Implement ILocalizationInterceptor

Description

Add Localization Interceptor based on the discussion in #7374
resolves #7374
Motivation: currently changing english texts requires hacks with changing the DefaultUICulture to something other then english, which can break a lot of things (especially when you actually want to use localization)
With the interceptor (proposed by @ScarletKuro ) it is now possible to change english texts, the whole localization behaviour or to just add stuff like logging of missing translation keys.
How Has This Been Tested?

just did a quick check with the existing unit tests and the docs server. Proper unit tests will follow.
Types of changes

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Documentation Example on how to use the LocalizationInterceptor to customize english texts

Checklist:

[x] The PR is submitted to the correct branch (dev).
[x] My code follows the code style of this project.
[ ] I've added relevant tests.

Proper unit tests and documentation will follow tomorrow. I just wanted to get the initial pull request done for today to allow code reviews

Noticed the inital code did not pass the IStringLocalizer and MudLocalizer instanes to ILocalizationInterceptor properly, so I added those as parameters to ILocalizationInterceptor.Handle. Now custom implementations don't have to worry about where to get those two localizers from.

I am not quite happy with how one has to basically reimplement the DefaultLocalizationInterceptor logic if one only wants to change some english text, but I don't have a better idea for now

I added those as parameters to ILocalizationInterceptor.Handle. Now custom implementations don't have to worry about where to get those two localizers from.

Sure, tho I think would be be solved with an example that shows how to get the needed things, that MudLocalizer is registered in DI and the IStringLocalizer is created from the factory. My worries is that this IStringLocalizer is created from ResourceManagerStringLocalizerFactory, what if they don't want it for some reason / want create it from other factory, then this is will be extra.

I am not quite happy with how one has to basically reimplement the DefaultLocalizationInterceptor logic if one only wants to change some english text, but I don't have a better idea for now

That was the whole point. Yes, you might want to change just a single line, for this the user will need to copy the default implantation. As I said, in my opinion there are way too many possible logic in localization, and it's better to offer freedom instead of trying to cover it with options, yet there will be someone will unique request.

Sure, tho I think would be be solved with an example that shows how to get the needed things, that MudLocalizer is registered in DI and the IStringLocalizer is created from the factory. My worries is that this IStringLocalizer is created from ResourceManagerStringLocalizerFactory, what if they don't want it for some reason / want create it from other factory, then this is will be extra.

MudLocalizer could easily be passed via DI, true.
For the IStringLocalizer, I am not so sure if that should be done, considering how that one just provides access to the default english localization which has to be parsed by a Factory capable of handling ResX files, but that is just a minor concern.

That was the whole point. Yes, you might want to change just a single line, for this the user will need to copy the default implantation. As I said, in my opinion there are way too many possible logic in localization, and it's better to offer freedom instead of trying to cover it with options, yet there will be someone will unique request.

Got it. That definitely makes sense. I am probably just thinking a bit too much of that one possible usecase.
In any case, I'll rework the code and documentation based on your input after work tomorrow.

The second idea that I described above:
#nullable enable
public interface ILocalizationInterceptor
{
    LocalizedString Handle(string key);
}

#nullable enable
public abstract class AbstractLocalizationInterceptor : ILocalizationInterceptor
{
    public IStringLocalizer Localizer { get; }

    public MudLocalizer? MudLocalizer { get; }

    protected AbstractLocalizationInterceptor(ILoggerFactory loggerFactory, MudLocalizer? mudLocalizer = null)
    {
        var options = Options.Create(new LocalizationOptions());
        var factory = new ResourceManagerStringLocalizerFactory(options, loggerFactory);
        Localizer = factory.Create(typeof(LanguageResource));
        MudLocalizer = mudLocalizer;
    }

    public abstract LocalizedString Handle(string key);
}

#nullable enable
public class DefaultLocalizationInterceptor : AbstractLocalizationInterceptor
{
    public virtual bool IgnoreDefaultEnglish => false;

    public DefaultLocalizationInterceptor(ILoggerFactory loggerFactory, MudLocalizer? mudLocalizer = null)
        : base(loggerFactory, mudLocalizer)
    {
    }

    public override LocalizedString Handle(string key)
    {
        if (!IgnoreDefaultEnglish)
        {
            var currentCulture = Thread.CurrentThread.CurrentUICulture.Parent.TwoLetterISOLanguageName;
            if (MudLocalizer is null || currentCulture.Equals("en", StringComparison.InvariantCultureIgnoreCase))
            {
                return Localizer[key];
            }
        }

        return TranslationWithFallback(key);
    }

    protected virtual LocalizedString TranslationWithFallback(string key)
    {
        var defaultTranslation = Localizer[key];
        if (MudLocalizer is null)
        {
            return defaultTranslation;
        }

        var res = MudLocalizer[key];
        return res.ResourceNotFound ? defaultTranslation : res;
    }
}

#nullable enable
internal sealed class InternalMudLocalizer
{
    private readonly ILocalizationInterceptor _interceptor;

    public InternalMudLocalizer(ILocalizationInterceptor interceptor)
    {
        ArgumentNullException.ThrowIfNull(interceptor);

        _interceptor = interceptor;
    }

    /// <summary>
    /// Gets the translation for the given translation key.
    /// </summary>
    /// <param name="key">the translation key to look up</param>
    /// <returns>The string resource as a <see cref="LocalizedString"/>.</returns>
    public LocalizedString this[string key] => _interceptor.Handle(key);
}

public static IServiceCollection AddMudLocalization(this IServiceCollection services)
{
	services.TryAddTransient<ILocalizationInterceptor, DefaultLocalizationInterceptor>();
	services.TryAddTransient<InternalMudLocalizer>();

	return services;
}

public static IServiceCollection AddLocalizationInterpreter<[DynamicallyAccessedMembers(DynamicallyAccessedMemberTypes.PublicConstructors)] TInterpreter>(this IServiceCollection services) where TInterpreter : class, ILocalizationInterceptor
{
	services.Replace(ServiceDescriptor.Transient<ILocalizationInterceptor, TInterpreter>());

	return services;
}

The main idea is that now the ILocalizationInterceptor is always registered in DI with our default implementation when AddMudServices is called. You can replace the default implementation with a custom one via AddLocalizationInterpreter.
People have thee options to customize:

Inherit DefaultLocalizationInterceptor and get the ability to override TranslationWithFallback and IgnoreDefaultEnglish. We can add more convenient options, it's our default implantation. This is mainly to fix the "DefaultLocalizationInterceptor logic if one only wants to change some English text" concern.
Inherit AbstractLocalizationInterceptor that comes with the IStringLocalizer and MudLocalizer. Honestly, it looks redundant, but fixes the "Now custom implementations don't have to worry about where to get those two localizers from" concern, they can just use it and DI and the abstraction will do the job for them.
Low lever interface for full customization without anything predefined in case they don't MudLocalizer or our preinitialized IStringLocalizer.

Let me know what you think, It's slightly complicated, requires more code from our side, but it should be easy to understand if well documentation. Making unit tests for this is also as easy as before.

Let me know if you are busy, I can to try to take over.

Let me know if you are busy, I can to try to take over.

Sorry for the late reply, a few unexpected things came up for me. It might be better if you take this over.
Your last proposal looks really good imo. I get that the whole AbstractLocalizationInterceptor layer feels redundant and I think I might have been focused too much on that single usecase there. With or without the abstraction layer it should be usable just fine in that case with proper examples in the documentation.

@henon I'm reviving this as I want to close this issue, and it was initially my idea.
Could you remind me how this LocalizationInterceptorCode.html is generated? I need to change the example.

Could you remind me how this LocalizationInterceptorCode.html is generated? I need to change the example.

AFAIK we don't have a good way to do it. I think you can let our generator generate it by temporarily creating an example razor where the code block contains the code you want to create, then copy the html into the manual html file.

Merging.
Fully revamped the initial PR. I'm really happy with the end result.


Fixed bugs in applying datashader operations

Fixes the dynspread operation which did nothing before and fixes a bug applying streams in the Dynamic utility when applying an dynamic operation to a static element.

Ready to merge.

Looks good.
My only suggestion is to maybe add a unit test for the condition fixed in Dynamic?

Oh and there is a bit of trailing whitespace after the max_px definition. :-)

I'll merge when the tests go green.

Looks good; thanks!  I'll update the Holoviews_Datashader tutorial once this is done, to add dynspread and timeseries operations (outliers).

Tests have now passed. Merging.


Bugfix - described objects with no url should not break the homepage.

If a described_object get_url() returned None an error occured on the index page.

Codecov Report

Merging #483 (5f101e8) into master (cd3cb9b) will decrease coverage by 0.01%.
The diff coverage is 0.00%.

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@@            Coverage Diff             @@
##           master     #483      +/-   ##
==========================================
- Coverage   91.82%   91.81%   -0.02%
==========================================
  Files         290      290
  Lines       17664    17666       +2
  Branches     1427     1428       +1
==========================================
  Hits        16220    16220
- Misses       1183     1185       +2
  Partials      261      261

Impacted Files
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common/models/mixins/description.py
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OK, YOLOing this, and will do a part two afterwards once I work out how to get our factories to recreate data like this for the frontend.


Example webpack.config.js

I have yet to be able to get this or any other configuration to properly load Materialize (or for that matter, jQuery, which is spotty at best) with Webpack.

It would be useful if you could please post an example webpack.config.js that actually works.
Your documentation is unclear as to exactly where the example code goes, and continually throws errors.

materialize-loader is not supposed to give support on webpack configurations.
I recommend you to look a create-react-app from @facebookincubator or react-boilerplate from @mxstbr

I understand webpack. But if your example as to how to enable this loader is unclear, why would you not think that you should provide some guidance for that?
It doesn't matter, anyway since your loader doesn't actually work correctly. It still improperly loads jQuery, which is due to the nature of JQuery, not your loader.

If you know webpack you know how to use this package. The documentation shows exactly where to put piece of code.
And the package does not need to load jQuery because materialize-css itself doesn't load jQuery. It is required as an external dependency, not internal.

JQuery 2.1.4 is included in the NPM module for materialize-css.


Writing a PermutationSpec for SDXL

Do you have any plans to Develop a PermutationSpec for SDXL?
If not, would you be so kind as to explain a bit more how you arrived at the one for 1.5?
I read through your conversation over on the original repo, but I'm having trouble following your work compared to a raw model.

I plan to write for XL. I'm just a bit swamped at the moment.

I think I got the hang of it.
I'm working up a PermutationSpec for SDXL without VAE keys (I find no reason to ever merge VAE, simply replace if necessary) if I get it to work, I'll link it here for your use.

https://github.com/vladmandic/automatic/blob/dev/modules/merging/merge_PermSpec_SDXL.py
SDXL PermutationSpec

Nicely done! Did you run a test ? Do you know what layers change when you attempt a merge ?

It seems to work fine (my code is based on @s1dlx code which is based on yours) but I haven't delved deeper.

Finally got it done.
https://github.com/6DammK9/Merge-Stable-Diffusion-models-without-distortion/blob/main/merge_PermSpec_SDXL.py
You need to "sew" it properly, the permutation loop somehow iterlate the whole model in sequence, and checking tensor sizes. No wonder why it is left untouched for months.
Sample image in my fork, with comparasion.

Amazing! I got it as far as I could, glad someone picked it up from there.


spurious issues from the prefer_const_constructors_in_immutables after the move to fasta

Context here: https://github.com/flutter/flutter/pull/21143#issuecomment-416986095
cc @danrubel

I don't think this is a fasta regression anymore; closing.

Can we keep this open to track regression that required adding //ignore analyzer directives? (I already added TODO that references this issue in flutter codebase).

I don't know that this is a regression so much as now properly reporting for this location in the source. I think we should either // ignore: for these locations, w/ a message as to why, or file a but against the specific lint if we think it shouldn't be warning here.

This bug reads to me as a bug against prefer_const_constructors_in_immutables lint: "spurious issues from the prefer_const_constructors_in_immutables".
Basically if you attempt to make const those three reported lints, you get more cascading prefer_const_constructors lints that ultimately can't be followed as nav_bar_test.dart:607 for example can't be made const as analyzer reports that Evaluation of this const expression throws an exception.
Is it possible for lint/analysis team to look at flutter codebase as part of this regression investigation?

Per https://github.com/flutter/flutter/pull/21143#issuecomment-417068555 let me keep this open until all right pieces land and we can remove analyzer ignore directives.


add json format output

In some cases we need logs in json format

thank you very much @zhangkyou


Abort/Commit

Customer says "one thing we are really missing is the ability to simply abort/commit the current session."

Abort/Begin/Commit and transaction mode controls are now present in the martinDev branch.


Add varaidic logging, Logger class.

Whoops, deleted the branch by mistake!
As decided, source location info has been replaced with variadic arguments to forward to std::format.
Close #38.
Comment from @Rinzii on original PR:

Could we still keep information for verbose logging with the ability to enable it though the Config but instead use something like __ FILE __ over source location? I know __ FILE __ and such is mega C like, but from my understanding its the best way we can handle this problem without source_location. What are your thoughts @karnkaul ?

@Rinzii Contributions are welcome for the FILE feature. 😉

@Rinzii Contributions are welcome for the __FILE__ feature. wink

I'm still working on the vulkan code, but can switch gears if help is needed! Or if @Kouros26 is not working on anything major right now and is down they could also give a go at it. :smile:

For now though I don't see any issues with the current code so I'm going to approve this all and create an issue for bringing back in the verbose logging using __ FILE __ and such. ^^

Sounds good!


Closing the Preview sometimes requires manual relaunch

_EXIT could be used to prevent the Preview from being closed in the first place.

As _EXIT is already used internally by InForm.ui, the alternative was to catch the BeforeUnload event.


Use as a debug repl?

Is there any way to use the REPL during debugging at a breakpoint?

Not that I know of, but that would be cool. Right now, I don't know how you would get access to the state of a running program. If you or anyone else finds out, let me know, though. I'll keep this open, too, because it would be a good thing to add.


bugfix: snapshotpolicy

这个 PR 实现什么功能/修复什么问题:
model manager 增加一个
是否需要 backport 到之前的 release 分支:

release/2.11

/cc @wanyaoqi
/area region

Codecov Report

Merging #2711 into master will not change coverage.
The diff coverage is n/a.

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======================================
  Coverage    7.23%   7.23%
======================================
  Files         472     472
  Lines       74442   74442
======================================
  Hits         5384    5384
  Misses      68606   68606
  Partials      452     452

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/lgtm
/approve


Fix url generation to git hosted Cargo.toml file

Property fixes urls containing //, which makes APIs return a redirect, breaking hyper since it can't follow them.

Is there an example url to hit to test this?

I can attest that this happens with the analysis of most repositories.
Example: http://localhost:8080/repo/github/deps-rs/deps.rs
Log output:
{"msg":"error: Status code 301 Moved Permanently for URI https://raw.githubusercontent.com/deps-rs/deps.rs/HEAD//Cargo.toml","level":"ERRO","ts":"2020-10-01T16:30:09.051622+01:00","http_path":"/repo/github/deps-rs/deps.rs","version":"0.1.0"}

I would have opted for removing extraneous forward slashes after HEAD/, but this might be more reliable.

now that the tests are added, it does rather seem like there could be some deduplication across these files

Having a separate module just for url generation probably didn't make sense. This should work better and avoid a lot of duplication

We should definitely avoid this unnecessary redirect as it causes a relatively large performance overhead that is just not necessary. (although we should be able to follow 301 redirects, as some repositories could be moved)

Could experiment with switching out the client (to eg reqwest) since it might be easier to support 301s.

Yeah, that would probably nice. At the same time it was cool that we were able to use hyper for both the server and the http client (less dependencies), though that's just a nice side effect. But there may also be more efficient/ergonomic choices for the server side by now, I don't know.

Thanks for the merge! The repo links still show up the known problem. When will the change be deployed?
https://deps.rs/repo/github/est31/rcgen

Hey, we just took over the project a few days ago and are still in the process of migrating the deployment, so it may take another couple of days until the change is live. If you want you can subscribe to #46. Once that's closed changes are going to be rolled out to the website automatically again.

@Feliix42 thanks for the reply. Will subscribe to the issue! Glad to see the project being in good hands again.


Adding proxy settings to client setting

Adding the same kubernetes config I added to cerberus in PR here, waiting for a private cluster to double check this. Will update if this doesn't work

@paigerube14 let's rebase the PR.

/funtest

closing as this functionality has moved to krkn-lib, will want to move the functionality over there


Multi select for many to many relationship editing

Changes

Adds multi-select support to tables when editing many-to-many relationship properties in the detail view
Fixed a bug where attributes wouldn't be removed from DOM elements under certain conditions
Removed addSelection and addEnabled. Just use select for both adding and removing instead.

Also removed findRelatedObject since it was referencing addEnabled and I couldn't tell what it was for. @adamvy is it fine to remove findRelatedObject or should I add it back? What does it do?

Screenshots
Adding items in a many-to-many relationship
Looking at a random group

After clicking "Add"

After making some selections

After clicking "Add"

Removing items in a many-to-many relationship
After clicking "Remove" in the detail view

After clicking the checkbox in the table header to select all

After clicking "Remove"

@TW80000 How does this scale? If the relationship had thousands or hundreds of thousand entries?

It's just a feature of the TableView and DAOController, so its performance is essentially just the performance of our TableView. All it's doing is an unfiltered select on the targetDAO specified in the relationship when adding and a filtered select on the targetDAO when removing. So it's just as performant as checking out a TableView of the targetDAO directly. The performance impact of the multi-select feature itself should be negligible.

I like this feature, we'll just have to be smart about which relationships we add it to.

This feature would be enabled for all relationships, and I think that's what we want. Just like we can render a TableView of any DAO no matter how many entries there are in it, we can use this feature for editing any many-to-many relationship through the GUI.


Atrous convolution does not preserve tensor shape

For an input with an undefined batch size, atrous_conv2d emits tensors where all except the final dimension are undefined:
input = tf.placeholder(tf.float32, (None, 256, 256, 3))

conv = tf.nn.conv2d(input, tf.zeros((3, 3, 3, 16)), strides=[1, 1, 1, 1], padding='SAME')
print(conv.get_shape()) # Correctly displays (?, 256, 256, 16)

dilated = tf.nn.atrous_conv2d(input, tf.zeros((3, 3, 3, 16)), rate=2, padding='SAME')
print(dilated.get_shape()) # Displays (?, ?, ?, 16)

(For concrete batch sizes, everything works as expected.)
Tested on 0.10.0rc0

Indeed I have reproduced the problem.  I believe @gpapan implemented atrous_conv2d, and might have thoughts on how easy this would be to fix.

:+1:

:+1:

Can I work on this? I think, I can solve this.

That would be great @AnishShah, can you describe what the problem is?

@vrv The problem is in this line. It is using ShapeOp to estimate paddings for ShapeToBatchOp. That is why it is not able to predict the output shape. I tried few things, but I was unsuccessful. What do you suggest?

fdsa

@AnishShah, do you have any updates?

I tried, but not able to solve it. Sorry.
On Feb 15, 2017 2:35 PM, "Andrew Selle"<EMAIL_ADDRESS>wrote:

@AnishShah https://github.com/AnishShah, do you have any updates?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
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I believe the source of confusion here may be due to varying definitions of atrous convolution depending on the paper being read. Basically, some papers defined atrous convolutions incorrectly when they really meant dilated convolutions. This is explained in Multi-Scale Context Aggregation by Dilated Convolutions with the authors' implementation in https://github.com/fyu/dilation.
Also see the related issue https://github.com/tensorflow/tensorflow/issues/3492.
I think what people are hoping for is a new function, or perhaps simply an additional parameter to the atrous function, is the ability to specify a constant scale of the output data so this can behave the same as these papers where the output dimensions are the same as the input, since this is particularly useful for semantic segmentation.
I believe this is implemented in tensorflow/models resnet_v2 in the function conv2d_same. It may even be simple enough to migrate that option directly upstream. @warmspringwinds is also very familiar with this and may be able to verify that everything I've said here is correct, or perhaps contribute something additional.
@vrv or @tatatodd regarding the TensorFlow API design, if this version of dilated convolution with constant input/output dimensions is supported directly in tf.nn should it be applied via:

atrous_conv2d with the SAME flag
atrous_conv2d with a separate parameter
a totally separate function

I'm going to delegate to @gpapan on this one, who knows more about semantic segmentation and atrous conv :).  I would suggest we'd need a totally separate function because of potential confusion between atrous and dilated.
That being said, perhaps someone just posts a good implementation of it here for now instead of having to add it to the API?  (Usually, a good sniff test for adding something to the API is whether it's used / fundamental in a state of the art model for an important problem.  Otherwise everything under the sun gets added to the core API and our team can't support it all).

@ahundt In tensorflow, "atrous convolution" and "dilated convolution" are used as synonyms to mean "dilated convolutions" as in the Multi-Scale Context Aggregation by Dilated Convolutions paper you cited.
@AnishShah tf.nn.convolution now provides a more generic interface for atrous convolution for any number of dimensions, and I believe it has slightly more complete shape inference, but there are still cases where it does not infer some of the output shape dimensions even when it could.  If you are going to add better shape inference code, I suggest adding it to tf.nn.convolution, as there is separate work underway (see #7545) to make atrous_conv2d simply forward to tf.nn.convolution.
To fix it you will need to use set_shape function on the output tensors to set the additional shape information.  I think it would be possible to do this inside of with_space_to_batch, specifically on the input_converted tensor and then again on the result_converted tensor.  You will unfortunately have to duplicate some of the work done in calculating the shapes for space_to_batch_nd and batch_to_space_nd.  The reason is that a tensor can either be constant or non-constant, but not partially constant.

@jbms Thanks for your comment. Does the current code in  with_space_to_batch or #7545 have a mode where the output tensor has the same dimensions as the input tensor?
This is the case for conv2d_same in tensorflow/models:
def conv2d_same(inputs, num_outputs, kernel_size, stride, rate=1, scope=None):
  """[snip...]
  Args:
    inputs: A 4-D tensor of size [batch, height_in, width_in, channels].
  [snip...]
  Returns:
    output: A 4-D tensor of size [batch, height_out, width_out, channels] with
      the convolution output.
  """

I think it would be very productive to add a note in with_space_to_batch explaining what the output dimensions would be relative to given input dimensions in.
Regarding your comment on atrous vs dilated convolutions, I quoted the following from a footnote in the Multi-Scale Context Aggregation by Dilated Convolutions:

Some recent work mistakenly referred to the dilated convolution operator itself as the algorithme a trous. This is incorrect. The algorithme a trous ` applies a filter at multiple scales to produce a signal decomposition. The algorithm uses dilated convolutions, but is not equivalent to the dilated convolution operator itself.

Perhaps this is a bit pedantic but if the paper is stating this correctly, wouldn't it mean TensorFlow is mistaken in its use of atrous and dilation as synonyms? This seems to imply that what is described as the atrous algorithm only dilated filter size, while the dilated version can be configured so the output is the same size as the input.

Okay I answered my own question. Yes, both tf.nn.atrous_conv2d and tf.nn.convolution produce the same output dimensions with the SAME flag. I was mixing up the effect of filter size on output dimension, sorry about that.
I made this test and ran it on tf 1.0 which does confirm the original issue:
import numpy as np

input_img_np = np.random.random((1, 256, 256, 1)).astype(np.float32)
kernel =  np.random.random((6,6,1,1)).astype(np.float32)

with tf.Session() as sess:
    concrete_input_op = tf.constant(input_img_np)
    concrete_output_op = tf.nn.convolution(concrete_input_op, kernel, padding='SAME', dilation_rate=np.array([2, 2]))
    concrete_output = sess.run(concrete_output_op)

    print('convolution + CONCRETE + SAME')
    print('concrete_input_op: ', concrete_input_op.get_shape())
    print('concrete_output_op: ', concrete_output_op.get_shape())
    print('concrete_output:', concrete_output.shape)
    assert(concrete_input_op.get_shape() == concrete_output_op.get_shape())

    undef_input_op = tf.placeholder(tf.float32, shape=(None, 256, 256, 1))
    undef_output_op = tf.nn.convolution(undef_input_op, kernel, padding='SAME', dilation_rate=np.array([2, 2]))
    undef_output = sess.run(undef_output_op, feed_dict={undef_input_op: input_img_np})

    print('convolution + UNDEF + SAME')
    print('undef_input_op: ', undef_input_op.get_shape())
    print('undef_output_op: ', undef_output_op.get_shape())
    print('undef_output:', undef_output.shape)
    # This assert will correctly fail even though the shapes are ok because shapes are only partially known
    # assert(undef_input_op.get_shape() == undef_output_op.get_shape())

    valid_concrete_input_op = tf.constant(input_img_np)
    valid_concrete_output_op = tf.nn.convolution(valid_concrete_input_op, kernel, padding='VALID', dilation_rate=np.array([2, 2]))
    valid_concrete_output = sess.run(valid_concrete_output_op)

    print('convolution + CONCRETE + VALID')
    print('valid_concrete_input_op: ', valid_concrete_input_op.get_shape())
    print('valid_concrete_output_op: ', valid_concrete_output_op.get_shape())
    print('valid_concrete_output:', valid_concrete_output.shape)

    valid_undef_input_op = tf.placeholder(tf.float32, shape=(None, 256, 256, 1))
    valid_undef_output_op = tf.nn.convolution(valid_undef_input_op, kernel, padding='VALID', dilation_rate=np.array([2, 2]))
    valid_undef_output = sess.run(valid_undef_output_op, feed_dict={valid_undef_input_op: input_img_np})

    print('convolution + UNDEF + VALID')
    print('valid_undef_input_op: ',  valid_undef_input_op.get_shape())
    print('valid_undef_output_op: ', valid_undef_output_op.get_shape())
    print('valid_undef_output:', valid_undef_output.shape)
    # This assert will correctly fail even though the shapes are ok because shapes are only partially known
    # assert(undef_input_op.get_shape() == undef_output_op.get_shape())
    ############################################################################
    # Now atrous
    concrete_input_op = tf.constant(input_img_np)
    concrete_output_op = tf.nn.atrous_conv2d(concrete_input_op, kernel, padding='SAME', rate=2)
    concrete_output = sess.run(concrete_output_op)

    print('atrous_conv2d + CONCRETE + SAME')
    print('concrete_input_op: ', concrete_input_op.get_shape())
    print('concrete_output_op: ', concrete_output_op.get_shape())
    print('concrete_output_op: ', concrete_output_op.get_shape())
    print('concrete_output:', concrete_output.shape)
    assert(concrete_input_op.get_shape() == concrete_output_op.get_shape())

    undef_input_op = tf.placeholder(tf.float32, shape=(None, 256, 256, 1))
    undef_output_op = tf.nn.atrous_conv2d(undef_input_op, kernel, padding='SAME', rate=2)
    undef_output = sess.run(undef_output_op, feed_dict={undef_input_op: input_img_np})

    print('atrous_conv2d + UNDEF + SAME')
    print('undef_input_op: ', undef_input_op.get_shape())
    print('undef_output_op: ', undef_output_op.get_shape())
    print('undef_output:', undef_output.shape)
    # This assert will correctly fail even though the shapes are ok because shapes are only partially known
    # assert(undef_input_op.get_shape() == undef_output_op.get_shape())

    valid_concrete_input_op = tf.constant(input_img_np)
    valid_concrete_output_op = tf.nn.atrous_conv2d(valid_concrete_input_op, kernel, padding='VALID', rate=2)
    valid_concrete_output = sess.run(valid_concrete_output_op)

    print('atrous_conv2d + CONCRETE + VALID')
    print('valid_concrete_input_op: ', valid_concrete_input_op.get_shape())
    print('valid_concrete_output_op: ', valid_concrete_output_op.get_shape())
    print('valid_concrete_output:', valid_concrete_output.shape)

    valid_undef_input_op = tf.placeholder(tf.float32, shape=(None, 256, 256, 1))
    valid_undef_output_op = tf.nn.atrous_conv2d(valid_undef_input_op, kernel, padding='VALID', rate=2)
    valid_undef_output = sess.run(valid_undef_output_op, feed_dict={valid_undef_input_op: input_img_np})

    print('atrous_conv2d + UNDEF + VALID')
    print('valid_undef_input_op: ',  valid_undef_input_op.get_shape())
    print('valid_undef_output_op: ', valid_undef_output_op.get_shape())
    print('valid_undef_output:', valid_undef_output.shape)
    # This assert will correctly fail even though the shapes are ok because shapes are only partially known
    # assert(undef_input_op.get_shape() == undef_output_op.get_shape())

Which produces this output:
convolution + CONCRETE + SAME
('concrete_input_op: ', TensorShape([Dimension(1), Dimension(256), Dimension(256), Dimension(1)]))
('concrete_output_op: ', TensorShape([Dimension(1), Dimension(256), Dimension(256), Dimension(1)]))
('concrete_output:', (1, 256, 256, 1))
convolution + UNDEF + SAME
('undef_input_op: ', TensorShape([Dimension(None), Dimension(256), Dimension(256), Dimension(1)]))
('undef_output_op: ', TensorShape([Dimension(None), Dimension(256), Dimension(256), Dimension(1)]))
('undef_output:', (1, 256, 256, 1))
convolution + CONCRETE + VALID
('valid_concrete_input_op: ', TensorShape([Dimension(1), Dimension(256), Dimension(256), Dimension(1)]))
('valid_concrete_output_op: ', TensorShape([Dimension(1), Dimension(246), Dimension(246), Dimension(1)]))
('valid_concrete_output:', (1, 246, 246, 1))
convolution + UNDEF + VALID
('valid_undef_input_op: ', TensorShape([Dimension(None), Dimension(256), Dimension(256), Dimension(1)]))
('valid_undef_output_op: ', TensorShape([Dimension(None), Dimension(246), Dimension(246), Dimension(1)]))
('valid_undef_output:', (1, 246, 246, 1))
atrous_conv2d + CONCRETE + SAME
('concrete_input_op: ', TensorShape([Dimension(1), Dimension(256), Dimension(256), Dimension(1)]))
('concrete_output_op: ', TensorShape([Dimension(1), Dimension(256), Dimension(256), Dimension(1)]))
('concrete_output_op: ', TensorShape([Dimension(1), Dimension(256), Dimension(256), Dimension(1)]))
('concrete_output:', (1, 256, 256, 1))
atrous_conv2d + UNDEF + SAME
('undef_input_op: ', TensorShape([Dimension(None), Dimension(256), Dimension(256), Dimension(1)]))
('undef_output_op: ', TensorShape([Dimension(None), Dimension(None), Dimension(None), Dimension(1)]))
('undef_output:', (1, 256, 256, 1))
atrous_conv2d + CONCRETE + VALID
('valid_concrete_input_op: ', TensorShape([Dimension(1), Dimension(256), Dimension(256), Dimension(1)]))
('valid_concrete_output_op: ', TensorShape([Dimension(1), Dimension(246), Dimension(246), Dimension(1)]))
('valid_concrete_output:', (1, 246, 246, 1))
atrous_conv2d + UNDEF + VALID
('valid_undef_input_op: ', TensorShape([Dimension(None), Dimension(256), Dimension(256), Dimension(1)]))
('valid_undef_output_op: ', TensorShape([Dimension(None), Dimension(None), Dimension(None), Dimension(1)]))
('valid_undef_output:', (1, 246, 246, 1))

@ahundt , in TF atrous and dilated convolution mean the same thing. One of the parameters that they accept is rate which specifies the dilation rate. Definition of rate is consistent in the Deep Lab paper and the paper that you have cited. I think the confusion with the naming is similar to the case with deconvolution which a lot of people use to mean that they perform fractionally strided convolution, while deconvolution at the same time refers to a completely different operation in Signal Processing field.
There are different ways to implement dilated convolution. TF has it implemented by sampling the input feature map which is described in the Deep Lab paper. The piece of code that you refer to actually uses this implementation under the hood.
At the same time, dilated convolution is itself an ordinary convolution -- meaning that if you apply it with the same padding, it should produce the output with the same spatial dimensions.
In case of Image Segmentation, dilated convolution is used to make it possible to use weights
from Image Classification networks after reducing their in-network downsampling (by means of removing layers responsible for downsampling or setting their stride to 1). All of this allows to acquire the prediction map that is downsampled by a smaller factor (most Image Classification models have a downsampling factor of 32 --  for example, it can be reduced to 8 by following the approach described in these papers). After that, you can use bilinear upsampling or learn the upsampling kernel yourself during training to get the prediction map of the same size as the input image. You can find an example of adopting Resnet-101 for Image Segmentation by employing the aforementioned approach here.

@warmspringwinds Thanks! Got it now.
All, sorry I ended up hijacking the issue due to the mismatch between my mental model and the design. At least a test script came from it and I learned something, thanks for the clarifications. :-)

@ahundt The precise definition of with_space_to_batch is given in the docstring.  However, the actual output dimensions depend entirely on the behavior of the underlying op that is passed as an argument.  I don't think it is possible to specify the output dimensions in a particularly concise way.  It isn't intended to be used directly normally, but rather is intended to be used to define new dilated operations.

#8411 doesn't actually fix this issue --- it just adds some documentation, but does not actually improve the static tensor shape information, which is what this issue is about.

Sorry about that.

Sorry, that was actually my fault! I meant to write that it resolves a point of confusion discussed in this issue.

No, it's my fault, I did edit your description to make the PR close this issue. That was a little optimistic.

Aha didn't realize that, well at least things are set correctly now.

This seems to be fixed in at least tensorflow version 1.1.0-rc2!

It has been 14 days with no activity and this issue has an assignee.Please update the label and/or status accordingly.

Closing since this seems obsolete, but please reopen if it needs attention.


GRU of PyDirectML throw error use the parameters of the ONNX example are used.

I wrote a simple example of using GRU operator:
import pydirectml as dml
import numpy as np

steps = 2
batchSize = 3
inputSize = 3
hiddenSize = 5
numDirections = 1

input_bindings = []

def append_input_tensor(builder: dml.GraphBuilder, input_bindings: list, input_tensor: dml.TensorDesc):
    tensor = dml.input_tensor(builder, len(input_bindings), input_tensor)
    input_bindings.append(dml.Binding(tensor, np.zeros(tensor.get_output_desc().sizes)))
    return tensor

# Create a GPU device, and build a model graph.
device = dml.Device(True, True)
builder = dml.GraphBuilder(device)
data_type = dml.TensorDataType.FLOAT32
flags = dml.TensorFlags.OWNED_BY_DML

input_data = [1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18]
input_array = np.array(input_data, np.float32)
input = dml.input_tensor(builder, 0, dml.TensorDesc(data_type, [1, steps, batchSize, inputSize]))
input_bindings.append(dml.Binding(input, input_array))
weight = append_input_tensor(builder, input_bindings, dml.TensorDesc(data_type, flags, [1, numDirections, 3 * hiddenSize, inputSize]))
recurrentWeight = append_input_tensor(builder, input_bindings, dml.TensorDesc(data_type, flags, [1, numDirections, 3 * hiddenSize, hiddenSize]))

gru = dml.gru(
  input = input,
  weight = weight,
  recurrence = recurrentWeight,
  activation_descs = [dml.FusedActivation(dml.OperatorType.ACTIVATION_SIGMOID), dml.FusedActivation(dml.OperatorType.ACTIVATION_SIGMOID)],
  direction = dml.RecurrentNetworkDirection.FORWARD,
  output_options = dml.OutputOptions.Single
)

# Compile the expression graph into a compiled operator
op = builder.build(dml.ExecutionFlags.NONE, [gru])

# Compute the result
output_data = device.compute(op, input_bindings, [gru])
output_tensor = np.array(output_data[0], np.float32)

print(output_tensor)

But it will throw the following error:
Traceback (most recent call last):
  File ".\Python\samples\gru.py", line 36, in <module>
    output_options = dml.OutputOptions.Single
RuntimeError: m_device->CreateOperator(&opDesc, IID_PPV_ARGS(&op))

Is there a problem with the example I wrote? BTW, are there any sample code for GRU usage?

@miaobin, did you happen to try DirectML debug layer and find more details?

@miaobin Did the debug layer enlighten?

@miaobin Did the debug layer enlighten?

Yes, with debugging tools we found two issues. We found a bug about creating the inputs of Gru. I submitted a PR to fix this and it has been merged. In addition, we note that DML_TENSOR_FLAGS of all structure DML_GRU_OPERATOR_DESC members must be set to DML_TENSOR_FLAG_NONE.
I thank this issue can be closed. Thanks a lot!

Aah, the issue was in the helper file DirectMLX.h. Thanks for contributing. Closing.


Could not connect to the Query Engine due to OSError [Errno 99]

Bug description

A user has encountered this error:
OSError: [Errno 99] Cannot assign requested address
  File "httpcore/_exceptions.py", line 10, in map_exceptions
    yield
  File "httpcore/backends/sync.py", line 94, in connect_tcp
    sock = socket.create_connection(
  File "socket.py", line 844, in create_connection
    raise err
  File "socket.py", line 832, in create_connection
    sock.connect(sa)

How to reproduce

Not currently reproducible. Theorised cause is a race condition between us picking a port to use & the query engine actually using it.
Expected behavior

This should not crash.

For me this happens only inside docker on a mac m2 chip.
And happens in combination with a segmentation fault in the prisma binary
So I suspect it has nothing to do with prisma python but the actual prisma binary itself and is related to https://github.com/prisma/prisma/issues/18510
This it would automatically solve once the prisma binary is upgraded here too

Can confirm it gets fixed if I set the following environment variables
PRISMA_VERSION=5.3.0-integration-arm-openssl-5-2-0.1
PRISMA_PY_DEBUG_GENERATOR=1


[lint] Unused var and import error

Fix an unused variable in actions/config
Disable the import error in utils, since that directory isn't really a package, but instead catalog_collections is just a script that gets run, so a full or relative import couldn't be used in this case.

recheck

recheck


Possible typo in kernels.py:sum_reduction function

https://github.com/soda-inria/sklearn-numba-dpex/blob/main/sklearn_numba_dpex/common/kernels.py#L221-L225
The function reads
def sum_reduction(summands):
    for kernel, result in kernels_and_empty_tensors_pairs:
        kernel(summands, result)
        summands = result
    return result

The returned variable result is outside of its scope of definition (local variable defined in the scope of the loop).
I believe the last line should be return summands instead.

I can change this in a PR if it's more readable, but in fact in python the scope of the variables defined in a loop is the same scope that other local variables.
e.g you can do
for i in range(10):
    pass
print(i)

output will be 9.
BTW we just merged unit tests for the reduction kernels and added a reduction for 2d tensors on axis 1 :grin:
(See https://github.com/soda-inria/sklearn-numba-dpex/pull/46 for some thinking on using custom kernels vs dpnp functions)

Thanks for highlighting #46 !
I think return summands would read better indeed, but its just a suggestion.


Form component - Backend validation

Good work on the form component.
I've tested it, but it's hard to use with a Laravel Precognition-type backend or normal backend validation.
I suggest two improvements:

the validation should be called with a second parameter, the name of the field that triggered the validation (validate(state, trigger)), so that we can validate only the field that the user actually touched.
Secondly, we should be able to give the list of error list directly in props. Some checks can only be made once the form has been submitted. It might be useful to be able to display errors afterwards.

Maybe somthing like this very dirty example:
let errors = [];
let response = ref<Todo|null>(null);
async function validate(state, trigger) {
    if (! trigger) {
        try {
            errors = [];
            response.value = await $fetch(
                '/api/todo',
                {
                    method: 'POST',
                    body: state.value
                })
        } catch (e) {
            response.value = null;

            if (e.response.status === 422) {
                errors = e.response.data.errors.map((errors, path) => ({
                    path,
                    message: errors[0],
                }));
            }
        }

        return errors;
    }

    try {
        errors = errors
            .filter(error => error.path !== trigger);

        const response = await $fetch(
            '/api/todo',
            {
                method: 'POST',
                body: {
                    [trigger]: state.value[trigger]
                },
                headers: {
                    'Precognition': 'true',
                    'Precognition-Validate-Only': trigger,
                }
            })
    } catch (e) {
        if (e.response.status === 422 && e.response.data?.errors?.[trigger]) {
            errors.push({
                path: trigger,
                message: e.response.data.errors[trigger][0],
            });
        }
    }

    return errors;
}

Can you try something like this?
<script setup lang="ts">
import useVuelidate from "@vuelidate/core";

const formRef = ref();
const f = useForm("post", "/users", {
  name: "",
  email: "",
});

async function validateWithPrecognition() {
  f.touch();
  await f.validate();
  return v.errors().entries().map((error) => ({
    message: error[1],
    path: error[0],
  }));
}

defineExpose({
  validate: async () => {
    await form.value.validate();
  },
});
</script>

<template>
  <UForm
    ref="formRef"
    :model="form.data()"
    :validate="validateWithPrecognition"
  >
    <slot />
  </UForm>
</template>

I checked this: https://github.com/laravel/precognition/blob/main/packages/vue/src/index.ts#L108
It looks like you can trigger validation without directly calling your endpoint

No you can't,
The precognition is a backend part of Laravel partial validation mecanism.
The Laravel packages are used to be implemented directly in vue and use axios for handling requests.
So I always self implements the Vue/Js part of Precognition.
The example you provide use frontend validation and not the precognition one.

I think per field validation and backend validations are two subject that require individual request


AggregateError - Adapter don't start

The Adapter Version 0.1.7 don't start
i have a new ebike and i try to install the Adapter
but in the log i found AggregateError.
2024-09-13 21:53:33.963  - info: bosch-ebike.0 (207636) Login to eBike flow
2024-09-13 21:53:34.077  - silly: bosch-ebike.0 (207636) States system redis pmessage io.system.adapter.bosch-ebike.0.logLevel/io.system.adapter.bosch-ebike.0.logLevel:{"val":"silly","ack":true,"ts":1726264414064,"q":0,"from":"system.adapter.bosch-ebike.0","lc":1726252703979}
2024-09-13 21:53:34.083  - silly: bosch-ebike.0 (207636) States user redis pmessage io.bosch-ebike.0.*/io.bosch-ebike.0.info.connection:{"val":false,"ack":true,"ts":1726264414080,"q":0,"from":"system.adapter.bosch-ebike.0","user":"system.user.admin","lc":1726252565892}
2024-09-13 21:53:34.319  - error: bosch-ebike.0 (207636) AggregateError
2024-09-13 21:53:34.320  - error: bosch-ebike.0 (207636) Could not extract form data
Whre to search for an solution=

auch nach dem Update auf Version 0.1.9 bekomme ich weiter den "AggregateError".
Es ist also kein LogIn möglich :(

Yes - i can open the site.
first try to login don't work. the second try works.
now the adapter also go to green and i see "trips"

no error - just a second login was required.
now it looks good.


selecting tab programatically not align correctly

Programatically selecting a tab does not move/push other tabs as it does when when we select the tab normally.
bottomBar.selectTabAtPosition(position, true);
I am using 3 tabs
' bottomBar.setMaxFixedTabs(2);

With the newest version, this is fixed.


please add cookie handling to readme

i want to know how to create a cookie jar as well as parse the cookie jar manually.
edit: and also add custom cookie to the request object.

Hi @chovy the second half of Request's examples section explains the use of the jar option quite well.
Did you open this issue to ask this for your own purposes or do you believe that this is very important and should be added to the Request-Promise README as well?

I would at least add a section pointing to the request docs in the request-promise readme.md

Hi @chovy we are currently working on a brand new Request/Request-Promise documentation. I will make sure to include the cookie handling.

thanks.

+1
I would really like to see how to use cookies and cookie jars on the request-promise README.md

Hey everyone, I just added an example to the README. Please make sure to use<EMAIL_ADDRESS>or higher for this to work. Version 4.2.1 includes a bug fix that made using tough-cookie possible.


fix: the callback of scrollToItem is called twice

fix: the callback of scrollToItem is called twice

Pull Request Test Coverage Report for Build 903083007

0 of 1 (0.0%)  changed or added relevant line in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.01%) to 2.064%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

src/useVirtual.ts
0
1
0.0%

Totals

Change from base Build 902965074:
-0.01%

Covered Lines:
7

Relevant Lines:
262

💛  - Coveralls


Setup instructions

Firstly thanks for this wonderfull upload.
I want to tell about something instructions in "Using jQuery File Upload (UI version) on websites without PHP" section.
I understand everything in this section. It's realy helpfull.
You give an example JSON output.
"Extend your custom server-side upload handler to return a JSON response akin to the following output"
But if ,  there is a error for uploading file, what should we use for JSON.
I need examples for errors.

I understand now how to manage with errors in this program...
But this kind of errors are client-based.
How we can managed the serve-side errors with JSON methot.

I understand now, how to manage the errors in this program.
But this kind of errors are client-based.
Maybe can add an option for server-side with JSON methot

You can find a server-side example here:
https://github.com/blueimp/jQuery-File-Upload/blob/master/example/upload.php#L138

that url doesn't work, there is no example/upload.php   not in the zip or on the tree of source files

https://github.com/blueimp/jQuery-File-Upload/blob/master/php/index.php#L149


feat: add event url and animation to event card

Overview of Changes:

Made the entire event card clickable for better navigation.
Verified that the "Read More/Show Less" functionality inside the card operates as intended.
Added a subtle scale-up animation effect to the card on hover.
Converted the "Register Now" and "Read More/Show Less" links to buttons for improved accessibility.

This PR fixes issue #56.
Video Preview: https://github.com/user-attachments/assets/388159ba-baee-48b3-9213-a96ac9116693

I've made the necessary changes to separate the link for the event card and the Register Now button.


WooCommerce product_attribute shortcode does not return results in other languages

Can you reproduce this issue on default Wordpress theme (eg Storefront)?
yes
Can you reproduce this issue when all other plugins are disabled except WooCommerce, Polylang and Hyyan WooCommerce Polylang Integration?
yes
What product versions and settings are you using when this issue occurs?

PHP: 7.0
WordPress: 4.8
WooCommerce: 3.1
Polylang:
Hyyan WooCommerce Polylang Integration: 1.0.2
Browser: any

Steps to Reproduce

use shortcode on post in main language:
[product_attribute attribute='color' filter='rec']
verify works fine in main language
translate post and attempt translated version of shortcode

What I Expected
expected translated results
What Happened Instead
empty - no results

actually this works, just have to take care to use the correct slug for both the attribute name and the term.


Use // => format more consistently in @examples

          I like `// =>` here, should we use it elsewhere?

Originally posted by @rmjohnson in https://github.com/taylorn16/fp-toolkit/pull/20#discussion_r1134626795

Opened #26 to address this.

#26 has been merged, closing this. 😎


Bring back "Guidelines for Contributing"

https://github.com/plone/volto/pull/3643#issuecomment-1248461207

We now have a Plone GitHub organization CONTRIBUTING.md. When a repo, including Volto, lacks a CONTRIBUTING.md file in its repo, then this will be displayed. Clearly this is not what we want.
I would suggest that we add a CONTRIBUTING.md file at the root of this repo, that contains only the following:
# Contributing to Volto

See [Contributing to Volto](https://6.dev-docs.plone.org/volto/developer-guidelines/contributing.html).

More information about GitHub Community Health Files, specifically About contributing guidelines.

Thanks!


python3Packages.jaxlib build failure on x86_64-linux as of b4fadf79

Issue description
Build of python3Packages.jaxlib failed on x86_64-linux as of b4fadf797d70840444299ea99c01c453ded4dcfb. This is currently breaking python39Packages.tensorflow-datasets.
error: builder for '/nix/store/xnc90lyi30bi4lzwkcrprzfqpd2q9252-bazel-build-jaxlib-0.3.22.drv' failed with exit code 1;
       last 8 log lines:
       > unpacking sources
       > unpacking source archive /nix/store/0sd34630xb88aca480v5wr8920s5pgnc-source
       > source root is source
       > patching sources
       > configuring
       > fixed output derivation was built for a different bazel version
       >      got: bazel-5.2.0
       > expected: bazel-5.3.2
       For full logs, run 'nix log /nix/store/xnc90lyi30bi4lzwkcrprzfqpd2q9252-bazel-build-jaxlib-0.3.22.drv'.
error: 1 dependencies of derivation '/nix/store/xl46cj99w4pdi6pvph4cg35v1dy5qrgy-python3.9-jaxlib-0.3.22.drv' failed to build
error: 1 dependencies of derivation '/nix/store/rfrz08jxr32w2qpcdpcvd3cajkjvskq7-python3.9-tensorflow-datasets-4.6.0.drv' failed to build

full build log
python39Packages.tensorflow-datasets maintainers cc: @ndl
python3Packages.jaxlib maintainers cc: @ndl
Other cc: n/a
Steps to reproduce

Checkout nixpkgs at commit b4fadf797d70840444299ea99c01c453ded4dcfb
Run nix-build -A python3Packages.jaxlib

Technical details
 - system: `"x86_64-linux"`
 - host os: `Linux 5.15.0-1022-azure, Ubuntu, 20.04.5 LTS (Focal Fossa), nobuild`
 - multi-user?: `yes`
 - sandbox: `yes`
 - version: `nix-env (Nix) 2.11.1`
 - nixpkgs: `/nix/store/qv9zbzkv9b989hfrbdzakqvzfhx4wkqz-source`

Misc.
This issue was automatically generated by nixpkgs-upkeep.

CI workflow that created this issue.
Internal tags: -3117183546679509583<PHONE_NUMBER>934102299

should be fixed by https://github.com/NixOS/nixpkgs/pull/198016 (kudos to @uri-canva!)


kubevirt v1.1 Cannot use hostdisk

What happened:
During the process of creating VMI again, use hostdisk and prompt to enable hostdisk

Searching for information indicates that the configmap needs to be modified to enable hostdisk, but the kubevirt 1.1 version does not have the kubevirt config configmap

Please refer to the user guide: https://kubevirt.io/user-guide/operations/activating_feature_gates/
You can activate the feature gate by doing:
$ kubectl edit kubevirt kubevirt -n kubevirt
    ...
    spec:
      configuration:
        developerConfiguration:
          featureGates:
            - HostDisk

Please refer to the user guide: https://kubevirt.io/user-guide/operations/activating_feature_gates/ You can activate the feature gate by doing:
$ kubectl edit kubevirt kubevirt -n kubevirt
    ...
    spec:
      configuration:
        developerConfiguration:
          featureGates:
            - HostDisk

Thank you for your answer


"Send Max" button does not work when going from OP -> any other chain due to OP gas estimation

The "send max" button does not work when sending from OP now that their regenesis has been completed. This is because we do not account for the L1 tx fee that is charged alongside the L2 tx fee.
We handled it in the bonder with #287, however it is unhandled in this case (and potentially any other input field that allows for sending ETH out of Optimism).
The error received is as follows:

Closed with a217618cdc6c26bd9b1b32f61b2be2d36642c0a3


Remove erroneous MonadRace references

It looks like the README hadn't been updated to reflect the changes introduced in purescript/purescript-parallel#10. I've just done a quick pass to remove references to MonadRace and race, and change     the reference from par to parallel.

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Very probably obsoleted by the rewrite, closing.


Line graph: Multiple data points at same X

My graph's X axis corresponds to a date and shows deposit events.  For accuracy the back end sends this data such that multiple events can happen on one day, to indicate that a deposit happened on that day.  For example there could be two entries for 1/3/2023, one with $1000 when the day stated, and one with $1500 following a deposit event later that day.

Vico seems to be placing subsequent entries further along the X axis, even if I have the same X value in each entry.  Note the slanted increases rather than them being vertical.  Is there a way to achieve this?  This behaviour is a biz and design requirement so I can't deviate from it - but I'd like to move on from MPAndroidCharts!

Hello @TomBell-Trove,
Can you confirm that you're using a DefaultPointConnector with cubicStrength equal to 0, and that x-axis Float values are exactly the same?

Hello! As such, it’s impossible for a line chart to have two points with the same x coordinate in a single data set, but I believe you can achieve the desired effect by creating a custom LineChart.LineSpec.PointConnector. You’d need to use lineTo twice, once for the horizontal line segment, and once for the vertical one.

Hello! Initializing DefaultPointConnector with cubicStrength equal to zero and giving the points that are to be displayed on top of one another identical x values, as @Gowsky has mentioned, produces the following result.

With that said, my suggestion for creating stepped line charts is to write a custom LineChart.LineSpec.PointConnector implementation that connects points by drawing two line segments: a horizontal one and a vertical one. This way, the ChartEntryModel doesn’t have to be adapted.

Thank you both.  I was using a simple path.lineTo() connector and will investigate further <3

You’re welcome!


[feat]: Add new variant to toast component

Feature description
The toast component has 2 variants: "default" and "destructive".
I would like to a new variant: "success", as it would be the most common variant to use with toast.
Affected component/components
Toast
Additional Context
No response
Before submitting

[X] I've made research efforts and searched the documentation
[X] I've searched for existing issues and PRs

Have you tried the Sonner component? Why are you using Toast over Sonner? Just curious.


Bump v0.1.1

Checklist

[x] Used a personal fork of the feedstock to propose changes
[x] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender


Two Pointers: Merge Sorted Array in Python

https://leetcode.com/problems/merge-sorted-array/

hi,
I like to be assigned for solving questions would you tell me what I should do ( i just should write the code?)

hi, I like to be assigned for solving questions would you tell me what I should do ( i just should write the code?)

Add code, and description and some comments how the code works, that should be fine

Hi, is this inactive or open to contribute to?

Hi, is this inactive or open to contribute to?

Open


Include 5169 diagram

Included 5169 Token Diagram.
Once reviewed - one more step will be added prior to merging to pull this image from the 'main' branch repo rather than this branch.


fix(relays): Prevening connection to non-circuit-relays

:tada: This PR is included in version 6.6.4 :tada:
The release is available on npm package (@latest dist-tag)
Your semantic-release bot :package::rocket:


Copy Endpoints Ruby Echo sample to a new location and make it generic.

We plan on cleaning up our docs for the various platforms and share this
sample throughout the various quickstart guides.
It no longer makes sense to have this under appgengine/flexible. Instead
it will live under endpoints/getting-started.
This also introduces how to deploy this sample using
GAE/GKE/GCE/GCE+Docker.

Looks great! 👍
Would you like to also git rm -r appengine/endpoints as part of this PR?
I'd like to see appengine/endpoints deleted along with this.  Especially as this feels like it's essentialls mv appengine/endpoints appengine/getting-started so additional, non-Flex samples can be supported 😄

@remi The docs still point to appengine/endpoints. We plan delete that when the docs are updated (soon)

@wmwong can you add region tags like this: https://github.com/GoogleCloudPlatform/python-docs-samples/commit/07dc91995f7065abb88fc1a92a531bbc9e44e184

@wmwong Docker image pushed, I needed to tweak the Dockerfile for it to listen on all addresses. I went ahead and pushed the changes to this branch.
@remi ready to merge.


libKiSAO wrapping

= Description =

Wrap libKiSAO (originally written for Java only) in order to make it available to Python programs. JCC is currently being tested in this regard - without success so far.

= Context =

KiSAO is an ontology of kinetic simulation algorithms; it is used for describing simulation algorithm in SED-ML. The BioPreDyn software suite should therefore be capable of reading this type of annotations.

= Success criteria =

libKiSAO API is callable from Python.

= Expected issues =

Wrapping tools are not exactly easy to understand / handle; that is an issue per se.

Imported from trac issue 11.  Created by bmoreau on 2013-10-03T11:45:23, last modified: 2015-01-19T11:52:31


X509V3_get_d2i.pod: Fix glitch on X509V3_get_ext_d2i vs. X509V3_get_d2i

Also align the order of the functions in the various sections.
Should this be backported?

[x] documentation is added or updated

Should this be backported?

I think why not.

Approved.

Thanks for the quick approvals.

You could consider, if you're already touching the file, using I<> for arguments and removing B around NULL. (in a separate commit)

Good point, done.

This pull request is ready to merge

Merged and backported to 3.0 - thanks @t8m and @mattcaswell.

I just found that backporting to 1.1.1 would require some conflict resolution, thus likely an extra PR -
I am uncertain if it is worth doing so.

I am uncertain if it is worth doing so.

I do not think it is.

Closing this since it has been merged.


Adjustment to the Breadcrumb component.

Change the color of the arrows (neutral 5) and the behavior (when clicking on the previous page, the following pages disappear).

The behaviour should be on another issue because it's a lot more complex to be developed, we'll probably need to add a service to breadcrumbs.
This issue will only fix the arrow colors.


Project has no license

Please assign a license to the project; for more info see: https://help.github.com/en/articles/licensing-a-repository

Thanks for pointing this out! 👍  I added the Apache License 2.0


Takeoff class should not be a class

First of all, it is odd that the Takeoff class is a class, and having only one method seems even odd. It was made that way so we could access both the "MTOW" computed by the takeoff analysis and the "mass_dict" dictionary which logged time-dependent variables calculated along with the test, which could then be used to plot detailed takeoff data.
The idea is honorable, but it simply doesn't need to be made that way. Python allows the return of multiple variables as a tuple, and so this entire class could be a single method.

Adressed in 2.0


Upgraded marked and marked-terminal packages due to a security vulnerability

PR type ?
Package Update

Did you add tests for your changes?
N/A
If relevant, did you update the documentation?
N/A
Summary
marked 0.6.3 has security vulnerability.
Description: Affected versions of marked are vulnerable to Regular Expression Denial of Service (ReDoS). The _label subrule may significantly degrade parsing performance of malformed input.
Recommendation: Upgrade to version 0.7.0 or later.
Does this PR introduce a breaking change?
No

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.:x: altinokdarici sign nowYou have signed the CLA already but the status is still pending? Let us recheck it.


Sync eng/common directory with azure-sdk-tools repository

Sync eng/common directory with azure-sdk-tools repository

Merging this while test failures are being investigated.

/check-enforcer override


Added Instructions for Relay configuration, updated driver's readme.

relay-config.md added in core/relay.

Closing this PR, because of other commits. Will open another PR.


Carsh on my iPhone

I meet two crash messages when i use ASScreenRecorder
i can provide the messages
1 *** -[AVAssetWriterInputPixelBufferAdaptor appendPixelBuffer:withPresentationTime:] Must start a session (using -[AVAssetWriter startSessionAtSourceTime:) before appending pixel buffers (__35-[ASScreenRecorder writeVideoFrame]_block_invoke_2 + 132)
2*** -[AVAssetWriterInputPixelBufferAdaptor appendPixelBuffer:withPresentationTime:] Must start a session (using -[AVAssetWriter startSessionAtSourceTime:) before appending pixel buffers (_mh_execute_header + 300096)
3*** Collection <CALayerArray: 0x1d48424c0> was mutated while being enumerated. (__35-[ASScreenRecorder writeVideoFrame]_block_invoke + 904)
4*** Collection <CALayerArray: 0x1d025e510> was mutated while being enumerated. (_mh_execute_header + 299708)
-------can you help me thks! @alskipp @jhefner

Have you figured out this problem? I also have this crash sometimes.


Please add TABLE and COLUMN comments to the new ViriHealth Canada table

Describe the bug
Similar to your fix for #158, the new ViriHealth Canada table VH_CAN_DETAILED is missing table and column comments.

To Reproduce
Steps to reproduce the behavior:
show tables;
desc table VH_CAN_DETAILED;

Expected behavior
Once this is populated, end users can see more detail about what each column does using native Snowflake functionality, and these fields are also used by some downstream solutions.
Additional context
Two of the BC records have a NULL Healthcare Region. Is this something that can be populated from the current source?
select * from VH_CAN_DETAILED
where HEALTHCARE_REGION is NULL;

Closing this down as we're losing Virihealth as a source. :(


ceph-ansible: failure in ceph-osd playbook

ceph-ansible failure after fixing the roles to include ceph-defaults and ceph-common [issue: 1737],
the failure now looks like below:
2017-08-08T22:05:52.560 INFO:teuthology.orchestra.run.mira023.stdout:TASK [ceph-osd : make sure an osd scenario was chosen] *************************
2017-08-08T22:05:52.560 INFO:teuthology.orchestra.run.mira023.stdout:task path: /home/ubuntu/ceph-ansible/roles/ceph-osd/tasks/check_mandatory_vars.yml:22
2017-08-08T22:05:52.606 INFO:teuthology.orchestra.run.mira023.stdout:fatal: [mira016.front.sepia.ceph.com]: FAILED! => {
2017-08-08T22:05:52.606 INFO:teuthology.orchestra.run.mira023.stdout:    "changed": false,
2017-08-08T22:05:52.606 INFO:teuthology.orchestra.run.mira023.stdout:    "failed": true
2017-08-08T22:05:52.606 INFO:teuthology.orchestra.run.mira023.stdout:}
2017-08-08T22:05:52.607 INFO:teuthology.orchestra.run.mira023.stdout:
2017-08-08T22:05:52.607 INFO:teuthology.orchestra.run.mira023.stdout:MSG:
2017-08-08T22:05:52.607 INFO:teuthology.orchestra.run.mira023.stdout:
2017-08-08T22:05:52.607 INFO:teuthology.orchestra.run.mira023.stdout:please choose an osd scenario
2017-08-08T22:05:52.615 INFO:teuthology.orchestra.run.mira023.stdout:fatal: [mira023.front.sepia.ceph.com]: FAILED! => {
2017-08-08T22:05:52.615 INFO:teuthology.orchestra.run.mira023.stdout:    "changed": false,
2017-08-08T22:05:52.615 INFO:teuthology.orchestra.run.mira023.stdout:    "failed": true
2017-08-08T22:05:52.615 INFO:teuthology.orchestra.run.mira023.stdout:}
2017-08-08T22:05:52.615 INFO:teuthology.orchestra.run.mira023.stdout:
2017-08-08T22:05:52.615 INFO:teuthology.orchestra.run.mira023.stdout:MSG:
2017-08-08T22:05:52.616 INFO:teuthology.orchestra.run.mira023.stdout:
2017-08-08T22:05:52.616 INFO:teuthology.orchestra.run.mira023.stdout:please choose an osd scenario
2017-08-08T22:05:52.623 INFO:teuthology.orchestra.run.mira023.stdout:fatal: [mira039.front.sepia.ceph.com]: FAILED! => {
2017-08-08T22:05:52.624 INFO:teuthology.orchestra.run.mira023.stdout:    "changed": false,
2017-08-08T22:05:52.624 INFO:teuthology.orchestra.run.mira023.stdout:    "failed": true

@tmuthamizhan, Sebastien pushed a commit to simplify the osd scenarios (see here)
you need to set osd_scenario either to collocated, non-collocated or lvm
depending on what you will choose for osd_scenario you will have to set others variable like: devices,dedicated_devices, etc.
each scenario is described in osds.yml.sample eg. here

would be great to update the wiki right ? https://github.com/ceph/ceph-ansible/wiki very frustrating having to be so involved to do a first instalation.
Still, the wiki just, talks about one branch witch you dont know if its master or what.

@acomisario sorry for the pain, these changes are pretty recent. But yes, I agree, the wiki needs to be updated.

Instead of updating the wiki, I think we ought to decommission the wiki and add new documentation to http://docs.ceph.com/ceph-ansible/master/

what about folks moving from jewel to new version and have journal_collocation: True ?

and I only discovered the wiki last week, after asking "where are the docs" for months.  Are any of the other Ceph tools documented only in a wiki?

what about folks moving from jewel to new version and have journal_collocation: True ?

Their configuration would need to change, journal collocation is still supported but the method of selecting it has changed. You now must set osd_scenario: collocated if you want OSDs with collocated journals instead of journal_collocation: True. This change was introduced in https://github.com/ceph/ceph-ansible/pull/1725 to make validation for user input easier to handle with ansible. Also, we hope that this method will be easier to understand.
I've started a PR here with documentation updates: https://github.com/ceph/ceph-ansible/pull/1772

Closed via #1772


Add documentation entry on general structure of package

The old general_demo.ipynb did a good job of laying out the pieces/core capabilities of the package. However, it ended up being deleted as:

It worked directly with models and solve_lmde, and this is now out of date since Solver was introduced.
It didn't really fit into any documentation category: it was a mix of tutorial/userguide/discussion.

I think though that we really need an updated version of this somewhere in the documentation. Probably either a User guide entry or a Discussion piece makes sense. I'm leaning towards "discussion" piece as I'm still conceptualizing "user guide" to be dedicated to more advanced/technical information about how to use the package in question/answer format, whereas this is more of a general description of how the package is organized.

Stale


The properties of User object are exchanged

Describe the bug
The properties of  User object are exchanged.
Are you using TwitchIO within a Discord Bot?
No
What commit of TwitchIO are you using?
Name: twitchio
Version: 1.2.2
Summary: A Python IRC and API wrapper for Twitch.
Home-page: https://github.com/TwitchIO/TwitchIO
Author: TwitchIO
Author-email: UNKNOWN
License: MIT
Location: ,venv\site-packages
Requires: aiohttp, async-timeout, websockets
Required-by:

To Reproduce
Just setup the client settings:
from twitchio import Client

client = Client(
    client_id="the client id",
    client_secret="client secret",
)

And call get_users inside any async function:
await client.get_users("gaules")

The return value is:

[User(id='181077473', login='gaules', display_name='Gaules', type='', broadcaster_type='partner', description='Mais um guerreiro da Maior Tribo do Mundo! Atuei como jogador profissional de CS por quase uma década, fui o primeiro treinador a ser campeão do mundo em 2007 com o MIBR. Acertei um pouco, errei muito, ganhei bastante coisa e tbm perdi demais! Atualmente faço live todos
os dias aqui na Twitch! ', profile_image=251644947, offline_image='2017-11-09T14:10:52.83257Z', view_count='https://static-cdn.jtvnw.net/jtv_user_pictures/5deb9374-f180-4ee0-8446-205cde623ec8-channel_offline_image-1920x1080.png', created_at='https://static-cdn.jtvnw.net/jtv_user_pictures/c495b77e-7f47-4bc5-a216-3045d7545796-profile_image-300x300.png', email=None)]

Problems:

profile_image  contains the value of view count;
view_count have the value of the offline image URL;
offline_image contains the value of the created_at;
created_at have the the profile image URL.

OS: win10 64
Python 3.9.1

'offline_image' field is also exchanged with the 'created_at' one ;)

Seeing the same:
Version 1.2.1 returns:
INFO:cogs.twitch:[User(id='15564828', login='nickmercs', display_name='NICKMERCS', type='', broadcaster_type='partner', description='Former MLG National Champion. A fellow gym rat, who streams mostly Competitive Shooters! Thank you all so much for your continued support. Follow the stream and my Twitter account to be notified when I will be going live - @Nickmercs ', profile_image='https://static-cdn.jtvnw.net/jtv_user_pictures/ff13760d-d795-49d9-8f3f-f05035930c81-profile_image-300x300.png', offline_image='https://static-cdn.jtvnw.net/jtv_user_pictures/de5ae820-2fe8-412d-9979-1e8777908d7e-channel_offline_image-1920x1080.png', view_count=164492687, created_at='2010-09-13T05:01:35.371022Z')]
Version 1.2.2 returns:
INFO:cogs.twitch:[User(id='15564828', login='nickmercs', display_name='NICKMERCS', type='', broadcaster_type='partner', description='Former MLG National Champion. A fellow gym rat, who streams mostly Competitive Shooters! Thank you all so much for your continued support. Follow the stream and my Twitter account to be notified when I will be going live - @Nickmercs ', profile_image=164492687, offline_image='2010-09-13T05:01:35.371022Z', view_count='https://static-cdn.jtvnw.net/jtv_user_pictures/de5ae820-2fe8-412d-9979-1e8777908d7e-channel_offline_image-1920x1080.png', created_at='https://static-cdn.jtvnw.net/jtv_user_pictures/ff13760d-d795-49d9-8f3f-f05035930c81-profile_image-300x300.png', email=None)]


SwipeRefreshLayout Can't use with RecyclerView

I use RecyclerView with SwipeRefreshLayout and get this exception:
java.lang.IllegalStateException: Currently, NOT already aligned RecyclerViewHeader can only be used for RecyclerView with a parent of one of types: LinearLayout, FrameLayout, RelativeLayout.

Unsupport for SwipeRefreshLayout?
source code:

    private void validateRecycler(RecyclerView recycler, boolean headerAlreadyAligned) {
        RecyclerView.LayoutManager layoutManager = recycler.getLayoutManager();
        if (layoutManager == null) {
            throw new IllegalStateException("Be sure to call RecyclerViewHeader constructor after setting your RecyclerView's LayoutManager.");
        } else if (layoutManager.getClass() != LinearLayoutManager.class    //not using instanceof on purpose
                && layoutManager.getClass() != GridLayoutManager.class
                && !(layoutManager instanceof StaggeredGridLayoutManager)) {
            throw new IllegalArgumentException("Currently RecyclerViewHeader supports only LinearLayoutManager, GridLayoutManager and StaggeredGridLayoutManager.");
        }

        if (layoutManager instanceof LinearLayoutManager) {
            if (((LinearLayoutManager) layoutManager).getOrientation() != LinearLayoutManager.VERTICAL) {
                throw new IllegalArgumentException("Currently RecyclerViewHeader supports only VERTICAL orientation LayoutManagers.");
            }
        } else if (layoutManager instanceof StaggeredGridLayoutManager) {
            if (((StaggeredGridLayoutManager) layoutManager).getOrientation() != StaggeredGridLayoutManager.VERTICAL) {
                throw new IllegalArgumentException("Currently RecyclerViewHeader supports only VERTICAL orientation StaggeredGridLayoutManagers.");
            }
        }

        if (!headerAlreadyAligned) {
            ViewParent parent = recycler.getParent();
            if (parent != null &&
                    !(parent instanceof LinearLayout) &&
                    !(parent instanceof FrameLayout) &&
                    !(parent instanceof RelativeLayout)) {
                throw new IllegalStateException("Currently, NOT already aligned RecyclerViewHeader " +
                        "can only be used for RecyclerView with a parent of one of types: LinearLayout, FrameLayout, RelativeLayout.");
            }
        }
    }

First of all, try exactly what the Exception suggests you to: try Header-already-aligned approach. And tell me if it solves your issue :smirk:

Did it solve your issue? Can I close it?

i just add the header myself.. because i use SwipeRefreshLayout to refresh the view..
In fact, i think most people use SwipeRefreshLayout to refresh they view, so will the SwipeRefreshLayout view to be supported further?

This works for me with Header-already-aligned approach
<android.support.v4.widget.SwipeRefreshLayout>

<android.support.v7.widget.RecyclerView/>
<com.bartoszlipinski.recyclerviewheader.RecyclerViewHeader/>

</android.support.v4.widget.SwipeRefreshLayout>

ok, can try the solution @Antpachon  supported. i close this issue.

@hwangjr, I told you to try **header-already-aligned" approach on the 29th of july. Shame you couldn't try that back then :(

@blipinsk , it's my fault.. i miss look the header-already-aligned on README.md and try to found it on branch, and then add header myself..
In fact, my header view has a little complex, like multiple focusable elements etc.. so finally i add a view type to RecyclerView.Adapter.
anyway, i will try it on my next integration, and add it  to my work board.

Good you went with the adapter with a header, that was probably the right decision (since you're sayin it was a relatively complicated header). Don't worry about this whole situation, I don't want you to feel obligated to use my library. I just shame that my post back then might have helped you, and you wouldn't have to worry to much about the issue. Nevermind :wink:

In fact, i am searching for some other solution about list view or recycle view ( include refresh and load more ), do u have some advise?
now i just write this wheel, but it's not stable, so i want to find a stable, extendable solution~~
other topic, do u have an app template for the rapid development?

What you need is SwipeRefreshLayout , this a guide to implement it
http://antonioleiva.com/swiperefreshlayout/
If you update to the latest version of Androdu Studio, you already have
some templates (Navigation Drawer..)
Cheers,
Antonio.
On 1 September 2015 at 13:35, HwangJR<EMAIL_ADDRESS>wrote:

In fact, i am searching for some other solution about list view or recycle
view ( include refresh and load more ), do u have some advise?
now i just write this wheel, but it's not stable, so i want to find a
stable, extendable solution~~
other topic, do u have an app template for the rapid development?
—
Reply to this email directly or view it on GitHub
https://github.com/blipinsk/RecyclerViewHeader/issues/19#issuecomment-136699261
.

--
Strictly private & confidential.Regards, Antonio.

While this might be a part of a valuable discussion it doesn't seem to be issue-related. Let me lock it, not to flood it with an off-topic. Thanks.


Filter null from list of tests to run

This PR adds applies a filter for null to the list of nodes to run a test for.
Rationale:
Clicking on "Run test" in the tree view calls a command that has a variadic arguments list.
In the current version of VS Code (1.37.1), this results in a list of size 1, containing exactly the test to execute.

In the insiders version (tested with 1.38.0-insider), however, this results in a list of size 2, where the second element is null. I tested this with two different test adapters (rust and catkin_tools), which behave the same:

This results in an aborted test execution in pickNodes(), because null cannot be mapped through
nodes.map(node => node.info.label);

Discussion
I could not find out if this is a bug in 1.38.0-insider or not. These changes are a workaround in case this will be the new behaviour.

Thanks!
I found out why this happens in 1.38-insiders: there is a new feature "Multi-select in custom tree view" - if you select multiple nodes in the tree and then click the run icon on one of them, the test-explorer.run command receives the clicked node in the first argument and all selected nodes in the second. So I made a different fix that is also a preparation for supporting this feature when it comes out (I can't support it properly now because the new API isn't published on npm yet).


Mnkellyk einvoice 10

Get all the packages worked out.

Closing this request and trying one more time.   Pytest results run through the work flow were not the same as mine.  Error indicates value returned needs to be a number, but it's already an int.


Existence of Database Documentation

Do you have any written or schematic documentation for the MySQL tables created and used by this app?
Thanks,
Bob

You can look at the sqlalchemy model of just run the DB init scripts and
then export the schema.
On Mon, Jan 16, 2017, 20:49 Bob Cochran<EMAIL_ADDRESS>wrote:

Do you have any written or schematic documentation for the MySQL tables
created and used by this app?
Thanks,
Bob
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/hozn/freezingsaddles/issues/21, or mute the thread
https://github.com/notifications/unsubscribe-auth/AAX7A4qoAduVXGGH52ww2x7tG2XZ2iv-ks5rTB4bgaJpZM4LlJMf
.

5.5, I believe. (Or whatever current stable release is these days.)


cache items not contain .git dir

I want using the plugin to cache git checkout speed, but I found it not store .git.
restore from cache object:

Thanks for bringing this up.
It seems that FilePath, which is used to create the tar archive, has default excludes (see https://ant.apache.org/manual/dirtasks.html#defaultexcludes) and .git is one of them. I'm not sure why, maybe because of sensitive data. We could disable the default excludes if the filter is set (e.g. **/*).

I'm still not sure about the final solution. Maybe it makes more sense to have includes and excludes as separate parameters and if excludes are not defined then the default excludes are used instead.
Any concerns/opinions?

@wuhuizuo It should be working now if you define a filter like **/*. BTW, what is your opinion about having includes and excludes as separate parameters?

I like it. glob may be high level, special file can exclude by excludes options. I think includes may be conflict with filter.
I suggest filter support array to contain more glob patterns.


Providing handlers for Data Persistence

Bot developers can connect to their favourite data stores now using this PR.

@kirsle @marceloverdijk any thoughts on this PR? Externalizing persistence is a good core feature.

@alecl do you think the proposed PersistenceHandler and PersistenceSessionManager  really adds benefits? It's merely another - but very similar - abstraction layer around the already existing SessionManager. I personally think the current SessionManager (http://static.javadoc.io/com.rivescript/rivescript-core/0.10.0/com/rivescript/session/SessionManager.html) offers enough flexibility already.
That being said I still think that a other out-of-the-box session manager as proposed in https://github.com/aichaos/rivescript-java/issues/35 should have value.
Personally I think you have to be careful using persistent session manager.
RiveScript tends to multiple calls to the session manager so if you are not careful it will mean multiple database calls within a single transaction to get a reply. I think @kirsle wrote an article about it in the past.
I tend to retrieve the user vars from my persistent store (e.g. memcache) and feed it to the RiveScript instance and then get the reply. After I get the reply I extract the user vars from the RiveScript instance, store them again in my persistent store and remove them from the RiveScript instance. The RiveScript instance itself uses the ConcurrentHashMapSessionManager.
For me that gives the best performance; but for other users a different approach might be more efficient.
Also providing a generic database session manager might not be suitable for many users. Think about supporting various database vendors, or even how to define the database schema.

It seemed like this PR was looking to come up with a tiered session storage abstraction with the "thaw" aspect. Maybe a write-through tiered cache is a more straightforward way to manage this though with Redis write-through to a relational db for safer longterm storage for example. Probably best to move further with #35 first to get some base implementations in.

@alecl Yes I think going further with #35 and deliver some base implementations is the way ahead. If we can provide some generic implementation I would be very happy. PR's are welcome :-)


Concatenating Strings with Plus Operator

Challenge Concatenating Strings with Plus Operator has an issue.
User Agent is: Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36.
Please describe how to reproduce this issue, and include links to screenshots if possible.
My code:

// Example
var ourStr = "I come first. " + "I come second.";

// Only change code below this line
var myStr;
myStr="This is the start " +"This is the end";

Can't pass this challenge, what's wrong with my code

sorry I have forgotton dots


Enable HTTPS for kubicorn.io once site is finished

We should enable for HTTPS for kubicorn.io. ~One way, and probably the most easiest way would be to use CloudFlare free tier, as GitHub Pages doesn't support SSL for custom domains.~
~There is a tutorial how it can be done https://blog.cloudflare.com/secure-and-fast-github-pages-with-cloudflare/~
GitHub Pages now supports out-of-box HTTPS. In order to enable it, we need to point our domain to IP addresses listed on this page. Then, we can just enable HTTPS from Settings page of the repository.

GitHub Pages now supports out-of-box HTTPS. In order to enable it, we need to point our domain to IP addresses listed on this page. Then, we can just enable HTTPS from Settings page of the repository.

I would like to help. where is the repo for the kubicorn.io?


ValueError: too many values to unpack (expected 2)

IMPORTANT: Please search the issues, including closed issues, and the FAQ before opening a new issue. The template is mandatory; failure to use it will result in issue closure.
Describe the bug

To Reproduce

Go to '...'
Click on '....'
Scroll down to '....'
See error

Expected behavior

Screenshots

System details

Home-assistant (version): 2023.5.2
alexa_media (version from const.py or HA startup): 4.6.3
alexapy (version from pip show alexapy or HA startup): 1.26.6
Amazon 2FA is enabled (y/n). <!---We will not debug login issues if unanswered--->:

Logs
Please provide logs.
2023-05-07 16:10:44.543 ERROR (MainThread) [homeassistant.config_entries] Error setting up entry<EMAIL_ADDRESS>- amazon.com for alexa_media
Traceback (most recent call last):
  File "/usr/src/homeassistant/homeassistant/config_entries.py", line 387, in async_setup
    result = await component.async_setup_entry(hass, self)
  File "/config/custom_components/alexa_media/__init__.py", line 326, in async_setup_entry
    await login.login(cookies=await login.load_cookie())
  File "/usr/local/lib/python3.10/site-packages/alexapy/alexalogin.py", line 347, in load_cookie
    return_cookies = self._get_cookies_from_session()
  File "/usr/local/lib/python3.10/site-packages/alexapy/alexalogin.py", line 554, in _get_cookies_from_session
    cookies = cookie_jar.filter_cookies(URL(f"https://{site}"))
  File "/usr/local/lib/python3.10/site-packages/aiohttp/cookiejar.py", line 239, in filter_cookies
    self._do_expiration()
  File "/usr/local/lib/python3.10/site-packages/aiohttp/cookiejar.py", line 150, in _do_expiration
    self.clear(lambda x: False)
  File "/usr/local/lib/python3.10/site-packages/aiohttp/cookiejar.py", line 115, in clear
    for (domain, path), cookie in self._cookies.items():
ValueError: too many values to unpack (expected 2)

Additional context
Workaround is to delete the pickle file at /config/.storage/alexa_media.[email].pickle and remove and readd the integration which will trigger a reuath. It looks like there may be some old data saved.

Came here to report this. So I'm having this same issue
+1

I get not enough values to unpack ... roll back to 4.6.2 works.
2023-05-08 00:54:32.277 ERROR (MainThread) [homeassistant.config_entries] Error setting up entry<EMAIL_ADDRESS>- amazon.com for alexa_media
Traceback (most recent call last):
  File "/usr/src/homeassistant/homeassistant/config_entries.py", line 387, in async_setup
    result = await component.async_setup_entry(hass, self)
  File "/config/custom_components/alexa_media/__init__.py", line 326, in async_setup_entry
    await login.login(cookies=await login.load_cookie())
  File "/config/deps/lib/python3.10/site-packages/alexapy/alexalogin.py", line 347, in load_cookie
    return_cookies = self._get_cookies_from_session()
  File "/config/deps/lib/python3.10/site-packages/alexapy/alexalogin.py", line 554, in _get_cookies_from_session
    cookies = cookie_jar.filter_cookies(URL(f"https://{site}"))
  File "/usr/local/lib/python3.10/site-packages/aiohttp/cookiejar.py", line 239, in filter_cookies
    self._do_expiration()
  File "/usr/local/lib/python3.10/site-packages/aiohttp/cookiejar.py", line 150, in _do_expiration
    self.clear(lambda x: False)
  File "/usr/local/lib/python3.10/site-packages/aiohttp/cookiejar.py", line 115, in clear
    for (domain, path), cookie in self._cookies.items():
ValueError: not enough values to unpack (expected 2, got 0)

Rolling back due to the above issue 👍🏽


snap no longer able to execute any binary commands

Running the snap on bionic or focal (haven't tried jammy yet) results in all subprocess.call failing e.g.
2023-03-12 13:41:20,265.265 4016561 DEBUG hotsos.client [-] <class 'subprocess.CalledProcessError'>: Command '['hostname']' died with <Signals.SIGSEGV: 11>.
And I also see this in dmesg:
[1031377.613736] hostname[4016792]: segfault at 7fff6d5a1ff8 ip 00007f9825f7aa43 sp 00007fff6d5a2000 error 6 in libc.so.6[7f9825eff000+195000]
I'm gonna go ahead and assume that the snap changes made in commit https://github.com/canonical/hotsos/commit/27db9dd6eae96af5b57f43685e9b6ebde310e1fb might be causing this.

not a problem on jammy it seems and I assume that is because the snap is built with core22

Confirmed. reverting the mentioned patch does resolve the issue. I will apply this to main but unfortunately this means that we are back where we started with python3-cryptography issues.

https://github.com/canonical/hotsos/commit/bacceb78c1f1bc4a25824c9990cacb314e296a1d

since the original issue is now resolved but this issue is being kept open for further investigation I think we can lower the severity.

no longer applies now that we have moved to a confined snap so closing.


Fix HC textPreformat colors

Fixes https://github.com/microsoft/vscode/issues/214412
I originally reversed these colors in https://github.com/microsoft/vscode/pull/213698 to address an issue with invisible shortcuts in the editor playground.
Seems like textPreformat.foreground needs to be used with textPreformat.background to be visible.

I agree this should be a candidate, make sure you set the labels and milestone on the issue too. I ran across it in https://github.com/microsoft/vscode/issues/214494


Remove API key requirement and rebrand to Python API (not Python Clie…

…nt API).

Tested in a notebook-- but fixed the date after.

Thanks for review! @beets I can submit a patch if you have any other feedback.


Error when click Deploy to Azure

There was an error loading the template from URI 'https://raw.githubusercontent.com/Azure/Azure-Security-Center/master/Secure Score/Secure Score Reduction Alerts'. Ensure that the template is publicly accessible and does not have any comments.

Thanks for reporting, I'll fix the broken links.

Deploy links are correct now, closing this issue.


[Bug]: Cannot individually stage files with accented characters in their file names

Describe the bug
In this plugin's Source Control View panel, files with accented characters in their file names cannot be individually staged.
Relevant errors (if available)
`pathspec` notifies a fatal error: file name did not match any files.

Steps to reproduce
Error notification for a file named "W- redención":

Expected Behavior
Processing accented characters (such as á, é, í, ó, ú, ü, ñ) is necessary for the plugin to be used by users who write in Spanish, French, Italian, etc.
Addition context
When the backup is automatically created in bulk for all files, they are staged and committed correctly.
Operating system
macOS

Duplicate of #121. Please use the fix provided in this issue.


KAFKA-7037: Improve the topic command description of --topic option

Committer Checklist (excluded from commit message)

[ ] Verify design and implementation
[ ] Verify test coverage and CI build status
[ ] Verify documentation (including upgrade notes)

retest this please

@ijuma, please take a look at this minor PR when possible. Might be worth including in the upcoming release.

@vahidhashemian Can you rebase the PR?

retest this please

Thanks @omkreddy. I rebased the PR. Could not figure out the reason for test failures. Scala code compiles fine locally. Will take a closer look later.

retest this please

@omkreddy looks like tests passed this time. Thanks again for catching that duplicate definition.