VSCode hitting 70%+ CPU

Issue Type: Performance Issue
This happens after having one medium-sized .NET Core solution with one ReactJS project
VS Code version: Code 1.32.3 (a3db5be9b5c6ba46bb7555ec5d60178ecc2eaae4, 2019-03-14T23:43:35.476Z)
OS version: Windows_NT x64 10.0.17763

System Info

Item
Value

CPUs
Intel(R) Core(TM) i7-7660U CPU @ 2.50GHz (4 x 2496)

GPU Status
2d_canvas: enabledchecker_imaging: disabled_offflash_3d: enabledflash_stage3d: enabledflash_stage3d_baseline: enabledgpu_compositing: enabledmultiple_raster_threads: enabled_onnative_gpu_memory_buffers: disabled_softwarerasterization: enabledsurface_synchronization: enabled_onvideo_decode: enabledwebgl: enabledwebgl2: enabled

Memory (System)
15.93GB (4.13GB free)

Process Argv

Screen Reader
no

VM
0%

Process Info
CPU %	Mem MB	   PID	Process
    0	    73	  2744	code main
    1	    68	  1416	   window (Issue Reporter)
   27	   237	  5512	   window (Common.csproj - platform - Visual Studio Code)
    0	    10	 17448	     watcherService
    0	     4	 15680	       console-window-host (Windows internal process)
   13	  1354	 17960	     extensionHost
    0	     2	 18544	       cmd /s /c "C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.omnisharp\1.32.8\OmniSharp.exe -s c:\Users\JonathanMiller\Repositories\platform\src\platform.sln --hostPID 17960 --stdio DotNet:enablePackageRestore=false --encoding utf-8 --loglevel information --plugin C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.razor\OmniSharpPlugin\Microsoft.AspNetCore.Razor.OmniSharpPlugin.dll formattingOptions:useTabs=false formattingOptions:tabSize=4 formattingOptions:indentationSize=4"
    0	     4	 18232	         console-window-host (Windows internal process)
    0	    71	 20988	         C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.omnisharp\1.32.8\OmniSharp.exe  -s c:\Users\JonathanMiller\Repositories\platform\src\platform.sln --hostPID 17960 --stdio DotNet:enablePackageRestore=false --encoding utf-8 --loglevel information --plugin C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.razor\OmniSharpPlugin\Microsoft.AspNetCore.Razor.OmniSharpPlugin.dll formattingOptions:useTabs=false formattingOptions:tabSize=4 formattingOptions:indentationSize=4
    0	    21	 18940	       C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.razor\rzls.exe -lsp --logLevel None
    0	     4	 11316	         console-window-host (Windows internal process)
    0	    16	 19824	       electron_node server.js
    0	    53	  5780	   shared-process
    1	   330	  6580	   gpu-process
   41	   382	 14580	   window (● VersionTrackerService.cs - ProductManagement - Visual Studio Code)
    0	    12	  2780	     watcherService
    0	     4	  7440	       console-window-host (Windows internal process)
    0	     9	 14352	     electron-crash-reporter
    0	    35	 16556	     searchService
   14	  1554	 18304	     extensionHost
    0	    23	  5368	       C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.razor\rzls.exe -lsp --logLevel None
    0	     4	  4264	         console-window-host (Windows internal process)
    0	    19	  8012	       electron_node tsserver.js
    0	    19	 15584	         electron_node typingsInstaller.js typesMap.js
    0	    31	 13512	       "C:\Users\JonathanMiller\AppData\Local\Programs\Microsoft VS Code\Code.exe" "c:\Users\JonathanMiller\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\json-language-features\server\dist\jsonServerMain" --node-ipc --clientProcessId=18304
    0	    18	 18760	       electron_node server.js
    0	     3	 20132	       cmd /s /c "C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.omnisharp\1.32.8\OmniSharp.exe -s c:\Users\JonathanMiller\Repositories\ProductManagement\src\src.sln --hostPID 18304 --stdio DotNet:enablePackageRestore=false --encoding utf-8 --loglevel information --plugin C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.razor\OmniSharpPlugin\Microsoft.AspNetCore.Razor.OmniSharpPlugin.dll formattingOptions:useTabs=false formattingOptions:tabSize=4 formattingOptions:indentationSize=4"
    0	   182	 12564	         C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.omnisharp\1.32.8\OmniSharp.exe  -s c:\Users\JonathanMiller\Repositories\ProductManagement\src\src.sln --hostPID 18304 --stdio DotNet:enablePackageRestore=false --encoding utf-8 --loglevel information --plugin C:\Users\JonathanMiller\.vscode\extensions\ms-vscode.csharp-1.17.1\.razor\OmniSharpPlugin\Microsoft.AspNetCore.Razor.OmniSharpPlugin.dll formattingOptions:useTabs=false formattingOptions:tabSize=4 formattingOptions:indentationSize=4
    0	     5	 21368	         console-window-host (Windows internal process)

Workspace Info
|  Window (● VersionTrackerService.cs - ProductManagement - Visual Studio Code)
|  Window (Common.csproj - platform - Visual Studio Code)
|    Folder (ProductManagement): 304 files
|      File types: json(51) cs(46) dll(41) js(40) cache(30) map(14) pdb(9)
|                  css(7) html(6) ico(6)
|      Conf files: csproj(3) package.json(2) launch.json(1) tasks.json(1)
|                  sln(1)
|      Launch Configs: coreclr(2)
|    Folder (platform): 7999 files
|      File types: dll(5906) cs(560) cache(284) json(277) js(208) pdb(176)
|                  map(97) xml(70) txt(46) css(41)
|      Conf files: csproj(16) package.json(7) settings.json(3) launch.json(1)
|                  tasks.json(1) sln(1)
|      Launch Configs: coreclr(6);

Extensions (19)

Extension
Author (truncated)
Version

bracket-pair-colorizer
Coe
1.0.61

vscode-markdownlint
Dav
0.25.0

xml
Dot
2.4.0

prettier-vscode
esb
1.8.1

dotnet-test-explorer
for
0.6.5

vscode-pull-request-github
Git
0.5.1

graphql-for-vscode
kum
1.13.0

azure-pipelines
ms-
1.147.2

vscode-azureappservice
ms-
0.13.0

vscode-azurestorage
ms-
0.7.0

mssql
ms-
1.4.0

python
ms-
2019.2.5558

azure-account
ms-
0.8.0

azurecli
ms-
0.4.4

csharp
ms-
1.17.1

vscode-node-azure-pack
ms-
0.0.5

azurerm-vscode-tools
msa
0.5.0

vscode-coverage-gutters
rya
2.3.1

vscode-icons
vsc
8.3.0

I'm having a similar issue, but with my CPU hitting 102% on mac os 10.14.2 using Python

Follow this steps to file a good issue please. Thanks
https://github.com/Microsoft/vscode/wiki/Performance-Issues

@isidorn - since this is a main window scenario, here is the attached javascript profile
CPU-20190325T112243.zip

@jonmill thanks for the profile. But can you reproduce with .NET core extension disabled?
If not, please file this issue with the profile to their extension repo

@isidorn - since @sallyamoore is having this issue while using Python, this appears to not be related to .NET Core

Follow this steps to file a good issue please. Thanks
https://github.com/Microsoft/vscode/wiki/Performance-Issues

Sorry about that, I'll provide full context the next time this happens. I restarted my machine immediately after replying and it hasn't happened since, but it has been an intermittent issue for a least the past few weeks. Will keep you updated.

@jonmill does not really work that way. He might have an issue with the python extension.
Please try reproducing withou the .NET core extension and with plain vscode insiders https://code.visualstudio.com/insiders/

I'm a she.

Apologies.

@isidorn - this is not an immediate repro, it takes time and isn't 100%. Moving my entire dev flow to not have intellisense and symbol lookup while waiting for this to repro isn't very reasonable and would definitely cause a loss for my company.
Could you please explain why it's necessary to jump through those hoops when we have provided two use cases using different extensions, a full profiling, and full information showing the problem in the main render window? This seems like it should be enough information to at least investigate on your end.

Looking at the cpu profile this seems to be coming from electron.asar. Internal crypto
Forwarding to @bpasero who would know more

Thanks for the quick follow-up @isidorn!

We are building exploration builds that use a much newer version of our UI framework (Electron version 4.0.x). I wonder if this issue reproduces with one of these builds, could you try? Download:

macOS: Download
Linux: Download
Windows: Download

We are building exploration builds that use a much newer version of our UI framework (Electron version 4.0.x). I wonder if this issue reproduces with one of these builds, could you try? Download:

macOS: Download
Linux: Download
Windows: Download

@bpasero
I'm also having this issue on the Insiders build (1.33.00-insider, MacOS Mojave 10.14.3), however I can't seem to reproduce it on the Exploration build, which is good. I can provide more information if needed.

Agreed; @bpasero - is there a general ETA for the move to electron 4.0.x to get to stable? Nothing concrete, but any general timeframe would be appreciated

We will ship with Electron 4 with our upcoming release 1.36 this week. As such I am closing this issue. To benefit from the update already today, consider to use our insiders version: https://code.visualstudio.com/insiders/


Cache str.len()

Rust str is utf-8, so it doesn't match to CPython str very well.
Probably we would reimplement PyString as same as CPython, but this is a
temporal fix for easy speedup.
Before:
$ time cargo run --release Lib/test/test_unicode.py
13.56s user 0.16s system 88% cpu 15.487 total
After:
$ time cargo run --release Lib/test/test_unicode.py
10.02s user 0.10s system 88% cpu 11.448 total

Great idea!

Is there anywhere that uses .chars().count() of a PyString to do some operation that we could replace with a call to len()?

Unfortunately, it is usually the opposite. We are using len() instead of .chars().count() so it sometimes make trouble with non-ascii strings.


update readme

the low in example code will cause undefined variable error since the required input should be a string. Nice gem :+1:

Well spotted, @DrakeW! Thanks for fixing it, I'll merge it right away.


meaningful commit messages

ability to have a custom commit message for the next save

The idea for this first version is hiding the complexity from the user. We will revisit this in near future, but for now i'm closing the issue. Please feel free to reopen if you want to add to the discussion.

Hello, I need this

@ekoeryanto See https://github.com/netlify/netlify-cms/issues/557.


Update releases

Please create new releases for each stable code change so this great module can be used safely in production by others.

@jdpleiness  thanks, that's what we do.
the latest release https://github.com/cloudposse/terraform-aws-cloudtrail-cloudwatch-alarms/releases/tag/0.3.0
let us know if you find when the code was merged to master but a release was not created - we'll fix that


Adding a new parameter for dist

Feature for a new possibility to replace LinuxMint with Ubuntu

@luckyraul Thanks for submitting the PR.
Could you please change the PR title to adding a new parameter for dist.
Also could you please fix the travis failures.

renamed.
Trigger a new build, the test fail is not related to changes

Thanks for your contribution @luckyraul


Broken Contribute link in README

The Contribute menu link in the README isn't working: https://github.com/vaxerski/Hyprland/blob/main/docs/Contribute.md

Yeah, that thing has now been worked into Issue Guidelines

wasnt, worked into issue guidelines, but fixed. thanks!


Relay Initial

So the linting commit I made renames some files, so you'll have to move stuff around.
Also, I've made this PR (https://github.com/trynmaps/tryn-react/pull/17), which shows how we should be implementing this - that's how future additions to the middleware should be made too :)


modify stacker_blueprints to use vpc nat gateway instead of nat instances

Since cloudformation and troposphere support nat gateways now, should they be used instead of nat instances? I'm working on trying to modify vpc.py to support that, but I keep doing something wrong, so I don't have a pull request ready yet. Is this a direction in which you are moving, or are you planning on sticking with nat instances?
Also, thanks for doing some great work with this and empire!

I'm actually really excited to get nat gateways going - but with that big of a change, I would first want to test what the failure case would be when upgrading (ie: the nat gateways get created, then the nat instances get deleted, etc).  Anyway, I'm definitely moving that way - just want to make sure it's safe for everyone.  That may mean having a new class, or something else (maybe a Parameter?)
Any ideas would be appreciated!  Thanks!

@phobologic Yeah, I get that.   I was able to modify vpc.py to create the nat gateways and everything, and it worked as I'd hoped - it created the new eip and nat gateway first, updated the routing table and then it tore down the old nat instances after everything completed properly.   So it updated my stack with the only interruption being the changing of the route table, which was almost instantaneous.
So, a couple things to think about:

Does there need to be support for both nat instances and nat gateways, even if for only backwards compatibility?  I think I answered my own question there.
What else needs to be tested for this?  Unfortunately, I'm new to the whole empire/stacker thing, so I'm not 100% sure what can break.

I'm going to work on getting a parameterized version of that file going so that the switch to nat gateways isn't the default and won't happen automatically if you don't set use_nat_gateways = true (or something like that).

Hey @cyommer - this was actually fixed back in April, so just getting around to cleaning things up.  Not sure if you're still working on this, but if so please take a look at the update to the vpc blueprint.  Thanks!


Incorrect classpath source when importing project into VS Code Java

Clone https://github.com/openliberty/guide-gradle-intro
Open the finish project with VS Code
Install Language Support for Java extension in VS Code
Set the extension to Standard mode which is needed for debugging (VS Code: Preferences, Settings, search java.server.launchMode and set to Standard).
Then make a change in any Java file (e.g. HelloServlet.java) and save it.  This causes the build folder to be created with a ton of recursive build folders within it.

The problem is that the .classpath file is being generated with:
<?xml version="1.0" encoding="UTF-8"?>
<classpath>
	<classpathentry kind="src" path=""/>
	<classpathentry kind="output" path="build/classes/java/main"/>
</classpath>

So it is taking the entire project root as source, and building it into the output dir.  The src path is incorrect in the above.  If I change the src path to "src/main/java", then it works properly.

This may be related to https://github.com/OpenLiberty/ci.gradle/issues/563 and this area of the code: https://github.com/OpenLiberty/ci.gradle/blob/e4f9ede7a5034c141dc6953a2401b297e4ae44d6/src/main/groovy/io/openliberty/tools/gradle/Liberty.groovy#L136

@ericglau Did PR #566  fix this issue?


Voxel extraction GLSZM fails [FEAT EXTRACTION]

Describe the bug
(1) I can compute all voxel features, but GLSZM fails in my data set. Why is GLSZM different? Do I need to change some settings?
(2) Why extraction of features (e.g. GLSZM statistics, which are extracted from computed arrays) takes 1 second, while computing voxel feature arrays takes a long time? How to define the optimum voxelBatch for the system setting?
PyRadiomics configuration
imageType:
Original: {}
featureClass:
glcm:
glrlm:
glszm:
gldm:
ngtdm:
setting:
binWidth: 12
label: 1
voxelSetting:
kernelRadius: 2
maskedKernel: false
initValue: nan
voxelBatch: 5000
PyRadiomics log file
INFO:radiomics.featureextractor: Loading parameter file C:\Users\me\mypath\R2B12.yaml
DEBUG:radiomics.featureextractor: Parameters parsed, input is valid.
DEBUG:radiomics.featureextractor: Applying settings
DEBUG:radiomics.featureextractor: Enabled image types: {'Original': {}}
DEBUG:radiomics.featureextractor: Enabled features: {'glszm': None}
DEBUG:radiomics.featureextractor: Settings: {'binWidth': 12, 'label': 1}
INFO:radiomics.featureextractor: Starting voxel based extraction
INFO:radiomics.featureextractor: Calculating features with label: 1
DEBUG:radiomics.featureextractor: Enabled images types: {'Original': {}}
DEBUG:radiomics.featureextractor: Enabled features: {'glszm': None}
DEBUG:radiomics.featureextractor: Current settings: {'minimumROIDimensions': 2, 'minimumROISize': None, 'normalize': False, 'normalizeScale': 1, 'removeOutliers': None, 'resampledPixelSpacing': None, 'interpolator': 'sitkBSpline', 'preCrop': False, 'padDistance': 5, 'distances': [1], 'force2D': False, 'force2Ddimension': 0, 'resegmentRange': None, 'label': 1, 'additionalInfo': True, 'binWidth': 12, 'kernelRadius': 2, 'maskedKernel': False, 'initValue': 'nan', 'voxelBatch': 5000, 'voxelBased': True}
INFO:radiomics.featureextractor: Loading image and mask
DEBUG:radiomics.imageoperations: Force casting mask to UInt32 to ensure correct datatype.
DEBUG:radiomics.imageoperations: Checking mask with label 1
DEBUG:radiomics.imageoperations: Calculating bounding box
DEBUG:radiomics.imageoperations: Checking minimum number of dimensions requirements (2)
DEBUG:radiomics.featureextractor: Image and Mask loaded and valid, starting extraction
DEBUG:radiomics.featureextractor: Creating image type iterator
INFO:radiomics.featureextractor: Adding image type "Original" with custom settings: {}
DEBUG:radiomics.featureextractor: Extracting features
DEBUG:radiomics.imageoperations: Yielding original image
INFO:radiomics.featureextractor: Calculating features for original image
DEBUG:radiomics.imageoperations: Cropping to size [15 49 40]
INFO:radiomics.featureextractor: Computing glszm
DEBUG:radiomics.glszm: Initializing feature class
DEBUG:radiomics.imageoperations: Discretizing gray levels inside ROI
DEBUG:radiomics.imageoperations: Calculated 21 bins for bin width 12 with edges: [-156. -144. -132. -120. -108.  -96.  -84.  -72.  -60.  -48.  -36.  -24.
-12.    0.   12.   24.   36.   48.   60.   72.   84.   96.])
DEBUG:radiomics.glszm: Calculating voxel batch no. 1/4
DEBUG:radiomics.glszm: Calculating GLSZM matrix in C
Version (please complete the following information):

OS: Windows 10
Python version: 3.7
PyRadiomics version 3.0

It appears to be failing in the C extension. There were some bugs in the code that are not yet part of the official release, but I don't think they apply here. Can you share an example image and mask to debug this issue?
As to the additional time required, this is to be expected, as features and matrices are calculated for each voxel separately, and not just once for the entire ROI.

Here is the image and mask to test.
test.zip

I was wondering if there are any updates on the issue? thanks

@kingaber, I believe I have found the bug, it was due to a faulty check in GLSZM's C calculation. I have made a PR of the fix (#635), which I will merge after checks pass.
I will also be making a new release of PyRadiomics soon, which will contain this fix.

Great news. Looking forward to test it soon.

@kingaber, the fix is now merged in the master branch. However, I'm currently unable to make a new release due to a (different) issue in the Mac testing CI (using TravisCI).
You can try to compile PyRadiomics from source by checking out the current master of this repository and running setup.py install (from repository root). This involves compiling the C Extensions, if you have any issues, let me know. In the worst case, I can build you a wheel (for either windows or linux), if you need this, please let me know your OS type and specific Python version.


Support for allocating more memory to tsserver

typescript.nvim allows providing this in the init_options setting
ex:
require("typescript").setup({
	server = {
		init_options = {
			maxTsServerMemory = 16000,
		},
	},
})

@WesleyT4N This landed on master instructions are included in README in config section!


consider wrapping the raw solr URL calls

E.g. https://github.com/cmungall/pygolr/blob/master/golr-fetcher.py
or @kltm's node.js clients
or, combining #2 and #5, we could have a simple XML generator that uses golr-fetcher, a yaml config, and enumerates all meaningful subject-object categories

@kltm where are your node.js clients?

https://github.com/geneontology/amigo/blob/master/scripts/amigo-data-demo.js
http://kltm.github.io/bbop-js/docs/files/core-js.html
https://github.com/berkeleybop/bbop-js
http://kltm.github.io/bbop-js/docs/files/golr/manager-js.html
Use GOLR response class when passed back in.   (look in AmiGO and Monarch-land for this).
Can link together with "OR" . . but need to POST.
https://github.com/geneontology/amigo/issues/358


286557 Bug in sample code

The sample code here is totally unneeded.  The protocol is a pretty trivial enum; it's not the place for creating an entire sample.
In addition, the sample has multiple problems:

the code hardly uses the Protocol enum at all
the code incorrectly doesn't actually read from most connections
the code incorrectly requires IPv4

Title
Removed an entire unneeded sample
Summary
No sample is needed for this simple enum
Fixes #286557
Details
Suggested Reviewers
If you know who should review this, use '@' to request a review.

This seems like a small (but important) contribution, so no Contribution License Agreement is required at this point. We will now review your pull request.
Thanks,
.NET Foundation Pull Request Bot


IntegrityError for ForeignKey in DRF Request POST

Hello,
I've just installed this package in my project and after following the guide, I'm getting an Integrity Error when performing POST requests.
I'll use an example to demo:
`
#models.py
class Book(models.Model):
id = HashidAutoField(primary_key=True)
title = models.CharField(max_length=200)
isbn = models.CharField(max_length=50)
author = models.ForeignKey('Author', related_name='book')
class Author(models.Model):
id = HashidAutoField(primary_key=True)
name = models.CharField(max_length=100)
books = models.ForeignKey(Book, related_name="author")
#serializers.py
class BookSerializer(serializers.ModelSerializer):
id = HashidSerializerCharField(source_field='my_app.Book.id')
author = serializers.PrimaryKeyRelatedField(pk_field=HashidSerializerCharField(source_field='my_app.Author.id'), read_only=True)
class Meta:
    model = Book
    fields = ("id", "title", "isbn", "author")

class AuthorSerializer(serializers.ModelSerializer):
id = HashidSerializerCharField(source_field='my_app.Author.id')
class Meta:
    model = Author
    fields = ("id", "name")

#views.py
class BooksList(APIView):
def get(self, request, format=None):
a_list = Book.objects.all()
serializer = BookSerializer(a_list, many=True)
return Response(serializer.data)
def post(self, request, format=None):
	serializer = BookSerializer(data=request.data)
	if serializer.is_valid():
		serializer.save()
		return Response(serializer.data, status=status.HTTP_201_CREATED)
	return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)

def delete(self, request, pk, format=None):
	item = self.get_object(pk)
	item.delete()
	return Response(status=status.HTTP_204_NO_CONTENT)

class BookDetail(APIView):
def get_object(self, pk):
try:
return Book.objects.get(pk=pk)
except Book.DoesNotExist:
raise Http404
def get(self, request, pk, format=None):
    item_list = self.get_object(pk)
    item_list = BookSerializer(item_list)
    return Response(item_list.data)

def put(self, request, pk, format=None):
    item = self.get_object(pk)
    serializer = Book(item, data=request.data)
    if serializer.is_valid():
        serializer.save()
        return Response(serializer.data)
    return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)

def delete(self, request, pk, format=None):
    item = self.get_object(pk)
    item.delete()
    return Response(status=status.HTTP_204_NO_CONTENT)

#urls.py
url_patterns = [
....
url(r'^api/books/$', views.BooksList.as_view()),
url(r'^api/books/(?P\w+)/$', views.BookDetail.as_view()),
....
`
I use token authentication for my APIs,
Now when I do a POST
curl -X POST 'http:localhost:8000/my_app/books/' -H "Authorizations: Token my_token_here" -d "title=TestBook&isbn=1234567890&author=7a5kPOq"
I get an error
IntegrityError at /my_app/api/books/ NOT NULL constraint failed:my_app_book.author_id Request Method: POST Request URL: http://localhost:8000/my_app/api/books/
(I have an author whose id = 7a5kPOq)
django == 1.11.6
django-hashid-fields == 2.0.1
The same worked before I introduced the HashidAutoField. Why can't it recognize the

Hmm, it looks like there's something tricky going on here, probably with the descriptor on the HashidAutoField, versus what normally happens with a regular AutoField. I will attempt to duplicate and look into it (probably this weekend, super busy with work this week), but in meantime, try setting author_id in the POST data instead of author and tell me if that makes any difference.

I did, but still not working, I still get the IntegrityError. My guessing is probably the to_representation function is not returning a value.

Just wanted to let you know I haven't forgotten you, I just haven't had time to look into this yet. It's been absolutely crazy lately. I used up what time I had with merging some PRs, but I will attempt to get to this in the next couple weeks. Thankfully you have a workaround for now. =)

Hi,
I have the same issue than Darius. Any progress on this issue ?
Thanks a lot.

Hi,
I had the same issue and I fixed it by changing the PrimaryKeyRelatedField "read_only=True" to "queryset=YourModel.objects.all()" , Then the POST worked.
f.e:
author = serializers.PrimaryKeyRelatedField(pk_field=HashidSerializerCharField(source_field='my_app.Author.id'), queryset=Author.objects.all())
Hope this helps~

Yes, @zakone is correct, this actually has nothing to do with django-hashid-fields, as is the behavior of DRF. The docs on serializer relationships states, "queryset - The queryset used for model instance lookups when validating the field input. Relationships must either set a queryset explicitly, or set read_only=True." I had a note about this in the documentation, but I am changing it slightly to be more explicit. Thanks!


Track if logger was lazy or not

Adds tracking mechanism for logger's opt method.
Thanks to that it is now possible to detect bad calls to logger that
are lazy and are expecting t.Callable[[], t.Any]
Closes: #6

@Delgan do you want to wait for @Jukkal or is it fine for you to merge?

@kornicameister I tested it and it seems perfectly fine, congrats for your work!


Add copy to clipboard function, python3 support and allow for pip install

Adds a --copy function which copies the export command to clipboard
Add makefile for installing requirements
Adds python3 support
Adds setup, this allows for aws-switchrole to be installed via pip

Thanks for the PR!  Really happy to take these features.
Looks like your Makefile didn't make it into this branch, though.
Could you also update the installation instructions in README.md to explain how to use the Makefile?


Taxon Constraint on GO:0007338 and children to exclude seed plants

I came across some loci in TAIR that were automagically IEA annotated to
GO:0007338 single fertilization (15 annotations)
and
GO:0007339 (1 annotation)
Can we EXCLUDE GO:0007338 and its children from being applied to the Spermatophyta (id 58024)

Done

https://github.com/geneontology/go-ontology/pull/17649


Single sign on for web apps

It would be great to have an ability to have web apps behind the authentication for Jupyterhub.

Hey @brl0, thank you for the suggestion. I need a little bit more information before making a ticket out of this to add to our list of ideas of possible improvements for QHub.
Is there a reason why you'd like this feature to be added? How would it benefit QHub users?
Any ideas about how we would implement it?
Thanks :)

Hey @brl0, thank you for the suggestion. I need a little bit more information before making a ticket out of this to add to our list of ideas of possible improvements for QHub.
Is there a reason why you'd like this feature to be added? How would it benefit QHub users?
Any ideas about how we would implement it?
Thanks :)

@laisbsc,
This is something that has been discussed with @costrouc and @dharhas in the past, they would probably have a better idea of what is needed to implement.
The idea is to integrate panel apps into qhub in such a way that would allow for those apps to use cluster resources such as the dask gateway to access workers on the cluster, conda store, and nfs, as well as hopefully sharing a common authentication and user management configuration.
The goal would be to make it easy to deploy end user facing big data processing apps.

@laisbsc,
This is something that has been discussed with @costrouc and @dharhas in the past, they would probably have a better idea of what is needed to implement.
The idea is to integrate panel apps into qhub in such a way that would allow for those apps to use cluster resources such as the dask gateway to access workers on the cluster, conda store, and nfs, as well as hopefully sharing a common authentication and user management configuration.
The goal would be to make it easy to deploy end user facing big data processing apps.

This is related to #267

This is related to #267


Add links to each of the linters to CONTRIBUTING.md

Also included the reasoning behind this list and the default config
files used by Hound.
The information was taken directly from the Hound configuration page
over here: https://houndci.com/configuration
Go programming language has been left out from the list since there is
no linter mentioned for it on the Hound configuration page.
https://github.com/thoughtbot/hound/issues/911

There's also https://github.com/thoughtbot/hound-swift/, and https://github.com/thoughtbot/hound-go. And both of them are still in Beta along with HAML

Good to know, thank you! I am adding those two now.
Also, I've included the default config for hound-swift as this file: https://github.com/thoughtbot/hound-swift/blob/f9870d10bd31fcfbd667bce203514091b7bd1408/config/default.yml Is that correct? I couldn't find the appropriate default config for the hound-go linter though. Would greatly appreciate any advice on how to deal with this.

All swift questions can be answered by @jakecraige, and @bernerdschaefer got Go covered

@bernerdschaefer Is there a default config file for hound-go I should add to the list?

@Alehanz The Go linter is golint and doesn't have any config.

@thorncp Great, thanks for letting me know!

@jakecraige I got confused and switched to golint instead of hound-go. Will fix it now, my bad.
Also, it seems that circleci has one failing test for my newer pull requests. Not entirely sure why, since I haven't changed anything except the list of linters in CONTRIBUTING.md
On a sidenote: does anyone think it would be a good idea to update the list of linters at https://houndci.com/configuration ?

@jakecraige I got confused and changed the link from hound-go to golint, will change it back now, my bad.
Also, it seems that circleci has a failing test for the newer pull-requests, even though I haven't changed anything except for the list of linters in CONTRIBUTING.md. Not entirely sure how to fix this. Any help would be appreciated.
On a sidenote: does anyone think it would be a good idea to update the list of linters here https://houndci.com/configuration?

Thanks for the work @Alehanz. We've just released https://github.com/thoughtbot/hound-markdown backed by https://github.com/mivok/markdownlint. The default config coming straight from the linter https://github.com/mivok/markdownlint/blob/master/lib/mdl/rules.rb

@gylaz Yeah, that's true. It probably doesn't make much sense to mix the underlying linters with thoughtbot own services. Should I add both? I can add the links to the underlying linters for all the thoughtbot services too, if that's a better way of doing this.
But then again, how should we deal with the linters that don't have a matching thoughtbot service, like RuboCop and JSHint, for example?
The original idea behind this list was to let people better see the architecture and know where to contribute or learn from. But that can be applied to both the thoughtbot services and the linters those services are using.
What does everyone think about this?
Will add the hound-markdown one now too, thanks!

I would perfer to link to each linter-service we have in Hound itself. And then document what specific linter is being used for each of the different services

@teoljungberg That sounds good. What about the linters that don't have a matching thoughtbot service, like RuboCop?

@Alehanz for those "internal" languages, I think it makes sense to link to the libraries for now

Alright, I've edited the list a little bit and added the links to the underlying linters for each available thoughtbot service.
Let me know what you all think.
Thanks.

One more minor comment, then good to rebase and squash.

Merged in https://github.com/thoughtbot/hound/commit/07fab057ec5076c4fecfe19b483c88b047ba4274
Thanks!


Devopstudent patch 1

Enabled Codecov

Added coverage.xml report
Added codecov action to GitHub Actions

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@9f88459). Click here to learn what that means.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master       #2   +/-   ##
=========================================
  Coverage          ?   95.71%
=========================================
  Files             ?        4
  Lines             ?      140
  Branches          ?        0
=========================================
  Hits              ?      134
  Misses            ?        6
  Partials          ?        0

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Symbol preview on Search tab reflecting the selected feature on map and not selected entry in Search list

Testing pull request #98
Selected spec 2525C_B2.
On Search tab, performed search on "infantry", selected an entry in the list...

Then selected a feature on the map...

And the symbol preview on the Search tab switched to the symbol for the selected feature on the map...

I believe the intent for the Search tab is to always display the symbol for the selected entry in the search list.

Right now (even before the PR) - selecting an item on the map automatically loads that symbol into the addin.
We can:

Disable this behavior when on the Search and Favorite tab - but the user would need to reselect if they move to another tab and wanted the selected item.
Automatically open the modify tab whenever a selection occurs (but there may be cases where they would want to stay on the symbol or label tab and make another selection)
Something else?

Just let me know the preferred behavior

I'm unable to reproduce this exact issue with 2525Bc2 settings so I'm not sure what I'm doing differently, but for me the issue is I search for a symbol in the search pane, see that preview, and when I select a feature on the map the preview disappears and neither symbol preview exists in the search pane. @csmoore did you update the symbol editor this morning to do this?  I think option 1 outlined above is our best bet, although I'm not sure this would apply to the favorites tab (favorites tab is working fine for me)

@csmoore further conversations have affirmed my opinion that we should go with your option 1 in regards to the search tab. I'm not sure who would go from the modify to the search tab, as they are separate workflows/ways to use the add-in.

Just summarizing the discussion (let me know if not correct):

Currently the addin loads a symbol's state into the addin whenever a valid military symbol is selected on the map
Change to disable this load behavior whenever on the search tab

Addressed in #121 - the change was:

Disables map feature selection from search tab
Clears style search selection if a feature or a favorite has been selected on another tab
a. So user has to reselect the search list item when they return to the search tab

@csmoore @Dbarnes1 Validated on single addin built 04 Jan 2017 13:38. Closing issue.


Dashboard vs. VPS

Hello, friends.
I really liked your Dashboard! I’ve been trying to install it for a week on VPS running Ubuntu and on my macbook, but 139 ruby error constantly appears.
Here is the detailed error: https://sun9-43.userapi.com/c855532/v855532056/2288f2/MSa6xmAwvZo.jpg
What could be the problem?

I am not sure, I have not designed or documented this project in such a way to allow other people to host these dashboards outside GitHub pages.  Also I am not sure what that error is.
I would suggest starting with fastpages and read that README carefully to understand how this website works.


Source connection to Harness NextGen platform doesn't work

Harness new version so called NextGen doesn't use graphQL API anymore and hence the connection is broken.
The connection tests failed.
Please verify your API ID or key are correct. Error: GraphQL Error (Code: 405): {"response":{"error":"\r\n405 Not Allowed\r\n\r\n405 Not Allowed\r\nnginx\r\n\r\n\r\n","status":405,"headers":{}},"request":{"query":"\n query getExecutions {\n executions(offset: 0, limit: 1) {\n pageInfo {\n total\n hasMore\n }\n nodes {\n id\n status\n }\n }\n }\n"}}

Is there are suggested API we could use instead?

API url - https://apidocs.harness.io/
Do you know if we can leverage APIs in faros ? I am new to faros and wanted to check


BUG - UTC Timezones for schedules need to be reworked

Are you a current Fivetran customer?

Fivetran created PR
Describe the bug

It was found that the start_time_utc and end_time_utc fields within the ticket_schedules table are no longer accurate. We will want to add the daylight_savings and timezone tables to the package and leverage the start_time and end_time fields for the schedules.
We will then convert these schedules to UTC using the two new tables appropriatley.
Expected behavior

UTC values are accurate.

This has been resolved in the latest release of the zendesk package


Feature/search page backend integration

Initial backend integration. Some card informations are missing compared to the mock data, so design of cards isn't complete but functional.
Currently search only works by exact match.

search works better (not only exact match). Still some issues with /projects as search happens by filename

Current state search works better (not only exact match). Still some issues with /projects as search happens by filename.
Also works with paul mock data if we decide to mock for the demo.


Update adopter-registration-rest.xml to solve #1934 issue

Solving issue #1934 Rename /admin-ng/adopter/statistics #1934
Your pull request should…

[ ] have a concise title
[ ] close an accompanying issue if one exists
[ ] be against the correct branch (features can only go into develop)
[ ] include migration scripts and documentation, if appropriate
[ ] pass automated testing
[ ] have a clean commit history
[ ] have proper commit messages (title and body) for all commits
[ ] have appropriate tags applied

Thanks for the patch. Will review this later today.
If you are interested, there is also the related issue #1935

Thanks Lars, it was my first open source contribution, so in case something is wrong please let me know.
In the following days I will review #1935 to continue contributing.

That's cool. I'll try to put some additional hints at the issue which might help. Feel free to ask if you have any questions. There is also a chat (linked on https://docs.opencast.org) where usually one or two developers hang around

@VictorSalgado, I did take a short first look. This changes the REST endpoint's location but does not change the usage. Shortly looking for places where it's being used (should all be in the admin-ui-frontend module revealed at least:
modules/adopter-statistics-impl/src/main/resources/OSGI-INF/adopter-registration-rest.xml:9:    <property name="opencast.service.path" value="/admin-ng/adopter/statistics"/>
modules/admin-ui-frontend/test/test/unit/shared/controllers/applicationControllerSpec.js:30:        $httpBackend.whenGET('/admin-ng/adopter/statistics/registration').respond(
modules/admin-ui-frontend/app/scripts/shared/resources/adopterRegistrationResource.js:25:  return $resource('/admin-ng/adopter/statistics/registration');

Can you check/update those additional places as well and update the pull request?

I prefer to learn how to do it! Please tell me the hints to change the
target branch please.
Thanks in advance Lars!
El vie., 9 oct. 2020 a las 19:58, Lars Kiesow<EMAIL_ADDRESS>escribió:

@lkiesow approved this pull request.
This looks good.
The only thing left to do it to redirect this pull request against the
r/9.x branch instead of develop. To do that, the target branch of this
pull request needs to be changed, and we need to rebase this against r/9.x
using git.
I can do that for you or I can give you a few hints if want to try
yourself. Let me know.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
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or unsubscribe
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.

Here in GitHub it's simply clicking the “edit” button at the top right of the pull request and selecting r/9.x instead of develop. But in the current state, this would include several additional patches which are in develop but not in the release branch. That's something we need to change.
Opencast's  branching for the next release and the ongoing development branch looks more or less like this
               A     B  C
develop ---*---*--*--*--*--*-->
            \    /        /
      r/9.x  *--*--*--*--*-->
                         X

You have commits like A, B or C which are in develop only and which you don't want to bring to r/9x – they will become part of Opencast 10 in the long run. Your branch patch-1 is currently based on develop and includes those patches. What we want is to put these patches at the end of r/9.x behind the commit X.
You can do this with a git rebase by running:
git checkout patch-1   <- make sure you are on your branch
git rebase -i r/9.x   <- rebase your patch
git push --force-with-lease origin patch-1   <- Overwrite your current pull request

The interactive rebase (git rebase -i) will open an editor and show you each patch which is in your current branch but not in the branch you are rebasing on from oldest to newest. So, your two patches should be at the end. this should look somewhat like this:
pick e6a285c780 Oldest patch
pick 0bfd3c62bf Second oldest patch
…

 Then save and close the file. Git will now start with r/9.x and put all patches you picked on top, one after another.
Using git rebase is also really handy if you want to update your patches e.g. before creating a pull request. In addition to using pick, you can also instruct git to combine patches, change the commit message, … But we don't need that here.
Finally, the forced push will overwrite your current pull request. As with all forced actions, be careful and check if you really want to do that ;-)
If you want to try this before actually working on your patch, create a temporary branch to play around with. Something like:
git checkout patch-1
git checkout -b tmp
git rebase -i r/9.x
git log --oneline --decorate

Hi Lars,
I'm very grateful that you to showed me how to do it and all the tips that you've given to me.
I've followed all the steps that you said to me and I think the pull request is ready.

Thanks again for the patch. Happy to talk anyone through something like this if they are interested ;-)
One very minor thing that was missing was to actually change the target branch here in GitHubs user interface. But since that's really just a click in the user interface… I just did that:

Have fun with other Hacktoberfest tasks! And let us know if you are looking for other small tasks to try (Also, what type of task JS, Java, Python, …)


extra -> tagc does only contain one entry where multiple are set

Hello folks,
I'm using Subler to set metadata on my mediafiles. Subler offers me to either declare a Subtitle as Forced, Auxiliary content, hearing impaired etc. Using Mediainfo I can also see this metadata at extra -> tagc
{
"@type": "Text",
"@typeorder": "6",
"ID": "9",
"Format": "Timed Text",
"MuxingMode": "sbtl",
"CodecID": "tx3g",
"Duration": "5669.916",
"BitRate_Mode": "VBR",
"BitRate": "72",
"FrameRate": "0.453",
"FrameCount": "2567",
"StreamSize": "51184",
"Language": "en",
"Default": "No",
"Forced": "No",
"AlternateGroup": "2",
"Encoded_Date": "UTC 2023-06-15 07:44:22",
"Tagged_Date": "UTC 2023-06-15 07:44:22",
"extra": {
"tagc": "public.accessibility.transcribes-spoken-dialog"
}
},

The problem here is that I can also set multiple values for a subtitle here using Subler, but mediainfo will only display one of them:

Can we please have all outputted ?
Thanks in advance

A sample file, please.

Sure, I created a mp4 file only containing tx3g subtitles, also using Subler, then I attached all tabs of all subtitles as separate picture. Please obtain the zip archive here:
issue assets.zip
thanks for your Help :)


Error while installing vscode via ubuntu software center. Also attached error log.

VSCode Version: code_1.17.1-1507645403_amd64.deb
OS Version: Ubuntu 16.04.3 64bits

Steps to Reproduce:

Download .deb for your vscode website
add it to gdebi package installer
Check Lintian output tab

Reproduces without extensions: Yes/No Not applicable
I am using Ubuntu 16.04. I am getting this output of error. I have managed to install via GDebi package manager. But not sure how stable it is now. The below is the error output of Lintian.
Lintian.txt
I hope this could help you to make it install via ubuntu software center. Thanks for making opensource software and keep doing the great job.

Also include terminal installation procedure for linux os. This will help us troubleshoot installation error and solve the installation failure.

same trouble here. @araviaravi you method worked
like for .deb
sudo dpkg -i <file>.deb
sudo apt-get install -f # Install dependencies
or for installing manually with the following script:
curl https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > microsoft.gpg
sudo mv microsoft.gpg /etc/apt/trusted.gpg.d/microsoft.gpg
sudo sh -c 'echo "deb [arch=amd64] https://packages.microsoft.com/repos/vscode stable main" > /etc/apt/sources.list.d/vscode.list'
sudo apt-get update
sudo apt-get install code # or code-insiders

Dupliate https://github.com/Microsoft/vscode/issues/20380


Login info for Web UI

I am not sure if i am just over looking it or if you forgot to say what the username and password is for the web interface?

Thank you for pointing this out. I've updated the Readme with default login info.
Email<EMAIL_ADDRESS>Password: npmlite


Incorrect window placement/scaling in QT apps

My window manager is Openbox and Cortile does not recognize the Openbox decoration specifically with QT-App. In GTK apps it recognizes the decoration without any problems. I noticed a hint in the log file as to what might be the problem. The (Tint2) panel is taken out by Cortile, which means I no longer have a 1920x1080 desktop resolution, but 1920 x 1052. My panel is 28px high, so that's fine. In the case of placing QT apps, Cortile probably uses a different resolution than GTK apps, which could explain the upward shift. Could you correct that?

It seems that with the QT apps, the resolution dimensions are taken from the value that the panel has already downscaled. Specifically, this means:
GTK app calculation of resolution = (1920x)1080px - panel height minus 28px = 1052 px desktop height, which is adopted as the internal cortile resolution. CORRECT
QT app calculation of resolution=(1920x)1052 -Panel height 28px = 1024 px desktop height which is adopted as internal cortile resolution. INCORRECT
So in the case of QT apps, the internal Cortile desktop only starts at 56 px (2 x 28px), because it takes the already downsampled value of 1052 px as a BASE and doesn't take 1080px again to downsample it. It pulls double duty as the Tint Panel.
This is my guess because everything points to it, and the incorrect additional scaling corresponds exactly to the height of the Tint2 Panel.

My previous assumption was incorrect, which is why I deleted the comment and added a more specific case description here. As can be seen from the images below, the discrepancy in scaling depends on the openbox decorations (green), especially the QT APPS. Especially in the slave window at the bottom right you can see how the distances at the very bottom edge change parallel to the title decoration size. If I enlarge the title bar, the distance to the bottom edge (top tint panel edge) becomes the same size as the Openbox title bar decoration. If I make the Openbox title bar decoration smaller, the distance below to the Tint panel edge also becomes smaller. The QT app on the right is oriented towards the GTK app on the left without taking the decoration into account, which is positioned correctly. So when scaling, the Openbox title bar is not taken into account and it is always based on the GTK app on the left without a title bar. And in the lower right QT app, a large space is added at the bottom, just like an Openbox title bar.

As can be seen from the images below, the discrepancy in scaling depends on the openbox decorations (green), especially the QT APPS.

I think you are on the right track here.
Can you give a minimal example QT application that I can use for testing?
Can you confirm that the issue does not appear if you set the default config
https://github.com/leukipp/cortile/blob/7c42aea195fc375afbac7b469653eb2b11ec5100/config.toml#L62
to window_decoration = false ?

With the standard configuration "Window Decoration = false" i.e. without decoration everything works perfectly. GTK and QT apps are positioned correctly. Only if I want to have the decoration, i.e. "Window Decoration = true", then this problem arises. All QT apps lead to problems. Especially in my case it is worth mentioning the file manager "pcmanfm-qt", note program "feathernotes". But all other QT apps that I tested alternatively also led to this behavior.

This should be fixed with the latest release. Feel free to reopen/create an issue if you encounter any other problems.


Fix qBittorrent injection edge cases

Hopefully fixes #74, fixes #144
Please test. Docker tag qbittorrent or clone the repo, check out the qbittorrent branch, npm link && npm link cross-seed

I'll deploy it on my server and report any issues. Thanks for all the effort you're putting into this. I really appreciate it.

Didn't run it for too long. When one had injected, which was a single file, it created it in a folder, so ended up re-downloading.

@muddro1 a couple questions

what content layout was the source torrent added with originally? (Subfolder, NoSubfolder, Original)
did you have auto torrent management on?
would you be willing to send me the torrent file in the discord after removing all announce urls?

@muddro1 a couple questions
* what content layout was the source torrent added with originally? (Subfolder, NoSubfolder, Original) - Not 100% sure. Do you mean the one prior to adding the cross-seed? If that one, then that was nosubfolder (is there a way for me to check to confirm, I am just basing this on it dling xxxxx.mkv directly with no folder.

* did you have auto torrent management on? - I generally have it on. In 3.3.0 the crossseeds would be added with ATM turned off. I think after that version they have been turned on by your app.

* would you be willing to send me the torrent file in the discord after removing all announce urls? -Sure if you can show me how.

Just to leave my comment on this as well, single file torrents are now exactly displayed like their "original", down to the folder view and category. Very nice. The only thing differentiating them is the tag.
@muddro1 If you had previous torrents without the subfolder and you're now using it together with this version of cross-seed, when it adds cross-seeds for those previous torrents, qBittorrent will put them in a folder and there's no way around that, so it'll download again. I circumvent that by simply not checking torrents older than 3 days. But yeah, that just tells me its working, cause it happened for one of mine as well and thats essentially my fault as I changed the setting back to subfolder creation.

If you had previous torrents without the subfolder and you're now using it together with this version of cross-seed, when it adds cross-seeds for those previous torrents, qBittorrent will put them in a folder and there's no way around that, so it'll download again.

Not sure I follow, but this does seem like a cross-seed problem. Could you elaborate with a more specific example?

Oh don't worry this is doesn't seem like a bug to me.
Essentially, before I switched back to subfolder creation I had torrents as single files to at least get cross-seed working, ya know.
So lets say the file is here: torrents/file.mkv
Now, because I re-enabled subfolder creation, the cross-seeding torrent corresponding to that original one will have a path of torrents/file/file.mkv. But that's to be expected. I should've moved the original to a subfolder first. This does not seem like a cross-seed problem to me, cause newly added torrents will be in a subfolder now and cross-seed will have a correct path when injecting cross-seeds for those.

But that's to be expected.

It's not. cross-seed doesn't check your global content layout setting, it attempts to read the current content layout of the source torrent in the client. Could you also answer these questions for the torrents you noticed failed?

what content layout was the source torrent added with originally? (Subfolder, NoSubfolder, Original)
did you have auto torrent management on?
would you be willing to send me the torrent file in the discord after removing all announce urls?

Oh interesting!

original
no
sure, am already on the discord, just ping me haha

Not 100% sure. Do you mean the one prior to adding the cross-seed? If that one, then that was nosubfolder (is there a way for me to check to confirm, I am just basing this on it dling xxxxx.mkv directly with no folder.

That could be NoSubfolder or Original. How did the torrent get added to qBittorrent in the first place? If it was automatic, you could check your Sonarr/Radarr (or whatever else added it) settings to see if there's a content layout option. Otherwise it would probably just be your default (which you can see in Settings)
Re: removing announce urls, one way to do it is right from inside your client. You can remove a tracker URL by right clicking on the tracker in the trackers list:

After that you can grab/copy the torrent file from the session directory, send it to me, then add the announce URL back.

In addition to the storage location issue, I just noticed that the cross-seed injected torrent also has no category. The ones before and after have it correctly set. Must be some really weird edge case :thinking:

In addition to the storage location issue, I just noticed that the cross-seed injected torrent also has no category. The ones before and after have it correctly set. Must be some really weird edge case.

The same exact torrent both has no category and also has missing files?
I'm wondering if it picked up a cross-seeded torrent from a previous run as the "source torrent" - this would be the reason it wouldn't have the category.
I'm wondering if the torrent it had identified as the source torrent was already in the "missing files" state. Might that have been the case?
What happens if you remove all torrents that cross-seed found and injected for the offending torret, and then run it again?

It definitely must've picked up the original, assuming it is correctly ignoring torrents with the "cross-seed" label.
The original torrent was definitely not in a missing files state.
Will test removing torrents and running it again in a few hours. Btw, with everything now set up using subfolders, new torrents being added and cross seed injecting more, everything seems to work flawlessly. This might just be a super rare edge case when your original has a different storage method (original) compared to what qBittorrent is set to now (subfolder). Is this actually something cross-seed should be able to handle now? Cause I don't think this will happen too often in the wild 🤔

It definitely must've picked up the original, assuming it is correctly ignoring torrents with the "cross-seed" label.
The original torrent was definitely not in a missing files state.

When cross-seed runs, we first read all the torrent files in your torrent directory, and then deduplicate them based on their names (cross-seed makes the assumption that any two torrents with the same name came from an earlier cross-seed run).
Because of this, for a given group of torrents that all have the same name, the representative torrent is not necessarily the "original" torrent, but the first torrent in the group (which is likely the one with the "earliest" info hash, alphabetically).
For the purposes of strictly finding cross-seeds, this is sufficient because all torrents in the group have identical file trees, which is how we do matching. Cross-seed only communicates with your torrent client when it finds a match and needs to inject it.
Because of this, for the "missing files" bug to fully go away (to the best of my knowledge thus far), you'll need to delete any torrents in the client which are in a "missing files" state, and for autoTMM to fully start working, you'll need to either delete all torrents that cross-seed previously injected and re-run it, or assign categories to all of the torrents cross-seed previously injected.

The original torrent was definitely not in a missing files state.

@Byter09 do you mean to say that there may have been some cross-seeds of the original torrent that were in a missing files state?

As described in a comment above, the torrent cross-seed injected was in a missing files state till I adjusted the location path again.

For the purposes of strictly finding cross-seeds, this is sufficient because all torrents in the group have identical file trees, which is how we do matching. Cross-seed only communicates with your torrent client when it finds a match and needs to inject it.
Because of this, for the "missing files" bug to fully go away (to the best of my knowledge thus far), you'll need to delete any torrents in the client which are in a "missing files" state, and for autoTMM to fully start working, you'll need to either delete all torrents that cross-seed previously injected and re-run it, or assign categories to all of the torrents cross-seed previously injected.

And for that exact reason I think its fine and not really a bug. This branch/image works perfectly so far. It's only that one torrent that it injected which ended up in a missing-files state, and I manually fixed that. So I really do not think this is something to worry about.
Kind of busy this coming week, so I can't really do any testing, but again, everything is working so far, with autoTTM off and subfolders on.

This is still broken - it's still matching single units with folders. Data is the exact same, it's the files themselves that are different. .mkv came first.

@KyleSanderson can you be more specific? I don't understand what you mean.

@KyleSanderson can you be more specific? I don't understand what you mean.

As part of BEP3 - a torrent file contains a name key that may or not may be honoured by the client.
In the case of a single torrent file, this contains the name of the file.
In the case of a multi-file torrent file, the name key is the suggested directory to house these multiple files.
The infohash will be the same, but the actual layout of the contents of the file will be different based on this differentiation. When cross-seed is injecting files, the infohash is the exact same, but some files come in the multi-file format, and others come in the single file format. This results in the client, qBittorrent, being unable to find the existing file, and instead triggers a brand new download action, resulting in two+ copies of the exact same file.
Lastly, this is using the "Original" Content Layout field on qBittorrent.

I'm pretty sure that the files array (for a multi file torrent) and length (single) are inside the info dictionary, meaning that you couldn't have a multi file torrent with the same info hash as a single file torrent. Ultimately though that probably doesn't have any impact on the bug.
Can you examine these torrent files and verify that cross-seed indeed matched a multi-file torrent to a single-file torrent?

I'm pretty sure that the files array (for a multi file torrent) and length (single) are inside the info dictionary, meaning that you couldn't have a multi file torrent with the same info hash as a single file torrent. Ultimately though that probably doesn't have any impact on the bug.
Can you examine these torrent files and verify that cross-seed indeed matched a multi-file torrent to a single-file torrent?

Yes - this is guaranteed.

Guaranteed by what?

Guaranteed by what?

There is no other way that these files are added other than cross-seed into this client.

Just because they downloaded data doesn't mean that cross-seed is finding false positives though.

Just because they downloaded data doesn't mean that cross-seed is finding false positives though. I think it means they're getting injected into the wrong place.

The source torrents are constructed fundamentally differently. It's the same underlying data, but the torrent types that it's not doing the placements (or migrations) properly stem from these single file torrents to multi-files, with a single directory. It's a single destination file, but under the files dict so it creates a dir as per BEP3 which is where cross-seed is falling short.

@KyleSanderson has identified a bug in this PR specifically with torrents which have autoTMM on but no category. @muddro1 do you use that configuration?

Okay @KyleSanderson that bug should be fixed. Instead of using this heuristic to determine the content layout:
const shouldManuallyEnforceContentLayout =
    isSingleFileTorrent(newTorrent) &&
    dirname(content_path) !== save_path;

I added another API call to qBittorrent (which I had been hoping to avoid):
async isSubfolderContentLayout(searchee: Searchee): Promise<boolean> {
	// hit /torrents/files endpoint and get json back as "files" variable
	return files.length === 1 && name !== path.posix.basename(name);
}

const shouldManuallyEnforceContentLayout =
    isSingleFileTorrent(newTorrent) &&
    (await this.isSubfolderContentLayout(searchee));

I use a category, but it sounds like what I was experiencing:
Original torrent added by arr, in Original layout. It was a single file so it was in the designated folder (per category) just the file (not contained within a folder of its own name). When injection happened it was placed in a subfolder of its own name, and obviously didn't match so started downloading all over again. I believe in that version cross seeds injected with atm on.

Okay, I think qbit injection has been broken on master for long enough lol, and I have a relatively high degree of confidence in this PR at this point. So I'm gonna merge this in. Hopefully any remaining bugs are in low-volume configurations.

v3.3.3

Okay @KyleSanderson that bug should be fixed. Instead of using this heuristic to determine the content layout:
const shouldManuallyEnforceContentLayout =
    isSingleFileTorrent(newTorrent) &&
    dirname(content_path) !== save_path;

I added another API call to qBittorrent (which I had been hoping to avoid):
async isSubfolderContentLayout(searchee: Searchee): Promise<boolean> {
	// hit /torrents/files endpoint and get json back as "files" variable
	return files.length === 1 && name !== path.posix.basename(name);
}

const shouldManuallyEnforceContentLayout =
    isSingleFileTorrent(newTorrent) &&
    (await this.isSubfolderContentLayout(searchee));

Still not correct on 3.4.0. The source content is a single file, I'm now forcing a directory for layout in qbittorrent. Getting "Missing Files" from the cross-seed inject (and even new downloads triggering).

Working as it should for me

@KyleSanderson  do you use windows or posix? Also can you try the command cross-seed tree on the torrent?


Grammatical Tweaks to the Docs

I just went through the docs with Grammarly trying to find any issues in the docs, it picked up some issues, while other changes can be viewed as more optional (sometimes redundancy is necessary when trying illustrate a point) so remove or tweak back anything you want to stay the same, and if not hopefully this caught atleast a couple things that should be changed, I also tried to stay within common sense and reason and not force any particular dialect of English onto the Docs!

@adlerjohn I added your changes I am pretty sure, I think I did it in the wrong order though so some got pushed to outdated and can't be directly commited, but combing through it looks like they were added. Lmk though if I missed something and another change is needed


adding apply button

Hi Pavel,
Here is the PR for my idea referenced in discussion #109. The code was mostly me asking ChatGPT questions as I don't know AHK syntax too well, so feel free to modify it or toss this PR out completely if you feel it's not the ideal solution -- I am glad to just have the feature 😀.
Thank you!

This was nicely done. Thank you for contributing this!
I made a few tweaks directly:

Separated the closing to keep ApplyMainSettings doing just what it says. (It's a tiny thing here, just a good habit.)
Designated only one button as "Default" (what happens when the user presses Enter).

BTW, there's also a way to use a default value for an argument (which I didn't use here) which lets you call ApplyMainSettings() without argument when you don't want to close the dialog:
   ...
    if ( close == true ) {
        CloseMainDialog()
    }
}`


Remove old docs

I forget the reasoning behind keeping old docs under an old folder, but I don't see any reason why we need this any more.  It might confuse user/contributors and we can always go back in time with git to see the old things.

This was only here because at the time we wanted to easily reference old version of docs so we didn't have to rewrite them. I think they're all so out of date now that they have no value.
Composing pipelines and provenance info has been documented elsewhere, right?
PR LGTM

Yeah, but everything is versioned here, so, if we needed to, we could pull an old version, right?  Composing pipelines and provenance are integrated, at least partially, in the pachyderm fundamentals section.


Sessions shouldn't be created with every request

aiohttp docs state

Note
Don’t create a session per request. Most likely you need a session per application which performs all requests altogether.
More complex cases may require a session per site, e.g. one for Github and other one for Facebook APIs. Anyway making a session for every request is a very bad idea.
A session contains a connection pool inside. Connection reusage and keep-alives (both are on by default) may speed up total performance.

We abuse that in quite a lot of places
https://github.com/Tert0/fastapi-discord/blob/ced6b8cb5ba772219b8995dd31e281bcb401719c/fastapi_discord/client.py#L54
https://github.com/Tert0/fastapi-discord/blob/ced6b8cb5ba772219b8995dd31e281bcb401719c/fastapi_discord/client.py#L58
https://github.com/Tert0/fastapi-discord/blob/ced6b8cb5ba772219b8995dd31e281bcb401719c/fastapi_discord/client.py#L76
https://github.com/Tert0/fastapi-discord/blob/ced6b8cb5ba772219b8995dd31e281bcb401719c/fastapi_discord/client.py#L88

Fixed as of b903e32e64ddc50249f005c5332fc1e5f0b79e94


Updating HealthcareApis to specify Kind

Updating HealthcareApis  SDK to support more than one kind of service
The *.csproj and AssemblyInfo.cs files have been updated with the new version of the SDK.
REST spec: https://github.com/Azure/azure-rest-api-specs/blob/master/specification/healthcareapis/resource-manager/Microsoft.HealthcareApis/preview/2018-08-20-preview/healthcare-apis.json

/azp run

/azp run net - mgmt - ci

@poadhika , could you follow the instruction to regenerate the PR? I did not see update in csproj and .txt

I regenerated the code pointing towards the latest swagger spec using the powersell cmd "AutoRestCodeGenerationWithLocalConfig ". Because while I was using "AutoRestCodeGeneration", it was constantly throwing me error.  " Error: Cannot write data to 'https://github.com/Azure/azure-rest-api-specs/blob/master/specification
/healthcareapis/resource-manager/generated/HealthcareApisManagementClient.cs'. Protocol 'https:' not supported for
writing. Make sure to specify a local, absolute path as target file/folder."

I notice that there's no C# configuration in https://github.com/Azure/azure-rest-api-specs/blob/master/specification/healthcareapis/resource-manager/readme.md, please follow other service to add, thanks.

@erich-wang
I updated the readme file and created a pull request for it. Following is the link: https://github.com/Azure/azure-rest-api-specs/pull/6890. This is blocking me to regenerate the SDK now. Is it possible for you to review this PR?

@poadhika , the spec is merged, please go update this PR

@erich-wang
I have updated the PR. Please take a look. We are hoping to meet the AzurePS deadline that is August 26. Since PS is dependent upon SDK nuget release, I am hoping to close this PR sooner.

@erich-wang I have updated the version in Assembly.info and .csproj


SN Light Curve Analysis

Develop SN Monitor code

Renaming this epic, as in #36. Twinkles SN light curve analyses are TBD, but this thread can be used to track their development.


LAB2: Bubble Sort Array

Fixes #
Changes proposed in this PR:

bubble sort program
unit test

Codecov Report

Merging #47 into master will not change coverage.
The diff coverage is 100%.

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=====================================
  Coverage     100%   100%
=====================================
  Files           2      3    +1
  Lines           9     22   +13
=====================================
+ Hits            9     22   +13

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02_bubble/main.go
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This all looks good. One change I would suggest if you want would be to get rid of TestBubbleSortOutput() and TestInsertionSortOutput() and just add those tests to the table-driven tests you have. You could use these same test function names for the table-driven tests since they are no longer all edge cases.
Anyway, just a suggestion for the future - if you can get away with less code (tests or main code), so much the better - less to maintain, less to understand.

@camh-anz thank you so much for your time and suggestions. You guys are awesome in knowledge sharing 👍


PresQT specific metadata homework

We are looking to come up with decisions on PresQT(specific) metadata.  This metadata will be dealing with file metadata and transnational metadata used for PresQT transactions preformed.  Note these are separate from the metadata partner sites use.
We are looking for a possible schema to use, what(if any) specific fields that PresQT will use, what fields(if any) are mandatory from partners vs optional and where/how to store the PresQT specific metadata.
Here are a couple of links to look in to and see if there is inspiration to be found with these sources.
http://openarchives.org/rs/1.1/resourcesync#motivExample
http://www.openarchives.org/pmh/tools/

here's a disciplinary interchange spec for an example https://compass.astm.org/EDIT/html_annot.cgi?E2077+00(2016)#s00015

Example of context block in JSON defining source URI's for terms:
https://github.com/share-research/api-schemas/blob/master/schemas/share_work_ld.json

Why we don't want to write a metadata file with each file transferred
https://writings.stephenwolfram.com/2015/04/scientific-bug-hunting-in-the-cloud-an-unexpected-ceo-adventure/


Is front camera used in stabilisation?

In your Readme it says that you use bottom camera for ground speed measurement. Is the front camera also used for similar stabilization/speed measurement ?

Not at this stage. An interesting development would be to use the video feed and perform some structure from motion to help improving the attitude estimation.


.Net: Weaviate configuration malformed

Describe the bug
If i want to connect to weaviate i have to specify the url as: [WeaviateURL]/v1/ and the api key as: Bearer [APIKEY]
Otherwise it doesn't connect
To Reproduce
Download the semantic-kernel repo and run the KernelSyntaxExample:Example46_Weaviate with the URL and API key you get from the weaviate cloud service dashboard admin
Doesn't work
"Weaviate:Endpoint": "https://example.weaviate.network/",
"Weaviate:ApiKey": "exampleKey"
Works
"Weaviate:Endpoint": "https://example.weaviate.network/v1/",
"Weaviate:ApiKey": "Bearer exampleKey"

Fixed in the new release, i used the old version


"address" command must require mnemonic parameter to be enclosed with quotes

Otherwise, if mnemonic is provided without quotes it shows a different address. Probably taking into account only the first word and ignoring the rest of the mnemonic.

Resolved by #49


Question about a difference in the value of the author's recall and my recall.

I have a question because there is a difference in the value of the author's top-k recall  and my top-k recall.
When validating with the checkpoint posted by the author, the result value as shown in the following picture comes out. This results in a value different from the value raised by the author(site:https://github.com/Cuberick-Orion/CIRPLANT/blob/main/DOWNLOAD.md), and the loss value is 0.3. What's the reason?

Hi,
Thank you for your interest in our work.
Without detailed error messages/debug info I cannot say for sure,  but the validation results you posted look like a random guess - suggesting maybe the checkpoint was not properly loaded.
We have verified that we are able to reproduce the numbers from our papers using the checkpoint.
Please comment with more details if you are unable to debug on your end.

If I proceed with the verification, it looks like the following, but there seems to be no errors. What's the problem?

Hi @GaEunKim-study, I seem to be running into the same issue as well, were you able to resolve the same?

Hi,
Following previous replies, could you upload a more detailed log of what happened?
Once again, the results resemble a random guess, suggesting that the checkpoint may not have been properly loaded. As evidence - the screenshot posted by @GaEunKim-study states Could not register shared tensor state dict hooks, which may be the reason.

Hi @GaEunKim-study, I seem to be running into this issue as well, were you able to resolve the same?

This is a more detailed log of my results, let me know if any other log files are required to diagnose this issue.
Global seed set to 88
===========
PLACEHOLDER (Insert manual comments here)
=====Args commenting======
Validation_test
===========
Using 16bit native Automatic Mixed Precision (AMP)
GPU available: True, used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
[18:22:20] INFO      Called with command (copy this for reproduction):                       lightning_logger.py:114trainval_oscar.py --dataset cirr --usefeat nlvr-resnet152_w_empty --max_epochs 300 --model CIRPLANT-img --model_typebert --model_name_or_path data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087/ --task_name cirr --gpus 1
--img_feature_dim 2054 --max_img_seq_length 1 --model_type bert --do_lower_case --max_seq_length 40 --learning_rate
1e-05 --loss_type xe --seed 88 --drop_out 0.3 --weight_decay 0.05 --warmup_steps 0 --loss st --batch_size 32
--num_batches 529 --pin_memory --num_workers_per_gpu 0 --comment Validation_test --output
saved_models/cirr_rc2_iccv_release_test --log_by recall_inset_top1_correct_composition --validateonly
--load_from_checkpoint ./saved_models/epoch_277_step_147061.ckpt

sorted args (complete list):
[18:22:21] INFO      random_seed::88                                                         lightning_logger.py:114           INFO     Better speed can be achieved with apex installed from                       modeling_bert.py:226                    https://www.github.com/nvidia/apex .
           INFO     Better speed can be achieved with apex installed from                      modeling_xlnet.py:339                    https://www.github.com/nvidia/apex .
Could not register sharded tensor state dict hooks
           INFO     loading configuration file                                                 modeling_utils.py:160                    data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087/config.json
           INFO     Model config {                                                             modeling_utils.py:177                      "attention_probs_dropout_prob": 0.1,
                      "finetuning_task": "cirr",
                      "hidden_act": "gelu",
                      "hidden_dropout_prob": 0.1,
                      "hidden_size": 768,
                      "img_feature_dim": 2054,
                      "img_feature_type": "faster_r-cnn",
                      "initializer_range": 0.02,
                      "intermediate_size": 3072,
                      "layer_norm_eps": 1e-12,
                      "max_position_embeddings": 512,
                      "num_attention_heads": 12,
                      "num_hidden_layers": 12,
                      "num_labels": 2,
                      "output_attentions": false,
                      "output_hidden_states": false,
                      "torchscript": false,
                      "type_vocab_size": 2,
                      "vocab_size": 30522
                    }

           INFO     Model name                                                             tokenization_utils.py:170                    'data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087/' not
                    found in model shortcut name list (bert-base-uncased,
                    bert-large-uncased, bert-base-cased, bert-large-cased,
                    bert-base-multilingual-uncased, bert-base-multilingual-cased,
                    bert-base-chinese, bert-base-german-cased,
                    bert-large-uncased-whole-word-masking,
                    bert-large-cased-whole-word-masking,
                    bert-large-uncased-whole-word-masking-finetuned-squad,
                    bert-large-cased-whole-word-masking-finetuned-squad,
                    bert-base-cased-finetuned-mrpc). Assuming
                    'data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087/' is a
                    path or url to a directory containing tokenizer files.
           INFO     loading file data/Oscar_pretrained_models/base-vg-labels/ep_107_119208 tokenization_utils.py:214                    7/added_tokens.json
           INFO     loading file data/Oscar_pretrained_models/base-vg-labels/ep_107_119208 tokenization_utils.py:214                    7/special_tokens_map.json
           INFO     loading file                                                           tokenization_utils.py:214                    data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087/vocab.txt
           INFO     loading weights file data/Oscar_pretrained_models/base-vg-labels/ep_107_11 modeling_utils.py:444                    92087/pytorch_model.bin
[18:22:22] INFO     BertImgModel Image Dimension: 2054                                          modeling_bert.py:158[18:22:23] INFO     Weights from pretrained model not used in ImageBertForImageFeature:        modeling_utils.py:505                    ['cls.predictions.bias', 'cls.predictions.transform.dense.weight',
                    'cls.predictions.transform.dense.bias',
                    'cls.predictions.transform.LayerNorm.weight',
                    'cls.predictions.transform.LayerNorm.bias',
                    'cls.predictions.decoder.weight', 'cls.seq_relationship.weight',
                    'cls.seq_relationship.bias']

Start init BaseDataset class...
           INFO      adding json split.rc2.val.json                                          lightning_logger.py:114           INFO      adding json cap.rc2.val.json                                            lightning_logger.py:114           INFO      adding json cap.ext.rc2.val.json                                        lightning_logger.py:114init CIRR_rc2 -> val -> None, usefeat::['nlvr-resnet152_w_empty'] ...
         total number of imgs:: 2297
         total number of pairs:: 4181

Start init BaseDataset class...
[18:22:24] INFO      adding json split.rc2.val.json                                          lightning_logger.py:114           INFO      adding json cap.rc2.val.json                                            lightning_logger.py:114           INFO      adding json cap.ext.rc2.val.json                                        lightning_logger.py:114init CIRR_rc2 -> val -> None, usefeat::['nlvr-resnet152_w_empty'] ...
         total number of imgs:: 2297
         total number of pairs:: 4181
           INFO                                                                              lightning_logger.py:114                     In testonly:: False

Init dataloader (split->val_loader):: val -> img+txt

Num_worker: 0, pin_memory: True
Init dataloader (split->val_loader):: val -> img

Num_worker: 0, pin_memory: True
           INFO      No. batch in train: 131                                                 lightning_logger.py:114           INFO      Optim::AdamW                                                            lightning_logger.py:114
===
Finished loading train/val datasets, entering train/val function

Could not register sharded tensor state dict hooks
           INFO     loading configuration file                                                 modeling_utils.py:160                    data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087/config.json
           INFO     Model config {                                                             modeling_utils.py:177                      "attention_probs_dropout_prob": 0.1,
                      "finetuning_task": "cirr",
                      "hidden_act": "gelu",
                      "hidden_dropout_prob": 0.1,
                      "hidden_size": 768,
                      "img_feature_dim": 2054,
                      "img_feature_type": "faster_r-cnn",
                      "initializer_range": 0.02,
                      "intermediate_size": 3072,
                      "layer_norm_eps": 1e-12,
                      "max_position_embeddings": 512,
                      "num_attention_heads": 12,
                      "num_hidden_layers": 12,
                      "num_labels": 2,
                      "output_attentions": false,
                      "output_hidden_states": false,
                      "torchscript": false,
                      "type_vocab_size": 2,
                      "vocab_size": 30522
                    }

           INFO     Model name                                                             tokenization_utils.py:170                    'data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087' not found
                    in model shortcut name list (bert-base-uncased, bert-large-uncased,
                    bert-base-cased, bert-large-cased, bert-base-multilingual-uncased,
                    bert-base-multilingual-cased, bert-base-chinese,
                    bert-base-german-cased, bert-large-uncased-whole-word-masking,
                    bert-large-cased-whole-word-masking,
                    bert-large-uncased-whole-word-masking-finetuned-squad,
                    bert-large-cased-whole-word-masking-finetuned-squad,
                    bert-base-cased-finetuned-mrpc). Assuming
                    'data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087' is a path
                    or url to a directory containing tokenizer files.
           INFO     loading file data/Oscar_pretrained_models/base-vg-labels/ep_107_119208 tokenization_utils.py:214                    7/added_tokens.json
           INFO     loading file data/Oscar_pretrained_models/base-vg-labels/ep_107_119208 tokenization_utils.py:214                    7/special_tokens_map.json
           INFO     loading file                                                           tokenization_utils.py:214                    data/Oscar_pretrained_models/base-vg-labels/ep_107_1192087/vocab.txt
           INFO     loading weights file data/Oscar_pretrained_models/base-vg-labels/ep_107_11 modeling_utils.py:444                    92087/pytorch_model.bin
[18:22:26] INFO     BertImgModel Image Dimension: 2054                                          modeling_bert.py:158[18:22:27] INFO     Weights from pretrained model not used in ImageBertForImageFeature:        modeling_utils.py:505                    ['cls.predictions.bias', 'cls.predictions.transform.dense.weight',
                    'cls.predictions.transform.dense.bias',
                    'cls.predictions.transform.LayerNorm.weight',
                    'cls.predictions.transform.LayerNorm.bias',
                    'cls.predictions.decoder.weight', 'cls.seq_relationship.weight',
                    'cls.seq_relationship.bias']

loaded checkpoint from ./saved_models/epoch_277_step_147061.ckpt

/home/aza6352/anaconda3/envs/cirr/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py:817: LightningDeprecationWarning: `trainer.validate(val_dataloaders)` is deprecated in v1.4 and will be removed in v1.6. Use `trainer.validate(dataloaders)` instead.
  "`trainer.validate(val_dataloaders)` is deprecated in v1.4 and will be removed in v1.6."
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3]
Validating: 0it [00:00, ?it/s]

[('recall_top1_correct_composition', 0.0009567089213106913),
 ('recall_top2_correct_composition', 0.001195886151638364),
 ('recall_top5_correct_composition', 0.0028701267639320736),
 ('recall_top10_correct_composition', 0.004305190145898111),
 ('recall_top50_correct_composition', 0.01961253288686917),
 ('recall_top100_correct_composition', 0.03982300884955752),
 ('recall_inset_top1_correct_composition', 0.21107390576417126),
 ('recall_inset_top2_correct_composition', 0.39416407558000477),
 ('recall_inset_top3_correct_composition', 0.5862233915331261)]

--------------------------------------------------------------------------------
DATALOADER:0 VALIDATE RESULTS
{}
--------------------------------------------------------------------------------
DATALOADER:1 VALIDATE RESULTS
{}
--------------------------------------------------------------------------------
Validating: 0it [00:05, ?it/s]

I think I have identified the issue, I am able to reproduce the recall scores while using ResNet152 image features. However, I wish to use the FRCNN image features along with this model. Which arguments do I need to change in order to use the FRCNN features in your script?

Hi,
Glad to hear that you managed to solve the issue. Indeed, our published result is based on ResNet152 features -- the global visual feature.
To use the FRCNN feature, you might need to modify the codebase a bit so that it accepts sequential image tokens.
Obviously, this comes after we published the ICCV paper -- but we did confirm that using sequential features brings some improvements to the performance.


Can no longer raise bug reports on forums.bridge.net?

If I go here:
https://forums.bridge.net/forum/bridge-net-pro/bugs
then there doesn't appear to be any "New Post" button. Is that a change or a mistake?
I realised that if I start here
https://forums.bridge.net/forum
and go to Premium Help (https://forums.bridge.net/forum/premium/premium-help) that maybe there would be no New Post button since I'm not a Premium member yet but it seems like I can't raise reports at all on the forum site!
Hardly the end of the world since I can raise GH issues but I thought that it was worth mentioning.

Hello @ProductiveRage! Sorry for the problem. The "bugs" forum is now inside the "premium" section of the site. So if you are not premium, you should not be able to post there.
But don't worry, post your bug report within the community *Help forum, then we move the report to the bugs forums as soon as it gets confirmed as a bug by us.
In fact, even premium users will not be able to post in the Bugs forums directly. Instead, the reports/requests can be made in the Premium Help forum. Likewise, when we confirm the thread as a bug, we just move them within the bugs forum.

I removed @fabriciomurta response since it contained some wrong information.
The Bugs forum will be open for everyone to post. Looks like it picked up the Premium group permissions when it was moved. All members should have access to create threads now. Please let me know if you do not.
Even through the Bugs forum is in the Premium forum group, the permissions are set to allow all members to create new threads, and to participate in any thread. The Bugs forum was placed inside the Premium group mainly out of convenience. I wanted it high on the forum page, it doesn't fit only in the Community group, I didn't want to create two bugs forums, etc. With the correct permissions, it seemed to fit best in the Premium group.
We are going to encourage all Bug reports to be reported in the forums vs GitHub. The Bridge team will move verified bugs or feature requests from the forums into GitHub issues as required.
Hope this helps clarify the process.


Refactoring/non-critical-typing-refactoring

Codecov Report

Merging #54 (8ee2618) into master (d789b60) will not change coverage.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##            master       #54   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files           17        17
  Lines          665       663    -2
  Branches        72       120   +48
=========================================
- Hits           665       663    -2

Impacted Files
Coverage Δ

aioauth/grant_type.py
100.00% <100.00%> (ø)

aioauth/models.py
100.00% <100.00%> (ø)

aioauth/server.py
100.00% <100.00%> (ø)

aioauth/fastapi/forms.py
100.00% <0.00%> (ø)

Continue to review full report at Codecov.

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Documentation improvement

The documentation for how to work with multiple checkboxes or a selectlist is sparse. In particular it would be very helpful to include examples that illustrate not only how to create a form with multiple checkboxes but also how to populate the checkboxes with checks.  I spent a couple days figuring out how to implement that basic functionality .  But if the documentation had included an example like this: https://github.com/lfernandez55/wtforms_checkbox_example  the learning would have gone much faster.   Perhaps example like these could be included in the crash course.

Happy to consider a PR, since it sounds like you know exactly what you want documented.


Configure and deploy an Azure API Management Service

As a developer, I can now configure and deploy Azure API Management Service
All Submissions:

[YES] Have you followed the guidelines in our Contributing document?
[YES] Have you added an explanation of what your changes do and why you'd like us to include them?
[YES] I have updated the documentation accordingly.
[NA] I have added tests to cover my changes.
[NA] All new and existing tests passed.
[YES] My code follows the code style of this project.
[NA] I ran lint checks locally prior to submission.
[YES] Have you checked to ensure there aren't other open Pull Requests for the same update/change?

What is the current behavior?

Issue Number: https://github.com/Microsoft/cobalt/issues/62
What is the new behavior?

Added an API Manager by using data inputs from the user in Terraform
Added App Insights by using data inputs from the user in Terraform

Does this introduce a breaking change?

[NO]

Any relevant logs, error output, etc?

(If it’s long, please paste to https://ghostbin.com/ and insert the link here.)
Other information

You are missing the API management connection to the VNET.

https://github.com/terraform-providers/terraform-provider-azurerm/pull/2582
This seems to be blocked from Terraform side.


Ipopt does not set pkgConfigModules

Describe the bug
Ipopt doesn't show up in PKG_CONFIG_PATH, so my library that needs it (casadi) cannot find it unless I manually set
export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:${ipopt}/lib/pkgconfig

Expected behavior
Ipopt provides meta.pkgConfigModules like other C++ libraries.

I'm currently building casadi with ipopt without doing the above (just the usual pkg-config in nativeBuildInputs and ipopt in buildInputs. Did someone fix this / can this be closed?


Lack of process_* metrics

Recently I’ve run into the problem that my processes don't have any process_ metrics although the platform (Ubuntu Trusty) hasn’t changed.
I’m not sure how to debug the problem, do you have any idea what could lead to this problem?  They are not using the new multiprocessing feature.

Are you doing anything that'd make /proc inaccessible?

Not that I’d know of.
They’re run using runit and inside envconsul.  The latter is the only recent change I can think of.  Other than that, it’s regular processes in an LXC container with a distinct user.
Are you saying that /proc problems are the only possible reason why those metrics might be missing?

With the current implementation, yes. We read from /proc/self/stat.

I've added a
with open("/proc/self/stat", "rb") as f:
    print(f.read())¬

block to the app's startup and before calling generate_latest(core.REGISTRY) and in both cases I get a legit-looking output back.
I suppose it's too late at that point anyway because something goes wrong write registering metrics?

OK it was /proc but not the self thing (free -m stopped working too).   Seems like procfs crashed and I needed to reboot the container.
It may be nice if the docs mentioned this error case?  Or a log message a la “could not access XYZ, process metrics won't be collected”?

I don't think we need to document that if kernel is hosed things will break. We don't log as that could get spammy in other circumstances.

OK.  Maybe if someone runs into it, they find this ticket.  :)


chore: Update jspm-cli to use resolutions flag

fixes #17
With the current generator.install() happening in the jspm build command we need to run the build by passing custom resolutions. And the flag is available in the latest version of the cli
https://github.com/jspm/jspm-cli/releases/tag/3.1.2

Thanks for sorting out this CLI release!


Add length restriction to migration file

If database's "DEFAULT CHARSET" is "utf8mb4", the error occurs like below when migrate,
ActiveRecord::StatementInvalid: Mysql2::Error: Specified key was too long; max key length is 767 bytes

Therefore, I added character length restriction to migration file.
Before:
t.index [:countable_type, :countable_id, :hour], unique: true, name: "index_coutable_hour"

After:
t.index [:countable_type, :countable_id, :hour], unique: true, name: "index_coutable_hour", length: {countable_type: 191}

Thank you.

@wakasa51  Give me reproduce code or test.


Allow customizing the protocol tag for each RoundTripper

This adds optional functional Options to the NewTransport method.
cc @lanzafame

Coverage increased (+5.5%) to 75.51% when pulling 4b86b328f1de1fa48a2eee194c61ab3e650dcef5 on feat/custom-tag into 6d651c6f6cead05446c970b816e2323cb411ea5c on master.


Make cache-write failures non-fatal

Summary
Closes https://github.com/astral-sh/ruff/issues/12284.

Perhaps we should either (1) make these failure in debug or (2) gate this on a smaller subset of exceptions that we might "expect" (like access denied on Windows).

One sec, making some changes.

Should we be retrying like we do in uv?

I don't think we should in this case because it's not a guard against anti-virus stuff like with binaries; it's a guard against the file being in-use, and it's not clear how long we'd expect that to be true or whether we should expect it to resolve.

Thanks for the fast fix (and the fast release cadence so I don't have to inquire about when we might get the fix)!