((1,"c"), (23, "a"), (32,"b"))

In my case userEvent.type(input, "abc{enter}"); didn't work because I need to modify and validate the value before submitting it. This worked.

test("should submit when pressing enter", async () => {
  const handleSubmit = jest.fn();
  const { getByLabelText } = render(<App handleSubmit={handleSubmit} />);
  const input = getByLabelText("Name:");

  fireEvent.change(input, { target: { value: "abc" } });
  await userEvent.type(input, '{enter}');

  expect(handleSubmit).toHaveBeenCalled();
});

Had similar issue, fixed it with adding empty __init__.py files on all levels in the package where it was missing

For me, it was caused by enabling legacy-peer-deps globally via ~/.npmrc config file. It was adding dev: true to package-lock.json file and caused the CI/CD pipeline to fail as mentioned by gordey4doronin above. The fix was removing legacy-peer-deps=true from ~/.npmrc file

So after a week of tinkering. I do believe I have cracked the nut!

The tutorial that I was trying to follow lead me around in circles and eventually I gave up on trying to update nodes G value as stated in the tutorials. Instead, I created a new hybrid cost value, I call the Bcost. Because I'm Brett ;P. I wont post the entire code here, but I will post a link to the test session where you can launch it in Android Studio and try it for yourself. The new Bcost makes the algorithm way more efficient and as you'll see, it barely ever chooses a node that isnt the best next node. I think it's probably 50-100% faster. However, my nextnodes() function is horribly bloated and if anyone wants to take a stab at making that method cleaner. I would love to see how you accomplish that.

http://nexxiom.com/android/AstarTesting.zip

It seems that

ReflectionOnlyLoadFrom() 

is intentionally set to throw a

System.PlatformNotSupportedException: 'ReflectionOnly loading is not supported on this platform.' 

so it's useless (on Windows anyway).

As for me it's easier and more reliable to do via custom actions:

1. Create custom action

2. Run it before install

3. Check architecture in custom action

4. Write it to variable:

[CustomAction]  
public static ActionResult CA(Session session)  
{  
  session["variable"] = architecture result;  
  return ActionResult.Success;  
}

5. Use it as variable in your wix

Adding the below block resolved the issue.

@csrf_exempt  # This decorator exempts CSRF protection for the POST request
    def post(self, request, *args, **kwargs):
        return super().post(request, *args, **kwargs)

Have faced the same issue in Kubernetes. Solved by setting explicitly

AIRFLOW__METRICS__STATSD_ON: "False"

same problem here (other tables) but the "kids-table" aren't filtered as expected.

Just in case someone lands here facing the issue on DBeaver then check for below settings. Uncheck it if checked.

In my case with Sequola 15.1

sudo CXXFLAGS="-I/opt/homebrew/opt/unixodbc/include/" LDFLAGS="-L/opt/homebrew/lib/" /Applications/MAMP/bin/php/php8.3.14/bin/pecl install sqlsrv pdo_sqlsrv

I have tried several attempts and when I run sudo plank, it works without any issues. However, when I run plank normally (without sudo), the problem occurs. Could anyone suggest what kind of permissions or adjustments are needed to make it work without running as root?

Thanks in advance for your help!

Second way - change your connection string to db. Replace localhost to your local IP.

The error was occurring due to the action setup where it says LINKTOFORM() changing it to LINKTOROW solved the error

add these :

predefinedPlaces={[]}
textInputProps={{}}

in your example

<GooglePlacesAutocomplete
   placeholder="Type a place"
   query={{key: 'My-API-Key'}}
   predefinedPlaces={[]}
   textInputProps={{}}
/>

try rebuild solution steps:

1. go to navbar.
2. click on build.
3. click on rebuild solution.

Use the following query to obtain the count of records available for each table in descending order (from high to low) - include conditions if necessary:

select distinct t.name as Table_Name,p.rows as Noof_Records from sys.tables t inner join sys.partitions p on t.object_id=p.object_id where create_date<='15-apr-2025'

order by p.rows desc

I know that each format has its own compression and I know that decompression is long and complicated.

But I would like to do the same thing using libraries that allow conversion to a same single format that is similar to .ppm.

any suggestions?

PS. trying .ppm, it stores RGB values ​​as unsigned

You could try the below

curl --data "client_id=CLIENT_ID&client_secret=CLIENT_SECRET&grant_type=client_credentials&scope=SCOPE_IF_YOU_HAVE" AUTHENTICATION_URL

curl --data "client_id=9######4-####-####-a4c7-############&client_secret=##########&grant_type=client_credentials&scope=api://#####-####-####-####-###########/.default" https://login.microsoftonline.com/########-####-####-####-#########/oauth2/v2.0/token

this info is also available via their api without web scraping

https://github.com/EnderLocke/pyespn

Just published an article few days ago: https://stripearmy.medium.com/i-fixed-a-decade-long-ios-safari-problem-0d85f76caec0
And the npm package: https://www.npmjs.com/package/react-ios-scroll-lock

Hope this fixes your problem.

Someone help me with the script where it will give first level second level and thrid approval details configrued in the access policy

In my case the class used as a std::vector element had member of type std::thread, but std::thread is not CopyConstructible or CopyAssignable.

Found my mistake. setIncomingAndReceive() returns the size of the transferred array (10 bytes in my case), i.e. instead of if ( ( numBytes != PayloadSize ) || (byteRead != 1) ) there should be if ( ( numBytes != PayloadSize ) || (byteRead != PayloadSize) ). And in addition, I also specified the offset inside the buffer incorrectly (should be Util.arrayCopy(buf, ISO7816.OFFSET_CDATA, data, (short) 0, PayloadSize)).

This is a useful complement of the documentation of Mermaid. Thank you for sharing your discovery!

So I've found a way. Basically this is the work of iot-gateway. It's just a small tweak from getting started guide: https://thingsboard.io/docs/iot-gateway/getting-started/#step-3-add-new-connector.

Scroll down to “Data conversion” section:

For “Device” subsection use the following options/values:

In the “Name” row, select “Constant” in the “Source” dropdown field, fill in the “Value / Expression” field with the “Device Demo” value.

In the “Profile name” row, select “Constant” in the “Source” dropdown field, fill in the “Value / Expression” field with the “default” value.

One just need to extract the name of the device from the message payload (or from path if applicable)

So just specify the device id like this in the connector configuration

"deviceInfo": {
      "deviceNameExpression": "Node ${your_id}",
      "deviceNameExpressionSource": "message",
      "deviceProfileExpressionSource": "constant",
      "deviceProfileExpression": "default"
}

After enabling debug logging I found that the issue isn't with LDAP, rather that the OSS version of JFrog doesn't support JFrog groups:

Search Ldap groups only supported for Pro license

delete from some_table where some_column = :someValue and (some_other_column is null or some_other_column = :someOtherValue)

should work

I am experiencing the same problem!

I had same error, and the reason was that I didn't have sentencepiece package installed.

So

pip install sentencepiece

solved the problem

Thanks to @musicamante, I realized I had to supply my own html template to export_html. That was not immediately clear to me as its named a bit weird. Not only was I injecting entire HTML pages into the TextEdit, but also the <pre> tags that are used by default cause the spacing issues, so i used <div> instead.

I also set the QTextEdit to use the monospace font that would normally be selected in the HTML stylesheet.

This is what ended up working:

class QTextEditLogger(QTextEdit, Handler):
    """A QTextEdit logger that uses RichHandler to format log messages."""
    def __init__(self, parent=None, level=NOTSET):
        QTextEdit.__init__(self, parent)
        Handler.__init__(self,level=level)
        self.console = Console(file=open(os.devnull, "wt"), record=True)
        self.rich_handler = RichHandler(show_time=False, show_path=False, show_level=True, markup=True, console=self.console, level=self.level)
        self.rich_handler.setLevel(self.level)
        self.setWordWrapMode(QTextOption.WrapMode.WordWrap)
        self.setAcceptRichText(True)
        self.setReadOnly(True)
        font = QFont(['Menlo','DejaVu Sans Mono','consolas','Courier New','monospace'], 10, self.font().weight())
        font.setStyleHint(QFont.StyleHint.TypeWriter)
        self.setFont(font)


    def emit(self, record) -> None:
        """Override the emit method to handle log records."""
        self.rich_handler.emit(record)
        html_template = '<div style="background-color: {background}; color: {foreground};><code style="font-family:inherit">{code}</code><br/></div>'
        html = self.console.export_html(clear=True, code_format=html_template, inline_styles=True)
        self.insertHtml(html)
        self.verticalScrollBar().setSliderPosition(self.verticalScrollBar().maximum())  
        c = self.textCursor()
        c.movePosition(QTextCursor.End)
        self.setTextCursor(c)

The formula in A9

=LET(a,GROUPBY(A2:A6,HSTACK(B2:B6,C2:C6),SUM),
b,CHOOSECOLS(a,2)/CHOOSECOLS(a,3),
HSTACK(a,b))

provisioned administration rights to the service account (credentials stored in AAP) authenticating to remote windows server and error was resolved

if ! grep -q '^[[:space:]]*rotate 1' /etc/logrotate.d/httpd; then
  sed -i -r '/^([[:space:]]*)missingok/ {
    s//\1missingok\
\1rotate 1\
\1size 1k/
  }' /etc/logrotate.d/httpd
fi

can´t make it work. ive tried other options but they never put qty, just one product. yours just come with error and i cant see de qty field. any sugestions?

On june 2024, Google introduced conditional access to Bigquery tables based on tags. This would be the best way to provide such privileges to a certain group of users.

Sources:
https://medium.com/codex/you-can-now-use-tags-for-bigquery-access-5b5c50fcf349
https://cloud.google.com/bigquery/docs/release-notes

It is also not working for me!
Maybe a mistake in the hook?

1. Make a Grid: Get all the x-coordinates from the vertical sides of your rectangles, and the start/end points x-coord. Same for y-coordinates: get all y's from horizontal sides and start/end points y-coord. Sort these x's and y's. These lines make up a grid over your area. The shortest path gonna turn only on these grid lines, right?

2. Find Valid Spots (Nodes): Look at every point where your grid lines cross (x, y). Is that point inside the area made by combining all your rectangles? If yes, this point is a node for a graph we're building.

3. Connect the Spots (Edges): Now, look at two nodes that are right next to each other on the grid (directly left/right or up/down). Draw a line segment between them. Is this entire line segment also inside your combined rectangle area? If yes, add an edge between these two nodes in your graph. The 'weight' or cost of this edge is just the distance between the points (like abs(x1-x2) + abs(y1-y2) cause its orthogonal).

4. Add Start/End: Make sure your start and end points are nodes too. You gotta connect them to the grid graph. Find the grid nodes they can reach with a straight horizontal or vertical line without leaving the rectangle area, and add edges for those connections.

5. Find Path: Now you got a graph. Just use a standard algorithm like Dijkstra's or A* search to find the path with the lowest total edge weight from your start node to your end node. [3]

I have worked out a method to achieve what I want. I am using two divs, the first one is my data entry div which can be setup to best allow entry and scale to the appropriate device.

The second div is a hidden div (display='none') which is basically just a table so I can align data nicely and create a neat and tidy pdf.

        <div id="contentsheet2" class="contentgrid" style="display:none">

Then when the download PDF button is clicked, I locate the hidden div, populate its cells with data from the input elements and generate a PDF.

            function generatePDF() {
            const compname = document.getElementById('compname').value;
            const hiddenDiv = document.getElementById('contentsheet2').innerHTML;
            var opt = {
                  margin: [4, 0, 4, 0], //top, left, bottom, right
                  filename: 'FREEProgram.pdf',
                  image: { type: 'jpeg', quality: 0.95 },
                  html2canvas: {
                    dpi: 300,
                    scale:2,
                    letterRendering: true,
                    useCORS: true,
                    scrollX: 0, 
                    scrollY: 0
                  },
                  jsPDF: { unit: 'mm', format: 'a4', orientation: 'portrait' }
                };              // Choose the element and save the PDF for your user.
            opt.filename = 'FREEProgramContentSheet-' + compname + '.pdf';
            html2pdf().set(opt).from(hiddenDiv).save();
        }

The gives me the ability to have both layouts independent of each other and make the user experience better whilst still getting a neatly generated PDF. The PDF is nicer than I had before because it doesn't have the constraints applied by the input elements.

Try to give both

advertised.listeners and listeners as:

PLAINTEXT://20.244.40.80:9092

You can now, with serverless, either disable the auto-pause or set it to a higher time limit. This is in the compute+storage slot setting for the sql db.

okey, just to have commands for every version of EF in one place, for EF6 it is:

update-database -TargetMigration <full migration name including id>

(origin: https://learn.microsoft.com/en-us/ef/ef6/modeling/code-first/migrations/#migrate-to-a-specific-version-including-downgrade )

I faced a similar problem earlier. Try to see the solution in this question: How to stretch the DropdownMenu width to the full width of the screen?

Since 2023, we can use the NodeSwift module, available both as an npm package and SwiftPM, to let them talk together bidirectionally: https://github.com/kabiroberai/node-swift

It should be better for performance than JavaScriptCore.

In some cases, if you use Node as a main runtime (e.g. Electron app), you can also create a CLI binary (with Swift, C++, or Objective-C), bundle it within the Electron app, and just call this binary as CLI inside the Electron app. An example for ScreenCaptureKit can be found here: https://github.com/mukeshsoni/screencapturekit-node

Math.round((amount + 0.000000000001) * 100) / 100

this one is equals to php's round with precision of two

round(amount,2);

Answer to question 1: Yes, there is a permission
<uses-permission android:name="android.permission.INJECT_EVENTS" />

This is because you redirect every route to a LandingPage here: <Route path="*" element={} /> correct its path which you need landing page route

It seem like this is not possible in TYPO3 13 anymore.

See: https://docs.typo3.org/c/typo3/cms-core/main/en-us/Changelog/13.0/Breaking-102970-NoDatabaseRelationsInFlexFormSectionContainers.html

It throws an error:

Invalid flex form data structure on field name "overlay" with element "settings.infoPoints" in section container "container_infoPoints": Nesting elements that have database relations in flex form sections is not allowed.

Has anyone fond a solution yet?

jus adding node_modules/ in .gitignore worked for me

I know I'm almost 4 years late, a few days ago I published a package which tackles this problem like a champ, here, have a look

https://www.npmjs.com/package/react-ios-scroll-lock

The new Informix JDBC driver 15.0.0.0 is not compatible with older Informix databases. It works with 14.10, 15.0, but does not work with 11.50.

TRY echo '<script> cleartext(); </script>'; at bottom of page before html body close..

There is a package uipasteboard on pub.dev focuses on providing iOS UIPasteboard access in the Flutter context.

SOLVED

The problem was, that my exec resource type had the parameter "cwd => /etc/facter/facts.d" which was also managed by my module "facts".
So, it lead to a dependency cycle.

@Raja Talha Do you find the Solution to this

Running into DB connection issues between PowerBuilder and OCI can be tricky—usually it's a config mismatch, missing drivers, or network/firewall restrictions. Double-check your connection string, ensure the Oracle client is properly set up, and that any required DLLs are accessible to PowerBuilder.

Honestly, debugging this feels like optimizing a build in Path of Building—so many dependencies and one wrong setting can throw everything off. Once it's all wired correctly though, it runs smooth.

Just try to use function for your decimal field in your view: COALESCE(NULLIF(your_view.your_decimal_value, ''), 0)

You are correct, regular REST API's can be accessed from the public endpoint stage URL or a custom domain name. A private REST API is deployed within a VPC using an interface VPC endpoint.

In both cases, regardless of the endpoint being public or private, there are still measures to control and manage access to the API. These may include resource policies, IAM permissions, and others.

it works just fine and gave me my exact location good job!

If your site uses authentication cookies or stored credentials, check:

• Control Panel → User Accounts → Credential Manager

• Under Windows Credentials and Web Credentials

check this out next docs

in your Home, try:

type SearchParams = { [key: string]: string | string[] | undefined }

export default async function Home({
  searchParams,
}: {
  searchParams: SearchParams
}) {
// ...
}

Can someone please guide me on how to convert a PyTorch .ckpt model to a Hugging Face-supported format so that I can use it with pre-trained models?

The model I'm trying to convert was trained using PyTorch Lightning, and you can find it here:
🔗 hydroxai/pii_model_longtransfomer_version

I need to use this model with the following GitHub repository for testing:
🔗 HydroXai/pii-masker

I tried using Hugging Face Spaces to convert the model to .safetensors format. However, the resulting model produces poor results and triggers several warnings.

These are the warnings I'm seeing:

Some weights of the model checkpoint at /content/pii-masker/pii-masker/output_model/deberta3base_1024 were not used when initializing DebertaV2ForTokenClassification: ['deberta.head.lstm.bias_hh_l0', 'deberta.head.lstm.bias_hh_l0_reverse', 'deberta.head.lstm.bias_ih_l0', 'deberta.head.lstm.bias_ih_l0_reverse', 'deberta.head.lstm.weight_hh_l0', 'deberta.head.lstm.weight_hh_l0_reverse', 'deberta.head.lstm.weight_ih_l0', 'deberta.head.lstm.weight_ih_l0_reverse', 'deberta.output.bias', 'deberta.output.weight', 'deberta.transformers_model.embeddings.LayerNorm.bias', 'deberta.transformers_model.embeddings.LayerNorm.weight', 'deberta.transformers_model.embeddings.token_type_embeddings.weight', 'deberta.transformers_model.embeddings.word_embeddings.weight', 'deberta.transformers_model.encoder.layer.0.attention.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.0.attention.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.0.attention.output.dense.bias', 'deberta.transformers_model.encoder.layer.0.attention.output.dense.weight', 'deberta.transformers_model.encoder.layer.0.attention.self.key.bias', 'deberta.transformers_model.encoder.layer.0.attention.self.key.weight', 'deberta.transformers_model.encoder.layer.0.attention.self.key_global.bias', 'deberta.transformers_model.encoder.layer.0.attention.self.key_global.weight', 'deberta.transformers_model.encoder.layer.0.attention.self.query.bias', 'deberta.transformers_model.encoder.layer.0.attention.self.query.weight', 'deberta.transformers_model.encoder.layer.0.attention.self.query_global.bias', 'deberta.transformers_model.encoder.layer.0.attention.self.query_global.weight', 'deberta.transformers_model.encoder.layer.0.attention.self.value.bias', 'deberta.transformers_model.encoder.layer.0.attention.self.value.weight', 'deberta.transformers_model.encoder.layer.0.attention.self.value_global.bias', 'deberta.transformers_model.encoder.layer.0.attention.self.value_global.weight', 'deberta.transformers_model.encoder.layer.0.intermediate.dense.bias', 'deberta.transformers_model.encoder.layer.0.intermediate.dense.weight', 'deberta.transformers_model.encoder.layer.0.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.0.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.0.output.dense.bias', 'deberta.transformers_model.encoder.layer.0.output.dense.weight', 'deberta.transformers_model.encoder.layer.1.attention.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.1.attention.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.1.attention.output.dense.bias', 'deberta.transformers_model.encoder.layer.1.attention.output.dense.weight', 'deberta.transformers_model.encoder.layer.1.attention.self.key.bias', 'deberta.transformers_model.encoder.layer.1.attention.self.key.weight', 'deberta.transformers_model.encoder.layer.1.attention.self.key_global.bias', 'deberta.transformers_model.encoder.layer.1.attention.self.key_global.weight', 'deberta.transformers_model.encoder.layer.1.attention.self.query.bias', 'deberta.transformers_model.encoder.layer.1.attention.self.query.weight', 'deberta.transformers_model.encoder.layer.1.attention.self.query_global.bias', 'deberta.transformers_model.encoder.layer.1.attention.self.query_global.weight', 'deberta.transformers_model.encoder.layer.1.attention.self.value.bias', 'deberta.transformers_model.encoder.layer.1.attention.self.value.weight', 'deberta.transformers_model.encoder.layer.1.attention.self.value_global.bias', 'deberta.transformers_model.encoder.layer.1.attention.self.value_global.weight', 'deberta.transformers_model.encoder.layer.1.intermediate.dense.bias', 'deberta.transformers_model.encoder.layer.1.intermediate.dense.weight', 'deberta.transformers_model.encoder.layer.1.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.1.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.1.output.dense.bias', 'deberta.transformers_model.encoder.layer.1.output.dense.weight', 'deberta.transformers_model.encoder.layer.10.attention.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.10.attention.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.10.attention.output.dense.bias', 'deberta.transformers_model.encoder.layer.10.attention.output.dense.weight', 'deberta.transformers_model.encoder.layer.10.attention.self.key.bias', 'deberta.transformers_model.encoder.layer.10.attention.self.key.weight', 'deberta.transformers_model.encoder.layer.10.attention.self.key_global.bias', 'deberta.transformers_model.encoder.layer.10.attention.self.key_global.weight', 'deberta.transformers_model.encoder.layer.10.attention.self.query.bias', 'deberta.transformers_model.encoder.layer.10.attention.self.query.weight', 'deberta.transformers_model.encoder.layer.10.attention.self.query_global.bias', 'deberta.transformers_model.encoder.layer.10.attention.self.query_global.weight', 'deberta.transformers_model.encoder.layer.10.attention.self.value.bias', 'deberta.transformers_model.encoder.layer.10.attention.self.value.weight', 'deberta.transformers_model.encoder.layer.10.attention.self.value_global.bias', 'deberta.transformers_model.encoder.layer.10.attention.self.value_global.weight', 'deberta.transformers_model.encoder.layer.10.intermediate.dense.bias', 'deberta.transformers_model.encoder.layer.10.intermediate.dense.weight', 'deberta.transformers_model.encoder.layer.10.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.10.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.10.output.dense.bias', 'deberta.transformers_model.encoder.layer.10.output.dense.weight', 'deberta.transformers_model.encoder.layer.11.attention.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.11.attention.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.11.attention.output.dense.bias', 'deberta.transformers_model.encoder.layer.11.attention.output.dense.weight', 'deberta.transformers_model.encoder.layer.11.attention.self.key.bias', 'deberta.transformers_model.encoder.layer.11.attention.self.key.weight', 'deberta.transformers_model.encoder.layer.11.attention.self.key_global.bias', 'deberta.transformers_model.encoder.layer.11.attention.self.key_global.weight', 'deberta.transformers_model.encoder.layer.11.attention.self.query.bias', 'deberta.transformers_model.encoder.layer.11.attention.self.query.weight', 'deberta.transformers_model.encoder.layer.11.attention.self.query_global.bias', 'deberta.transformers_model.encoder.layer.11.attention.self.query_global.weight', 'deberta.transformers_model.encoder.layer.11.attention.self.value.bias', 'deberta.transformers_model.encoder.layer.11.attention.self.value.weight', 'deberta.transformers_model.encoder.layer.11.attention.self.value_global.bias', 'deberta.transformers_model.encoder.layer.11.attention.self.value_global.weight', 'deberta.transformers_model.encoder.layer.11.intermediate.dense.bias', 'deberta.transformers_model.encoder.layer.11.intermediate.dense.weight', 'deberta.transformers_model.encoder.layer.11.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.11.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.11.output.dense.bias', 'deberta.transformers_model.encoder.layer.11.output.dense.weight', 'deberta.transformers_model.encoder.layer.2.attention.output.LayerNorm.bias', 'deberta.transformers_model.encoder.layer.2.attention.output.LayerNorm.weight', 'deberta.transformers_model.encoder.layer.2.attention.output.dense.bias', 'deberta.transformers_model.encoder.layer.2.attention.output.dense.weight', 'deberta.transformers_model.encoder.layer.2.attention.self.key.bias', 'deberta.transformers_model.encoder.layer.2.attention.self.key.weight', 'deberta.transformers_model.encoder.layer.2.attention.self.key_global.bias', 'deberta.transformers_model.encoder.layer.2.attention.self.key_global.weight', 'deberta.transformers_model.encoder.layer.2.attention.self.query.bias', 'deberta.transformers_model.encoder.layer.2.attention.self.query.weight', 'deberta.transformers_model.encoder.layer.2.attention.self.query_global.bias', 'deberta.transformers_model.encoder.layer.2.attention.self.query_global.weight', 'deberta.transformers_model.encoder.layer.2.attention.self.value.bias', 'deberta.transformers_model.encoder.layer.2.attention.self.value.weight', 'deberta.transformers_model.encoder.layer.2.attention.self.value_global.bias', 'deberta.transformers_model.encoder.layer.2.attention.self.value_global.weight', 'deberta.transformers_model.encoder.layer.2.intermediate.dense.bias', 'deberta.transformers_model.encoder.layer.2.intermediate.dense.weight', 'deberta.transformers_model.encoder.layer.2.output.LayerNorm.bias', 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You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

I also encountered this problem, after many hours of troubleshooting, found that by commenting out the line proxy_set_header X-Forwarded-Proto $scheme; , problem solved.

Perhaps the jenkins itself build the 302 redirect url with header X-Forwarded-Proto if it exists

My approach is get rid of the numbers between the two characters '.' and '+' first by replacing those numbers to _.

import re

input_string = "manual__2025-04-08T11:37:13.757109+00:00"
result = re.sub(r'\.(\d+)\+', r'_', input_string)
result = result.replace(':', '_').replace('+', '_')

print(result)

see next docs

  cacheHandler: path.resolve(__dirname, "./lib/cache-handler.js"),

One-liner:

s = re.sub(r'\.\d+(?=\+)', '', 'manual__2025-04-08T11:37:13.757109+00:00').replace(':', '_').replace('+', '_')

I know I'm almost 5 years late, but a few days ago I published a small package that tackles this problem, check it out

https://www.npmjs.com/package/react-ios-scroll-lock

In April 2025

Setting budget to $1 for Actions Product allowed me to continue the build.

I also set the Artifacts and Logs retention to 1 day, as I don't need more than that.

I have been trying to do the same but experimenting instead with the greater flexibility provided by xelatex on the use of fonts. The following code produces a fine result but I am not sure if changing the sans-serif font won't mess with scanned elements.

exams2nops(questions, n = 2, dir = "nops_pdf", name = "test",
           usepackage = c("unicode-math"),
           header="\\setmainfont{TeX Gyre Pagella}\\setmathfont{TeX Gyre Pagella Math}\\setsansfont{Roboto}",
           texengine="xelatex")

Can you comment, please?

No one added an important piece of information. When you're connecting to github such an error may occur when using RSA algorithm for private key generation. Try switching to ECDSA.

I had the same issue when try to build apk with android studio

i am using ionic-cordova to build android application. this is happen to me because i used JDK 21 instead of JDK 17, so just modify JDK version fixed my issue.

Hope it will help ):

The following worked on the default Ubuntu (24.04.1) terminal using bash as the shell interpreter.

The Ctrl-V solution

This is the "what you see is what you get" (WYSIWYG) solution that I think you're looking for since you mentioned trying "shift+return, alt+return, ctrl+return.. etc".

Just try Ctrl+V followed by Ctrl+J to get a new line on your terminal.

This should place the cursor on your terminal at the beginning of a new line allowing you to continue introducing text inside your double quoting just like your example shows (an actual multiline block of text as if you're inside a text editor). That combination will pass the equivalent of a line feed character ('\n') to the command.

$ echo "line1
line2
line3" >multiline_from_ctrlvj
$ cat multiline_from_ctrlvj 
line1
line2
line3
$

Related to this, entering Ctrl+V followed by TAB will "print" a tabulation on your terminal and send a '\t' character to the shell

$ echo "one    two     three   four"
one two three   four
$

Entering Ctrl+V followed by ENTER will print a '^M' on your terminal but will send a carriage return to the shell":

$ echo "this will be overwritten by^MTHIS"
THIS will be overwritten by
$

The ANSI C quoting solution

(already pointed out by @KamilCuk)

If you don't care about how your terminal looks like while typing but just want to insert the newline as part of the argument string, you can always use the ANSI C quoting style as an alternative to the double quoting. The ANSI C quoting style requires a leading $ sign and simple quotes:

$'any text including ANSI C special characters such as '\n' or others'

$ echo $'line1\nline2' >multiline_from_ANSI_C_quoting
$ cat multiline_from_ANSI_C_quoting 
line1
line2
$

Notice that the $'...' quoting must be used instead double quoting "...", since something like this won't work as desired (double quoting removes the special meaning of the $ sign for the shell):

$ echo "line1$'\n'line2"
line1$'\n'line2
$

The command substitution solution

(already pointed out by @KamilCuk)

Whatever you put inside $(...) gets executed in a subshell and its output (not exactly but irrelevant here) is used to replace the entire $(...)construction. That is why this is also an option:

git commit -m "$(printf "%s\n" "message" "" "description")"

Notice that any double quoting inside $(...) doesn't affect the outer double quoting.

PD: The recommended way to commit

A well documented commit should have a title (single short line) and a body (multiline block). When you use the git commit -m "brief title of the commit" you're just attaching a title to the commit while leaving its body empty. As pointed out by @KamilCuk, you should have your git configured to use a text editor (such as vim). If that's the case, entering just git commit will open the text editor where you must: 1) enter the first line as the commit title; 2) leave the second line empty; 3) start your commit detailed multiline description from the third line; 4) save and quit the text editor; then the commit will be done.

Check your .gitconfig file for something like this to confirm if you have an associated text editor for git:

[core]
    editor = vim

Execute something like this to configure a text editor for git:

$ git config --global core.editor "vim"

I handled it in C# :

var fileChooser = await page.RunAndWaitForFileChooserAsync(async () =>
{
    await page.GetByText("Upload file").ClickAsync();
});
await fileChooser.SetFilesAsync("temp.txt");

I received a similar error and I use AWS Amplify. I added the AmplifySSRLoggingRole IAM role to Amplify -> App Settings -> IAM Roles -> Service role, and it worked.

if you struggle to resolve the problem with python libs. Check this article. it helped me a lot. https://aws.plainenglish.io/easiest-way-to-create-lambda-layers-with-the-required-python-version-d205f59d51f6

DateTime.parse has a second argument, which uses UTC for the conversion.

print(widget.asset.purchaseDate);
DateTime temp = DateTime.parse(widget.asset.purchaseDate, true);
print(temp.toLocal());

{
            "autoUpdateMode": "AUTO_UPDATE_HIGH_PRIORITY", 
            "packageName": "com.samsung.android.knox.kpu", 
            "defaultPermissionPolicy": "GRANT", 
            "installType": "FORCE_INSTALLED", 
            "managedConfigurationTemplate": {
                "templateId": mcmId
            }
        }, 

for me this was not working.

try „Clear-Host“ as you are using PowerShell

There were two main reasons for the problem. 1. Reason

When I manually received, my bindings were failing. I added the endpoints directly in the context as shown in the documentation. cfg.ConfigureEndpoints(context);

2. Reason

There were old exchanges with the same name and queues connected to them. During the tests, it was not enough to just delete the queue. There are exchanges that the queue is connected to. Since the same exchange already exists, it is not recreated. Since the exchange was not recreated, it could not reconnect while connecting the relevant queue. Clearing all exchanges and running the tests from scratch solved my problem.

Turns out Entra Groups are not supported.

https://learn.microsoft.com/en-us/azure/azure-sql/database/authentication-azure-ad-logins?view=azuresql#microsoft-entra-group-server-principal-limitations

• Azure SQL Database server roles aren't supported for Microsoft Entra groups.

When someone leaves the job, updating the EMPLOYEES table on status column (like True or False values) will do the trick for you. You can request developers to set up such a table structure.

I used 2 Facebook profiles that were connected. The first page shared it's link on the second profiles page and the same the other way. The first would be able to go back and forth freely. After the link was open both profiles could forward the 1 profile page. However it only works 1 way. It took a while to create the link for the second profile. Even after I had deleted the first profile. But I think I have a way for both profiles to jump from there page to any other page. And the second has the way to get back. It's an infinity jumping link lol

depends_on:
      eureka:
        condition: service_healthy
      customerapp:
        condition: service_healthy
      cardapp:
        condition: service_healthy
      loanapp:
        condition: service_healthy

how can i make noreply mail.Is it enough for me ?

data['h:Reply-To']="" 

Go through this link https://github.com/rvm/rvm/issues/5507

curl -sSL https://github.com/ruby/ruby/commit/1dfe75b0beb7171b8154ff0856d5149be0207724.patch -o ruby-307-fix.patch && rvm install 3.0.7 --patch ruby-307-fix.patch --with-openssl-dir=$(brew --prefix [email protected]) && rm ruby-307-fix.patch;

The above command worked for me.

Add the folder in which you stored the "my-project-env" to the VSCode workspace.

For anyone searching for how to draw labels on top of the bars:

in options > scales > x or y > ticks you add z: 1.
z property changes the layer, above 0 is above the bars.

Here's the documentation:
https://www.chartjs.org/docs/latest/axes/_common_ticks.html

This package is working okay if you use "Intervention\Image\Laravel\Facades\Image" v2.x version. but if you use your version 3.* or grater then you need to update blow code.

use Intervention\Image\ImageManager;
use Intervention\Image\Drivers\Gd\Driver;

// create image manager with desired driver
$manager = new ImageManager(new Driver());

// read image from file system
$image = $manager->read('images/example.jpg');

// resize image proportionally to 300px width
$image->scale(width: 300);

// insert watermark
$image->place('images/watermark.png');

// save modified image in new format 
$image->toPng()->save('images/foo.png');

Reference : https://image.intervention.io/v3

I have the same problem. I couldn't install the solution. I think the problem may not be in the code. If you find the solution, I would be very happy if you share it.

Yeah, so short version: after 4.2, the old getContent hack just stopped working because WordPress rewrote how MCE views work. You can’t just override the template anymore without re-registering the whole gallery view. There’s no clean hook, no magical filter, no partial override, you either unregister and rebuild it like you did, or you live with the default. Everything else like extending or patching after init is a no-go. It's messy, but that’s the only way it actually works now.

Go to:
Android Studio > Preferences (or Settings)
→ Keymap
→ Search: Show Context Actions

Make sure it's mapped to:

• macOS: Option + Enter

• Windows/Linux: Alt + Enter

If it’s not mapped, right-click and "Add Keyboard Shortcut", then set it manually.

I think I finally found the answer. It is implied by the first comment of this bug description:
https://github.com/docker/compose/issues/3415#issue-153068282

When we recreate a container we start by renaming the old container by adding the container short id as a prefix. If the start or create fails, the container is left with that prefixed name.

You want to get the path of the executable at runtime, it would be like this:

string projectPath = Path.GetDirectoryName(Assembly.GetEntryAssembly().Location);

After I ran it the result was this:

C:\\Users\\<user>\\source\\repos\\App7\\App7\\bin\\x64\\Debug\\net8.0-windows10.0.19041.0\\win-x64\\AppX

Thanks, everyone. At the end, I went to sleep and came back to this problem today, and solved with the strum and strum_macros crates. I marked my enum with #[derive(EnumDiscriminants, EnumString, AsRefStr)] and #[strum_discriminants(derive(EnumString, AsRefStr))], which gives me a new enum called ErrorDiscriminant that contains all the same variants but without extra data, as well as a method ErrorDiscriminant::from(&Error) that I can use to map each Error variant to an ErrorDiscriminant variant. From there, I can just do <error-discriminant> as i32 and the problem is solved.

As I'm new to Rust and this is the solution I just found, I cannot guarantee it is correct, but it's working for me so far and it makes sense.

I think GeometryReader dynamicIsland is not working as expected. That's why the image might not look the way you want it to.

Initially, I misunderstood the communication pattern and confused CSMS and CS roles. I thought that CS is a server and CSMS is a client. But actually, the things are exactly the opposite. To get data from the CS one should implement CSMS as a server and setup CS to connect with this CSMS. Hope that it will be useful for someone.

I battled with this problem for days. I am working on a JavaEE project running on Wildfly 26.1.3 with Java 11 and Hibernate 5.6.15.Final. Adding the following property to my persitence.xml file fixed the problem for me:

 <property name="org.hibernate.flushMode" value="COMMIT" />

Yes this was an airflow version issue.

Thank you @Kombajn zbożowy for testing the code in airflow 2.10.5

I have since upgraded from 2.10.3 --> 2.10.5 and get the desired task outputs. This issue is probably the one highlighted on github here.

Despite attempts using version 2.10.3 to ensure trigger_rule='all_success' in the @task decorator args this bug was only fixed with upgrading.

For me , it was the atomicfu dependency and to fix it I just added this line in build.gradle.kt after the plugins section:

atomicfu {
    transformJvm = false  // Disable transformation for Android target
}

No need to downgrade Kotlin version!