text:
Remove template argument list from destructor name

This is not valid since C++20, see https://wg21.link/cwg2237

I'm 100% fine with the change, but I also wonder how you spotted that as pythran always compiles with -std=c++11 on Linux

No, I didn't spot that. I was compiling a preprocessed .ii file that somebody provided to me (to debug the problem fixed by #1976) and decided to see what would happen if I added -std=c++20. So this isn't causing a problem for me (or Fedora), it was just something I noticed.

authors: jwakely serge-sans-paille

repo: serge-sans-paille/pythran


text:
Change LiveCode entry to OpenXTalk

Hello! Please change LiveCode entry to OpenXTalk because LiveCode has suddenly dropped all support for the open source builds.
There is an effort to keep a open-source fork going here:
https://github.com/PaulMcClernan/OpenXtalk-IDE-DontPanicEdition

There is now a new fork and forums setup to continue the OS version of LiveCode Community Edition under the new name OpenXTalk, Thanks!
https://github.com/orgs/OpenXTalk-org/
https://forums.openxtalk.org

Because LiveCode  suddenly dropped  support for the open source builds.

source: gharchive/issue

authors: LYLYYL PaulMcClernan serhii-londar

repo: serhii-londar/open-source-mac-os-apps

license_type: permissive

license_source: github-api


text:
Remove Telegram's deprecated entry

Project URL

https://github.com/overtake/telegram
Category

Chat
Description

Removes Telegram's deprecated entry on applications.json

          1 Warning

:warning:
Found 2 link issues, a project collaborator will take care of these, thanks :)

Link issues by awesome_bot

Line
Status
Link

2993
404
https://raw.githubusercontent.com/sindresorhus/gifski-app/master/Stuff/screenshot.jpg

5591
301
https://github.com/jwilm/alacritty redirects tohttps://github.com/alacritty/alacritty

  Generated by :no_entry_sign: Danger

1 Warning
⚠	Found 2 link issues, a project collaborator will take care of these, thanks :)
Link issues by awesome_bot
Line	Status	Link
2993	404 https://raw.githubusercontent.com/sindresorhus/gifski-app/master/Stuff/screenshot.jpg
5591	301 https://github.com/jwilm/alacritty redirects to
https://github.com/alacritty/alacritty
Generated by 🚫 Danger

Fixes applied on https://github.com/serhii-londar/open-source-mac-os-apps/pull/504/commits/8c414b61145ec57da3abe29e45958ee72ddf5a38 and https://github.com/serhii-londar/open-source-mac-os-apps/pull/504/commits/03bcb6b71770e2ac7dee26a4c1e2327ec8f59681

source: gharchive/pull-request

authors: dominguezcelada serhii-londar


text:
if node isn't exist in hashring, don't refresh hashring

[RemoveNode()]: if node isn't exist in hashring, don't refresh hashring

Thank you for your contribution!

repo: serialx/hashring

license: mit

license_source: bigquery


text:
Dependency issue with Microsoft.Data.SqlClient

Bug Report / Support Request Template
If you are opening a feature request, you can ignore this template. Bug reports and requests for assistance usually require the same basic information described below. This will help us more quickly reproduce and investigate the problem you're reporting. (If you are using Serilog.Sinks.MSSqlServerCore, that package is deprecated, please switch to Serilog.Sinks.MSSqlServer before reporting an issue.)

Please clearly describe what the SQL Sink is doing incorrectly:

Failing to log entry in database. Getting the following error log in seri debug log:
05/12/2021 13:30:36 - 2021-12-05T13:30:36.3263420Z
Unable to write 1 log events to the database due to following error: Could not load file or assembly 'Microsoft.Data.SqlClient, Version=1.13.20136.2, Culture=neutral, PublicKeyToken=23ec7fc2d6eaa4a5' or one of its dependencies. The located assembly's manifest definition does not match the assembly reference. (Exception from HRESULT: 0x80131040)
I tried to create an assembly manifest called SeriLog.Sinks.MSSqlServer.dll.config to re-direct to the new version with the following:

but to no avail. I also tried the specific version of Microsoft.Data.SqlClient but same error.
Any ideas how I can resolve this?

Please clearly describe the expected behavior:

Should write log details to database

List the names and versions of all Serilog packages used in the project:

Serilog: 2.5.0
Serilog.Sinks.MSSqlServer: 5.6.1
Serilog.Sinks.PeriodicBatching: 2.30
(configuration, etc.)

Target framework and operating system:

[ ] .NET Core 2.0
[x] .NET Framework 4.7
[ ] .NET Framework 4.6.x
[ ] .NET Framework 4.5.x
OS:

Provide a simple reproduction of your Serilog configuration code:

Nothing special about the code and works locally on my dev machine. Just not on test server so a dependency file or similar must be missing or needs to be redirected to the new version.

Provide a simple reproduction of your Serilog configuration file, if any:

Same about the configuration. Just passing a connection string to library and using standard code. As mentioned above, it works locally on my dev machine but not on our test server.

Provide a simple reproduction of your application code:

Hi,
My bad!! I spent a ridiculous amount of time on this only to find out what I was not upgrading my web.config as part of my deployment and that my local web.config had the following assembly redirection in it:
			<dependentAssembly> 				<assemblyIdentity name="Microsoft.Data.SqlClient" publicKeyToken="23ec7fc2d6eaa4a5" culture="neutral" /> 				<bindingRedirect oldVersion="0.0.0.0-4.0.0.0" newVersion="4.0.0.0" /> 			</dependentAssembly>
Once I added that I knew I was on the right track as my error changed to a certificate trust issue!
Sorry about that!
Thanks.

I do still receive this error even though assembly redirection is done for me.
2022-07-05T04:10:34.5689340Z Exception creating table LogEvents: System.IO.FileLoadException: Could not load file or assembly 'Microsoft.Data.SqlClient, Version=1.13.20136.2, Culture=neutral, PublicKeyToken=23ec7fc2d6eaa4a5' or one of its dependencies. The located assembly's manifest definition does not match the assembly reference. (Exception from HRESULT: 0x80131040) File name: 'Microsoft.Data.SqlClient, Version=1.13.20136.2, Culture=neutral, PublicKeyToken=23ec7fc2d6eaa4a5'    at Serilog.Sinks.MSSqlServer.Platform.SqlClient.SqlConnectionWrapper..ctor(String connectionString, String accessToken)    at Serilog.Sinks.MSSqlServer.Platform.SqlConnectionFactory.Create()    at Serilog.Sinks.MSSqlServer.Platform.SqlTableCreator.CreateTable(DataTable dataTable)
This is my assmbly binding from web config
<dependentAssembly> 				<assemblyIdentity name="Microsoft.Data.SqlClient" publicKeyToken="23EC7FC2D6EAA4A5" culture="neutral"/> 				<bindingRedirect oldVersion="0.0.0.0-4.8.3" newVersion="4.8.3"/> 			</dependentAssembly>
If I update serilog and the mssql sink, then the error stops application from running altogether.

authors: baffourt tfierens

repo: serilog-mssql/serilog-sinks-mssqlserver


text:
Allow { and }

cheapbotsdonequick.com says they can now be escaped as \\{ and \\}. Example grammar:
{
	"origin": ["\\{\\}#{}#"],
        "{}": "no problem!"
}

Not sure if that's a new feature or not, but they can be added as special cases in MarkovTracery.py (char_renderings, char_symbols might not be necessary).
Also, remove the proscription against them in index.html.

{
"origin": "\{ \} \{ \}"
}

repo: serin-delaunay/cheapmarkovstracedquick

license: MIT


text:
Feature request: Provide kWh consumed through API

It might exceed the processing power of the ESP32, but would it be possible to provide a (calculated) value for "EV charged kWh" and "EV total kWh"?
In my setup (without a seperate kWh meter with modbus) these values now stay empty.

If you dont have a kWh meter that measures the power, how would SmartEVSE know how much power is charged?
The charging current that is shown is the MAXimum current the EV us allowed to draw, the EV can easily slow charging down or even stop it without letting the EVSE know.
That kind of info should be given by the EV, not the EVSE.

I think you might have a point there ;-)  I did not think about the fact the EVSE does not know the power actually used to charge. It is just aware of the status of MAINS instead which is the sum of all things connected and not just the EV.
Guess you can close this one :-)


text:
Class CreateModelCommand not found

Hi,
I downloaded your repository for Laravel 5. The installation was successful but when I typed php artistan panel:install I got this error:

Adding the prefix Commands\ to class names solve the problem.

Please make sure you are getting the latest changes from 'master'  branch
of our package.
On Sat, Mar 14, 2015 at 1:05 AM, Piotr Suchanek notifications@github.com
wrote:

Hi,
I downloaded your repository for Laravel 5. The installation was
successful but when I typed php artistan panel:install I got this error:
[image: image]
https://cloud.githubusercontent.com/assets/5399813/6647672/3a5f135e-c9d1-11e4-8ccf-42b96924bf1f.png
—
Reply to this email directly or view it on GitHub
https://github.com/serverfireteam/panel/issues/7.

@daverdalas I have check the problem and it did fixed , please if you did face the problem , report it here

authors: alenoosh daverdalas serverfire

repo: serverfireteam/panel


text:
default value

in the yaml file can I specify a default value for the field?
class: Address
table: address

fields:
  address: String
  used: bool
    #default: true  #something like this?

@vlidholt do you envision any special way how this should be implemented? Sounds like a nice PR...

we can handle the default value on the sql side or dart side

It would be a cool addition, but I think the implementation needs to be thought through. Handling the default value on the Dart side is probably best, but it may only be possible to do primitive types (other serializable objects would be tricky). Also, what should the syntax look like. Needs to feel clean and be backwards compatible.

I think it would be best to provide the serialized version of the data in the yaml file. This could be used to set the default in the database, and a dart default could be constructed, too, by using the SerializationManager.
I'm currently working on a package that helps specify and parse yaml based configuration files. I think it'd be the perfect fit for specifying the class definitions. (Had this as a usecase in mind)

Closing this as duplicate for the more specified issue here https://github.com/serverpod/serverpod/issues/1140.
PS. This is being implemend right now 🙌

authors: SandPod fischerscode lastmeta ramyak-mehra vlidholt

repo: serverpod/serverpod


text:
🛑 ukgrpc.serverip.my.id is down

In e6e9ed8, ukgrpc.serverip.my.id (ukgrpc.serverip.my.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: ukgrpc.serverip.my.id is back up in 8a53db2 after 1 day, 6 hours, 8 minutes.

repo: serversshnet/server-status


text:
🛑 sg1ray.serverip.my.id is down

In ed0beb4, sg1ray.serverip.my.id (sg1ray.serverip.my.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: sg1ray.serverip.my.id is back up in 6f06921 after 25 minutes.


text:
🛑 id2-ray.ipservers.xyz is down

In 6709f11, id2-ray.ipservers.xyz (id2-ray.ipservers.xyz) was down:

HTTP code: 0
Response time: 0 ms

Resolved: id2-ray.ipservers.xyz is back up in e3c7ef1 after 1 hour, 42 minutes.

repo: serversshnet/uptime


text:
🛑 id1go.ipservers.xyz is down

In 90324dc, id1go.ipservers.xyz (id1go.ipservers.xyz) was down:

HTTP code: 0
Response time: 0 ms

Resolved: id1go.ipservers.xyz is back up in 5efc38b after 29 minutes.


text:
🛑 Colchester Repairs is down

In 22fe332, Colchester Repairs (https://colchester-repairs.co.uk) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Colchester Repairs is back up in da42be8.

repo: servicesite/upptime


text:
Modo Direct-LVM

Alterar o modo do storage driver devicemapper de loop-lvm para direct-lvm de acordo com https://docs.docker.com/engine/userguide/storagedriver/device-mapper-driver/

Foram criadas três partições no ambiente de desenvolvimento:

Uma para o elasticsearch
Uma para o direct-lvm (para guardar os containers e as imagens do Docker)
Uma para o centos

E já foi alterado o device mapper para trabalhar no modo LVM.
Próximo passo é alterar o ambiente de produção (criando essas partições e o modo LVM)

Outra atividade feita nessa issue foi tentar melhorar a solução de contorno da issue #12, usando a solução encontrada: http://blog.hashbangbash.com/2014/11/docker-devicemapper-fix-for-device-or-resource-busy-ebusy/, da issue https://github.com/docker/docker/issues/5684#issuecomment-69052334, porém os containers ainda continuaram com o mesmo problema na hora de atualizar.

repo: servicosgovbr/docker


text:
Project status questions after Mozilla layoffs

Just want to ask if this project will be continued after the Mozilla layoffs and closing the servo team.
I hope this continues.

Nobody is actively working on this project anymore.

authors: DavidBM jdm

repo: servo/pathfinder


text:
Aiofiles version conflict in grahrag and chainlit

I am trying to integrate graphrag with chainlit.
While installing the package's I get the following error.
ERROR: graphrag 0.3.1 has requirement aiofiles<25.0.0,>=24.1.0, but you have aiofiles 23.2.1.
ISSUE: Chainlit requires aiofiles<24.0.0  and graphrag requires  aiofiles version >=24.1.0.
The application works on my local machine, but when I try to deploy it on Azure Web App, the build fails, citing the above error.
Is there any workaround?

i hava the same problem

I also have a version conflict, but between gradio and this project, more specifically:
gradio 5.6.0 requires aiofiles<24.0,>=22.0, but you have aiofiles 24.1.0 which is incompatible.
graphrag 1.0.13.dev51 requires aiofiles<25.0.0,>=24.1.0, but you have aiofiles 23.2.1 which is incompatible.
So gradio requires an aiofiles version lower than 24 but this rag project requires a version higher than 24.1.0?
How to solve this ? Any ideas?

I also have a version conflict, but between gradio and this project, more specifically:
gradio 5.6.0 requires aiofiles<24.0,>=22.0, but you have aiofiles 24.1.0 which is incompatible. graphrag 1.0.13.dev51 requires aiofiles<25.0.0,>=24.1.0, but you have aiofiles 23.2.1 which is incompatible.
So gradio requires an aiofiles version lower than 24.0 but this rag project requires a version higher than 24.1.0. And this project depend on gradio... How to solve this ? Any ideas?

Have you solved yet?

+1


text:
Test failures

A number of dataset, dataloader, and wrappers tests fail.
Complete steps to reproduce the bug
poetry run pytest

Expected behavior
All tests pass.
Environment

OS: Ubuntu 20.04
Library Version: fork torchmeta 1.7 before changes, and dev branch
Using the poetry environment
The lock file has not been changed on dev

Additional context
Test output:
============================= test session starts ==============================
platform linux -- Python 3.8.3, pytest-5.4.3, py-1.10.0, pluggy-0.13.1
rootdir: /home/datenstrom/workspace/src/github.com/sevro/torchmetal
collected 275 items

tests/test_torchmetal.py .                                               [  0%]
tests/datasets/test_datasets_helpers.py ..F.......F.......F.......F..... [ 12%]
..F.......F.....                                                         [ 17%]
tests/modules/test_activation.py ........................                [ 26%]
tests/modules/test_container.py ..                                       [ 27%]
tests/modules/test_conv.py ............                                  [ 31%]
tests/modules/test_linear.py ........                                    [ 34%]
tests/modules/test_module.py ..                                          [ 35%]
tests/modules/test_parallel.py ..........                                [ 38%]
tests/modules/test_sparse.py ........                                    [ 41%]
tests/toy/test_toy.py ...........                                        [ 45%]
tests/transforms/test_splitters.py ..                                    [ 46%]
tests/utils/test_dataloaders.py ......F.......F.......F.......F.......F. [ 61%]
......F......                                                            [ 65%]
tests/utils/test_gradient_based.py ...                                   [ 66%]
tests/utils/test_matching.py ....                                        [ 68%]
tests/utils/test_prototype.py ...                                        [ 69%]
tests/utils/test_r2d2.py ............................................... [ 86%]
.............                                                            [ 91%]
tests/utils/test_wrappers.py ..F.......F.......F.....                    [100%]

=================================== FAILURES ===================================
________________ test_datasets_helpers[train-1-tieredimagenet] _________________

name = 'tieredimagenet', shots = 1, split = 'train'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/datasets/test_datasets_helpers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
________________ test_datasets_helpers[train-5-tieredimagenet] _________________

name = 'tieredimagenet', shots = 5, split = 'train'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/datasets/test_datasets_helpers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
_________________ test_datasets_helpers[val-1-tieredimagenet] __________________

name = 'tieredimagenet', shots = 1, split = 'val'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/datasets/test_datasets_helpers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
_________________ test_datasets_helpers[val-5-tieredimagenet] __________________

name = 'tieredimagenet', shots = 5, split = 'val'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/datasets/test_datasets_helpers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
_________________ test_datasets_helpers[test-1-tieredimagenet] _________________

name = 'tieredimagenet', shots = 1, split = 'test'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/datasets/test_datasets_helpers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
_________________ test_datasets_helpers[test-5-tieredimagenet] _________________

name = 'tieredimagenet', shots = 5, split = 'test'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/datasets/test_datasets_helpers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
___________ test_datasets_helpers_dataloader[train-1-tieredimagenet] ___________

name = 'tieredimagenet', shots = 1, split = 'train'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_dataloader(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_dataloaders.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
___________ test_datasets_helpers_dataloader[train-5-tieredimagenet] ___________

name = 'tieredimagenet', shots = 5, split = 'train'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_dataloader(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_dataloaders.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
____________ test_datasets_helpers_dataloader[val-1-tieredimagenet] ____________

name = 'tieredimagenet', shots = 1, split = 'val'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_dataloader(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_dataloaders.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
____________ test_datasets_helpers_dataloader[val-5-tieredimagenet] ____________

name = 'tieredimagenet', shots = 5, split = 'val'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_dataloader(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_dataloaders.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
___________ test_datasets_helpers_dataloader[test-1-tieredimagenet] ____________

name = 'tieredimagenet', shots = 1, split = 'test'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_dataloader(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_dataloaders.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
___________ test_datasets_helpers_dataloader[test-5-tieredimagenet] ____________

name = 'tieredimagenet', shots = 5, split = 'test'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('shots', [1, 5])
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_dataloader(name, shots, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=shots,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_dataloaders.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
_____________ test_datasets_helpers_wrapper[train-tieredimagenet] ______________

name = 'tieredimagenet', split = 'train'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_wrapper(name, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=1,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_wrappers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
______________ test_datasets_helpers_wrapper[val-tieredimagenet] _______________

name = 'tieredimagenet', split = 'val'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_wrapper(name, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=1,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_wrappers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
______________ test_datasets_helpers_wrapper[test-tieredimagenet] ______________

name = 'tieredimagenet', split = 'test'

    @pytest.mark.skipif(not is_local, reason='Requires datasets downloaded locally')
    @pytest.mark.parametrize('name', helpers.__all__)
    @pytest.mark.parametrize('split', ['train', 'val', 'test'])
    def test_datasets_helpers_wrapper(name, split):
        function = getattr(helpers, name)
        folder = os.getenv('TORCHMETAL_DATA_FOLDER')
        download = bool(os.getenv('TORCHMETAL_DOWNLOAD', False))

>       dataset = function(folder,
                           ways=5,
                           shots=1,
                           test_shots=15,
                           meta_split=split,
                           download=download)

tests/utils/test_wrappers.py:21:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
torchmetal/datasets/helpers.py:168: in tieredimagenet
    return helper_with_default(TieredImagenet, folder, shots, ways,
torchmetal/datasets/helpers.py:35: in helper_with_default
    dataset = klass(folder, num_classes_per_task=ways, **kwargs)
torchmetal/datasets/tieredimagenet.py:89: in __init__
    dataset = TieredImagenetClassDataset(root, meta_train=meta_train,
torchmetal/datasets/tieredimagenet.py:128: in __init__
    self.download()
torchmetal/datasets/tieredimagenet.py:181: in download
    download_file_from_google_drive(self.gdrive_id, self.root,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

file_id = '1g1aIDy2Ar_MViF2gDXFYDBTR-HYecV07'
root = '/home/datenstrom/workspace_ssd/datasets/torchmetal/tieredimagenet'
filename = 'tiered-imagenet.tar', md5 = 'e07e811b9f29362d159a9edd0d838c62'

    def download_file_from_google_drive(file_id, root, filename=None, md5=None):
        """Download a Google Drive file from  and place it in root.

        Args:
            file_id (str): id of file to be downloaded
            root (str): Directory to place downloaded file in
            filename (str, optional): Name to save the file under. If None, use the id of the file.
            md5 (str, optional): MD5 checksum of the download. If None, do not check
        """
        # Based on https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
        import requests
        url = "https://docs.google.com/uc?export=download"

        root = os.path.expanduser(root)
        if not filename:
            filename = file_id
        fpath = os.path.join(root, filename)

        os.makedirs(root, exist_ok=True)

>       if os.path.isfile(fpath) and check_integrity(fpath, md5):
E       NameError: name 'check_integrity' is not defined

torchmetal/datasets/utils.py:67: NameError
=============================== warnings summary ===============================
tests/modules/test_parallel.py::test_dataparallel_params_maml[model0]
  /home/datenstrom/.cache/pypoetry/virtualenvs/torchmetal-hZltVvxe-py3.8/lib/python3.8/site-packages/torch/cuda/nccl.py:48: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.9 it will stop working
    if not isinstance(inputs, collections.Container) or isinstance(inputs, torch.Tensor):

tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[train-1-omniglot]
tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[train-5-omniglot]
tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[val-1-omniglot]
tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[val-5-omniglot]
tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[test-1-omniglot]
tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[test-5-omniglot]
tests/utils/test_dataloaders.py::test_overflow_length_dataloader
  /home/datenstrom/.cache/pypoetry/virtualenvs/torchmetal-hZltVvxe-py3.8/lib/python3.8/site-packages/torchvision/transforms/functional.py:942: UserWarning: Argument interpolation should be of type InterpolationMode instead of int. Please, use InterpolationMode enum.
    warnings.warn(

-- Docs: https://docs.pytest.org/en/latest/warnings.html
=========================== short test summary info ============================
FAILED tests/datasets/test_datasets_helpers.py::test_datasets_helpers[train-1-tieredimagenet]
FAILED tests/datasets/test_datasets_helpers.py::test_datasets_helpers[train-5-tieredimagenet]
FAILED tests/datasets/test_datasets_helpers.py::test_datasets_helpers[val-1-tieredimagenet]
FAILED tests/datasets/test_datasets_helpers.py::test_datasets_helpers[val-5-tieredimagenet]
FAILED tests/datasets/test_datasets_helpers.py::test_datasets_helpers[test-1-tieredimagenet]
FAILED tests/datasets/test_datasets_helpers.py::test_datasets_helpers[test-5-tieredimagenet]
FAILED tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[train-1-tieredimagenet]
FAILED tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[train-5-tieredimagenet]
FAILED tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[val-1-tieredimagenet]
FAILED tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[val-5-tieredimagenet]
FAILED tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[test-1-tieredimagenet]
FAILED tests/utils/test_dataloaders.py::test_datasets_helpers_dataloader[test-5-tieredimagenet]
FAILED tests/utils/test_wrappers.py::test_datasets_helpers_wrapper[train-tieredimagenet]
FAILED tests/utils/test_wrappers.py::test_datasets_helpers_wrapper[val-tieredimagenet]
FAILED tests/utils/test_wrappers.py::test_datasets_helpers_wrapper[test-tieredimagenet]
================= 15 failed, 260 passed, 8 warnings in 15.24s ==================

The problem originates in torchmetal/datasets/utils.py and is related to a comment in that file which should be an issue.

QKFIX: The current version of download_file_from_google_drive (as of torchvision==0.8.1)
is inconsistent, and a temporary fix has been added to the bleeding-edge version of
Torchvision. The temporary fix removes the behaviour of _quota_exceeded, whenever the
quota has exceeded for the file to be downloaded. As a consequence, this means that there
is currently no protection against exceeded quotas. If you get an integrity error in torchmetal
(e.g. "MiniImagenet integrity check failed" for MiniImagenet), then this means that the quota
has exceeded for this dataset. See also: https://github.com/tristandeleu/pytorch-meta/issues/54
See also: https://github.com/pytorch/vision/issues/2992
The following functions are taken from
https://github.com/pytorch/vision/blob/cd0268cd408d19d91f870e36fdffd031085abe13/torchvision/datasets/utils.py

Most likely the failed tests are not an issue just this file has been over quota recently. It also seems that Torchvision has merged a fix (https://github.com/pytorch/vision/pull/4109) which could be incorporated that would give a better error for users.

repo: sevro/torchmetal


text:
Fail Fast for Certain Errors

Hi! I implemented a SSH connection pool in my project, and noticed when the connection can't be created (no route to host, failed to authenticate etc), get_timeout will actually retry until timeout.
I'd like to have an option to allow fail-fast for such case. In my fork, I added can_retry function in HandleError, and when it returns false, it will fail immediately without retry.
https://github.com/sfackler/r2d2/compare/6ab3302eeca82732a5e6c9385092fdb6e011f173...aaa2a2ba08582ad685ecdaaa74cc4ac47fe46efa
Do you think this feature makes sense? If so, I'll create a pull request.

@sfackler would you mind taking a look into this? i would greatly appreciate this feature...
https://github.com/sfu-db/connector-x/issues/710

@guilhermedelyra I have tested that feature for a while and it worked pretty fine. In the meantime you could use patch in Cargo.toml to use my commit ID first.

@guilhermedelyra I have tested that feature for a while and it worked pretty fine. In the meantime you could use patch in Cargo.toml to use my commit ID for now.

thanks for the suggestion! although i'm not sure if i'll be able to do this...
i'm using python's Connectorx, that relies on the rust's Connectorx implementation, which has a wrapper on top of r2d2 😅
since i'm not building connectorx from scratch (i'm using pip install connectorx), i dont think i'm able to patch the lib hehe
but again, thanks for starting the discussion and opening the PR 😀

Hey @sfackler, bumping this issue as the retry logic currently performs 7 attempts over 30 seconds. When coupled with a wrong password in an enterprise setting, MSSQL accounts get locked as it exceed the number of attempts allowed by DBA. Hence, having the option to fail fast can prevent this and allow for immediate remediation.

Do other connection pool libraries have this concept? What kinds of errors other than auth issues would be considered non-retryable?

That SQLAlchemy case seems to be covering detection disconnections of active sessions, not failing early on pool creation.

any status on this? 😃

I am still waiting to see an example of another connection pool library that does this.

authors: guilhermedelyra mariotaku pangjunrong sfackler


text:
Update to rand v0.8

Update to the latest version of the rand crate. This also requires
bumping the MSRV to 1.36.0.
Resubmission of #200.

The nightly tests are broken here and on master, but this successfully passed the tests on stable Rust.
@sfackler, are you still maintaining this, or should I try to track down @abonander?

The nightly tests are broken here and on master, but this successfully passed the tests on stable Rust.
@sfackler, are you still maintaining this, or should I try to track down @abonander?

Oh, yeah, looks like you need to re-bless the compile-fail tests cause rustc semi-recently added the -Z macro-backtrace suggestion to errors in macros

Oh, yeah, looks like you need to re-bless the compile-fail tests cause rustc semi-recently added the -Z macro-backtrace suggestion to errors in macros

Ok, let's hope that works. 🤞🏽

Ok, let's hope that works. 🤞🏽

It did! Let me see if I can track down someone with the merge bit.

It did! Let me see if I can track down someone with the merge bit.

Hello, first, thanks everyone ( especially @abonander and @sfackler ) for providing easy access to PHFs in rust.
Right now I'm attempting to deduplicate my project dependencies, and this crate is the last one in my tree still hanging on to the old 0.7.x versions of rand world.  Would it be possible for this version update to go forward?

authors: ZackPierce benesch coolreader18

repo: sfackler/rust-phf


text:
Add domain

Please add domain support with ssl

No, I'm lazy

I think it's supported by ocserv by default.

You can do it by yourself and raise a pull request :smiley:.

I did it by port forwarding port 443 tcp/udp and then add a record to my domain and point to my public IP so now I enter vpn.mydomain.com


text:
(feature) Sort TP folders according to slides

Add a number before every folder in TP according to the slides.
Also fixed typos in docs/markdown/directive/exercice_directive_use.md and docs/markdown/forms/template-friven-form/exercice_create_form.md

@parsyval I didn't find any change since previous commit 63096db in exercice_directive_use nor in exercice_create_form, are you sure you pushed these changes ?

Arf right, I forgot to push these sry, it's on now.

You rename all TP directories but not the according slide steps.
You should also rename the TP indication in every exercise slides and solution slides. You should change the forlder pattern on the slide "Déroulement des exercices"

Done, I'll fix the conflicts after #7 is merged

@Nicoss54 @kuroidoruido Done, I'll fix the conflicts after #7 is merged

You can fix conflict, the #7 PR is merged :slightly_smiling_face:

authors: ValentinParsy Xartok kuroidoruido parsyval

repo: sfeir-open-source/sfeir-school-angular


text:
fix datetime picker

If I edit a field with type: DateTime everything is stored properly.
If I don't edit a time input - time is set to '00:00', because there is no change event.

ra.datetimepicker was replaced with Bootstrap datetimepicker by #2391.

authors: mshibuya nazarok


text:
🛑 CatamarcaCapital is down

In 67142ce, CatamarcaCapital (https://www.catamarcaciudad.gob.ar) was down:

HTTP code: 0
Response time: 0 ms

Resolved: CatamarcaCapital is back up in 31e9737 after 4 minutes.

repo: sfvc/upptime


text:
🛑 Nodo is down

In f3d4bcb, Nodo (https://nodotecnologico.catamarcacapital.edu.ar/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Nodo is back up in d880d77.


text:
🛑 Transporte is down

In 327b337, Transporte (https://transporte.catamarcacapital.gob.ar/login) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Transporte is back up in e48b6cd.


text:
Ability to change keyswitch from the UI

Sforzando has it and it makes it easier to quickly test different articulations.

hello, in sfizz the red keys are used for that purpose, or do you mean something else?

exactly thank you

authors: redtide tapir

repo: sfztools/sfizz-ui


text:
Change Name Doesn't Save Value

When using the change name function on the options page, the value of that saved name does not persist if you close Chrome. This means that the name is not being saved to the currentGroup object most likely. If that is not the problem, it likely stems from the currentGroup not being saved to groups[]. Will need to look into this further

Found the bug, but I want to offer it up to someone who has never contributed to open source software! I will write the instructions on how to fix it below.
How to Fix this Bug
First make sure that you have followed the instructions in the README.md file and understand how to get a hold of the code. Once you have a local working copy, open up background.js and scroll down until you see line 97. Line 97 is changing the name of currentGroup but I forgot to save the data after changing the name, whoops! Alright so the way to fix this is by inserting saveData(); directly below currentGroup.name = request.newName; but before sendResponse({'message': 'Updated currentGroup.name'}); Once you have made the change to the file, you will want to make a pull request so that I can take a look at the file and make sure the change is there! I will then pull your PR into the staging branch to prepare it for the next release!

repo: sgalizia/StartUp


text:
Travis CI badge stuck on "failing" even though builds are passing

Describe the bug
Our Travis CI status badge is stuck on failing despite successful builds. https://github.com/travis-ci/travis-ci/issues/4024 Unfortunately there doesn't seem to be any clear guidance on how this is being handled.
To Reproduce
Run any CI build in master.
Expected behaviour
Our Travis CI badge is green and passing.

And as if by magic, merging #52 fix it!


text:
Supprimer la et les références à Cogefi

Il faut extraire du site la page de l'outil Cogefi.
Etats d'âme de l'auteur principal du logiciel, il est préférable d'ôter ce logiciel de notre catalogue. D'une manière générale, ce projet-là n'a pas tiré parti du coaching à Etalab, il a sa propre vie. Pas la peine d'aller au conflit.

C'est fait

authors: Flightan Intendant-zonard

repo: sgmap/open-academie


text:
Update locales.js

Updated with Dutch

Updated with Dutch

Add your pull request here, I took over and updated the packages etc:
https://github.com/WhateverItWorks/hat.sh-reworked

Add your pull request here, I took over and updated to v2.3.7
https://github.com/WhateverItWorks/hat.sh-reworked

authors: David-git-code xbdmHQ


text:
DialogTrigger with kbd (Hydration failed)

Hi, i have a problem with kbd in Button in DialogTrigger
<DialogTrigger asChild>
	<Button className='me-2 p-3 border text-muted-foreground' variant="outline"><Search className="md:mr-2 h-[1.2rem] w-[1.2rem] dark:text-white md:text-inherit" />
		Search

					⌘K

	</Button>
</DialogTrigger>

Error
Unhandled Runtime Error
Error: Hydration failed because the initial UI does not match what was rendered on the server.

Warning: Expected server HTML to contain a matching
 in .

See more info here: https://nextjs.org/docs/messages/react-hydration-error

Component Stack
p
span
button
_c
./src/components/ui/button.tsx (40:11)
eval
./node_modules/@radix-ui/react-slot/dist/index.mjs (46:23)
eval
./node_modules/@radix-ui/react-slot/dist/index.mjs (20:23)
eval
./node_modules/@radix-ui/react-primitive/dist/index.mjs (44:26)
eval
./node_modules/@radix-ui/react-dialog/dist/index.mjs (109:28)
Provider
./node_modules/@radix-ui/react-context/dist/index.mjs (47:28)
$5d3850c4d0b4e6c7$export$3ddf2d174ce01153
./node_modules/@radix-ui/react-dialog/dist/index.mjs (77:28)
SearchMovie
./src/components/SearchMovies/SearchMovies.tsx (34:88)
div
div
header
div
f
./node_modules/next-themes/dist/index.module.js (8:597)
$
./node_modules/next-themes/dist/index.module.js (8:348)
ThemeProvider
./src/components/ThemeProvider.tsx (13:11)
body
html
Call Stack
throwOnHydrationMismatch
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (7076:0)
tryToClaimNextHydratableInstance
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (7105:0)
updateHostComponent$1
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (16503:0)
beginWork$1
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (18390:0)
HTMLUnknownElement.callCallback
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (20461:0)
Object.invokeGuardedCallbackImpl
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (20510:0)
invokeGuardedCallback
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (20585:0)
beginWork
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (26763:0)
performUnitOfWork
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (25587:0)
workLoopConcurrent
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (25573:0)
renderRootConcurrent
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (25529:0)
performConcurrentWorkOnRoot
node_modules\next\dist\compiled\react-dom\cjs\react-dom.development.js (24382:0)
workLoop
node_modules\next\dist\compiled\scheduler\cjs\scheduler.development.js (261:0)
flushWork
node_modules\next\dist\compiled\scheduler\cjs\scheduler.development.js (230:0)
MessagePort.performWorkUntilDeadline
node_modules\next\dist\compiled\scheduler\cjs\scheduler.development.js (534:0)

hey brother !
can you explain more about it ?

hey brother ! can you explain more about it ?

yes, I'm trying to add a  to the Button, but an error occurs (Hydration failed) if I remove kbd everything becomes fine

repo: shadcn-ui/ui


text:
Bug: Sidepanel should be on top of Sonner.

Why:

Sonner: ol z-index: 9999999
Sidepanel: body style="pointer-events: none;"

Result:

Sonner under pointer-events: none; is non-interactive.

Solution:
https://github.com/emilkowalski/sonner/blob/6a9460389699d6862579e3e4eceeac269bc758d7/src/styles.css#L50
-className="toaster group"
+className="toaster group !z-40"

+1, I would love to be able to close the toast while keeping the panel open.

This issue has been automatically closed because it received no activity for a while. If you think it was closed by accident, please leave a comment. Thank you.

authors: NikitaIT metuan shadcn


text:
Ignore Arrays in Rails i18n yml files

Fixes #1126

This change is

@vcarel any update?

@justin808 I'm on vacation for 2 weeks. I'll look into that when I'll be back in. Thx for your review.

@justin808 I just did the update, sorry for the delay.

@vcarel can you please rebase on top of master and ensure that CI passes.

Coverage remained the same at ?% when pulling 1994c245e6759beb84507c4e575d171fc0576344 on vcarel:fix/ignore-arrays-in-rails-i18n-yml-files into c80f264efa4c7929da2a17344510d7b6802b632e on shakacode:master.

Thanks @vcarel!

authors: coveralls justin808 vcarel


text:
What is binary in update-binary

Hi, update-binary has a blob in it. Is this the busybox binary? If so what version and where does it come from? One shouldn't run code like this without knowing what it does.

The entire update-binary was grab from older Magisk.zip (20307, 72f6770d) and unfortunately John removed the older canary releases on github so I could not get you the origin file. In the mean while if you don't trust me:

DO NOT USE
Replace the update-binary extracted from here: https://github.com/topjohnwu/magisk_files/blob/f595d0624b70289ed273f933a33075fee986b533/magisk-debug.zip

Also

repo: shakalaca/MagiskOnEmulator


text:
🛑 Shakedown Social - Uploads is down

In ac4d7c3, Shakedown Social - Uploads (https://files.shakedown.social/accounts/avatars/109/357/389/718/265/462/original/dd80d2c95e48cfd2.jpeg) was down:

HTTP code: 403
Response time: 557 ms

Resolved: Shakedown Social - Uploads is back up in 53851c7.

repo: shakedown-social/upptime


text:
🛑 Shakedown Social - Uploads is down

In 7c0deb9, Shakedown Social - Uploads (https://files.shakedown.social/accounts/avatars/109/357/389/718/265/462/original/dd80d2c95e48cfd2.jpeg) was down:

HTTP code: 403
Response time: 375 ms

Resolved: Shakedown Social - Uploads is back up in dbeab74.


text:
🛑 Shakedown Social - Uploads is down

In 510542b, Shakedown Social - Uploads (https://files.shakedown.social/accounts/avatars/109/357/389/718/265/462/original/dd80d2c95e48cfd2.jpeg) was down:

HTTP code: 403
Response time: 596 ms

Resolved: Shakedown Social - Uploads is back up in fff7290.


text:
🛑 Shakedown Social - Uploads is down

In 1027db4, Shakedown Social - Uploads (https://files.shakedown.social/accounts/avatars/109/357/389/718/265/462/original/dd80d2c95e48cfd2.jpeg) was down:

HTTP code: 403
Response time: 358 ms

Resolved: Shakedown Social - Uploads is back up in d93d771.


text:
Improve OAuth

Short description of what this resolves:
Notify user if OAuth listener started failed.
Changes proposed in this pull request:
https://github.com/shanalikhan/code-settings-sync/issues/1053#issuecomment-538248184_
Fixes: #1053
How Has This Been Tested?

Execute > Sync: Reset Extension Settings
Reload Visual Studio, the landing page will be shown
Run Thunder on Windows or use http-server to listen 54321 (hs -a :: -p 54321)
Click "Login with GitHub" button, it should show a error notification at right-down corner, and won't open the authorization page
Click "Troubleshooting" button in the notification, it will open the wiki
Back to step 4 again, close the notification will do nothing (don't open the wiki)
Close the application that started in step 3, then retry Login with GitHub, it will works fine.

Screenshots (if appropriate):

Checklist:

[x] I have read the contribution guidelines.
[ ] My change requires a change to the documentation and GitHub Wiki.
[ ] I have updated the documentation and Wiki accordingly.

It should update the Wiki that about how to find which process listened the port, or how to configure manually. But I'm poor in English so It's a little hard to me. Does anyone will do that?

Can you resolve the conflicts so i can merge

Merged. Feel free to contribute in other problems as well.

authors: PMExtra shanalikhan

repo: shanalikhan/code-settings-sync


text:
Update README to reflect new GitHub settings page

Depends on updated images from https://github.com/shanalikhan/shanalikhan.github.io/pull/1

Thanks

authors: eliasmeire shanalikhan


text:
BUG:  posx and posy should be finite values

Issue Description
Hi, I am trying to plot using shap.force_plot but I got an error with no reason. Any idea how to solve it?
Minimal Reproducible Example
# Plot the SHAP values for the Malignant case
plot = shap.force_plot(shap_explainer.expected_value[0],
                       shap_values[0][malignant_idx2,:],
                       X_test.numpy()[malignant_idx2,:],
                       feature_names=data['feature_names'],
                       link="logit",
                       matplotlib=True)

shap_explainer.expected_value[0] = -0.43953
shap_values[0][malignant_idx2,:] = array([ 0.        ,  0.        ,  0.25509583,  0.23371664,  0.        ,
        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
        0.        ,  0.01199562,  0.        , -0.09863244,  0.01999477,
        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
        0.02997689,  0.        ,  0.11880713, -2.51902776,  0.        ,
        0.        ,  0.        ,  0.        ,  0.        ,  0.        ])
X_test.numpy()[malignant_idx2,:] = array([1.940e+01, 2.350e+01, 1.291e+02, 1.155e+03, 1.027e-01, 1.558e-01,
       2.049e-01, 8.886e-02, 1.978e-01, 6.000e-02, 5.243e-01, 1.802e+00,
       4.037e+00, 6.041e+01, 1.061e-02, 3.252e-02, 3.915e-02, 1.559e-02,
       2.186e-02, 3.949e-03, 2.165e+01, 3.053e+01, 1.449e+02, 1.417e+03,
       1.463e-01, 2.968e-01, 3.458e-01, 1.564e-01, 2.920e-01, 7.614e-02])

Traceback
No response
Expected Behavior
I wanted to get a plot but It doesn't work.
Bug report checklist

[X] I have checked that this issue has not already been reported.
[X] I have confirmed this bug exists on the latest release of shap.
[X] I have confirmed this bug exists on the master branch of shap.
[ ] I'd be interested in making a PR to fix this bug

Installed Versions
shap               0.44.0

Thanks for the report. Here is a version of your code that is better reproducible:
import shap
import numpy as np

# Plot the SHAP values for the Malignant case
expected_value = -0.43953
shap_values = np.array([ 0.        ,  0.        ,  0.25509583,  0.23371664,  0.        ,
                         0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
                         0.        ,  0.01199562,  0.        , -0.09863244,  0.01999477,
                         0.        ,  0.        ,  0.        ,  0.        ,  0.        ,
                         0.02997689,  0.        ,  0.11880713, -2.51902776,  0.        ,
                         0.        ,  0.        ,  0.        ,  0.        ,  0.        ])

X_test = np.array(
      [1.940e+01, 2.350e+01, 1.291e+02, 1.155e+03, 1.027e-01, 1.558e-01,
       2.049e-01, 8.886e-02, 1.978e-01, 6.000e-02, 5.243e-01, 1.802e+00,
       4.037e+00, 6.041e+01, 1.061e-02, 3.252e-02, 3.915e-02, 1.559e-02,
       2.186e-02, 3.949e-03, 2.165e+01, 3.053e+01, 1.449e+02, 1.417e+03,
       1.463e-01, 2.968e-01, 3.458e-01, 1.564e-01, 2.920e-01, 7.614e-02]
       )
plot = shap.force_plot(expected_value,
                       shap_values,
                       X_test,
                       link="logit",
                       matplotlib=True)

But for me that works on master. Could you please also post the error message?

authors: CloseChoice Jalilnkh

repo: shap/shap


text:
Remove device-dependent encryption parameters

Description:
While optimizing Shapeshift's runtime performance, particularly for devices with lower computational power, it's evident that the current encryption parameter benchmarking mechanism poses a bottleneck. The benchmark takes 4s to run on an M2 Mac and significantly more time on older mobile devices, causing undesirable delays during first boot. This issue aims to discuss and implement a hard-coded set of sensible defaults for encryption parameters, thereby removing the need for device-dependent benchmarks.
This issue is specific to native wallet only - other wallets are unaffected.
Additional Context
To reproduce the issue, launch the app for the first time (empty indexed db) to notice the benchmark run - it runs when the native wallet is first opened.

Benchmark code: argonBenchmark.ts
Consumption code: rawVault.ts
The benchmark aims to optimize for a target of 1000ms boot time but often exceeds this, especially on lower-end devices.
The benchmark iteself takes 4s to run on an M2 Mac and significantly more time on older mobile devices.
The current parameter set (e.g., 32MB buffer, 54 iterations) appears to be overkill for browser storage requirements.

Actions

Hardcode sensible defaults for encryption parameters, skipping the benchmark.
Conduct a performance analysis on a variety of devices to determine an optimal default set.

Acceptance criteria

Performance Metrics: Demonstrate that the new hardcoded encryption parameters result in a boot time that is notably faster than the current dynamic benchmarking method, especially on lower-end devices. Aim for a boot time under 1 second for modern devices and under 3 seconds for older devices.
Security Analysis: Conduct a security assessment to confirm that the hardcoded encryption parameters provide adequate protection against brute-force attacks and other vulnerabilities. The parameters should adhere to industry-standard security guidelines.
Backward Compatibility: Ensure that existing users who have wallets encrypted with the old parameters can seamlessly transition to using the new hardcoded parameters without any data loss or additional steps.
Cross-Device Consistency: Validate that the new hardcoded encryption parameters provide consistent boot times and security levels across a variety of devices (e.g., different models of smartphones, tablets, and desktops).

@woodenfurniture to take a look at pre-implementation to see what was done before this feature was added.

repo: shapeshift/web


text:
support NIO for ComStmtExecutePacket

support NIO for ComStmtExecutePacket

Codecov Report

Merging #1097 into dev will increase coverage by 0.01%.
The diff coverage is 0%.

@@            Coverage Diff             @@
##              dev    #1097      +/-   ##
==========================================
+ Coverage   57.66%   57.68%   +0.01%
==========================================
  Files         636      636
  Lines       12610    12617       +7
  Branches     2030     2031       +1
==========================================
+ Hits         7272     7278       +6
- Misses       4876     4877       +1
  Partials      462      462

Impacted Files
Coverage Δ

...ort/mysql/packet/command/CommandPacketFactory.java
0% <0%> (ø)
:arrow_up:

...ingsphere/proxy/backend/BackendHandlerFactory.java
0% <0%> (ø)
:arrow_up:

...and/query/binary/execute/ComStmtExecutePacket.java
0% <0%> (ø)
:arrow_up:

...orchestration/reg/newzk/client/cache/PathTree.java
72.91% <0%> (+1.56%)
:arrow_up:

...OrchestrationMasterSlaveDataSourceFactoryBean.java
77.77% <0%> (+11.11%)
:arrow_up:

...hestration/reg/newzk/client/cache/PathResolve.java
100% <0%> (+11.76%)
:arrow_up:

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authors: chidaodezhongsheng codecov-io

repo: sharding-sphere/sharding-sphere


text:
Improve badges by following shields.io conventions

This is what the current badges look like:

While most other badges look like this:

There is a great project (shields.io) which aims
to standardize badges and provide standard badges for other services.
I opened an issue there to request them to serve badges
for github latex, but they said there is no API (for querying a build status I suppose).
I'd like to propose that sharelatex build badges follow their proposed standard:

I think it should be as simple as using their templates modulo licensing.

This boils down to patching app/views/badges/pdf.jade, the new svg would look something this:
svg(xmlns="http://www.w3.org/2000/svg", width="#{it.widths[0]+it.widths[1]}", height="20")

	lineargradient#smooth(x2="0", y2="100%")
		stop(offset="0", stop-color="#bbb", stop-opacity=".1")
		stop(offset="1", stop-opacity=".1")

	mask#round
		rect(width="#{it.widths[0]+it.widths[1]}", height="20", rx="3", fill="#fff")

	g(mask="url(#round)")
		rect(width="#{it.widths[0]}", height="20", fill="#{it.escapeXml(it.colorA||'#555')}")
		rect(x="#{it.widths[0]}", width="#{it.widths[1]}", height="20", fill="#{it.escapeXml(it.colorB||'#4c1')}")
		rect(width="#{it.widths[0]+it.widths[1]}", height="20", fill="url(#smooth)")

	g(fill="#fff", text-anchor="middle", font-family="DejaVu Sans,Verdana,Geneva,sans-serif", font-size="11")
		text(x="#{(it.widths[0])/2}", y="15", fill="#010101", fill-opacity=".3") #{it.escapeXml(it.text[0])}
		text(x="#{(it.widths[0])/2}", y="14") #{it.escapeXml(it.text[0])}
		text(x="#{it.widths[0]+it.widths[1]/2-1}", y="15", fill="#010101", fill-opacity=".3") #{it.escapeXml(it.text[1])}
		text(x="#{it.widths[0]+it.widths[1]/2-1}", y="14") #{it.escapeXml(it.text[1])}

Which is an almost direct translation of shields flat template.
Though it still needs a replacement for this it context object, it should be possible to get at least some acceptable hard coded values if I had a working environment of shields, and I would still need and environment for github-latex-ci to test this.
I may open a pull request with the untested changes for validation.

Closed by #20

authors: jansegre jpallen

repo: sharelatex/github-latex-ci


text:
Vet dependencies

Two commits.

Deduplicate predicates

hexyl depends on predicates v2.0.
hexyl depends on assert_cmd v2.0, which depends on predicates v3.0.
So we end up compiling two versions of the same crate.
Fixed by bumping the direct dependency from 2.0 to 3.0. Shouldn't have broken anything, from what I can tell after reading the changelog and seeing how little the library is actually used in this codebase.

Run cargo update

Not necessary, but since we're at it...

Thank you!

authors: GrigorenkoPV sharkdp

repo: sharkdp/hexyl


text:
Add isNearSingular method

A method is needed that returns true when the robot arm configuration is near singular.

@shaun-edwards! Determinant of the Jacobian is what we are concerned here, right?

Yes...although @geoffreychiou expressed some reservation about using the jacobian to determine singularity.

@geoffreychiou Can you please elaborate?

Basically a singularity occurs when the determinant of the Jacobian is equal to zero, but I found a article/stackoverflow  comment a while back saying that you can't just take the determinant of J and check if it is close to zero.
One possibility is to compare the joint velocities to the Cartesian velocity. When the robot is near a singularity, the joint velocities should be very large compared to the Cartesian velocity. It would be up to you to determine what the threshold should be.

authors: geoffreychiou nsnitish shaun-edwards


text:
Traceback error

Having the same issue as mentioned in https://github.com/shawngmc/game-extraction-toolbox/issues/54
Traceback (most recent call last):   File "c:\users\(username)\appdata\local\programs\python\python38\lib\runpy.py", line 194, in _run_module_as_main     return _run_code(code, main_globals, None,   File "c:\users\(username)\appdata\local\programs\python\python38\lib\runpy.py", line 87, in _run_code     exec(code, run_globals)   File "c:\users\(username)\.local\bin\gextoolbox.exe\__main__.py", line 4, in <module>   File "C:\Users\(username)\.local\pipx\venvs\game-extraction-toolbox\lib\site-packages\gex\toolbox.py", line 6, in <module>     from gex.commands.file.file import file   File "C:\Users\(username)\.local\pipx\venvs\game-extraction-toolbox\lib\site-packages\gex\commands\file\file.py", line 3, in <module>     from .deinterleave import deinterleave   File "C:\Users\(username)\.local\pipx\venvs\game-extraction-toolbox\lib\site-packages\gex\commands\file\deinterleave.py", line 5, in <module>     from gex.lib.utils.blob import transforms   File "C:\Users\(username)\.local\pipx\venvs\game-extraction-toolbox\lib\site-packages\gex\lib\utils\blob\transforms.py", line 20, in <module>     def merge(chunks: list[bytes]) -> bytearray: TypeError: 'type' object is not subscriptable PS C:\Users\(username)\.local\pipx\venvs\game-extraction-toolbox\Scripts>
I've tried both python 3.10.10 and 3.10.11 and ran cmd from both the path in which gextoolbox.exe is in as well as from a standard command prompt. any command gives the same issue.

The traceback is showing python 3.8. Can you try running removing python 3.8, then installing PIPX and GEX with the newer version of Python? I suspect that pipx and/or gex system paths are taking precedence...

On uninstall I get this error:
C:\Windows\System32>pipx install game-extraction-toolbox Fatal error in launcher: Unable to create process using '"c:\users\(USERNAME)\appdata\local\programs\python\python38\python.exe"  "c:\users\(USERNAME)appdata\roaming\python\python38\scripts\pipx.exe" install game-extraction-toolbox': The system cannot find the file specified.

It looks like it's trying to use pipx from Python 3.8.
Try reinstalling pipx via python -m pip install pipx.

Seems it cant find the newest version of python when I attempt to reinstall. I did make sure to install the latest version

So I figured it out, it doesn't matter what python version you have so long as its newer than python38.
All I had to do was go into C:\Users\AppData\Local\Programs\Python and rename my python 311 (or presumably whichever version of python you might have) and rename it to python38

authors: JohnGhostly shawngmc

repo: shawngmc/game-extraction-toolbox


text:
disable logs

Could we have an option to disable the logs?
They are a bit expensive in AWS lambda
Thank you

@girotomas  now there won't be any logs as default , if you need them , you can set process.env.DEBUG=true, then all logs will appear, include the puppeteer logs

authors: girotomas shawnliujw

repo: shawnliujw/puppeteer-lambda


text:
Implementation of zip function #72

Code + Tests implementing issue number #72

Codecov Report

Merging #92 into master will increase coverage by <.01%.
The diff coverage is 100%.

@@             Coverage Diff              @@
##             master      #92      +/-   ##
============================================
+ Coverage     99.03%   99.04%   +<.01%
- Complexity      154      160       +6
============================================
  Files             3        3
  Lines          4153     4167      +14
  Branches         54       58       +4
============================================
+ Hits           4113     4127      +14
  Misses           23       23
  Partials         17       17

Impacted Files
Coverage Δ
Complexity Δ

src/main/java/strman/Strman.java
88.27% <100%> (+0.52%)
158 <6> (+6)
:arrow_up:

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Addressed.
On 13 June 2017 at 21:35, Shekhar Gulati notifications@github.com wrote:

@shekhargulati commented on this pull request.
In src/main/java/strman/Strman.java
https://github.com/shekhargulati/strman-java/pull/92#discussion_r121789453
:

@@ -1334,5 +1336,40 @@ private static long countSubstr(String value, String subStr, boolean allowOverla
return countSubstr(value.substring(offset), subStr, allowOverlapping, ++count);
}

/**

* Aggregates the contents of n strings into a single list of tuples.

*

* @param inputs A list of strings.

* @return A list of strings if there are enough elements in the input and none of them is null or empty.

* An empty list otherwise.

*/

public static List zip(String... inputs) {

   if (inputs.length < 2) {

       return emptyList();

@Cs4r https://github.com/cs4r ok let me explain because I think what I
said make sense. Scala's list function is called on a list, so you have two
lists two work with. One with length 0 and second with length 3. The way
zip works is that it picks minimum of the two so you get empty list.
The code that you have written allows user to pass single String element
so I expect it should just give me single element list. Python's zip
implementation is similar to what you have written and this is what it does
zip([1,2,3])
[(1,), (2,), (3,)]
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/shekhargulati/strman-java/pull/92#discussion_r121789453,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ABQIDtJFpEHOTjwx5gOu7yN5MO98G559ks5sDvKLgaJpZM4N46TL
.

I have addressed your review comments so far.

repo: shekhargulati/strman-java


text:
Installation via HACS - Integrations does not work

get the following error:
Logger: homeassistant.config_entries
Source: config_entries.py:698
First occurred: 10:17:04 (1 occurrences)
Last logged: 10:17:04
Error occurred loading configuration flow for integration dyson_cloud: No module named 'custom_components.dyson_local'

You need to install dyson local (https://github.com/shenxn/ha-dyson) as well for this to work.

authors: FransHalsjes shenxn

repo: shenxn/ha-dyson-cloud


text:
Run local server

Context:
To run local server, we need nodemon, which was missing from the dependencies.
Fix:
Added nodemon as a dev dependency.
Also added documentation describing how to run the local server and to start the project.

@nurmerey

repo: shescoding/projects-platform-frontend


text:
Fushigi crashing at startup

Describe the bug
Fushigi crashes after the "Initializing Window" line in terminal
the terminal says:
Starting Fushigi v0.6...
Not running on osx
Loading user settings...
Loading parameter database...
Loading area parameter loader...
Checking for imgui.ini
Initializing Window
To Reproduce
Steps to reproduce the behavior:
build Fushigi from source
go to Fushigi\Fushigi\bin\Debug\net8.0
run Fushigi.exe
Operating System:
Windows 11
.net info
.NET SDK:
Version:           8.0.100
Commit:            57efcf1350
Workload version:  8.0.100-manifests.6c33ef20
Laufzeitumgebung:
OS Name:     Windows
OS Version:  10.0.22621
OS Platform: Windows
RID:         win-x86
Base Path:   C:\Program Files (x86)\dotnet\sdk\8.0.100\
installed.NET-Workloads:
Workload version: 8.0.100-manifests.6c33ef20
Es sind keine installierten Workloads zum Anzeigen vorhanden.
Host:
Version:      8.0.0
Architecture: x86
Commit:       5535e31a71
.NET SDKs installed:
8.0.100 [C:\Program Files (x86)\dotnet\sdk]
.NET runtimes installed:
Microsoft.AspNetCore.App 8.0.0 [C:\Program Files (x86)\dotnet\shared\Microsoft.AspNetCore.App]
Microsoft.NETCore.App 5.0.17 [C:\Program Files (x86)\dotnet\shared\Microsoft.NETCore.App]
Microsoft.NETCore.App 6.0.22 [C:\Program Files (x86)\dotnet\shared\Microsoft.NETCore.App]
Microsoft.NETCore.App 7.0.11 [C:\Program Files (x86)\dotnet\shared\Microsoft.NETCore.App]
Microsoft.NETCore.App 8.0.0 [C:\Program Files (x86)\dotnet\shared\Microsoft.NETCore.App]
Microsoft.WindowsDesktop.App 5.0.17 [C:\Program Files (x86)\dotnet\shared\Microsoft.WindowsDesktop.App]
Microsoft.WindowsDesktop.App 6.0.22 [C:\Program Files (x86)\dotnet\shared\Microsoft.WindowsDesktop.App]
Microsoft.WindowsDesktop.App 7.0.11 [C:\Program Files (x86)\dotnet\shared\Microsoft.WindowsDesktop.App]
Microsoft.WindowsDesktop.App 8.0.0 [C:\Program Files (x86)\dotnet\shared\Microsoft.WindowsDesktop.App]
Other architectures found:
x64   [C:\Program Files\dotnet]
registered at [HKLM\SOFTWARE\dotnet\Setup\InstalledVersions\x64\InstallLocation]
Environment variables:
Not set
global.json file:
Not found

I have the same issue...

repo: shibbo/Fushigi