin/task/zeppelin/ZeppelinTaskException.java
0.00% <0.00%> (ø)

...inscheduler/plugin/task/zeppelin/ZeppelinTask.java
54.16% <0.00%> (ø)

...duler/plugin/task/zeppelin/ZeppelinParameters.java
70.00% <0.00%> (ø)

... and 6 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 8a2fbd2...ab1c543. Read the comment docs.


after finetuning model consistently produces the last token of prompt again.

I have a special token at the end of prompt. after finetuning the model is producing it as first token even though i give it the token in prompt

opened by mistake


Join stake pool shelley

Issue Number

#1709
Overview

[x] I have mocked stake pool layer and added joinStakePool to shelley api server
[x] I have added first tests (now wallet id and no pool id) for stake pools in shelley
[x] I have added impl for mkDelegationJoinTx
[x] I have extended mkDelegationJoinTx by adding WalletDelegation
[x] I have added tests for joining/rejoining

Comments

I need to still improve on mkDelegationJoinTx as I have :
  1) API Specifications STAKE_POOLS_JOIN_01 - Can join existant stakepool
       expected: Status {statusCode = 403, statusMessage = "Forbidden"}
        but got: Status {statusCode = 500, statusMessage = "Internal Server Error"}

       from the following response: Left (DecodeFailure "{\"code\":\"created_invalid_transaction\",\"message\":\"That's embarrassing. It looks like I've created an invalid transaction that could not be parsed by the node. Here's an error message that may help with debugging: ApplyTxError [LedgerFailure (DelegsFailure (DelegateeNotRegisteredDELEG {pfDELEGSpoolNotRegistered = KeyHash 89eb0d6a8a691dae2cd15ed0369931ce0a949ecafa5c3f93f8121833646e15c3})),LedgerFailure (UtxowFailure (UtxoFailure (FeeTooSmallUTxO {pfUTXOminFee = Coin 133100, pfUTXOgivenFee = Coin 122500}))),LedgerFailure (UtxowFailure (MissingVKeyWitnessesUTXOW {pfUTXOmissingWitnesses = fromList [KeyHash c839b8b6a66a79f710b321be030e33bc7c206b0a0ff42730dc3123449b96c2a3]}))]\"}")

bors try

bors r+

bors r+

bors r-

(buildkite failed: https://buildkite.com/input-output-hk/cardano-wallet/builds/8081#512cba9c-4c3b-41ee-b355-34d157978a34)

bors r+

bors r+

bors try

Retrying submitTx worked when testing locally...
bors try

bors r+


Is it possible to add custom labels to sidekiq_queue metrics?

Hi,
I'd like to add the environment label to ruby_sidekiq_queue_ metrics, is this possible?
Also interested if it's possible to have a queue name label in ruby_sidekiq_job_ metrics, and in ruby_active_record_ metrics that are related to sidekiq.

Looks like the issue here is that SidekiqQueue doesn't respect Client.default labels, it just overwrites them @mrsimo


feat(Terra) CW-7795 Support Terra 2.0

Update Chain ID for Terra 2.0
Update smart contract URL for Terra 2.0

Task linked: CW-7795 SDK coin-terra to support Terra 2.0


Force-merge API supports primary_only parameter

Description
Add primary_only parameter to the document of force-merge API.
Issues Resolved
https://github.com/opensearch-project/documentation-website/issues/6662
Checklist

[x] By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license and subject to the Developers Certificate of Origin.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Hi @hdhalter @vagimeli , this PR is ready for review, please help to review, thank you!


Flip scaling on -ve flux images

As @mnicholl pointed out in email conversation, we should flip the scaling on JPEG images containing negative transient flux. This will be more intuitive to the unversed user. For example see:
https://lasair.roe.ac.uk/object/ZTF18aahsqfq/

The first 2 images are positive flux detections, the third is negative and scale should be flipped.

Good idea, but it would mean some changes to the jpg_stamps code
https://github.com/lsst-uk/lasair/blob/master/src/post_ingest/jpg_stamps.py
Because what you suggest is not just finding triples of files as now, but adds in a database query to find out isdiffpos for each candidate. Not too difficult, but more than a few lines of code.

Hi Roy, it's even easier than that ;)
You can just do it with CSS. When you render the HTML give negative flux images a class of say "neg" and than add this css rule:
img.neg {
   -webkit-filter: invert(1);
   filter: invert(1);
}

Of-course it's only the diff image that needs flipped (not science or reference). I'm not sure how you have saved the jpg images - are they stitched together?

You are right, it would be easy to flip from the webserver, cos we already know the isdiffpos at that time. But Yes they are stitched together ... maybe I should just flip the whole triplet?

I would avoid flipping the whole triplet — that doesn’t help much in making the subtraction results look intuitive, and may cause even more confusion when people see the ’negative’ reference images!
For example something that fades compared to the template then brightens again — we would want the user to see the same reference image for every epoch but see negative differences at some epochs and positive at others. If the template images are flipped at some epochs it may not come across at a glance that they are all the same template.

On 13 Mar 2019, at 09:27, Roy Williams<EMAIL_ADDRESS>wrote:
You are right, it would be easy to flip from the webserver, cos we already know the isdiffpos at that time. But Yes they are stitched together ... maybe I should just flip the whole triplet?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub https://github.com/lsst-uk/lasair/issues/43#issuecomment-472344318, or mute the thread https://github.com/notifications/unsubscribe-auth/AHP-QvYlNZlKmI2ULOe37u3TImcJDOdbks5vWMR-gaJpZM4bra-x.

=========================
Matt Nicholl
Royal Astronomical Society
Research Fellow,
IfA, University of Edinburgh
IGW, University of Birmingham
mattnicholl.net

This -ve flux issue should have gone away now that FITS images are being rendered directly on web pages. Also, the new web interface (in prep) now uses JS9 to display images directly from FITS files.


Update MD file on new branch 2017-12-08_19-31-54

:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

split/updateTestRef1.md
:white_check_mark:Succeeded

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


std::optional instead of std::tuple

I assume that this library is based on C++17 (by using std::variant) — so wouldn't it be better to replace std::tuple with std::optional in the Parse function?
Suggestion:
std::optional<DnsMessage> Parse(const uint8_t *buf, size_t bufSize)

What do you think?

I think so


Enhancement: Added Email validation in registration page

Fixes #4
Successfully added the email validation handling in the registration page of the application
https://github.com/Vanshika-73/Proshop/assets/94698235/bcebf7c6-e176-4f9a-9429-21bae25bbdf0

Did you made any changes in the backend repo?
On Tue, 17 Oct, 2023, 12:46 am Fardeen, @.***> wrote:

Fixes #4 https://github.com/Vanshika-73/Proshop/issues/4
Successfully added the email validation handling in the registration page
of the application
https://github.com/Vanshika-73/Proshop/assets/94698235/bcebf7c6-e176-4f9a-9429-21bae25bbdf0
You can view, comment on, or merge this pull request online at:
https://github.com/Vanshika-73/Proshop/pull/7
Commit Summary

32d2441
https://github.com/Vanshika-73/Proshop/pull/7/commits/32d2441c051358c0e893753d8c645f1798e9401f
Enhancement: Added Email validation in registration page

File Changes
(1 file https://github.com/Vanshika-73/Proshop/pull/7/files)

M src/screens/Register.jsx
https://github.com/Vanshika-73/Proshop/pull/7/files#diff-89d6e7b0a349f73bbc77aa23d088a7086229c270935799b3008480ff6049cb0f
(348)

Patch Links:

https://github.com/Vanshika-73/Proshop/pull/7.patch
https://github.com/Vanshika-73/Proshop/pull/7.diff

—
Reply to this email directly, view it on GitHub
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.
You are receiving this because you are subscribed to this thread.Message
ID: @.***>

Great work @FardeenCODEIIEST.

@FardeenCODEIIEST please pull the latest code first and then commit. Your register.jsx file contains previous code and is creating merge conflicts.

@FardeenCODEIIEST please pull the latest code first and then commit. Your register.jsx file contains previous code and is creating merge conflicts.

Ok no problem


No TelsaMate logs in Docker Desktop, receiving invalid character error

Is there an existing issue for this?

[X] I have searched the existing issues

What happened?
My TeslaMate logs have stopped about 7 days ago, and I have the following error:
error from daemon in stream: Error grabbing logs: invalid character '\x00' looking for beginning of value
Assuming I need to remove the offending characters from the log, but I don't know where they are, can't find them.
Expected Behavior
Logs are viewable
Steps To Reproduce

Open Docker
View TeslaMate-1 Logs

Relevant log output
error from daemon in stream: Error grabbing logs: invalid character '\x00' looking for beginning of value

Screenshots
No response
Additional data
No response
Type of installation
Docker
Version
1.27.3

I found this because I'm getting the same error in an app I'm working on. I'm pretty sure mongo is logging the character causing this issue. Hope that is of some help to yall


Is this comme\and right?

To evaluate llama3 instruct on the leaderboard dataset. i used this command:
lm_eval --model hf \     --model_args pretrained=meta-llama/Meta-Llama-3.1-8B,dtype="bfloat16"\     --tasks leaderboard_gpqa\     --device cuda:0 \     --num_fewshot 0\     --apply_chat_template\     --batch_size auto:2
But the results are too different from the leaderboard even when using normalization described  at https://github.com/huggingface/leaderboards/blob/main/docs/source/en/open_llm_leaderboard/normalization.md
So I would like to know if this is the right command.

Tasks
Version
Filter
n-shot
Metric

Value

Stderr

leaderboard_gpqa
N/A

- leaderboard_gpqa_diamond
1
none
0
acc_norm
↑
0.2778
±
0.0319

- leaderboard_gpqa_extended
1
none
0
acc_norm
↑
0.2491
±
0.0185

- leaderboard_gpqa_main
1
none
0
acc_norm
↑
0.2612
±
0.0208

This question is probably better asked in official Open LLM Leaderboard channels where @clefourrier and team can more easily see and comment on it.

Hi!
Some changes:

you don't need to set few shot
since this is a base model you should not be using the chat template (and if you were using the chat template you would also need to select the multiturn parameter)
you should compare these results with the raw results in the leaderboard (or the result file directly).

Thanks @haileyschoelkopf for the tag!
Indeed, please open a discussion on the leaderboard next time so we can keep track of it

(For future reference, is there a precise URL I can point people to or include in an FAQ doc?

Yes! :)
Doc is here and discussions should be opened here


LOT/LOF is created even if all tables/figures are in hidden draft-comments

Expected Behavior
GIVEN it's not a draft build
AND all figures and tables are in draft-comments
WHEN building PDF
THEN don't add empty LOT/LOF
Actual Behavior
empty LOT/LOF (confusing)

there's like three places this causes issues:

lot-lof
bookmarks
toc

so for example lot-lof.xsl#L56 should read
<xsl:if test="
(exists(//*[contains(@class, ' topic/table ')]/*[contains(@class, ' topic/title ' )]) and $DRAFT eq 'yes')
 or
exists($context//*[contains(@class, ' topic/table ')]/*[contains(@class, ' topic/title ')][not(exists(ancestor::*[contains(@class, ' topic/draft-comment ')]))])
">

or something along those lines, so that if it's not a draft, then don't look for tables in draft comments, but if it's a draft, then do

question: where do I find the tests for this part? and where do I find out more about tests in general? :D

PDF doesn't really have that many tests due to difficulty in comparing output.


uffizzi project create

Tell us about your request
Implement support for creating projects via $ uffizzi project create subcommand.
Which service(s) is this request for?
uffizzi_cli
Tell us about the problem you're trying to solve. What are you trying to do, and why is it hard?
A user or automation (e.g. GitHub Action) should be able to create Uffizzi projects.
Describe the solution you'd like
$ uffizzi project create help (also `--help`, `-h`)

UFFIZZI-PROJECT-CREATE()

NAME
    uffizzi-projec-create - Creates a new project

SYNOPSIS
    uffizzi project create [--name=NAME] [--slug=SLUG]
         [--description=DESCRIPTION] [UFFIZZI_WIDE_FLAG ...]

DESCRIPTION
    Create new project.

    This command can fail for the following reasons:
        - The project --description is too long.
        - The project --name flag is not specified.
        - The project --slug is malformed or used by another project.

    For more information on the uffizzi project command, see:
    https:/github.com/UffizziCloud/uffizzi_cli

FLAGS
    --description=DESCRIPTION
       Description for the project you want to create. Max of 256
       characters.

    --name=NAME
       Name for the project you want to create.

    --slug=SLUG
       A URL-compatible name. Do not include whitespaces or special
       characters. Project slugs must be globally unique across all
       Uffizzi projects.

 Run $ uffizzi
    help for details.

EXAMPLES
    To create a new project with name My App, project slug my-app, and
    description "My first project", run:

        $ uffizzi project create --name="My App" --slug="my-app" \
          --description="My first project"

Are you currently working around the issue?
The user must use a single default project
Additional context
N/A

bundle exec uffizzi project create --name=test_1 --slug=slug_2 --description=desc_1 returns an error:

bash-5.1# bundle exec uffizzi project create --name=test_1 --slug=slug_2 --description=desc_1
bundler: failed to load command: uffizzi (/bundle_cache/ruby/3.0.0/bin/uffizzi)
/gem/lib/uffizzi/clients/api/api_client.rb:32:in `create_project': undefined method `make_post_request' for Uffizzi::HttpClient:Class (NoMethodError)
	from /gem/lib/uffizzi/cli/project.rb:72:in `handle_create_command'
	from /gem/lib/uffizzi/cli/project.rb:47:in `run'
	from /gem/lib/uffizzi/cli/project.rb:30:in `create'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor/command.rb:27:in `run'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor/invocation.rb:127:in `invoke_command'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor.rb:392:in `dispatch'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor/invocation.rb:116:in `invoke'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor.rb:243:in `block in subcommand'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor/command.rb:27:in `run'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor/invocation.rb:127:in `invoke_command'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor.rb:392:in `dispatch'
	from /gem/lib/uffizzi/cli.rb:70:in `dispatch'
	from /bundle_cache/ruby/3.0.0/gems/thor-1.2.1/lib/thor/base.rb:485:in `start'
	from /gem/exe/uffizzi:5:in `<top (required)>'
	from /bundle_cache/ruby/3.0.0/bin/uffizzi:25:in `load'
	from /bundle_cache/ruby/3.0.0/bin/uffizzi:25:in `<top (required)>'
	from /usr/local/lib/ruby/3.0.0/bundler/cli/exec.rb:58:in `load'
	from /usr/local/lib/ruby/3.0.0/bundler/cli/exec.rb:58:in `kernel_load'
	from /usr/local/lib/ruby/3.0.0/bundler/cli/exec.rb:23:in `run'
	from /usr/local/lib/ruby/3.0.0/bundler/cli.rb:478:in `exec'
	from /usr/local/lib/ruby/3.0.0/bundler/vendor/thor/lib/thor/command.rb:27:in `run'
	from /usr/local/lib/ruby/3.0.0/bundler/vendor/thor/lib/thor/invocation.rb:127:in `invoke_command'
	from /usr/local/lib/ruby/3.0.0/bundler/vendor/thor/lib/thor.rb:392:in `dispatch'
	from /usr/local/lib/ruby/3.0.0/bundler/cli.rb:31:in `dispatch'
	from /usr/local/lib/ruby/3.0.0/bundler/vendor/thor/lib/thor/base.rb:485:in `start'
	from /usr/local/lib/ruby/3.0.0/bundler/cli.rb:25:in `start'
	from /usr/local/lib/ruby/gems/3.0.0/gems/bundler-2.2.32/libexec/bundle:49:in `block in <top (required)>'
	from /usr/local/lib/ruby/3.0.0/bundler/friendly_errors.rb:103:in `with_friendly_errors'
	from /usr/local/lib/ruby/gems/3.0.0/gems/bundler-2.2.32/libexec/bundle:37:in `<top (required)>'
	from /usr/local/bundle/bin/bundle:23:in `load'
	from /usr/local/bundle/bin/bundle:23:in `<main>'
bash-5.1#

The error was caused by qa conflicts

@NealArw Added automatic slug generation in case the slug option is missing

@gadkins Hi!
We add automatic slug generation in case the slug option is missing. I think we need to add this information in the help for the command?

TESTED - OK
bash-5.1# bundle exec uffizzi project create --name=test_4 --slug=slug_4 --description=descr_4
Project test_4 was successfully created
bash-5.1# bundle exec uffizzi project create --name=test_5 --description=descr_5
Project test_5 was successfully created
bash-5.1# bundle exec uffizzi project list
test_5-tuffzf
slug_4
test_3-w0sahm
test_2-q8rn7e
test_1-tkrvq
test-lvqkhl
default
bash-5.1#

TESTED - OK
bash-5.1# bundle exec uffizzi project create --name=test_4 --slug=slug_4 --description=descr_4
Project test_4 was successfully created
bash-5.1# bundle exec uffizzi project create --name=test_5 --description=descr_5
Project test_5 was successfully created
bash-5.1# bundle exec uffizzi project list
test_5-tuffzf
slug_4
test_3-w0sahm
test_2-q8rn7e
test_1-tkrvq
test-lvqkhl
default
bash-5.1#

@NealArw We can add this line:
A URL-compatible name. Do not include whitespaces or special characters. Project slugs must be globally unique across all Uffizzi projects. If a slug is not provided, Uffizzi will automatically generate one.

@moklidia Please, add text from the https://github.com/UffizziCloud/uffizzi_cli/issues/77#issuecomment-1126092884

TESTED - OK
bash-5.1# bundle exec uffizzi project create --name=test_1
Project test_1 was successfully created

bash-5.1# bundle exec uffizzi project list
test_1-c9ccpe
default

bash-5.1# bundle exec uffizzi project create --name=test_2 --slug=test_2_slug
Project test_2 was successfully created

bash-5.1# bundle exec uffizzi project list
test_2_slug
test_1-c9ccpe
default

bash-5.1# bundle exec uffizzi project create --name=test_3 --description=test_3_description
Project test_3 was successfully created

bash-5.1# bundle exec uffizzi project list
test_3-ehubow
test_2_slug
test_1-c9ccpe
default

verified in production